Why it is important to listen to children in a contemporary society?

Basic Recommended Reading
Listening to children: being and becoming
• Book by Bronwyn Davies 2014
Hearing the voices of children: social policy for a new century
• Book edited by Christine Hallett; Alan Prout 2003
Children’s experiences of classrooms: talking about being pupils in the classroom
• Book by Eleanore Hargreaves 2017
Theorizing childhood
• Book by Allison James; Chris Jenks; Alan Prout 1998

Listening to children: a practitioner’s guide
• Book by Alison McLeod 2008
A handbook of children and young people’s participation: perspectives from theory
and practice
• Book edited by Barry Percy-Smith; Nigel Thomas 2010
Helping vulnerable children and adolescents to stay safe: creative ideas and
activities for building protective behaviours
• Book by Katie Wrench; foreword by Ginger Kadlec 2016
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Other Reading to relating to Module concept description
Childhood as a cultural and social construction, examining beliefs, images about children’
· Defining the term ‘listening’.
· Why it is important to listen to children in a contemporary society
Foucault, power, and education
• Book by Stephen J. Ball 2013
Listening to children: being and becoming
• Book by Bronwyn Davies 2014
Pedagogy of the oppressed
• Book by Paulo Freire 2017
Pedagogy of hope: reliving pedagogy of the oppressed
• Book by Paulo Freire 2014
Theorizing childhood
• Book by Allison James; Chris Jenks; Alan Prout 1998
Constructing and reconstructing childhood: contemporary issues in the
sociological study of childhood
Underlying philosophies and approaches to children’s rights, participation and protection.
· Considering the concept of Voice, participation and agency.
· Considering how children are defined in law.
· Critical reflections on children’s participatory rights
Young children’s rights: exploring beliefs, principles and practice
• Book by Priscilla Alderson; Douglas Carleton Frechtling 2008
Hearing the voices of children: social policy for a new century
• Book edited by Christine Hallett; Alan Prout 2003
Children’s rights-based approaches: the challenges of listening to taboo/
discriminatory issues and moving beyond children’s participation
• Journal by Konstantoni, K. 2013
The Constitution of Society – Chapter 1
• Book by Anthony Giddens 1984
• Playing with power: children’s participation in theory.
• Examining theories and models that have influenced thinking within the field of voice,
agency and participation.
• Exploring how this framework can support the authentic participation and values of
children.
The Constitution of Society – Chapter 1
• Book by Anthony Giddens 1984
Children’s Participation. From tokenism to citizenship
• Document
A handbook of children and young people’s participation: perspectives from theory
and practice
• Book edited by Barry Percy-Smith; Nigel Thomas 2010
Considering some of the challenges of engagement with children and young people in a
professional context.
· Why is no one listening to me? Issues of agency and structure.
· Case studies to explore hidden voices.
Ethics and politics in early childhood education
• Book by Gunilla Dahlberg; Peter Moss 2005
Nurturing a listening culture in practice for safeguarding vulnerable children.
· Working within the safeguarding and child protection remit.
Conceptualising Listening to Young Children as an Ethic of Care in Early Childhood
Education and Care in Children & Society
• Article by Caroline Bath 09/2013
Listening to young people in school, youth work and counselling
• Book by Nick Luxmoore 2000
Helping vulnerable children and adolescents to stay safe: creative ideas and
activities for building protective behaviours
• Book by Katie Wrench; foreword by Ginger Kadlec 2016
Exploring communication skills for listening.
· Debating the concept of power and interpretation.
· Nurturing a listening culture in practice
· Pedagogy of relationships and listening. Considering new ways of thinking about
and interactions with children.
· Empowerment
Conceptualising Listening to Young Children as an Ethic of Care in Early Childhood
Education and Care in Children & Society
• Article by Caroline Bath 09/2013
Listening to children: a practitioner’s guide
• Book by Alison McLeod 2008
Capturing the voices of children.
· Exploring tools and strategies for listening. Pedagogy of listening- Voices from Reggio
Emilia.
· The |Mosaic approach.
Spaces to play: more listening to young children using the Mosaic approach
• Book by Alison Clark; Peter Moss; National Children’s Bureau c2005

Listening to young children: the mosaic approach
• Book by Alison Clark; Peter Moss; National Children’s Bureau c2011
Inviting the messy: Drawing methods and ‘children’s voices’ in Childhood
• Article by Sara Eldén 02/2013
A Handbook of Children and Young People’s Participation: Perspectives from … in
Children & Society
• Article 2010

In dialogue with Reggio Emilia: listening, researching, and learning
• Book by Carlina Rinaldi 2005
Children as researchers
· Voices in education.
· Advocacy- speaking up for children and children as advocates.
Understanding research with children and young people
• Book by Open University 2014
Children’s experiences of classrooms: talking about being pupils in the classroom
• Book by Eleanore Hargreaves 2017
Listening to young children: the mosaic approach
• Book by Alison Clark; Peter Moss; National Children’s Bureau c2011
Children’s participation in decision-making
• Document
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Additional reading
• Children’s commissioner
• Children’s Rights Alliance for England – Children’s rights and the law
• Children’s Rights Alliance for England – State of children’s rights in England – Review of
Government action on United Nations’ recommendations for strengthening children’s
rights in the UK
• Government is stripping UK children of rights, says report to UN (Guardian
Newspaper )
• UNICEF Children’s Rights
• Equality and Human Rights Commission
• Conceptualising listening to young children as an ethic of care in early childhood education and
care. ( Sheffield Hallam University)
• Engaging with children and young. People (Mary Kellett – Open University)
• Children’s right Alliance for England Children’s participation in decision-making
• Cambridge Journal of Education – What is a child? Children’s Perception,
the Cambridge Primary Review and implications for education (Routledge)
• Children’s commissioner: If only someone had listened – Office of the children’s
commissioner’s inquiry into sexual exploitation in gangs and groups
• I want to play – Barbados
• Its wrong but you get used to it – University of Bedfordshire
• (Childrens’ Commisioner)
A qualitative study of gang-associated sexual violence towards, and exploitation of,
young people in England
• Voices of Children in Foster Care (Children’s Commissioner)
• Promoting children’s Agency – journal
• Novitas Royal ( Research on Youth and Language) 2011,5 (1) 15-38
Angela MASHFORD-SCOTT & Amelia CHURCH
• Silence in the Context of ‘Child Voice’
Ann Lewis School of Education, University of Birmingham, Birmingham, UK
• Conceptualising Listening to Young Children as an Ethic of Care in Early Childhood Education
and Care
(Caroline Bath Department of Education, Childhood and Inclusion, Sheffield Hallam University,
Sheffield, S1 2NE, UK)
• DfE-RR239b_report: Listening to children’s perspectives: Improving the Quality of.
provision in EARLY YEARS settings
• Why and how we listen to young children – Listening as a way of life ( national
children’s bureau)
• How safe are our children-2018-report NSPCC
• The voice of the child: learning lessons from serious case reviews Ofsted 2010
• The voice of the child in the child protection system. (NCB Research Centre)
• Coram Voice – getting young voices heard
• Putting listening practice at the heart of early years practiceAn evaluation of the Young Children’s
Voices Network Rachel Blades, Vijay Kumari. ( Research Centre ncb)
• Engaging with children and young people
• The Mosaic approach
• Young children are researchers: Children aged four to eight years engage in important research
behaviour when they base decisions on evidenceEuropean Early Childhood Education Research
Journal ( Routledge)

What is the difference in knowledge of the participants about the intervention to improve or prevent bullying before and after the professional development has been implemented?

Task 1: Prospectus

Capstone: Bullying in Schools

PART A: Bullying Impacts students’ academic Performance

A study done by the Barrington (2018) shows that bullying exists in almost every school bout private and pubic and the main effect it has on students is the decline of their academic performance. In the research that involved 200 students from the grades 4 to 12 showed that the academic bullying affected their performance by 19% since they started being bullied. The results also show an interesting effect on the academic performance of the bullies which shows that the bullies’ academic performances are affected by a 3.8% change when involved in bullying activities. Academic performance is also affected indirectly by bullying because it is because it leads to lack of engagement in class discussions or missing school sessions altogether. It is therefore evident that bullying has an adverse effect on performances.

This is a problem for school administrators because those affected by bullying tend to miss classes and due to the lack of a proper learning environment in school. As Barrington (2018) explains, 10% of all those who are bullied end up dropping out of school. The problem that this presents to the administrators is that students fail to achieve their full potential while in school. School administrators are responsible for ensuring that students have an environment where they can learn peacefully and perform well in their studies. Administrators should create programs that will stop bullying because bullying deters students from realizing their full academic performance and it is also because of bullying that 10% of students drop out of school. To prevent this from happening school administrators need to be vigilant in creating a learning environment that will serve the students effectively.

 

PART B:

Problem Statement

Bullying affects students’ academic performance and is one of the major reasons students struggle in school, exhibit low self-esteem, perform at a lower level and in some cases, drop out of school. The problem of bullying affects the local school setting by negatively impacting the school environment making it harder for administrators to provide a conducive learning environment for their students.

Problem Explanation

Bullying refers to the use of force and threat to intimidate others. The study done by UCLA shows that students who are frequently bullied report lower academic performances and less involvement in school activities (Oliviera et al, 2018). Barrington (2018) also shows that bullying is a leading cause of dropouts in school. Bullying is can be caused by a possible number of elements such as depression, behavioral change from students and mental health issues.

The propagation of bullying in the school is caused by the lack of proper governance from school administrators. School administrators need to create proper reporting systems and anti-bullying programs to mitigate bullying. Bullying is also caused by the lack of school administrators’ involvement. Bullying requires stringent policies and school administrators to place systems that will deter such activities.

Solution

The solution here is to educate staff about how to identify students who are bullies, and those who are victims, how to respond to them, who to report to and what to report, and how to become an advocate to both instigative students and victims, ultimately reducing bullying and creating a more conducive learning environment. This will all be accomplished through a professional development training.

Proposed Research

The research will utilize the feedback from 20 educators, staff and counselors that interact with students daily. These staff members will vary in gender, age, race, and number of years of experience in education. 16 of the 20 will be female and 4 will be male. 5 of the 20 are under the age of 30. 6 of the 20 are between the ages of 30-50, and 9 of the 20 are over the age of 50. All 20 are Caucasian. 10 of the 20 have less than 5 years of experience in education. 3 of the and 20 have between 5-10 years of experience in education, and 7 of the 20 have more than 10 years’ experience in education.

Research Questions

There are two research questions, and they will be measured and defined before and after the professional development that will be implemented.

Quantitative – What is the difference in knowledge of the participants about the intervention to improve or prevent bullying before and after the professional development has been implemented?

Qualitative – What is the difference in knowledge of the participants about the intervention to improve or prevent bullying before and after the professional development has been implemented?

Answering the Research Questions

Quantitative – I will be issuing a Likert format 5-7 question survey via Google Forms, whereas all questions will be relative to the professional development. This will be given to the staff pre-training and post-training.

Qualitative – I will be issuing a questionnaire with 2-3 open ended questions with narrative response answers via Google Forms. The questions will be relative to the professional development. This will be given to the staff post-training only.

Data Analysis

Quantitative – I will be using a descriptive statistical analysis approach. I will take the average of each question pre professional development and compare to the average of each question post professional development. I will then use a positive or negative compare and a positive or negative contrast difference. I will report this data using a chart or graph.

Qualitative – I will be using a descriptive narrative analysis approach. I will take the responses for each question and categorize them into common themes and similar responses. Once that is done, I am then going to look for the most predominant response and use that for the response to the question. I will report this data using a simple table.

References

Oliveira, F. R., de, M. T. A., Irffi, G., & Oliveira, G. R. (January 01, 2018). Bullying effect on student’s performance. Economia, 19, 1, 57-73.

Barrington, K. (May 01, 2018). How Does Bullying Affect a Student’s Academic Performance? Public School Review.

Shetgiri, R. (November 01, 2017). Bullying and Children’s Academic Performance. Academic Pediatrics, 17, 8, 797-798.

 

 

 

 

 

 

 

 

What internal and external factors affect the effectiveness of school-based curricula?

IDENTIFYING THE IMPLICATIONS OF DIVERSE METHODOLOGIES AND METHODS

Identifying the Implications of Diverse Methodologies and Methods

Introduction

The proposed topic is “The development of project plan to support implementation of school wellness.” It is critical in the advancement of plans and policies that ensure the overall improvement of school-based curricula. Furthermore, the analysis of play-based learning vs traditional in early years will allow the researcher to identify the potential areas of improvement in the designing of future curricula by determining how the two approaches can be merged together to develop a more advanced syllabus (Barnhardt et al., 2016). The professional relevance of the given research topic will be through interaction with teachers, students and other relevant stakeholders.

Research Questions

  1. What internal and external factors affect the effectiveness of school-based curricula?
  2. What roles do teachers play in the improvement of school-based curricula?
  3. What methodologies are applied in the selection of modes of learning in schools?

The given research questions were developed based on the research topic and the existing literature review. As such, the investigation of existing knowledge and texts in educational research play a key role on how a researcher develops their research questions based on a specific topic. Sandberg and Alvesson (2011) provide that the available methodological principles also play a role in answering the questions. It may be explained by the fact that they enable the researcher to understand the research topic and consequently guide the research process. Therefore, it is critical to establishing intertextual coherence and problematisation while determining the research questions (Sandberg and Alvesson, 2011). These aspects allow for clear determination of the research’s position and determination of the most appropriate methodology of the study.

Possible Research Designs and Methods

Mixed method will be the best approach for answering the research questions as it involves the collection and analysis of both quantitative and qualitative data. Diller (2016) determines that this type of research allows the combination or mixing of the two approaches in a specific manner. The fundamental rationale for this type of research design is that the researcher can learn more about their topic. Since the three questions need to be answered through both quantitative and qualitative approaches, mixed methods provide the integration of the strengths of the two methodological paradigms.

Withams (2016) refers to this aspect as the fundamental principle of mixed methods research. However, Fletcher (2016) argues that to achieve reliable and accurate findings, it is important to combine them in a manner that achieves complete complementary strengths and non-overlapping weaknesses. This logic will ensure that the researcher is able to apply the quantitative methodology in the conceptualization of variables, the profiling of dimensions, determining the existent of relationships and formalising comparisons (Fry, 2016).

On the other hand, the qualitative research allows the investigator to achieve the strengths of sensitivity to meaning and context. Moreover, the great methodological strength of this approach enhances the ability to study process and change. Therefore, quantitative methods can be of advantage in areas where quantitative methods are weak and vice versa (Jackson, 2016). This approach is the best for this methodological study as at will allow the investigator to determine what internal and external factors affect the effectiveness of school-based curricula, what roles do teachers play in their improvement, and what methodologies are applied in the selection of modes of learning in schools.

Ethical Considerations

During the collection of data on the development of project plan to support implementation of school wellbeing, various ethical considerations may arise. First, before commencing the collection of data, the investigator will need to gain consent from the study participants. Punch (2009) provides that this action prevents the participants from feeling compelled to participate in the study. As such, the BERA guidelines state that a consent form is provided allowing the researcher to collect data from each subject.

Furthermore, the investigator is obliged to keep all the collected information confidential by maintaining a strict chain of command to protect the subjects in the study. Finally, there is need to ensure that no harm, both physical and emotional is done to the subjects while participating in the study. This factor means that the dignity of all subjects must be respected at all times. These concerns will be addressed by following the stipulated standard operating procedures while interacting with the research participants. Any type of communication relating to the research should be done with honesty and transparency by avoiding all forms of misleading information as well as representing the collecting data in an unbiased manner. This concern is addressed by using the appropriate data analysis technology and approaches to provide accurate findings.

Evaluation of Contrasting Methodological Approaches

Qualitative Research Design

In educational research, qualitative design mostly concentrates on the evaluation of human behaviour and other and social life. Jackson (2016) argues that its richness and complexity mean that there exists other means of analysing social life such as education, an element that presents multiple perspectives and practices in the collection and analysis of the data. Qualitative research provides an alternative approach to the analysis of the research questions.

In the determination of what external and internal factors affect the effectiveness of school-based curricula, this type of methodological design would be the most appropriate as it provides the contextualisation of the theoretical insights that are needed to understand the significant elements that affect education in this regard (Lund, 2019). Thus, qualitative methodology provides not only faster but more effective means of answering the research questions at hand through the application of interviews and case study research to provide an in-depth insight in regards to the elements affecting the school-based curricula.

This type of methodological approach would also be appropriate for determining what methodologies are applied in the selection of modes of learning in schools. This research question is relevant in the determination of the standard operating procedures that are applied in the establishment of school-based curricula and the subsequent modes of learning (Pugsley, 2001). Through the use of interviews with educators and other relevant stakeholders, the researcher is able to gather relevant data in regards to how modes of learning are selected and how these approaches can be utilised in the provision of school wellbeing programs.

The analysis of qualitative data will need the application of coding to assign names, labels, and tags to the collected data. As such, the researcher is able to assign meaning to each piece of data while still indexing it and providing the basis for storage and retrieval (Robertson, 2018). However, there must be clear links between data indicators and the conceptual labels that are given to it as they enable the investigator to check and test the reliability of each code before giving out the final findings.

A qualitative research design provides a rich and detailed analysis of why people act in a certain manner and how these actions affect the final outcome. Sych (2018) argues that this type of approach allows a researcher to evaluate attitudes, feelings and behaviours. Furthermore, qualitative approach creates openness in the sense that it encourages people to expand their response thus leading to more in-depth information. Techniques such as interviews have been shown to stimulate individual’s experiences allowing the research to gather insights that would be otherwise impossible with other techniques (Sych, 2018).

However, studies show that qualitative research design has its own share of disadvantages. The approach is generally more time consuming than quantitative methodology, an aspect that reduces the number of study participants. As such, due to the reduced number of research participants, it becomes difficult to generalise the findings (Hay et al., 2015). A researcher is unable to make systemic comparisons and the accuracy usually depends on the skills of the researcher.

Quantitative Research Design

The use of surveys in the collection of data in educational research has over the years proven relevant when reliability needs to be maintained (Sych, 2018). The use of questionnaires in determining what roles teachers play in the improvement of school-based curricula allows the investigator to gather factual information and provides an effective means of measuring participants’ attitudes, opinions and beliefs. However, Yoo, Jang and Park (2018) argue that the development of the different parts of a survey should depend on the types of measurements involved. As such, it is critical for the investigator to design the questions and approach the respondents professionally in order to ensure that accurate data is gathered.

Quantitative methodological approach allows for a broader study that provides for an increased number of research participants. This element ensures greater objectivity and accuracy of results by allowing few variables and extended cases (Sych, 2018). Thus, personal bias can be avoided as the findings are based on the response of the subjects and not the investigator’s conclusions.

However, quantitative methodology has been found to collect much narrower and sometimes superficial datasets making the results limited as they provide less elaborate accounts of human perception rather than the detailed narrative (Barnhardt et al., 2016). Also, the development of standard questions by investigators has been found to contribute to structural bias which subsequently leads to false representation.

References

Barnhardt, C., Reyes, K., Vidal Rodriguez, A. and Ramos, M. (2016). A Transformative mixed methods assessment of educational access and opportunity. Journal of Mixed Methods Research. 12(4), pp.413-436.

Diller, H. (2016) Literature and the learner: Methodological approaches. System. 20(1), pp.99-101.

Fletcher, A. (2016). Applying critical realism in qualitative research: Methodology meets method. International Journal of Social Research Methodology. 20(2), pp.181-194.

Fry, E. (2016). Research tools: Instrumentation in educational research. Review of Educational Research. 30(5), p.513.

Hay, J., Puckeridge, M., McDonald, R. and Kelly, M. (2015). Ermington family learning centre: Breaking the cycle of disadvantage through parents and children learning together. Children Australia. 20(1), pp.13-17.

Jackson, E. (2016). Quantitative methods in educational research: The role of numbers made-easy. Journal of Mixed Methods Research. 12(3), pp.358-359.

Lund, T. (2019). Combining qualitative and quantitative approaches: Some arguments for mixed methods research. Scandinavian Journal of Educational Research. 56(2), pp.155-165.

McKim, C. (2016). The value of mixed methods research. Journal of Mixed Methods Research. 11(2), pp.202-222.

Pugsley, L. (2001). The researcher experience in qualitative research. Qualitative Research. 1(1), pp.120-122.

Punch, K. (2009). Introduction to research methods in education. British Journal of Educational Technology. 40(6), pp.1149-1150.

Robertson, S. (2018). The qualitative research process as a journey: Mapping your course with qualitative research software. Qualitative Research Journal. 8(2), pp.81-90.

Sandberg, J. and Alvesson, M. (2011) Ways of constructing research questions: Gap-spotting or problematization? Organization. 18(1) pp.23-44.

Sych, T. (2018). Methodological approaches in research of education management problems. International Scientific Journal “Internauka”. 10(50), pp.51-54.

Withams, S. (2016). Ethical guideline reviews need time. Nursing Standard. 10(34), pp.11-11.

Yoo, Y., Jang, J. and Park, S. (2018). A study on the analysis of the current status of applying CPTED project to school. Korea CPTED Association. 9(1), pp.180-210.

What are its impacts on household assets and financial stability?  What are its intended and/or unintended consequences?

The Paradox of Wealth and Poverty

Guidelines for the Final Paper

 

We have examined a variety of different policy and programmatic responses that address widening inequality and/or the difficulties faced by many poor and working-class people in the U.S. and around the globe.  We have also discussed their strengths and weaknesses, evaluating their potential effectiveness. For this assignment, we ask that you delve deeper into an issue that you are interested in investigating further.

 

Please select one specific example of a policy or programmatic response targeting inequality (e.g., living wage, state EITC, educational initiatives, voucher programs, housing initiatives, community capacity project, asset building project, unionization campaign, etc.). Class lecture, discussions, and readings have presented a variety of possibilities for exploration, however, you are welcome to choose an alternative. Your policy/program need not be one we went over in class, but should work within the context of course themes.

 

Please construct an 8-11 page case study of your particular example. Your paper should address the following:

  • Document, describe and frame the specific problem your policy/program addresses
    • Outline your policy/programmatic response in detail and evaluate it in light of all that you have learned this semester – what does it do and how? Why is it important?
  • Establish how this initiative is an effort to assuage the problem/ inequality
  • Marshal evidence to support your claims and establish trends throughout. You may use course materials and outside sources to back up your points and suppositions.

Please consider all aspects of the question and be clear, concise, well organized. Use your classmates as a resource- you can brainstorm with each other!

 

Note that papers should be double spaced with 1 inch (top, bottom, left and right) margins, have page numbers, 12-point font and be between 8-11 pages in length (excluding bibliography) and be free of typos/spelling errors and grammatically correct. Include a bibliography/references page in addition to citations in text based on a standard and consistent format for references (Chicago, APA, MLA).

 

 

 

 

 

Final Paper Tips

Suggested Structure of Paper:

  1. Introduction (1/2 page):
    1. name and BRIEFLY describe the problem and your policy solution
    2. state your overall evaluation (remember, it can have several parts to it, e.g. the policy helps in some ways but has unintended consequences that cause harm)
    3. state the 3-4 points you are going to make about it that support your overall evaluation
  2. Problem description (1 ½-2 pages – approx. 1/5 of paper):
    1. describe the problem and how your policy seeks to address it
  3. Policy description (approx. 1 page):
    1. Describe the policy and how it works.  What is the policy supposed to do?  How is it supposed to do it?
    2. Provide context: the policy/program history, intent/goals, how it works
  4. Critical analysis (6-8 pages) Supporting Points
    1. Your evaluation using the themes from the course as a lens
    2. Is the policy doing what it is supposed to be doing?  In what ways?
    3. In light of the themes we have discussed in class, consider these questions:
  1. Is the policy an effective tool to address inequality? or to create opportunities for mobility?
  2. Does it dismantle the barriers to mobility we have discussed in class? Does it create more barriers to mobility?
    1. Use DATA to show the actual impacts of the policy!  Data can be quantitative or qualitative or both.  Your use of evidence to support your claims is the most important part of your paper.
    2. Underlying mechanisms – engage themes and concepts from the class
    3. What works/what doesn’t/how would you change the policy
  1. Conclusion (1/2 page): summarize your paper and, if you want, add in any of the following:
    1. Your idea of how to fix the policy so that it works the way it is supposed to
    2. An area of research around the policy that has not been looked at yet

 

While writing your papers, you may want to consider the following list to make sure that you have the following items covered:

 

  • Clear definition of a policy or issue or program related to inequality, poverty, etc.
  • History of the policy/issue/program
  • Goals of the policy/issue/program
  • What are its impacts on household assets and financial stability?  What are its intended and/or unintended consequences?
  • Distributive consequences (intended or unintended) – have some people been helped or hurt more than others?
  • Demonstrated understanding of themes and concepts discussed in the course.
  • Relationship between policy or issue and the main themes and concepts of the course.
  • Use of data/examples from research to support argument
  • Overall clarity and organization
  • Works cited (sufficient sources, correct use of citation style)

 

 

For Review: Engage themes and concepts of the course:

  • Major theme of class: how policy can create or address inequality
    1. Part I: Introduction
      1. Using data to measure poverty, inequality, quality of life
      2. Link between structure barriers and individual agency in driving poverty
      3. Effects of inequality
      4. Increasing inequality
    2. Part II: Ain’t No Making It
      1. Social mobility vs. reproduction
        1. Intra/intergenerational
        2. Role of the habitus
        3. Meritocracy
      2. How policy can create or perpetuate inequality
        1. Education
        2. What data do we need to answer the question?
        3. Intent v. Impact
      3. Forms of capital
        1. Social
        2. Financial
        3. Human
        4. Natural
        5. Cultural
        6. Political
      4. Structure, culture and agency
  • Part III: South Africa & Globalization
    1. How policy is used to create and redress inequality deliberately
      1. Apartheid, TRC
    2. Not if but how
      1. What kind of labor market do you want?
        1. Parking tickets example: technology vs. employment
      2. Role of policy in creating global markets and regulating them
        1. World Bank, IMF, trade agreements
      3. Part IV: Wealth, Toxic Inequality
        1. Leveraging assets as tool for social mobility
          1. Housing
        2. Legacy of racialized policy in the past – how it is implicated in present inequality
          1. Legacy of Slavery; Jim Crow
          2. Redlining
          3. Drug Policies (AKA “The New Jim Crow”)
        3. Contemporary policies and practices
          1. Residential segregation
          2. Estate tax
          3. Home mortgage interest deduction
        4. Part VI: Policy solutions
          1. Fiscal & Monetary Policy
          2. Asset policy
            1. Children’s savings accounts
            2. IDAs
          3. Minimum wage
          4. Living wage
          5. EITC

 

 

 

 

What do you want the child to learn from the activity? Will you be focusing on one domain? Which domain did you choose and how does your activity represent that domain?

ECE 203 Week 2 Discussion One

****ATTACHED PDF TEXT BOOK MUST BE USED AS ONE OF THE CITATION SOURCES**

Please review assignment, attachments, required resources & lecture below

 

Assignment Details:

Planning and the Domains of Development [WLOs: 1, 2] [CLOs: 3, 4]

Prior to beginning work on this discussion, review the ECE203 Case Studies  (Links to an external site.)and select one that looks interesting to you. To be an effective early childhood educator in the United States today, it is imperative that you are able to adapt curriculum and instruction to meet each and every child’s varied needs across each developmental domain, regardless of the age of the children. This discussion builds on the Week 1 discussion about creating trust with students, and further prepares you to design for each and every child’s success in your classroom, which is a component of the Final Project in Week 5.

For your discussion, you will create a developmentally appropriate activity that enhances one domain of development (cognitive, physical, effective, or language) for one of the children in the case study examples. An example activity for this discussion is located in the Week 2 Instructor Guidance.

To prepare for this discussion,

For your initial post,

  • Design an activity for your selected case study child. Your post should include the following:
    • The name and age of the child as indicated in the case study you chose.
    • A description of the setting the instruction will take place in (e.g., childcare center, classroom).
    • The goal of the activity, including which domain it is geared towards.
    • The materials necessary to support student learning for the activity.
    • The procedure for how the activity will be implemented. This section of your response must be at least one full paragraph and provide a substantial description of the procedure.
    • A description of specifically how your activity aligns with NAEYC’s article The Case of Brain Science and Guided Play: A Developing Story(Links to an external site.) and the importance of play in the early childhood learning environment.

 

Required Resources

Required Text

Jaruszewicz, C. (2019). Curriculum and methods for early childhood educators [Electronic version]. Retrieved from https://content.ashford.edu/

  • Chapter 4: Curriculum and Development
  • Chapter 6: What Are My Responsibilities as a Planner?
  • Chapter 7: Approaches to Learning: Exploratory Play and Creative Arts

Articles

Hassinger-Das, B., Hirsh-Pasek, K., & Golinkoff, R. M. (2017). The case of brain science and guided play: A developing story (Links to an external site.). Retrieved from https://www.naeyc.org/resources/pubs/yc/may2017/case-brain-science-guided-play

  • This resource provides information about play in early childhood and is required for your Planning for Domains of Development discussion this week.
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    Privacy Policy(Links to an external site.)

NAEYC. (2009). Where we stand on professional preparation standards (Links to an external site.). Retrieved from https://www.naeyc.org/sites/default/files/globally-shared/downloads/PDFs/resources/position-statements/2009%20Where%20We%20Stand%20Standards%20rev%204_12.pdf

  • This article summarizes each of the six of NAEYC professional preparation standards. This resource will help you complete the Planning for Domains of Development discussion.
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Recommended Resources

Articles

Almon, J. (2013, September/October). It’s playtime: The value of play in early education, and how to get teachers on board (Links to an external site.). Retrieved from http://www.naesp.org/principal-septemberoctober-2013-early-learning/it-s-playtime

  • This resource provides information about play in early childhood and may assist you in your Planning for Domains of Development discussion this week.
    Accessibility Statement does not exist.
    Privacy Policy(Links to an external site.)

Clarke, G.-A. (2016, March 20). 20 DAP checklist questions for teachers (Links to an external site.) [Blog post]. Retrieved from http://www.naeyc.org/blogs/20-dap-checklist-questions-teachers

  • This resource provides information on planning developmentally appropriate activities in the classroom or center. This resource may support you as you complete your Developmentally Appropriate Practices Assignment this week.
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Web Page

NAEYC. (n.d.). Articles for families on play (Links to an external site.). Retrieved from https://www.naeyc.org/our-work/families/play

  • This web page provides information about play in early childhood and may assist you in your Planning for Domains of Development discussion this week.
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Week 2 Overview

Discussion 1: Planning for Domains of Development  

As you have read, human development is divided into three broad domains: physical, cognitive and affective domains.  Although we study each as distinct and different, they are far from actually being distinct.  Instead, they “combine in an integrated, holistic fashion to yield the living, growing child” (Berk, 2013, p. 4).  Having a solid base in each of these domains will assist you in helping children grow to reach their potential.  “A cornerstone of quality teaching is having a firm understanding of child growth and development” (Estes & Krogh, 2012, p. 63). As an integrated set, each domain is influenced by and influences the other.  To illustrate an example of this interconnectedness, consider a baby learning to reach, crawl, sit and eventually walk (physical domain).

This new ability contributes “greatly to infants’ understanding of their surroundings” (cognitive domain) (Berk, 2013, p.4 ).  As babies begin to “think and act more competently, adults stimulate them more with games, language, and expressions of delight at their new achievements” (affective domain) (p.4).  As a result, these newly expanded encounters promote all aspects of development (p.4).  As educators and caregivers it is important for us to have this holistic view of child development.  While one domain may occasionally be more dominant than others in a given activity, children always function holistically.  That is why it is important for us to have a solid understanding of each of the domains of development!

There is a series from Help Me Grow on Youtube that you might find useful when looking at individual age ranges of children (such as you will need to do for this discussion).  Each age and stage is represented.  Below is an example of Two Year Old Child Development Stages & Milestones.

For your first discussion this week you are asked to look at case studies.  The purpose of this activity is to help you gain insight into how each of these domains of development might actually look in children, and the importance again of learning each of our students’ individual needs.  Look at each of the Case Studies in depth, and choose the one that interests you most (Trevor, Jenny, Amiee, Abby, and Bradley).

After choosing a case study from above, think about and plan an activity you could use to assist the child with his/her need.  Your activity should be developmentally appropriate and should enhance or support each of the developmental domains (i.e., cognitive, physical, and affective). Remember “researchers and curriculum specialists also emphasize that growth and learning occur as an integrated process across multiple domains (Gestwicki, 2011; Hull, Goldhaber, & Capone, 2002; Levine & Munsch, 2011, as cited in Jaruszewicz, 2019, Section 4.1). This means that you do not need to create three separate activities, per se, but rather one or more activities that address multiple domains simultaneously.  The following illustrates an example of how one might incorporate each domain into an activity (but keep in mind you must create an original activity for your discussion that includes each of the bullet points below):

To Prepare for this Discussion:

For your Initial Post:

Design an activity for your selected case study child.  Your post should include the following:

  • The name and age of the child as indicated in the case study you chose.
  • A description of the setting the instruction will take place in (e.g., childcare center, classroom).
    • Where will you be completing the lesson? What does the setting where you will be teaching look like? Will you be completing the activity on the carpet or at a table? Will other children be present or will you be doing the activity one on one?
  • The goal of the activity, including which domain it is geared towards.
    • What do you want the child to learn from the activity? Will you be focusing on one domain? Which domain did you choose and how does your activity represent that domain?
  • The materials necessary to support student learning for the activity.
    • Is it an art based activity or a writing based activity? Will you need toys to complete your activity or perhaps some gross motor equipment? What materials will you need to accomplish your goal?
  • The procedure for how the activity will be implemented. This section of your response must be at least one full paragraph and provide a substantial description of the procedure.
    • You have explained the setting of your activity, the goal of your activity, and the materials you will need. Now it’s time to put it all together. Takes us through a step by step detailed plan of how you will complete this activity. How will you start the activity? What words will you use? How will you get the child to engage in the activity?
  • A description of specifically how your activity aligns with NAEYC’s article The Case of Brain Science and Guided Play: A Developing Story(Links to an external site.) and the importance of play in the early childhood learning environment.
    • You have just read about the importance of play and the role it has in children’s learning. How does your activity incorporate the importance of play? If it did not align with the article, what could you add to your activity to incorporate play?

Guided Response: Respond to at least two of your peers’ posts. In each response, explain how your peer’s suggested activity specifically upholds any of the 6 NAEYC Standards for Early Childhood Professional Preparation, which are summarized in the Where We Stand on Professional Preparation Standards (Links to an external site.) resource.  Describe all standards your peer upheld and how, and include suggestions on how they might incorporate any that are missing.

  • NAEYC is one of the governing bodies in early childhood education. As you continue in the field of early education, NAEYC standards will become very familiar to you. Use this Guided Response as a tool to help you become more familiar with NAEYC standards.

 

What are the basic and central values of the educational technology professional community?

Ethics in educational technology: towards a framework for ethical decision making in and for the discipline

  1. Michael Spector1

Published online: 5 October 2016

Association for Educational Communications and Technology 2016

Abstract This special issue of ETR&D is devoted to ethics in the broad domain of educational technology. Many ethical issues arise involving the study and use of educational technologies. A well-known issue involves the digital divide and the degree to which the introduction of new technologies is increasing the digital divide and disadvantaging some students while benefitting others. The potential of educational technologies to improve learning and instruction is generally well known. Many of the problems associated with the successful implementation of educational technologies are also generally well known. However the ethical issues involved with educational technology implementation, use and research are not well explored nor widely known. This paper provides a preliminary framework for ethical decision making with regard to educational technologies.

Keywords Educational technology ethics  Ethics framework  Educratic oath  Ethics framework  Value-driven educational practice

Introduction

The definition of educational technology embraced by the Association for Educational Communications and Technology (AECT) is as follows: ‘‘Educational technology is the study and ethical practice of facilitating learning and improving performance by creating, using, and managing appropriate technological processes and resources’’(Januszewski&Molenda,2007, p. 1). This definition, developed and approved by the AECT definitions and terminology committee is striking due to the inclusion of ethics as an essential aspect of educational technology. Given that emphasis by such a prominent international association of scholars and professional practitioners,it is worth exploring the role of ethics in educational technology.This

& J. Michael Spector

mike.spector@unt.edu

1   Learning Technologies, University of North Texas, Denton, TX 76207, USA

article is a step towards creating a framework for the inclusion of ethical decision making in efforts aimed at facilitating, improving and supporting learning, instruction and performance. The discussion is primarily conceptual rather than being research based.

Professional practice, standards and values

As a precursor to the argument and framework to be presented, consider the broad domain of medical practice. There are many professions within that domain, within each of those professions there are specializations. Consider nursing, for example. A general definition of that profession is basically that it involves the practice of promoting health, caring for individuals and preventing illness, not unlike a parallel definition for physicians (see http://www.icn.ch/ who-we-are/icn-definition-of-nursing/). The word ‘ethics’ does not appear in the definition of the profession or discipline. Rather, the International Council of Nurses publishes a separate code of ethics that emphasizes respect for the rights and dignity of individuals(ICN,2012).That code begins with four basic value statements involving the promotion of health, the prevention of illness, restoring health and alleviating suffering. What follows those value statements are a number of elements comprising the code of ethics, which can be considered performance standards for ethical conduct as a professional nurse. One can find other such frameworks that distinguish professional practice, ethical standards and values. As a result, that general organizing framework that separates practice and ethics is adopted herein.

I believe that those who crafted the AECT definition of educational technology did so to emphasize the importance and centrality of ethics in the broad domain of educational technology. I share that general inclination but embedding ethics in what educational technology professional practitioners and scholars do glosses over the important distinction between performance and standards (ethical standards in this case but one could also include quality standards).

To make these distinctions concrete, consider a certified nurse performing a particular job task. The nurse is clearly a practicing professional and has gone through extensive training to become certified. Nonetheless, that nurse may be careless in drawing blood from a patient on an occasion. In such a case, a quality standard is relevant. If carelessness recurs, some kind of action or remediation may be required. On another occasion, a certified nurse may refuse to treat or interact with a patient on account of the patient’s race, religion or other characteristic. That is not a violation of a quality standard. It would be a violation of the nursing code of ethics and a failure to fully embrace the four values that guide nursing practice and ethical standards. While additional training may be appropriate for quality violations, ethical violations often require a different kind of response, including the loss of a job or certification.

One might then ask how far from such a framework is professional practice and scholarship in the domain of educational technology. Responding to that question is the specific task undertaken herein.

Defining ethics and values

The word ‘ethics’ is used by many people in a variety of contexts without an attempt to provide a definition. For that reason, many will separate ethics from morals, which this author believes is wrongheaded. Classically, ethics is a branch of philosophy that dates back thousands of years. Modern philosophers often divide ethics into three categories: (a) metaethics that focuses on the origin and meaning of ethical principles, (b) normative ethics aimed at establishing standards to distinguish and regulate right and wrong conduct, and (c) applied ethics that tends to focus on difficult to resolve cases and issues (see http:// www.iep.utm.edu/ethics/ for an elaboration of these categories).

What seems most appropriate for this discussion is the notion of normative ethics, as that category is typically associated with codes of conducts and distinguishing good or acceptable behavior and practice from unacceptable or harmful behavior and practice. The representative ethical statements presented in the next section clearly fall into the category of normative ethics. Normative ethics represent the specific behaviors and practices that a community, culture, institution, or profession expect all members to follow. In some cases, failure to adhere to an ethical principle is also a violation of the law. For example, delaying treatment of an individual in need of immediate attention may result in that patient’s death. In such a case, the medical practitioner who delayed treatment not only commited a violation of a basic ethical principle (e.g., do no harm), but may also be guilty of involuntary homicide. Regardless of the legal implications, ethical violations should be regarded as serious and reported to the responsible authorities, as a general rule (and perhaps also an instance of a normative ethics statement). The honor code at the United States Air Force Academy states that ‘‘we will not lie, steal, or cheat nor tolerate among us anyone who does’’ (see http://www.academyadmissions.com/the-experience/character/honor-code/). The implication of that code is that not reporting a violation is also a violation.

Codes of conduct and ethical principles can be found for many professional associations and communities of practice. A few are presented below. Such normative ethical statement cover a wide range of behaviors, including such things as taking unfair advantage of others, misrepresenting relationships, overlooking evidence, violating trust and confidentiality, and much more. Such statements are generally representative of the values of an association, community, or profession. That leads to several questions: (a) What are the basic and central values of the educational technology professional community? (b) How were those values established? (c) How are those values to be interpreted?

AECT’s TechTrends; Linking Research and Practice to Improve Learning periodically has a column on professional ethics written by Andrew Yeaman. Those columns provide insight into a number of aspects of normative and applied ethics in educational technology practice (see http://link.springer.com/journal/11528). For example, in a recent issue, Yeaman (2016) presented a scenario about problems in a training department that lead to a decision with regard to whom responsibility should be delegated to improve the situation. The value involved is commitment to the profession, and the ethics involved focus on fixing the situation rather than assigning blame.

One way to conceptualize values is in terms of a hierarchy of responsibilities and obligations. One interpretation of Plato’s early dialogues that recount Socrates’ trial and last day, is that Socrates had such a hierarchy which proceeded from self to family to state to the voice of the oracle. The reason a hierarchy is needed is that values can conflict. One may value one’s own well-being or prosperity, but that would be superseded by the well being of family or community or profession or society if there should arise a conflict. The most difficult cases when there are conflicts at the same level within such a hierarchy. Jonassen (2007) calls such ethical dilemmas the most challenging kind of problems because there is essentially a lose–lose aspect to such dilemmas—whichever choice is made, an ethical principle will be violated.

As an example, consider a professor who is supervising a doctoral student with a severe disability that prevents the student from writing and speaking clearly. The student’s speech is difficult to understand, and the writing often incoherent. Nevertheless, with support from the professor, friends and the medical profession, the student has managed to successfully complete all of the required coursework for the degree. The problem now is completing a dissertation. The student is passionate about completing the degree, and the professor wants to help the student succeed. However, the level of support from the professor to complete a dissertation given the student’s condition appears challenging (as much as 10 h a week based on recent experience). In spite of having spent a great deal of time with the student, there has not been much progress, and the date for the dissertation proposal defense is approaching. Failure to defend the proposal on that date will result in the student being put on probation; a previous extension has already been granted to avoid that outcome. Being on probation means that the student’s financial aid will be discontinued. Another extension could be requested, and that would support the professor’s commitment to the student. However, the professor believes that will only postpone the inevitable, which would violate the principle of being honest with students. What to do? Such decisions are not easy, and intuitions can often be misleading. Passionate and dedicated students can often far surpass one’s expectations.

The framework of ethical decision included herein is encapsulated in the Educratic Oath (see below). While specific categories and contexts are not mentioned, the general notion of doing no harm and respecting individual rights includes (a) not being persuaded by money but being persuaded by evidence, (b) recognizing that not every solution helps every student, (c) being fair to all while providing as much support for individual initiative as possible, (d) considering what is best in the long run for learners, teachers and the institution, (e) recognizing the impact of introducing any change into an educational context. In other words, this is intended to be the basis for a broad ethical decision-making framework.

Professional ethics statements

The international board of standards for training, performance and instruction (ibstpi) periodically conducts large-scale surveys of practice in a number of education professions (e.g., evaluation, instructional design, instructor, online learner, training management) that form the competencies and performance standards for the discipline. With regard to instructional design, there is one competency statement in the foundations area that ibstpi included in spite of lack of strong support from surveys – namely, identifying and responding to ethical, legal, and political implications of design in the workplace (Koszalka et al., 2013). It is worth noting that while AECT and ibspti place strong emphasis on ethical practice, that emphasis is not as evident in other educational technology associations (see, for example, the standards of the International Society for Technology in Education at http://www.iste.org/standards/standards).

The American Psychology Association has a set of principles and code of conduct that begins with five principles or values: (a) beneficence and nonmaleficence, (b) fidelity and responsibility, (c) integrity, (d) justice, and (e) respect for people’s rights and dignity (APA, 2010a). Section of the APA code of conduct pertains to education and training and has been considered in developing the educational technology ethical framework to be presented below. The APA publication manual (APA, 2010b) also has ethical guidelines pertaining to authorship—namely, authorship should include all those who have made a primary or significant contribution to the data collection, concepts, and interpretation of work to be published, including those who do not do the actual writing. Unfortunately, there are far too many violations of that ethical standard pertaining to authorship in the educational technology professional and scholarly community.

The Educratic oath

There is a great deal of commonality among the various ethics statements just reviewed. They bear a remarkable similarity to the Hippocratic Oath (attributed to a Greek physician who lived in the fifth century BCS; see https://www.nlm.nih.gov/hmd/greek/greek_oath. html for the original version and http://guides.library.jhu.edu/c.php?g=202502&p= 1335759 for a modern version). While the first principle of the Hippocratic Oath is often cited as ‘‘do no harm,’’ that statement did not appear in the version attributed to Hippocrates. Nonetheless, that phrase does capture a general of medical practice in ancient Greece that still exists today.

Based on an interpretation of the Hippocratic Oath and the kinds of ethical principles reviewed above, Spector (2005) proposed a similar oath for educators, the Educratic Oath:

(1) do nothing to impair learning and instruction; (2) do what you can to improve learning and instruction; (3) base your actions on evidence that you and others have gathered and analyzed; (4) share the principles of instruction that you have learned with others; and, (5) respect the individual rights of all those with whom you interact. (p. xxxvi).

The Educratic Oath has not been widely embraced, nor has any other such ethical code for educators. As a result, Spector (2015) decided to move from principles, such as those in the Educratic Oath, to a more general concern with values. Figure 1 represents the values that might be associated with a learning environment effort.

One could take each of the values statements in Fig. 1 and develop specific principles that might represent how that value could be articulated. Regardless of agreeing or disagreeing with the values in Fig. 1, that framework is incomplete in many ways. First, it primarily represents an instructional design perspective. Second, it does not take into

Fig. 1 A values hierarchy for learning environments (adapted from Spector, 2015)

account the many activities in which instructional designers engage, nor does it take into account those with whom instructional designers interact nor any of the technologies involved. The next section takes up these shortfalls.

Educational technology practice

Recalling AECT’s definition of educational technology will provide pointers to those involved in educational technology and what they do. Those who facilitate learning and performance are involved (e.g., teachers, tutors, teaching assistants, coaches, etc.). Those who create technology resources and processes are involved (e.g., instructional designers, graphics artists, media specialists, writers, web designers, etc.). Those who manage those resources and processes are involved (e.g., lead instructors, department chairs, deans, technology coordinators, information specialists, etc.). Those who make use of the resources are involved (e.g., students). Those who conduct studies about the design, development, deployment, use and evaluation of the processes and resources are involved (e.g., researchers and evaluators). The educational technology community includes a number of sub-communities, disciplines, and people with different backgrounds, training and interests. Given the complexity of the AECT definition, as elaborated above, there is no such person as a representative educational technologist, just as there is no such person as a representative nurse. There are emergency room nurses, oncology nurses, pediatric nurses, neonatal nurses, and so on. Nurses interact with other nurses, physicians, patients, family members, and others. Educational technology is at least as complex in terms of sub disciplines and specializations as is nursing. The implication is that the ethical principles and kinds of ethical decision making involved are likely to be specific to a particular context.

If one considers the sub-discipline of instructional design and what has been written about instructional design practice, one will not find much with regard to ethics other than AECT’s ethical standards and the one ibstpi competency referred to earlier that also includes adherence to legal standards as well as ethical standards (Koszalka et al., 2013). The importance of values is emphasized in Spector’s (2005, 2015) works and values are mentioned briefly in a few chapters in the Handbook of Research on Educational Communications and Technologies (Spector et al., 2013). However, in major treatments of instructional design practice, there is very little discussion of ethics or values (see, for example, Dijkstra, 2004; Larson & Lockee, 2014; Merrill, 2013; Reigeluth, 1983). In the influential roadmap for education technology (Woolf, 2010), there is no mention of ethics or values. Yet the digital divide remains a reality and is prioritized in the 2016 National Education Technology Plan (see http://tech.ed.gov/files/2015/12/NETP16.pdf). Surely the digital divide involves ethical issues due to the fact that some students (especially those without access to new technologies or with little experience in using advanced learning technologies) are falling further and further behind as new technologies are integrated into teaching and learning. While educational technologists are generally well-intention ed and seek to promote learning and improve instruction, it often happens that the introduction of a new technology will have a negative impact on some students as well as some teachers. Planning to minimize negative impact and properly supporting both students and teachers when introducing a new technology should be a high priority for educational technologist.

As new technologies emerge at an increasing rate, an educational technologist may decide to try something new just because it can be done. The operational outlook should not be ‘‘because we can.’’ The educational technologist’s motto should be ‘‘because we can do better for all involved.’’ Adhering to that creed requires taking an evidence-based approach rather than one based on fads and fancies.

A preliminary educational technology ethics framework

Figure 2 provides a somewhat deeper framework for thinking about ethical issues involving educational technology. This framework is intended to be a starting point for further development and exploration of the usefulness of such a framework for educational technology ethics.

There are three interacting dimensions in this framework: values, principles and people. Two additional dimensions are relevant but not depicted: context (e.g., school, university, workplace, culture, country, regulatory environment, etc.) and technology (e.g., specific technologies and their intended use and purpose). If the simplified framework presented here gets those involved with educational technology to think more seriously about the ethics of practice and research involving educational technology, then this framework is perhaps a step forward.

To encourage the progressive development of this framework, an elaboration of the intersection of these three dimensions is provided: (a) students in the people dimension, (b) evidence in the values dimension, and (c) the ethical principle of being fair and open in assessing and evaluating progress. The intersection of these three dimensions in the framework is one that is commonly encountered and, as a consequence, perhaps useful as a starting point for further elaboration.

Suppose the context is a public high school course that involves history. A major portion of the grade in that course is a student-authored paper analyzing and discussing the causes of World War II. The technologies involved include the internet, media and word processing. Students are required to (a) include links to at least three internet sites that provide different analysis of the causes, (b) include a figure or diagram that represents the resolution of the differences among a variety of perspectives, and (c) submit the final paper as a PDF file to an online learning management system. The instructor has provided

Fig. 2 A preliminary educational technology ethics framework

students with a rubric that indicates how the paper will be graded. The rubric includes requirements such as due date, length, format, required components (e.g., overview, perspectives explored, differences and similarities among those perspectives, etc.), how the quality of each requirement will be determined, and the weight assigned to each of the requirements. Additional notes in the syllabus are provided with regard to plagiarism and other related matters.

The rubric is in the course syllabus and students have been given frequent reminders. Specific drafts of the major components (overview, internet sites found, etc.) have been assigned along the way and feedback on those drafts provided to students. In short, the instructor has created a clear and coherent course plan that includes emphasis on evidence to be used in assessing the final paper.

Student Y has received a failing grade based on making use of another’s work without credit or citation. The student claims it was a simple oversight and is asking the instructor to be given another chance to correct the problem in order to get a passing grade that is required for graduation. What specific ethical issues and principles are involved?

There is the value of making evidence-based decisions, and the evidence of plagiarism in this case is clear. There is the principle of making open and fair assessments. The rubric was well known in advance as was the penalty for plagiarism. Other principles are also involved. The instructor did establish clear and specific goals and expectations. The student failed to recognize the contributions of others. More fundamentally, the instructor has an obligation not to disadvantage others who may want a second chance to improve a grade.

The decision of the instructor to stand by the grade seems to be ethically defensible and perhaps obvious. However, there is a consequence for the student that may be harmful— namely, failure to graduate. Due to the failing grade, the student may be severely punished by a parent or drop out of high school. This instructor happens to know the student’s parents and is aware of some abusive treatment. In addition. The instructor knows with whom the student associates and how well the student has done in other courses. The instructor believes this student could be successful in college and would like to see the student continue education after high school.

Given that knowledge, the instructor now confronts an ethical dilemma—namely, promote benefits and minimize deficits for this student or make fair and open assessments for all students. As Jonassen (2007), ethical dilemmas are challenging. For some, this situation may not seem like a dilemma, but for others it may well be a difficult decision making process. Regardless of how one may perceive this imagined situation, it is clear that the instructor should not decide based on what is easy or convenient for the instructor. What is best for this and other students should be the primary consideration. What might be good for oneself is seldom the primary ethical perspective. Ethical decision making is often other directed rather than being self-directed. There is a self-directed aspect to ethical decision making, however. Basically, that aspect involves reflecting on the kind of person one is becoming on account of the decisions and choices one is making.

Concluding remarks

Some will be inclined to say that this approach to ethics in educational technology is unnecessary or is making something that is quite simple more complex than it needs to be. Ethical decision making in any aspect of life is quite challenging and complex. Ethical decision making should be introduced early and often in the development of a child.

Simply adhering to a law, rule, policy, or guideline involves no ethical decision making. Recognizing the many interacting aspects of a situation is a step toward understanding how different people, values and ethical principles might guide desirable behavior and the responsible conduct of using and studying educational technologies. A suggested earlier in this paper, the attitude that might inform values and ethical principles is the notion that we can do better with regard to supporting learning, improving instruction and understanding how best to make effective use of educational technologies. We can do better.

References

APA. (2010a). Ethical principles of psychologists and code of conduct. Retrieved from file:///C:/Users/jms/ Documents/PDFs/apa-principles.pdf.

APA. (2010b). The publication manual of the American Psychology Association. Washington, DC: American Psychology Association.

Dijkstra, S. (2004). Theoretical foundations of learning and instruction and innovations of instructional design and technology. In N. M. Seel & S. Dijkstra (Eds.), Curriculum, plans and processes of instructional design: International perspectives. Mahwah: Lawrence Erlbaum.

ICN. (2012). The ICN code of ethics for nurses. Retrieved from http://www.icn.ch/images/stories/ documents/about/icncode_english.pdf.

Januszewski, A., & Molenda, M. (Eds.). (2007). Educational technology: A definition with commentary (2nd ed.). New York: Routledge.

Jonassen, D. H. (2007). Toward a taxonomy of meaningful learning. Educational Technology, 47(5), 30–35. Koszalka, T., Russ-Eft, D., & Reiser, R. (2013). Instructional design competencies: The standards (4th ed.). Charlotte: Information Age Publishing.

Larson, M. B., & Lockee, B. B. (2014). Streamlined ID: A practical guide to instructional design. New York: Routledge.

Merrill, M. D. (2013). First principles of instruction: Identifying and designing effective, efficient and engaging instruction. San Francisco: Wiley.

Reigeluth, C. M. (Ed.). (1983). Instructional-design theories and models: An overview of their current status. Hillsdale: Lawrence Erlbaum Associates.

Spector, J. M. (2005). Innovations in instructional technology: An introduction to this volume. In J. M. Spector, C. Ohrazda, A. Van Schaack, & D. A. Wiley (Eds.), Innovations in instructional technology: Essays in honor of M. David Merrill (pp. xxxi-xxxvi). Mahwah: Erlbaum.

Spector, J. M. (2015). Foundations of educational technology: Integrative approaches and interdisciplinary perspectives (2nd ed.). New York: Routledge.

Spector, J. M., Merrill, M. D., Elen, J., & Bishop, M. J. (Eds.). (2013). Handbook of research on educational communications and technology (4th ed.). New York: Springer.

Woolf, B. P. (Ed.). (2010). A roadmap for education technology [National Science Foundation Grant#0637190]. Washington, DC: National Science Foundation.

Yeaman, A. R. J. (2016). Competence and circumstance. TechTrends, 60, 195–196.

  1. Michael Spector is a Professor and Former Chair of Learning Technologies at the University of North Texas. He earned a Ph.D. in Philosophy from The University of Texas at Austin. His research focuses on intelligent support for instructional design, assessing learning in complex domains, and technology integration in education. Dr. Spector served on the International Board of Standards for Training, Performance and Instruction (ibstpi) as Executive Vice President; he is a Past President of the Association for Educational and Communications Technology as well as a Past Chair of the Technology, Instruction, Cognition and Learning Special Interest Group of AERA. He is editor of Educational Technology Research & Development and serves on numerous other editorial boards. He edited the third and fourth editions of the Handbook of Research on Educational Communications and Technology, as well as the Encyclopedia of Educational Technology, and has more than 150 publications to his credit.

 

Educational Technology Research & Development is a copyright of Springer, 2016. All Rights Reserved.

• What influence does a merger of two companies have on the SF of their PCMS system?

PART ONE: To be completed by the student

Module code: DB8003
Student name:  
Student number:  
Cohort:  
Adviser:  
Date Due:
Submission Date:
 
Extension Date:  
Surnames of module tutors:  

 

PART TWO: To be completed by the marker
Feedback – with reference to assessment criteria and suggestions for improvement

 

An excellent assignment. Very well and clearly structured with concise and convincing arguments.

You demonstrate very good understanding of the different paradigms and come to your own conclusion with regards to your own position.

Well and extensively referenced throughout. Am I right in assuming that you have not read all sources in the original? Sometimes, you indicate that you reference an author by way of another one. Please do this consistently throughout. This is good practice.

 

Well done, keep going and all the best for the next assignment and the thesis as a whole.

Grade : S

Performance: A

I have reviewed this paper and agree with the first markers view. A well thought out and constructed assignment.

 

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MARKING CRITERIA FOR DBA (taught component) ASSIGNMENTS –

This is a guide, not prescriptive nor a mechanical aid to grading. Some aspects, such as research methodology, may not be relevant to all assignments. The grid is a potentially useful starting point for discussion about assignment requirements. Students should ask tutors if there is anything in the grid – or in the attached comments – which they do not understand or is there is additional guidance. Please note – final overall grading is either Satisfactory (S) or Unsatisfactory (UF)

Criteria Grade – S Grade – S Grade – S Grade – S Grade – UF Grade – UF
Performance: A Performance: B Performance: C Performance: D Performance: Redeemable Performance: Fail
Organization

 

Structure

 

Focus

 

Organization of argument

Excellent structure

 

Original/imaginative; high quality selection of material

Very clear focus throughout, clarifying complex issues

Persuasive articulation of argument, displaying academic rigour and scholarly style

Clear structure

 

Well-argued selection of key issues

Very clear focus throughout

Argued fluently throughout

 

Structure adequate but with some limitations

Major issues identified

 

Clear focus throughout

 

Argument cogent and clear throughout

Structure adequate but with limitations

Some major issues identified

Clear focus throughout the majority of the piece

Argument mainly cogent and clear

Limited organization of material, but structure implied

Issues relevant but with minor gaps

Clear but rather limited focus

Reasonable line of argument; occasional inconsistencies/omissions

Poor organization of material obscures the sense of the writing

Some key issues missed

 

Unclear focus, meanders from topic to topic

Tendency to incoherence of argument

Critical appraisal of literature

 


Use of quotation

 

Sources

Scholarly evaluation of the literature

Persuasive and original use of relevant quotation; effective & appropriate use of paraphrase

Impressive and original use of a wide range of relevant and current sources

Substantial and consistent critical appraisal of literature

 

Consistently apposite use of relevant quotation and paraphrase

Shows originality in choice and range of sources; relevance to context consistently considered

Evidence of critical appraisal of literature, though not consistent throughout; some recognition of different perspectives

Effective use of relevant quotation; some suitable use of paraphrase

A variety of sources used effectively to support points; context usually, but not always, taken into account

Evidence of critical appraisal of in relation to part of the literature, limited recognition of different perspectives

Some effective use of quotation; modest use of appropriate paraphrase

A variety of sources used to support points; context sometimes taken into account

Limited criticality; breadth of possible perspectives not explicitly recognized

 

Some relevant use of quotation; inconsistency in quality/use

 

Uses sources in a limited way to support arguments; relies too heavily on single sources

Literature discussed but with insufficient critical engagement

 

Inappropriate choice and/or insufficient use of quotation

 

Very narrow range of sources; barely goes beyond recommended sources; outdated sources

Depth of Understanding

 


Evidence

 

Interpretation and critical analysis

 

Argumentation

 

Impressive and original depth of understanding of topic

 

Highly reflective use of evidence; creation of effective argument in the absence of complete data

Highly critical and reflexive analysis

 

Convincing synthesis of evidence, analysis and understanding, demonstrating informed judgement on complex issues

Thorough and comprehensive understanding of topic

Considered weighing of evidence

 

Thorough and sustained critical analysis

 

Convincing synthesis of evidence, analysis and understanding in argumentation

Thorough but not comprehensive understanding of topic

 

Arguments sustained by reference to relevant evidence

Issues and theories usually, though not  always, considered critically

Credible argument making good use of evidence, analysis and understanding

Clear understanding of topic

 

Arguments usually sustained by reference to relevant evidence

Issues and theories usually considered though not  sometimes not critically

Credible argument making use of evidence, with some analysis

Conversant with topic but minor gaps or errors

 

Some use of evidence; tendency to express unsupported assertions

Limited interpretation; limited critical analysis

 

Reasonably well argued discussion of topic

Conversant with topic but serious gaps or errors

 

General lack of evidence in supporting arguments

 

Insufficient evidence of deep understanding; insufficient critical analysis

Inconsistent argumentation and/or lack of clarity

Presentation

 

Referencing

Presentation of consistently high quality

 

 

Referencing is always correct

Well presented; typos/errors in punctuation etc. are rare

 

Referencing is always correct

Follows required presentational practices; a few typos/errors in punctuation or grammar

Referencing conventions are used, though occasionally incorrectly

Follows required presentational practices; a few typos/errors in punctuation or grammar

Referencing conventions are used, though incompletely

Usually follows required practice but with some issues to be addressed e.g. typos, punctuation

 

Referencing is variable in quality

Has not followed required conventions; poor proof-reading

 

Many errors in referencing

 

Methodology

(criteria only apply where relevant to assessment task)

Critical appraisal of research design

 

 

Methods and procedures

 

 

Synthesis of analysis with literature

 

Assured and critical discussion of methodology and implications

 

 

Critical and reflexive appraisal of overall research design; shows secure understanding of ethical academic enquiry

 

Displays highly critical, reflective understanding and analysis of methods and procedures used

 

Reflective discussion of convergence/divergence of research findings in context of literature

Clear discussion of methodology, showing understanding of implications

 

Clear critical appraisal of overall research design

 

 

Displays critical understanding and analysis of methods and procedures used

 

Consistently relates and discusses convergence and divergence of findings from research literature

Discussion of methodology, showing awareness of implications

 

Critical analysis of overall research design

 

 

Displays clear understanding and analysis of methods and procedures used

 

Usually provides appropriate discussion of convergence and divergence of findings from research literature

Limited discussion of methodology, though showing awareness of implications

 

Some critical analysis of overall research design

 

 

Displays an understanding and some analysis of methods and procedures used

Some appropriate discussion of convergence and divergence of findings from research literature

Some awareness of research methodologies and their implications

 

 

Critique of research design attempted, with some inconsistencies

 

 

Reasons for choice of methods and procedures stated

 

Limited discussion of convergence and divergence of findings from research literature

No clear evidence of understanding research methodologies

 

 

Poor critique of research design

 

 

Methods and procedures explained, but no reason for choice given

 

Insufficient discussion of convergence and divergence of findings from research literature

 

Submitted in partial fulfilment of the requirements for the degree of

Doctorate in Business Administration

Methodological fundamentals:

Strategic fit of product cost management systems from the perspective of realism, constructionism and interventionism – a paradigm simulation

 

(summative)

 

 
Module code: DB8003 (Summative hand in)
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Module code: DB8003 (Summative hand in)
Student name:  
Student number:  
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Adviser:  
Date Due:
Submission Date:
 
Extension Date:  
Surnames of module tutors:  

 

PART TWO: To be completed by the marker
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Table of Contents

 

Abbreviations                                                                                                                                                    2

List of figures                                                                                                                                        2

List of tables                                                                                                                              2

Abstract                                                                                                                                                             3

1 Introduction                                                                                                                           4

  • Allocation of research perspective debate in research process                   4
  • Assignment goal and structure              5

 

  • Brief overview about research philosophies                                      7
    • Historical background               7
    • Framework to describe research paradigms               8

3 Paradigm simulation on strategic fit of product cost management systems                       12

  • Realist perspective   12
    • Description of realism and selection of traditional realism 12
    • Impact on understanding of research problem, design and researcher’s skills   14
    • Contribution to knowledge   16
  • Constructionist perspective   17
    • Description of constructionism and selection of social constructivism 17
    • Impact on understanding of research problem, design and researcher’s skills   18
    • Contribution to knowledge   20
  • Interventionist perspective   21
    • Description of interventionism and selection of action research 21
    • Impact on understanding of research problem, design and researcher’s skills   22
    • Contribution to knowledge   24
  • Conclusion                                                               25
    • Summary reflections on paradigm simulation   25
    • Impact on choice of approach   26

References                                                                                                                                28

Annex                                                                                                                                        37

Declaration of original content                                                                                                39

Abbreviations

 

PCM: Product cost management

PCMS: Product cost management system/s

PCS: Product cost strategy

SF: Strategic Fit

 

List of Figures

Figure 1: Research process as Martini Glass                                                                             5

Figure 2: Structure of assignment                                                                                               6

Figure 3: Development of research perspectives                                                                   7

Figure 4: Framework with simplified stereotype research perspectives                                      10

Figure 5: Framework to describe research paradigm impact                                             11

Figure 6: Selected research perspectives for assignment                                                     12

Figure 7: Conception of a traditional realist research approach                                        13

Figure 8: Traditional realist background of research topic                                                  14

Figure 9: Sketch of a PCM-Strategy-Fit Matrix                                                                        16

Figure 10: Conception of a social constructionist research approach                              18

Figure 11: Conception of an action research approach                                                        22

List of Tables

Table 1: Impact of research approaches on research problem

Abstract

The purpose of this assignment is to present three alternative research perspectives on the strategic fit (SF) of product cost management systems (PCMS). Specifically, it explores the view of a realist, constructionist and interventionist research philosophy.

In order to develop a joint understanding of terms and meanings in the paradigm debate, a brief historical and terminological foundation is conceptualized prior to the paradigm simulation, applying four dimensions of research: ontology, epistemology, axiology and methodology.

For each perspective then, its impact on research problem and research design is outlined as well as the influence on researcher values and required skills to execute each research design. Explicitly, light is shed on the background of the research topic, the general rationale and purpose of the research, the concrete goal of the research project and the research questions / hypotheses as well as on the research process, applied methodology and the stance towards data. The investigation of the contribution to knowledge ends each paradigm simulation.

Reflections of the observed differences conclude the paradigm simulation enclosing the exposure of the impact on the potential choice of approach supporting Feyerabend’s theoretical pluralism for the research area overall and a pragmatists, purpose-related standpoint for the concrete research project.

1  Introduction

1.1 Allocation of research perspective debate in research process

Research implicitly or explicitly follows a certain process in order to reach the research goal. However, within this process the researcher comes along various decision points how to conduct the research (Burke, 2007; Creswell, 2013), which leads to multiple variations of research procedures impacting the research result and quality (Lee & Lings, 2008, p.5). Questions of subjective or objective research philosophies, deductive or inductive approaches, as well as qualitative or quantitative methods are, amongst others, debated (Ahrens, 2008; Baard, 2010; Fleetwood, 2005; Jönsson, 2010; Moses & Knutsen, 2012; Nonaka & Peltokorpi, 2006).

Although reality shows that research is not a linear but an iterative, spiral or even somewhat messy process (Bryman & Bell, 2015, p.15/87; Lee & Lings, 2008, p.8) several authors argue that there are certain indicators for an ideal research practice.

In terms of process sequence Guba and Lincoln (1994, p.105) hold the opinion that issues regarding research methods are less important to issues regarding research philosophies. Holden and Lynch (2004, p.2) propose that research should not be methodologically led but based on a defined philosophical stance considering the purpose of the researcher, which makes the research process a matter of individual, purpose-related, choice.

Scholars such as Aliyu, Bello, Kasim, and Martin (2014, p.86) point out another aspect of the research process, the appropriate matching of different research steps. They claim that epistemological and ontological choices have to match, which supports the statement that it is important to make philosophical backgrounds of research explicit (Wahyuni, 2012, p.69) as it guides the behaviour of the researcher (Jonker & Pennik, 2010; Lee & Lings, 2008, p.4/5).

Synthesising the various inputs from scholars, the process model shown in figure1 can be derived. It combines a process flow as proposed by Saunders, Lewis and Thornhill (2009, p.11) with the logic of a “progressive narrowing of the topic” (Hart, 2014, p.13), visualized by a “Martini Glass” (Braun, n.d., p.1).

Starting point of this assignment is the research topic “Strategic Fit (SF) of Product Cost Management Systems (PCMS)” as formulated in the Literature Review Assignment. Next step is to define the research philosophy with its implications on the research design. This decision should be prepared with this assignment.

  • Assignment goal and structure

In agreement with Connell and Nord (1996, p.408) there is no general right or wrong of research philosophies and choices have to be justified in each single research case (Aliyu et al., 2014, p.87).

Therefore the assignment has the goal to help define and justify the research philosophy for the dissertation on SF of PCMS as part of management science. Sub goals to do so are to understand the different philosophies first (Lee & Lings, 2008, p. 49/50). Second, the developed understanding should help to advocate the selected research perspective and the choices related to its alternatives (Johnson & Clark, 2006). Finally, it should open up the mind and enhance confidence in the selected approach (Holden & Lynch, 2004, p.13) in order to ensure the quality, e.g. relevance and rigour, of the research undertaken (Aldag & Fuller, 1995; Schön, 1995).

The assignment structure follows a four-step logic. First, the foundation for understanding the major philosophical research perspectives is laid in section 2. Afterwards, three research perspectives are critically described with their impact on the understanding of the research problem and research design, the researcher’s values and required skills as well as their contribution to knowledge in section 3. Summary reflections on the paradigm simulation and its impact on the choice of approach end this assignment in section 4.

Should section 3 be differently labelled in this figure?

2  Brief overview about research philosophies

2.1 Historical background

For the purpose of this assignment a short summary about research perspectives and how they emerged (illustrated in figure4) is given prior to the more detailed exploration of three selected research perspectives in order to develop an understanding of the author’s wording.

As Goles and Hirschheim (2000) state, there are “two essential problems in science”            (p.250), the questions of “how do we know what we know” and “how do we acquire knowledge”, which are addressed by different research perspectives.

Whereas in natural science the positivist view is pre-dominant, in social science the situation is not that clear to answer and subject for debate (Fendt, Kaminska-Labbé, & Sachs, 2008). The positivist view claims that there is an objective reality / truth independent from the researcher, which can be measured in order to gain knowledge, whereas non-positivists, especially in social science, argue that knowledge is conditional, relative and therefore subjective (Aliyu et al., 2014, p.81/82). For social science, post-positivists developed alternative views on research philosophies, trying to create more suitable approaches for research (Aliyu et al., 2014, p.83/84).

Seminal works of Kuhn (1962) or Burrell and Morgan (1979) have stimulated a controversy and ongoing debate about competing research paradigms as alternatives to the positivist view, cumulating in what is nowadays called the “paradigm war” (Datta, 1994; Klaes, 2012; Shepherd & Challenger, 2013; Tashakkori & Teddlie, 1998). Tsoukas exemplifies this debate with the discussion between Ansoff (1991) and Mintzberg (1990, 1991) about strategy knowledge, positioning Ansoff as mechanistic and Mintzberg as a contextualist (Tsoukas, 1994, p.761). This example illustrates the meaning of a paradigm in Kuhn’s sense to share basic assumptions about core beliefs and values in research as well as e.g. “unspoken norms, taken-for-granted assumptions, and implicit codes of conduct” (Anderson, 1998, p.32).

Baum and Dobbin (2000, p.390-391) list major benefits of a common ?? paradigm in science referring to authors such as Pfeffer (1993), which can be summarized as to facilitate scientific progress, e.g. in terms of easier communication, evaluation of results or coordination of research activities.

As one trigger for the intensive debate about and diverse advancing of research paradigms was Burrell and Morgan’s claim about the incommensurability of paradigms (Shepherd & Challenger, 2013, p.225), two ways to overcome have been added to the paradigm debate: multi-paradigm perspectives (Gioia & Pitre, 1990) and paradigm interplay (Schultz & Hatch, 1996). Both views claim that a single research perspective might be too narrow to comprehensively cover the complexity of social reality (Feyerabend, 1985; Willmott, 1993). Tashakkori and  Teddlie finally see pragmatism as an attempt to make use of “whatever philosophical … approach … works best for the particular research” (1998, p.5), with the specific, individual research topic as starting point as the opportunity to end the pointless paradigm war (Goles & Hirschheim, 2000).

2.2 Framework to describe research paradigms

Although paradigms have been and still are heavily debated, to date there is no common agreed definition but a widespread, sometimes confusing, use of the term “paradigm” and their characteristics with different meanings (Guba, 1990a, p.17; Mkansi & Acheampong, 2012), rooting back to Kuhn himself, who used the term with more than 21 different meanings (Masterman, 1970). On the opposite, as Hassard (1988, p.248) states, synonyms for the term “paradigm”, such as “perspective”, “school”, “discipline” or “worldview” have randomly been used and applied, reflecting the “individual nature of paradigm-building” (Lincoln, 1990, p.67; Charmaz, 2008). Taking up this practice, within this assignment paradigm, philosophy, approach and perspective are used as synonyms, whereas other terms are avoided for the purpose of simplification.

Resuming the two essential problems in science concerning knowledge and how to gain knowledge as mentioned above, research paradigms can be described using mainly four different “ologies”, which are, with different emphasis, used by scholars: ontology, epistemology, axiology and methodology (Easterby-Smith et al., 2012, p.17ff.; Mouton & Marais, 2003; Neuman, 2014, pp.91-124; Sobh & Perry, 2006).

Ontology is consistently defined as to be concerned about the scientist’s assumptions about “the nature of reality” (Lee & Lings, 2008, p.11; Saunders et al., 2009, p.110; Easterby-Smith et al., 2012, p.17). In doing so, it forms the basis for most debates on research perspectives and is the core of a researcher’s set of beliefs. Saunders et al. (2009, p.110) simplify the ontological debate, being framed between objectivist and subjectivist views. Proponents of the objectivist view claim that the nature of reality is independent of our individual perception, so that an objective reality exists “out there” (as a dictum), whereas advocates of the subjectivist view hold the opinion that reality is (mind-inter-)dependent and created by humans’ perceptions (Holden & Lynch, 2004; Sayer, 2000, p. 2).

Epistemology should derive from an ontological position (Lee & Lings, 2008, p.11) and describes ways how to inquire the nature of the world, being stereotyped with positivism and constructionism (Easterby-Smith et al., 2012, p.21/22). Remenyi, Williams, Money, and Swartz (1998, p.32) explain positivism as aiming for observable and measurable inquiry of the reality leading to law-like generalisations, comparable with outcomes of the natural sciences. The opposing stereotype, constructionism, emphasises “on the ways that people make sense of the world especially through sharing their experiences” (Easterby-Smith et al., 2012, p.23) leading to the appreciation of different interpretations and meanings of individuals.

Axiology should also be aligned with the other “ologies” and addresses “in essence … the ‘aims’ of your research”, “the overriding goal” (Lee & Lings, 2008, p.11/59), what is valued by the researcher and whether or not researcher’s values play an important role in the research (Saunders et al., 2009, p.117). In a nutshell, a researcher either aims for explanation and prediction of the reality, which is value-free, or alternatively for understanding and description of the reality, value-bound, taking a corresponding etic or emic position towards research (Wahyuni, 2012, p.70).

Methodology finally completes the description of different perspectives by most commonly distinguishing quantitative and qualitative approaches (Bryman & Bell, 2015; Lee & Lings, 2008, p.12) describing two ends of a continuum with mixed methods approaches in between but without a “discrete” distinction (Creswell, 2013, p.3). An alternative scheme to classify methodological approaches is to separate nomothetic ways of inquiry and ideographic methods (Holden & Lynch, 2004, p.5), the latter one more matching with qualitative, the first one more resembling the quantitative approach.

Figure4 illustrates in a simplified dichotomous way (Zuber-Skerritt, 2001, p.5) two stereotype research perspectives, indicating that each stereotype combines in a meaningful way the peculiarities of ontology, epistemology, axiology and methodology.

Nevertheless, it has to be underlined that this introductory section on research perspectives aims only to prepare the ground for the in-depth paradigm simulation by defining structure, content and wording. More detailed explanations or debates (e.g. Baert, 2015; Guba, 1990b, Morgan & Smircich, 1980) are left out due to space limitations.

To complete the framework for this assignment, next to the research perspectives and how to describe them in a meaningful way, key dimensions of what they impact in terms of understanding of the research problem and design should be explained prior to the investigation in the next section.

At the same time it can be stated that debates about what aspects to include or not when outlining the impact are less intense compared to the paradigm debate and thus less discussed in this assignment. Comparing e.g. text book structures / frameworks from Easterby-Smith et al. (2012), Saunders et al. (2009) and Hallebone and Priest (2009), it can be concluded that they share similar and overlapping aspects.

Hence, in terms of understanding of the research problem, attention in this assignment is directed mainly to the background of the research topic, the general rationale / purpose of the research, the concrete goal of the research project and the research questions / hypotheses to be developed. Besides this, the impact on research design will be detailed with emphasis on research process, applied methodology, approach towards data and researchers values. Finally, a glimpse into the two major required skills for each approach is taken. These key elements of the assignment are illustrated in figure5.

Importantly it is stated, that the description of these aspects in the paradigm simulation in section 3 does not qualify for three distinct and completely cohered research proposals one after the other. Conversely, the examples within one paradigm are loosely, if at all, connected in order to elucidate the differences between the different paradigms selected.

3  Paradigm simulation on strategic fit of product cost management systems

From the variety of different research perspectives, three have been selected (see Annex: Assessment brief) in order to develop a first glimpse into their implications on the research topic SF of PCMS. These three philosophies are the realist, the constructionist and the interventionist perspective.

For all three, as a first step, a general description of the specific perspective is outlined prior to the selection of one particular sub-perspective. Afterwards their impact on the understanding of the research problem and the research design and the researcher’s skill is explained, followed by a description of their potential contribution to knowledge.

3.1 Realist perspective

3.1.1 Description of realism and selection of traditional realism

Realism in social sciences has “as an approach with its own specificity … developed since the mid-1970s” (Burrows, 1989, p.46) with Bhaskar (1975, 1986) as one of the early proponents and influencing authors. Ackroyd and Fleetwood state that “entities exist independently of us and our investigations of them” (2000, p.6), indicating that it is the objectivist ontological position which distinguishes the realist paradigm from other paradigms.

 

Whereas this ontological position coheres realist scholars, the epistemological stance is “relatively open or permissive” (Sayer, 2000, p.32) although not ignored (Ackroyd & Fleetwood, 2000, p.6). While traditional (classical, naive) realists claim that only observable / measureable phenomena can create knowledge by focussing on causality and law-like generalisations, internal realists hold the opinion, that reality cannot be observed directly and only indirect evidence can be generated (Easterby-Smith et al., 2012, p.19; Wahyuni, 2012, p.70). Consequently, observations and measurements on the empirical domain can be misleading, so that explanations of mechanisms and contexts are included (Saunders et al., 2009, p.119; Wahyuni, 2012, p.70).

 

In terms of axiology realist perspectives are either value-free (traditional, classical, naive realism) or value-laden (critical realism) if the research “is biased by world views, cultural experiences and upbringing” (Saunders et al., 2009, p.119). The latter holding an intermediate position between value-free and value-bound as it corresponds to the ontological position that there is an external, objective reality, however interpreted and therefore biased by researchers. Indeed, critical realism “acknowledges differences between the real world and their particular view of it” (Sobh & Perry, 2006, p.1200), while traditional realists, focussing on causality and law-like predictions, consequently have to adopt a value-free, etic position in order to advocate the independence of reality from the researcher (Wahyuni, 2012, p.70).

Methodology in realism paradigms finally either emphasises quantitative, nomothetic approaches (e.g. for traditional realists to proof the developed law-like generalisations) or, as critical realists do, also make use of qualitative techniques, when focussing on the explanations within a context (Wahyuni, 2012, p.70). Methods such as forecasting research, laboratory experiments, large-scale surveys, simulations or stochastic modelling are core elements in realist’s research (Holden & Lynch, 2008, p.8)

In order to create a certain breadth in this assignment about paradigm simulation the realist perspective is selected which is most opposed to the constructionist or the interventionist view: traditional realism. In taking up the above outlined description of realism, the traditional realist can be characterised as shown in figure7.

3.1.2 Impact on understanding of research problem, design and researcher’s skills

Beginning with the impact on the research problem regarding the topic’s background, the traditional realist’s objectivist ontology implies the independent, actual existence of SF and PCMS as objective mental objects. The corresponding (post-)positivistic epistemological position furthermore entails the opportunity that these constructs are both, observable and measureable and, indeed, contribute to causality, impacting the performance of an organisation.

This causality can be expressed in a reductionist way stating: “If A fits to B, then C,” or more elaborated in a post-positivistic sense, which allows, next to strict causality of positivism or Poppers falsicism also correlations/probabilities (Creswell, 2013, p.7; Lee & Lings, p.31/32): “The better A fits to B the more likely is C”, A being the product cost strategy (PCS), B the product cost management configuration and C the company’s performance (figure8, adapted from Abernethy & Guthrie, 1994, p.53).

The rationale behind this understanding of the research topic is that even though it has been claimed by several authors that PCS influences the PCMS, there is a gap in existing knowledge in linking both and, moreover, create a normative conclusion towards the performance of a company. This normative conclusion, deriving from the traditional realist stance would then be the general purpose of the thesis. Taking up above introduced formula, connecting A, B and C together the characterising, normative and simplified law-like-generalisation: “If you want to achieve C (Performance), than A (PCS) and B (PCMS) have to fit” could be derived.

 

In order to continue the paradigm simulation, concrete goals of a traditional realist perspective accordingly could be, to…

  • …determine different levels of SF between PCS and PCMS
  • …define the correlation between SF of PCS and PCMS and company’s performance
  • …calculate the effect the fit of PCS and PCMS has on the performance of companies.

Subsequently, corresponding research questions and hypotheses could be derived as follows, starting with the research questions:

  • Which PCMS can be identified?
  • What is their SF fit to a defined set of product cost strategies?
  • What is the contribution to business performance of fitting PCMS vs. non fitting systems?

Hypotheses of a traditional realist can be exemplified with the following set:

H1: Product costs vary in their importance as strategic success factor over different cost strategies depending on different external factors

H2: The maturity level of PCM activities in companies varies over time and differs between companies.

H3: Comparing the specific importance of product costs and the corresponding maturity level of companies in PCM, there is no one-to-one correlation, but…

H3a: there are companies, being less mature in PCM than they have to

H3b: there are companies, showing an appropriate match between strategic relevance of costs and their actual PCM maturity level

H3c: there are companies, being more mature in PCM than they have to

H4: The better the maturity level fits to the importance of product costs as success factor, the better the performance of the company.

 

Continuing with the description of the impact of the chosen research perspective concerning the research design, the research process typically follows a hypothetic-deductive two-step-approach with prior theory first to develop a conceptual framework, possibly including generation of hypotheses, which then in step 2 are aimed to be confirmed (Holden & Lynch, 2008, p.8; Sobh & Perry, 2006, p.1201-1202).

With respect to methodology of the traditional realist (see e.g. Easterby-Smith et al., 2012, p.25/72), the verification of the hypotheses will be executed mainly making use of quantitative methods, possible defining dependent and independent variables. In the example given through the conceptual framework above, the independent variable could be the SF, whereas the dependent variable could be the business performance. For both, quantifiable measures have to be defined and a meaningful statistical procedure, e.g. regression analysis, to be developed to examine the relationship between the variables. The relationship normally would be tested in a survey with a defined sample according to adequate size (large) and structure (representative).

This set up already indicates the traditional realist’s stance towards data and his/her own values. As the data, is “out there”, independent from the research, the data can be collected with the appropriate measurements / methods, reducing the research topic to measureable variables. Data about the relationship between SF and business performance can be obtained from an external perspective, taking an etic position of the researcher and, as the relationship is independent from the researcher, the research is also value-free. It is the deterministic nature of the relationship between SF and performance of the classical realist approach why the researcher’s values do not matter, because reality is independent from the researcher.

This determinism is also one major influencing factor for the needed researcher’s skills. In order to set up adequate measurements and proper analysis, researchers must have conceptual expertise to operationalize the research questions, means to reduce the complex reality down to a few measurable entities. Furthermore, after having selected a meaningful analysis method the right conclusions from the collected data have to be drawn, which is also a competence, exclusive versus the two other paradigms due to the highly quantitative nature of the realist’s approach (Bryman & Bell, 2015, pp.157-387).

 

3.1.3 Contribution to knowledge

To discuss the contribution to knowledge of the traditional realist approach as described above, a potential outcome should be summarized first by charting a Strategy-Fit-Matrix which could be derived from the research questions / hypotheses (figure 9, Maxion, 2015).

In this matrix it is assumed for the momentthat the postulated fit between PCS and PCMS could be measured by comparing the importance of product cost as a strategic success factor and the maturity level of PCMS.

The contribution to theory would be twofold. First, to close the research gap of a currently missing PCMS described by different maturity levels, combining two sub aspects: The first sub-aspect as the explicit research on product costs as object of cost management (which has received comparably low attention so far) and the second as a comprehensive view on cost management instead of isolated investigation of single aspects to date. The second main contribution would be to extend the existing concept of SF to the field of product costs, which would, in turn, further advance this concept as part of research on strategic success factors.

 

The contribution to practice would be to develop a normative guide for managers how to configure PCMS in order to enhance business performance, representing three sub cases: define the proper PCMS, avoid excessive effort, as not necessary, or intensify efforts in order to meet the requirements from product costs being a strategic success factor. In doing so and to bring matters to the head of the traditional realist approach, the impact of the SF on the company’s performance could be indicated. Exemplary an ultimate finding of a dissertation according to the traditional realist approach could be: “Companies which show a SF between PCS and PCMS higher than X% achieve Y% higher EBIT, compared to companies with a SF less than X%”.

3.2 Constructionist perspective

3.2.1 Description of constructionism and selection of social constructionism

Constructionism as a research paradigm in social science emerged in the 1960s as a response to the criticism which was postulated against the positivist approach (Gubrium & Holstein, 2008, p.3; Lincoln, 1990). The fundamental difference lies in the subjectivist ontological position as opposed to the objectivist view of positivism or realism (Saunders et al., 2009, p.116; Neuman, 2014, pp.91-124). Moreover, this fundamental distinctive feature of constructionism is so outstanding, prompting Guba to claim, that constructionists “celebrate subjectivity” (1990a, p.17).

Although for constructionism it is difficult to provide a single definition due to the diverse use of similar / related terms such as constructivism or interpretivism, which are often used as synonym (Moses & Knutsen, 2012, p.9; Bryman & Bell, 2015, p.33; Hallebone & Priest, 2015, p.113; Greene, 1990, p.233), different “sub-perspectives”, such as hermeneutics, phenomology, foucauldian, social, discursive, critical constructionism or existentialism (Lee & Lings, 2008, p.60-64; Holstein & Gubrium, 2008) share same basic beliefs with regard to the four “ologies” (Gubrium & Holstein, 2008, p.5).

With respect to the ontological position of constructionism, the subjective character of this research paradigm is the belief that there is no objective, independent reality “out there” but that reality is constructed, interpreted and reconstructed by individuals (Chua, 1986, p. 615) or even, in an extreme position, only a “projection of human imaginations” (Morgan & Smirich, 1980, p.492). Thus there are multiple realities, dependent on the individuals’ interpretations, which are, on top, constantly changing (Saunders et al., 2009, p.119; Van der Meer-Kooistra & Vosselmann, 2012, p.251).

This subjectivist ontological belief of constructionism is then manifested in the epistemological position as the conditional, idiosyncratic nature of knowledge. Knowledge is context-related and ??? cannot be obtained by observing and measuring but by experience and reflection in relation to different contextual factors (Moses & Knutsen, 2012, p.10). Therefore the exploration of differences and differentiation is emphasised and not the aim to unify knowledge in law-like generalisation (Saunders et al., 2009, p.116).

The constructionist’s axiological view consequently is a value-bound position, taking an emic approach towards the research as the reality is not independent of the observer, but in contrast interpreted in interaction with the subjects being observed (Lee & Lings, 2008, p.60; Holden & Lynch, 2004, p.9). Not cause-and-effect to predict the reality but meaning-and-understanding to describe the reality are the researcher’s overarching goals. The central nature of the goal to understand reality in constructivism is condensed in the German term “verstehen” which is even used in the English paradigm debates to elevate the distinct focus of this approach (Lee & Lings, 2008, p.59). In doing so, the assumption is that the researched problem is best understood, if investigated comprehensively from different point of views and not if reduced to a few variables (Holden & Lynch, 2004, p.9).

To end the description of constructivism as research paradigm, the methodological aspect contains mainly qualitative, ideographic approaches but is not limited to those (Lee & Lings, 2008, p.65). Methods such as ethnography, game role / playing, participant-observer techniques or in-depth-interviews are allocated to constructionist approaches, stressing the emic and dialogic position of the researcher (Hallebone & Priest, 2009, p.35/76; Holden & Lynch, 2004, p.8).

Out of the various different constructionist sub-paradigms social constructivism is selected for the paradigm simulation as it is one of the paradigms which is highlighted as an opposing alternative to the dominant realist / functionalist paradigms in management science and organization studies (Samra-Fredericks, 2008, p.129). In taking up the above outlined description, the social constructivist can be characterised as shown in figure 10.

3.2.2 Impact on understanding of research problem, design and researcher’s skills

Applying the same categories as for the traditional realist perspective to illustrate the social constructionist’s impact on the research topic “Strategic Fit of Product Cost Management Systems” the background of the topic derives from the inherent subjective ontological stance. SF, seen from the perspective of social constructionism, is not a given mental object, independent from actors, neither is strategy or PCMS, but virtually a construct, interpreted by those various and multiple individuals which experience the SF.

Consecutively, due to the individuals’ different contexts and interpretations which are, on top, possibly interacting, SF is not seen as a constant but an evolving and multifarious phenomenon even more possibly occupying different meanings. These different interpretations and meanings of the idiosyncratic nature of SF are in focus of the researcher’s interest in terms of understanding and describing.

This background indicates as well the rationale and the purpose behind the topic. In order to understand the nature of SF, the researcher would deep-dive into the topic to gain an as comprehensive view as possible, investigating external and internal context factors of actors which impact or are impacted. Differences in meanings and interpretations would be explored in order to describe characteristics of SF – and not to predict it – as well as to generate theory, not to verify it.

The conceptual framework would considerably change compared to the traditional realist view. Not the causality would be the centre of the framework but the “verstehen” of the construct of SF.

In order to continue the paradigm simulation, concrete goals of a social constructionist perspective hence could be, to…

  • …explore the characteristics of SF of PCMS from the perspective of product management, controlling and engineering
  • …understand the perception of SF of PCMS by management functions and operations
  • …explain the emotional, cognitive and intentional implications of the SF of PCMS on product managers

 

Successively, corresponding research questions could be derived as follows:

  • Are there, and if, which, characteristics of SF of PMCS are perceived by different operational functions in companies?
  • How is the SF of PCMS evaluated by management / operational functions?
  • How does the SF of PCMS affect product manager’s behaviour?

Hypotheses would not be generated prior to the research but might be formulated as a result of the research, which is a matter of the research design, more specifically, the research process. For the social constructivist an inductive research process is in general characterised, as “the social constructionist ontology necessitates gaining data on how individuals construct reality” (Lee & Lings, 2008, p.65). Furthermore, a central iterative phase is characterising for social constructionism, including data generation and analysis, validation and synthesis (Hallebone & Priest, 2009, p.56/58). This iterative stage affects the process as a whole by making it impossible to plan the research process to the end; indeed, some parts of the research process would be open-ended (Easterby-Smith et al., 2012, p.73).

This iterative research process is mirrored in the methods by which the researcher interacts with the actors, typically dialogic methods such as interviews. This underlines the emic position of the researcher, his/her role and own interpretations of what interviewees or focus groups would express. Continuing with the research question examples, one might openly ask product managers about the implications of the SF of PCMS. This might lead to an interpretation of the researcher, to continue with a certain focus in a second row of interviews, e.g. emotional aspects as most answers / comments have been given related to “frustration”, “anger” or “satisfaction” towards working atmosphere.

With respect to data, in doing so, the social constructionist approach towards SF of PCMS would not exclude quantitative methods like in this case simple counting (Lee & Lings, 2008, p.65). Emphasis on the other side would be on the generation of qualitative “rich data”, based on small samples to contribute to the main purpose, the understanding of the construct of SF.

Finally, in the described set up of the social constructionist researcher, her/his values do play an important role. While interpreting the actors interpretation, the researcher brings in own meanings, own understandings which are biased by the researcher’s own contexts, creating an individual understanding from the value-bound position. Intentionally or not, the construct of SF of PCMS might be described from a point of view the researcher is most familiar with (Charmaz, 2008, p. 402).

The researcher’s skills, which are most unique versus those of the other two paradigms, derive from the distinct research focus of the social constructionist, meaning instead of measurement by interacting with others to condense their different interpretations. This suggests that the researcher should have a highly distinctive self-awareness, yet empathetic stance in order to avoid unintentional personal bias while interpreting other people’s interpretation of the world (Saunders et al., 2009, p.116). Secondly, the competence to sensitively recognize and work out what e.g. interviewees really mean, but might not be able to communicate, is critical to the research outcome as well.

3.2.3 Contribution to knowledge

Foundation for the evaluation of the contribution to knowledge is the potential outcome of the social constructionist research. Continuing with the simulation and assuming that answers to the research questions as exemplified above are found, the outcome would be a description of characteristics and perceptions of SF fit of PCMS possibly differentiated between different functions or hierarchical levels in a company. Also a narrative about emotional, cognitive or intentional implications of the (missing) fit on product manager’s behaviour would be a result of the social constructionist’s research.

The contribution to theory could be allocated in those research streams of cost management in which strategy- or personal-related issues are investigated such as motivation, participation, implementation barriers or interdisciplinarity of work organization and management commitment (Shields & Young, 1991; Konle, 2003; McGowan & Klammer, 1997; Krüsi Schädle, 2001; Franz & Kajüter, 2002a/b; Himme, 2008; Kim, Ansari, Bell, & Swenson, 2002; Stoi, Horváth, & Reichmann 1999). The exploration of characteristics and perception of SF in PCM would be novel to that research area and contributing to the understanding how strategic aspects, which are claimed to be an important influencing factor (Kajüter, 2000, p.14), impact individuals minds and possibly behaviour. A theory, e.g. that the SF of PCMS is perceived in a more emotional and a more negative way by product managers compared to the perception of top management might be generated after having understood in more depth the characteristics of SF by different functions.

For management practice the contribution would be to make use of the enhanced understanding of the strategic fit’s implications / characteristics as perceived by different roles, either e.g. different functions, different hierarchical levels or even different stakeholders such as customers or suppliers. If managers are concerned, worried or interested in the SF of their PCMS, they would benefit from an increased understanding of the nature of this fit. However, as social constructionist’s research is partly open-ended, the contribution to practice is so, too.

3.3 Interventionist perspective

3.3.1 Description of interventionism and selection of action research

Interventionism as the third of the selected research paradigms goes back to the influential work of Lewin (1946; 1948, as cited in O’Brien, 1998; Fendt et al., 2008, p.482; Suomala, Lyly-Yrjänäinen, & Lukka 2014, p.305) as one prominent advocate.

 

Emerging in management science during the last years of the 20th century, the research perspective is not only a response to positivism but also to constructionism by those scholars who “felt that the constructivist stance did not go far enough” (Creswell, 2013, p. 9) to develop a meaningful alternative to positivism and to narrow the relevance gap between practice and academic theory (Lukka, 2006, p.36; Westin & Roberts, 2010, p.8). Research approaches within interpretivism are e.g. (participative) action research, (critical) action learning, co-operative inquiry, experiential learning (Easterby-Smith et al., 2012, p.49/50; Heron 1996; Howell, 1994).

 

Although this paradigm is comparably new, still in development and therefore knowledge about the approach still is in its adolescence, a distinguishing feature of interventionist research approaches is the intervention of the researcher itself as an actor in organizational contexts (Argyris, Putnam, & Smith, 1985; Babüroglu & Ravn, 1992; Suomala et al., 2014), which does have implications for the four ologies of research paradigms.

 

The ontological and epistemological position of interventionist research is close to the interpretive stance “where understanding and knowledge is built on close interaction and communication between practitioner and the researcher” … and … “socially constructed by that interaction” (Westin & Roberts, 2010, p.7-8). Nonetheless, in terms of epistemology the intervention itself sheds light on two distinct beliefs. The first one claiming that in order to understand and get in touch with reality the researcher has to make his/herself part of the reality (Hastrup, 2005, p.141), the second that reality can only be understood, when it is changing by investigating “what” changes and “how and why” changes evolve (Creswell, 2013, p. 9; Van de Ven & Poole, 1995; Westin & Roberts, 2010, p.8).

 

With reference to axiology, interventionists have to be effective in the emic (being an insider of the subject under investigation) and etic (to link outcome to theory) way (Suomala et al., 2014, p.305). In Interventionism, the researcher does not only influence the research by creating contact points with social actors in order to investigate their interpretations and interpreting the already interpreted reality through own values. Furthermore, the researcher becomes one with reality, participating and actively impacting other actors / reality. Then again, the researcher has to step back in order to reflect and to develop findings and theories, although they derive from value-laden positions.

From the methodological point of view, due to the diversity of different research designs, neither qualitative nor quantitative approaches seem to dominate. The uniqueness of interventionist’s research contexts and the aim to gain deepest insight and knowledge are arguments to imply the combination / mixed use of qualitative and quantitative methods under the umbrella of longitudinal case studies (Suomala et al., 2014, p.305).

 

In order to indicate the interventionist’s impact on the research topic, an action research approach is sketched next with a simplified description as shown in figure11. However, is has to be stated, that scientific debates about the nature and implications of interventionism is still in its infancy / puberty years (Westin & Roberts, 2010), so there is no claim for a generalised view by this selection of “ological” implications.

3.3.2 Impact on understanding of research problem, design and researcher’s skills

An action researcher’s background of the topic “Strategic Fit of Product Cost management Systems” would consider the fit as being a subjective und unique matter of an organization which needs to be investigated over time. The SF would best be understood, if any aspect, constituting the fit, would change.

The general rationale behind and purpose of the research would be, that if the SF would change for any reason, this would have consequences and implications, which could be investigated by actively participating in the organization. The change could be stimulated actively during the research by initiating the change, e.g. re-define the PCS, or by re-actively investigate the topic after a change has already occurred, e.g. a PCM department was implemented.

Consequently, concrete research goals of an action research could be, to…

  • …transform a company’s PCMS after the change of the company’s product cost strategy
  • …restructure the PCM department in order to better fit to the product cost strategy
  • …align the different PCMS after the merger of two companies to better fit to the joint product cost strategy

Subsequently, corresponding research questions could be derived as follows:

  • How does the strategy change in company X affect their PCMS?
  • What are essential barriers for SF, when restructuring a PCM department?
  • What influence does a merger of two companies have on the SF of their PCMS system?

The interventionist character of action research also has a significant impact on the research design. Zuber-Skerritt (2001) points out the similarities of action research and action learning, shedding light on the research process, which can be divided into a phase model, based on the Lewinian Model of Action Research and Dewey’s Model of Learning (as cited in Kolb, 1984, p.21-23). According to these prominent scholars, four phases might be distinguished, commencing with the active participation and observation of an action, the subsequent reflection and sense-giving of that observation, which is the core of the action research, and ending with a conceptualisation or generalisation as the outcome, being possibly a theory. In order to test the theory, a new cycle of participation/observation would start, leading to a spiral research process to further develop theory.

 

Derived from the focal point in this process, the reflection, reflective tools are under special attention as methods in action research, e.g. portfolios, conversation / dialogue, journal writing, concept mapping, case records, shadowing and reflective interviewing (Bruce, 1999; Gray, 2006; Kottkamp, 1990).

 

The impact on data and researcher’s values is similar to the constructionist paradigm, with a nuance, that the researcher’s value are even more obvious in action research, as the researcher steps out from his/her role as an observer and takes over active roles such as catalyst (Dumay, 2010) or liberator (Sunding & Odenrick, 2010) as Westin and Roberts (2010, p.9) point out.

Condensing the various implications of the action research approach, the impact on the researcher’s skills is different compared to the other approaches, too. One of the critical skills characteristic for action research is the “ability to … conceptualize the particular experience” (Eden & Huxham, 1996, p.79).  More specifically, as the reflective phase has an outstanding importance in action research approaches, compared to other paradigms, the researcher should show highly reflective skills in terms of methodology. In addition, the paradigm’s inherent feature to include “numerous sources of tensions” leads to the necessity to balance different interests, agendas or resistance e.g. trough building trust, which is a social competence the research needs to have (Suomala et al., 2014, p.312/313).

3.3.3 Contribution to knowledge

Taking up the similarity of action research / learning, the outcome of action research is learning while producing theoretically grounded solutions, which is condensed in theory building (Suomala et al., 2014, p.305; Westin & Roberts, 2010). These theories develop incremental in small steps as emergent theories being “a synthesis of what emerges from the data and … the use in practice of the body of theory which informed the intervention” (Eden & Huxham, 1996, p.80).

In the case of SF of PCMS, action research would deliver a contribution to theory as a novel theory based on the generalization of experiences reflected in a particular restructuring/ strategy project on PCM in which the researcher actively participated. The action research would produce highest quality research materials including nuanced data (Suomala et al., 2014, p.311). On top, there is the opportunity to narrow the relevance gap as the researcher takes over a practitioner’s agenda, which is a radical challenge of research paradigms compared to the other two perspectives (Fendt et al., 2008, p.472).

The contribution to practice is not far to seek: due to the nature of the intervention, the change which is implemented, there should be an immediate “improved practice” triggered by the research project (Jönsson, 2010, p.124) which is explicitly designed to impact practical issue as it “puts managerial problems under critical scrutiny in order to resolve them” (Lukka, 2006, p.36).

A final differentiator for action research as an interventionist paradigm lies in its relative novelty as approach in management science, as “knowledge of the interventionist alternative … is still in its adolescence” (Suomala et al., 2014, p.305). An action research dissertation in the field of PCM would for that reason, assuming research design and process are published and debated, contribute to the development and advancement of the paradigm itself, a “meta-contribution to theory”.

4 Conclusion

Having critically outlined the impact of the three selected research approaches on research problem, design, researcher’s values and required skills including differences with respect to particular defined points, now concluding reflections should be summarized and the impact on the choice of approach portrayed. Basis for this summary is table 1 in the annex, p. 38, consolidating the major findings of the paradigm simulation for each approach.

  • Summary reflections on paradigm simulation

Main trigger for the paradigm simulation was the ongoing paradigm debate, primarily discussing whether one or another alternative is (more) scientific compared to the other(s). Anderson, Herriot, and Hodgkinson for example distinguish four different types of science based on their theoretical and methodological rigour and their practical relevance (Anderson, Herriot, & Hodgkinson, 2001; Hodgkinson, Herriot, & Anderson, 2001).

The inclusion of the latter, practical relevance, as a criterion of science can be understood as a reaction to overcome the postulated relevance gap of science, especially in management science (Fendt et al., 2008; Tucker & Parker, 2012, 2014). Since then, a contribution to practice, e.g. new insights or normative guidelines or practical application, are demanded by scientific work (Ghoshal, 2005; Gibbons et al., 1994; Hambrick, 1994, 2005; Huff, 2000; Ittner & Larcker, 2002; Shrivastava, 1987).

Likewise, a contribution to theory is claimed since long for contributing to “good” science deriving from the former criterion, rigour. Whereas there is agreement about the requirement itself, less harmony has to be stated about the opinions what constitutes rigour or a theoretical contribution (Whetten, 1989; Wright, 2015). Emphasis is put mainly on the difference between qualitative and quantitative research approaches being evaluated by different criteria of rigour such as reliability, validity, replicability, generalisability for quantitative and credibility, transferability, dependability, confirmability for qualitative research (Wahyuni, 2012, p.76/77; Lincoln & Guba 1985; Parker, 2012).

Reflecting the differences of the three research philosophies which became obvious in the paradigm simulation focussing on the research problem and the research design, they can be mirrored versus rigour and relevance. Although three completely different approaches have been sketched, with, summarized in the Annex, almost no single equality regarding the described categories, they do have in common three general characteristics.

First and foremost, as the basis for subsequent arguments, for each of the paradigms a research problem incl. concrete goals and research questions can be developed. Secondly, consistent and meaningful research designs built on the research questions were outlined, potentially leading to, thirdly, defined outcomes which contribute to theory according to the paradigms philosophical background and practice, no matter whether immediately for one company or lagged later? for a larger amount of companies.

In conclusion, if all three approaches deliver a certain contribution to knowledge and by contrast no single approach can deliver all the contributions alone, this suggests that a single research perspective might be too narrow to “fully reflect the multifaceted nature of social, organizational, and phenomenological reality” (Goles & Hirschheim,  2000, p.256).

Transferring this logic to the reflection on the researcher’s values and skills this would mean, that a distinct, complete value-free or value-laden position, taking an extreme emic or etic approach alone would not qualify for comprehensive research in management science but only for a partial view on certain aspects. This suggests that multi-paradigm-approaches or paradigm interplay, at least an intermediate position, should be aimed for in order to triangulate results and to further advance knowledge in a particular research area (Aram & Salipante, 2003, p.192; Cox & Hassard, 2005; Holden & Lynch, 2004, p.14).

Consequently, this has also impact on the required researcher’s skills. Although it was shown during the paradigm simulation with two examples each, that each research approach demands distinct research skills, the majority of competencies should be inherent to every researcher, independent of the research approach (Easterby-Smith et al., 2012, p.6; Lee & Lings 2008, p.70). Due to the fact that some research methods can contribute to different research paradigms (Holden & Lynch, 2004, p.8) and that a researcher should be able to justify decisions about selected and discarded methods, basic skills should be acquired prior to the research.

  • Impact on choice of approach

The paradigm simulation clearly showed that the topic of SF of PCMS does have the potential to be worked on in a doctoral thesis acc. to the three described research paradigms. This is in line with the ongoing paradigm shift in Management Accounting Research as well as Strategic Management Research (Baum & Dobbin, 2000, p.391; Suomala et al., 2014, p.304; Wahyuni, 2012, p.72.).

Likewise, it supports Feyerabend’s view that there is no perspective superior to another and one single set of beliefs, rules and procedures is not enough to gain comprehensive knowledge (Feyerabend, 1985; Lee & Lings, 2008, p.32). Moreover, there is a growing recognition that paradigmatic and theoretical pluralism is fruitful (Van der Meer-Kooistra & Vosselman, 2012, p.246-247; Chua, 1986; Hassard & Kelemen, 2002; Hopwood, 2002; Luft & Shields, 2002, Lukka & Mouritsen, 2002; Zimmermann, 2001). Nonetheless, there is much to be said for that this pluralism might be more promising for a research discipline overall than on an individual research project level (Chua, 1986; Chua & Mahama, 2012; Parker, 2012), especially for a novice researcher in a dissertation. The first impact on the choice of approach consequently is that there is a choice!

With respect to researcher’s values and skills it has to be stated that although differences have been worked out, it was also argued, that basic awareness for and competence of values and research skills should be inherent to every researcher independently from the research perspective (Blaxter, Hughes, & Tight, 2010, pp.55-59; Crowther & Lancaster, 2008, p.2). Furthermore, one should avoid being trapped by a decision based on the familiarity with methods or the absence of skills as this contradicts the goal of further development of knowledge, in this case, on a personal level (Lee & Lings, 2008, p.64; Moses & Knutsen, 2012, p.1). The second impact on the choice of approach therefore is the awareness of the own position/values, the required skills which might be developed more extensively compare to others and finally the explicitness of the decision for an approach.

Synthesizing what remains after advocating pluralism in general and moderating values and skills as impacting factors on the research topic, is a pragmatist’s view, holding the opinion, that out of the set of various different potential approaches the one should be selected “(that) works best for the particular research program under study” (Tashakkori & Teddlie, 1998, p.5). This underlines the importance of the researcher’s individual purpose with the need to justify the research approach in each single case in terms of match of purpose and research approach as stated at the beginning of the assignment.  This should be seen as the ultimate impact of the paradigm simulation on the choice of approach, independent from the concrete outcome of the choice itself.

To conclude, the assignment goals a highlighted in section 1.2, understand different and justify / advocate the selected research perspective/s have been achieved by in parallel opening the researcher’s mind and enhancing own confidence. The potential for a high quality research with regard to appropriate quality criteria for that approach has been developed.

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Annex: Assessment brief

Annex: Table 1: Impact of research approaches on research problem

Declaration of original content

I declare that the work in this assessment was carried out in accordance with the regulations of the University of Gloucestershire and is original except where indicated by specific reference in the text. No part of the assessment has been submitted as part of any other academic award.

Any views expressed in this assessment are those of the author and in no way represent those of the University.

Signed: <<Claude Maxion, Pforzheim>>

Date: 14/12/2015

 

Explain why one might choose an inductive argument over a deductive argument.

207
Deduction and Induction: 6
Putting It All Together
Wavebreakmedia Ltd./Thinkstock and GoldenShrimp/iStock/Thinkstock
Learning Objectives
After reading this chapter, you should be able to:
1. Compare and contrast the advantages of deduction and induction.
2. Explain why one might choose an inductive argument over a deductive argument.
3. Analyze an argument for its deductive and inductive components.
4. Explain the use of induction within the hypothetico–deductive method.
5. Compare and contrast falsification and confirmation within scientific inquiry.
6. Describe the combined use of induction and deduction within scientific reasoning.
7. Explain the role of inference to the best explanation in science and in daily life.
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Contrasting Deduction and Induction Section 6.1
Now that you have learned something about deduction and induction, you may be wondering
why we need both. This chapter is devoted to answering that question. We will start by learning
a bit more about the differences between deductive and inductive reasoning and how the
two types of reasoning can work together. After that, we will move on to explore how scientific
reasoning applies to both types of reasoning to achieve spectacular results. Arguments
with both inductive and deductive elements are very common. Recognizing the advantages
and disadvantages of each type can help you build better arguments. We will also investigate
another very useful type of inference, known as inference to the best explanation, and explore
its advantages.
6.1 Contrasting Deduction and Induction
Remember that in logic, the difference between induction and deduction lies in the connection
between the premises and conclusion. Deductive arguments aim for an absolute connection,
one in which it is impossible that the premises could all be true and the conclusion false.
Arguments that achieve this aim are called valid. Inductive arguments aim for a probable
connection, one in which, if all the premises are true, the conclusion is more likely to be true
than it would be otherwise. Arguments that achieve this aim are called strong. (For a discussion
on common misconceptions about the meanings of induction and deduction, see A Closer
Look: Doesn’t Induction Mean Going From Specific to General?). Recall from Chapter 5 that
inductive strength is the counterpart of deductive validity, and cogency is the inductive counterpart
of deductive soundness. One of the purposes of this chapter is to properly understand
the differences and connections between these two major types of reasoning.
There is another important difference
between deductive and inductive reasoning.
As discussed in Chapter 5, if
you add another premise to an inductive
argument, the argument may
become either stronger or weaker. For
example, suppose you are thinking of
buying a new cell phone. After looking
at all your options, you decide that one
model suits your needs better than
the others. New information about the
phone may make you either more convinced
or less convinced that it is the
right one for you—it depends on what
the new information is. With deductive
reasoning, by contrast, adding premises
to a valid argument can never
render it invalid. New information
may show that a deductive argument
Fuse/Thinkstock
New information can have an impact on both
deductive and inductive arguments. It can render
deductive arguments unsound and can strengthen
or weaken inductive arguments, such as arguments
for buying one car over another.
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Contrasting Deduction and Induction Section 6.1
is unsound or that one of its premises is not true after all, but it cannot undermine a valid
connection between the premises and the conclusion. For example, consider the following
argument:
All whales are mammals.
Shamu is a whale.
Therefore, Shamu is a mammal.
This argument is valid, and there is nothing at all we could learn about Shamu that would
change this. We might learn that we were mistaken about whales being mammals or about
Shamu being a whale, but that would lead us to conclude that the argument is unsound, not
invalid. Compare this to an inductive argument about Shamu.
Whales typically live in the ocean.
Shamu is a whale.
Therefore, Shamu lives in the ocean.
Now suppose you learn that Shamu has been trained to do tricks in front of audiences at an
amusement park. This seems to make it less likely that Shamu lives in the ocean. The addition
of this new information has made this strong inductive argument weaker. It is, however, possible
to make it stronger again with the addition of more information. For example, we could
learn that Shamu was part of a captive release program.
An interesting exercise for exploring this concept is to see if you can keep adding premises to
make an inductive argument stronger, then weaker, then stronger again. For example, see if
you can think of a series of premises that make you change your mind back and forth about
the quality of the cell phone discussed earlier.
Determining whether an argument is deductive or inductive is an important step both in
evaluating arguments that you encounter and in developing your own arguments. If an argument
is deductive, there are really only two questions to ask: Is it valid? And, are the premises
true? If you determine that the argument is valid, then only the truth of the premises remains
in question. If it is valid and all of the premises are true, then we know that the argument is
sound and that therefore the conclusion must be true as well.
On the other hand, because inductive arguments can go from strong to weak with the addition
of more information, there are more questions to consider regarding the connection
between the premises and conclusion. In addition to considering the truth of the premises
and the strength of the connection between the premises and conclusion, you must also consider
whether relevant information has been left out of the premises. If so, the argument may
become either stronger or weaker when the relevant information is included.
Later in this chapter we will see that many arguments combine both inductive and deductive
elements. Learning to carefully distinguish between these elements will help you know what
questions to ask when evaluating the argument.
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Section 6.1 Contrasting Deduction and Induction
A Closer Look: Doesn’t Induction Mean Going From Specific
to General?
A common misunderstanding of the meanings of induction and deduction is that deduction goes from the general to the specific, whereas induction goes from the specific to the general. This definition is used by some fields, but not by logic or philosophy. It is true that some deductive arguments go from general premises to specific conclusions, and that some inductive arguments go from the specific premises to general conclusions. However, neither statement is true in general.
First, although some deductive arguments go from general to specific, there are many deductive arguments that do not go from general to specific. Some deductive arguments, for example, go from general to general, like the following:
All S are M.
All M are P.
Therefore, all S are P.
Propositional logic is deductive, but its arguments do not go from general to specific. Instead, arguments are based on the use of connectives (and, or, not, and if . . . then). For example, modus ponens (discussed in Chapter 4) does not go from the general to the specific, but it is deductively valid. When it comes to inductive arguments, some—for example, inductive generalizations—go from specific to general; others do not. Statistical syllogisms, for example, go from general to specific, yet they are inductive.
This common misunderstanding about the definitions of induction and deduction is not surprising given the different goals of the fields in which the terms are used. However, the definitions used by logicians are especially suited for the classification and evaluation of different types of reasoning.
For example, if we defined terms the old way, then the category of deductive reasoning would include arguments from analogy, statistical syllogisms, and some categorical syllogisms. Inductive reasoning, on the other hand, would include only inductive generalizations. In addition, there would be other types of inference that would fit into neither category, like many categorical syllogisms, inferences to the best explanation, appeals to authority, and the whole field of propositional logic.
The use of the old definitions, therefore, would not clear up or simplify the categories of logic at all but would make them more confusing. The current distinction, based on whether the premises are intended to guarantee the truth of the conclusion, does a much better job of simplifying logic’s categories, and it does so based on a very important and relevant distinction.
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Choosing Between Induction and Deduction Section 6.2
Practice Problems 6.1
1. A deductive argument that establishes an absolute connection between the premises
and conclusion is called a __________.
a. strong argument
b. weak argument
c. invalid argument
d. valid argument
2. An inductive argument whose premises give a lot of support for the truth of its conclusion
is said to be __________.
a. strong
b. weak
c. valid
d. invalid
3. Inductive arguments always reason from the specific to the general.
a. true
b. false
4. Deductive arguments always reason from the general to the specific.
a. true
b. false
6.2 Choosing Between Induction and Deduction
You might wonder why one would choose to use inductive reasoning over deductive reasoning.
After all, why would you want to show that a conclusion was only probably true rather
than guaranteed to be true? There are several reasons, which will be discussed in this section.
First, there may not be an available deductive argument based on agreeable premises.
Second, inductive arguments can be more robust than deductive arguments. Third, inductive
arguments can be more persuasive than deductive arguments.
Availability
Sometimes the best evidence available does not lend itself to a deductive argument. Let us
consider a readily accepted fact: Gravity is a force that pulls everything toward the earth.
How would you provide an argument for that claim? You would probably pick something up,
let go of it, and note that it falls toward the earth. For added effect, you might pick up several
things and show that each of them falls. Put in premise–conclusion form, your argument looks
something like the following:
My coffee cup fell when I let go of it.
My wallet fell when I let go of it.
This rock fell when I let go of it.
Therefore, everything will fall when I let go of it.
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Section 6.2 Choosing Between Induction and Deduction
When we put the argument that way, it should be clear that it is inductive. Even if we grant that the premises are true, it is not guaranteed that everything will fall when you let go of it. Perhaps gravity does not affect very small things or very large things. We could do more experiments, but we cannot check every single thing to make sure that it is affected by gravity. Our belief in gravity is the result of extremely strong inductive reasoning. We therefore have great reasons to believe in gravity, even if our reasoning is not deductive.
All subjects that rely on observation use inductive reasoning: It is at least theoretically possible that future observations may be totally different than past ones. Therefore, our inferences based on observation are at best probable. It turns out that there are very few subjects in which we can proceed entirely by deductive reasoning. These tend to be very abstract and formal subjects, such as mathematics. Although other fields also use deductive reasoning, they do so in combination with inductive reasoning. The result is that most fields rely heavily on inductive reasoning.
Robustness
Inductive arguments have some other advantages over deductive arguments. Deductive arguments can be extremely persuasive, but they are also fragile in a certain sense. When something goes wrong in a deductive argument, if a premise is found to be false or if it is found to be invalid, there is typically not much of an argument left. In contrast, inductive arguments tend to be more robust. The robustness of an inductive argument means that it is less fragile; if there is a problem with a premise, the argument may become weaker, but it can still be quite persuasive. Deductive arguments, by contrast, tend to be completely unconvincing once they are shown not to be sound. Let us work through a couple of examples to see what this means in practice.
Consider the following deductive argument:
All dogs are mammals.
Some dogs are brown.
Therefore, some mammals are brown.
As it stands, the argument is sound. However, if we change a premise so that it is no longer sound, then we end up with an argument that is nearly worthless. For example, if you change the first premise to “Most dogs are mammals,” you end up with an invalid argument. Validity is an all-or-nothing affair; there is no such thing as “sort of valid” or “more valid.” The
Alistair Scott/iStock/ThinkstockDespite knowing that a helium-filled balloon will rise when we let go of it, we still hold our belief in gravity due to strong inductive reasoning and our reliance on observation.
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Section 6.2 Choosing Between Induction and Deduction
argument would simply be invalid and therefore unsound; it would not accomplish its purpose of demonstrating that the conclusion must be true. Similarly, if you were to change the second premise to something false, like “Some dogs are purple,” then the argument would be unsound and therefore would supply no reason to accept the conclusion.
In contrast, inductive arguments may retain much of their strength even when there are problems with them. An inductive argument may list several reasons in support of a conclusion. If one of those reasons is found to be false, the other reasons continue to support the conclusion, though to a lesser degree. If an argument based on statistics shows that a particular conclusion is extremely likely to be true, the result of a problem with the argument may be that the conclusion should be accepted as only fairly likely. The argument may still give good reasons to accept the conclusion.
Fields that rely heavily on statistical arguments often have some threshold that is typically required in order for results to be publishable. In the social sciences, this is typically 90% or 95%. However, studies that do not quite meet the threshold can still be instructive and provide evidence for their conclusions. If we discover a flaw that reduces our confidence in an argument, in many cases the argument may still be strong enough to meet a threshold.
As an example, consider a tweet made by President Barack Obama regarding climate change.
Although the tweet does not spell out the argument fully, it seems to have the following structure:
A study concluded that 97% of scientists agree that climate change is real, man-made, and dangerous.
Therefore, 97% of scientists really do agree that climate change is real, man-made, and dangerous.
Therefore, climate change is real, man-made, and dangerous.
Given the politically charged nature of the discussion of climate change, it is not surprising that the president’s argument and the study it referred to received considerable criticism. (You can read the study at http://iopscience.iop.org/1748–9326/8/2/024024/pdf/1748
–9326_8_2_024024.pdf.) Looking at the effect some of those criticisms have on the argument is a good way to see how inductive arguments can be more robust than deductive ones.
One criticism of Obama’s claim is that the study he referenced did not say anything about whether climate change was dangerous, only about whether it was real and man-made. How does this affect the argument? Strictly speaking, it makes the first premise false. But notice that even so, the argument can still give good evidence that climate change is real and
Twitter/Public Domain
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Section 6.2 Choosing Between Induction and Deduction
man-made. Since climate change, by its nature, has a strong potential to be dangerous, the argument is weakened but still may give strong evidence for its conclusion.
A deeper criticism notes that the study did not find out what all scientists thought; it just looked at those scientists who expressed an opinion in their published work or in response to a voluntary survey. This is a significant criticism, for it may expose a bias in the sampling method (as discussed in Chapters 5, 7, and 8). Even granting the criticism, the argument can retain some strength. The fact that 97% of scientists who expressed an opinion on the issue said that climate change is real and man-made is still some reason to think that it is real and man-made. Of course, some scientists may have chosen not to voice an opposing opinion for reasons that have nothing to do with their beliefs about climate change; they may have simply wanted to keep their views private, for example. Taking all of this into account, we get the following argument:
A study found that 97% of scientists who stated their opinion said that climate change is real and man-made.
Therefore, 97% of scientists agree that climate change is real and man-made.
Climate change, if real, is dangerous.
Therefore, climate change is real, man-made, and dangerous.
This is not nearly as strong as the original argument, but it has not collapsed entirely in the way a purely deductive argument would. There is, of course, much more that could be said about this argument, both in terms of criticizing the study and in terms of responding to those criticisms and bringing in other considerations. The point here is merely to highlight the difference between deductive and inductive arguments, not to settle issues in climate science or public policy.
Persuasiveness
A final point in favor of inductive reasoning is that it can often be more persuasive than deductive reasoning. The persuasiveness of an argument is based on how likely it is to convince someone of the truth of its conclusion. Consider the following classic argument:
All Greeks are mortal.
Socrates was a Greek.
Therefore, Socrates was mortal.
Is this a good argument? From the standpoint of logic, it is a perfect argument: It is deductively valid, and its premises are true, so it is sound (therefore, its conclusion must be true). However, can you persuade anyone with this argument?
Imagine someone wondering whether Socrates was mortal. Could you use this argument to convince him or her that Socrates was mortal? Probably not. The argument is so simple and
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Choosing Between Induction and Deduction Section 6.2
so obviously valid that anyone who accepts the premises likely already accepts the conclusion.
So if someone is wondering about the conclusion, it is unlikely that he or she will be
persuaded by these premises. He or she may, for example, remember that some legendary
Greeks, such as Hercules, were granted immortality and wonder whether Socrates was one
of these. The deductive approach, therefore, is unlikely to win anyone over to the conclusion
here. On the other hand, consider a very similar inductive argument.
Of all the real and mythical Greeks, only a few were considered to be immortal.
Socrates was a Greek.
Therefore, it is extremely unlikely that Socrates was immortal.
Again, the reasoning is very simple. However, in this case, we can imagine someone who had
been wondering about Socrates’s mortality being at least somewhat persuaded that he was
mortal. More will likely need to be said to fully persuade her or him, but this simple argument
may have at least some persuasive power where its deductive version likely does not.
Of course, deductive arguments can be persuasive, but they generally need to be more complicated
or subtle in order to be so. Persuasion requires that a person change his or her mind
to some degree. In a deductive argument, when the connection between premises and conclusion
is too obvious, the argument is unlikely to persuade because the truth of the premises
will be no more obvious than the truth of the conclusion. Therefore, even if the argument
is valid, someone who questions the truth of the conclusion will often be unlikely to accept
the truth of the premises, so she or he may be unpersuaded by the argument. Suppose, for
example, that we wanted to convince someone that the sun will rise tomorrow morning. The
deductive argument may look like this:
The sun will always rise in the morning.
Therefore, the sun will rise tomorrow morning.
One problem with this argument, as with the Socrates argument, is that its premise seems to
assume the truth of the conclusion (and therefore commits the fallacy of begging the question,
as discussed in Chapter 7), making the argument unpersuasive. Additionally, however,
the premise might not even be true. What if, billions of years from now, the earth is swallowed
up into the sun after it expands to become a red giant? At that time, the whole concept of
morning may be out the window. If this is true then the first premise may be technically false.
That means that the argument is unsound and therefore fairly worthless deductively.
The inductive version, however, does not lose much strength at all after we learn of this troubling
information:
The sun has risen in the morning every day for millions of years.
Therefore, the sun will rise again tomorrow morning.
This argument remains extremely strong (and persuasive) regardless of what will happen
billions of years in the future.
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Section 6.3 Combining Induction and Deduction
Practice Problems 6.2
1.
Which form of reasoning is taking place in this example?
The sun has risen every day of my life.
The sun rose today.
Therefore, the sun will rise tomorrow.
a.
inductive
b.
deductive
2.
Inductive arguments __________.
a.
can retain strength even with false premises
b.
collapse when a premise is shown to be false
c.
are equivalent to deductive arguments
d.
strive to be valid
3.
Deductive arguments are often __________.
a.
less persuasive than inductive arguments
b.
more persuasive than inductive arguments
c.
weaker than inductive arguments
d.
less valid than inductive arguments
4.
Inductive arguments are sometimes used because __________.
a.
the available evidence does not allow for a deductive argument
b.
they are more likely to be sound than deductive ones
c.
they are always strong
d.
they never have false premises
6.3 Combining Induction and Deduction
You may have noticed that most of the examples we have explored have been fairly short and simple. Real-life arguments tend to be much longer and more complicated. They also tend to mix inductive and deductive elements. To see how this might work, let us revisit an example from the previous section.
All Greeks are mortal.
Socrates was Greek.
Therefore, Socrates was mortal.
As we noted, this simple argument is valid but unlikely to convince anyone. So suppose now that someone questioned the premises, asking what reasons there are for thinking that all Greeks are mortal or that Socrates was Greek. How might we respond?
We might begin by noting that, although we cannot check each and every Greek to be sure he or she is mortal, there are no documented cases of any Greek, or any other human, living more
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Section 6.3 Combining Induction and Deduction
than 200 years. In contrast, every case that we can document is a case in which the person dies at some point. So, although we cannot absolutely prove that all Greeks are mortal, we have good reason to believe it. We might put our argument in standard form as follows:
We know the mortality of a huge number of Greeks.
In each of these cases, the Greek is mortal.
Therefore, all Greeks are mortal.
This is an inductive argument. Even though it is theoretically possible that the conclusion might still be false, the premises provide a strong reason to accept the conclusion. We can now combine the two arguments into a single, larger argument:
We know the mortality of a huge number of Greeks.
In each of these cases, the Greek is mortal.
Therefore, all Greeks are mortal.
Socrates was Greek.
Therefore, Socrates was mortal.
This argument has two parts. The first argument, leading to the subconclusion that all Greeks are mortal, is inductive. The second argument (whose conclusion is “Socrates was mortal”) is deductive. What about the overall reasoning presented for the conclusion that Socrates was mortal (combining both arguments); is it inductive or deductive?
The crucial issue is whether the premises guarantee the truth of the conclusion. Because the basic premise used to arrive at the conclusion is that all of the Greeks whose mortality we know are mortal, the overall reasoning is inductive. This is how it generally works. As noted earlier, when an argument has both inductive and deductive components, the overall argument is generally inductive. There are occasional exceptions to this general rule, so in particular cases, you still have to check whether the premises guarantee the conclusion. But, almost always, the longer argument will be inductive.
Fran/CartoonstockSometimes a simple deductive argument needs to be combined with a persuasive inductive argument to convince others to accept it.
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Section 6.4 Reasoning About Science: The Hypothetico–Deductive Method
A similar thing happens when we combine inductive arguments of different strength. In general, an argument is only as strong as its weakest part. You can think of each inference in an argument as being like a link in a chain. A chain is only as strong as its weakest link.
6.4 Reasoning About Science: The Hypothetico–
Deductive Method
Science is one of the most successful endeavors of the modern world, and arguments play a central role in it. Science uses both deductive and inductive reasoning extensively. Scientific reasoning is a broad field in itself—and this chapter will only touch on the basics—but discussing scientific reasoning will provide good examples of how to apply what we have learned about inductive and deductive arguments.
At some point, you may have learned or heard of the scientific method, which often refers to how scientists systematically form, test, and modify hypotheses. It turns out that there is not a single method that is universally used by all scientists.
In a sense, science is the ultimate critical thinking experiment. Scientists use a wide variety of reasoning techniques and are constantly examining those techniques to make sure that the conclusions drawn are justified by the premises—that is exactly what a good critical thinker should do in any subject. The next two sections will explore two such methods—the
hypothetico–deductive method and inferences to the best explanation—and discover ways that they can improve our understanding of the types of reasoning used in much of science.
The hypothetico–deductive method consists of four steps:
1.
Formulate a hypothesis.
2.
Deduce a consequence from the hypothesis.
3.
Test whether the consequence occurs.
4.
Reject the hypothesis if the consequence does not occur.
Although these four steps are not sufficient to explain all scientific reasoning, they still remain a core part of much discussion of how science works. You may recognize them as part of the scientific method that you likely learned about in school. Let us take a look at each step
in turn.
Practice Problem 6.31. When an argument contains both inductive and deductive elements, the entire argu-ment is considered deductive.a. trueb. false
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Section 6.4 Reasoning About Science: The Hypothetico–Deductive Method
Step 1: Formulate a Hypothesis
A hypothesis is a conjecture about how some part of the world works. Although the phrase “educated guess” is often used, it can give the impression that a hypothesis is simply guessed without much effort. In reality, scientific hypotheses are formulated on the basis of a background of quite a bit of knowledge and experience; a good scientific hypothesis often comes after years of prior investigation, thought, and research about the issue at hand.
You may have heard the expression “necessity is the mother of invention.” Often, hypotheses are formulated in response to a problem that needs to be solved. Suppose you are unsatisfied with the performance of your car and would like better fuel economy. Rather than buy a new car, you try to figure out how to improve the one you have. You guess that you might be able to improve your car’s fuel economy by using a higher grade of gas. Your guess is not just random; it is based on what you already know or believe about how cars work. Your hypothesis is that higher grade gas will improve your fuel economy.
Of course, science is not really concerned with your car all by itself. Science is concerned with general principles. A scientist would reword your hypothesis in terms of a general rule, something like, “Increasing fuel octane increases fuel economy in automobiles.” The
hypothetico–deductive method can work with either kind of hypothesis, but the general hypothesis is more interesting scientifically.
Step 2: Deduce a Consequence From the Hypothesis
Your hypothesis from step 1 should have predictive value: Things should be different in some noticeable way, depending on whether the hypothesis is true or false. Our hypothesis is that increasing fuel octane improves fuel economy. If this general fact is true, then it is true for your car. So from our general hypothesis we can deduce the consequence that your car will get more miles per gallon if it is running on higher octane fuel.
It is often but not always the case that the prediction is a more specific case of the hypothesis. In such cases it is possible to infer the prediction deductively from the general hypothesis. The argument may go as follows:
Hypothesis: All things of type A have characteristic B.
Consequence (the prediction): Therefore, this specific thing of type A will have characteristic B.
Since the argument is deductively valid, there is a strong connection between the hypothesis and the prediction. However, not all predictions can be deductively inferred. In such cases we can get close to the hypothetico–deductive method by using a strong inductive inference instead. For example, suppose the argument went as follows:
Hypothesis: 95% of things of type A have characteristic B.
Consequence: Therefore, a specific thing of type A will probably have characteristic
B.
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Section 6.4 Reasoning About Science: The Hypothetico–Deductive Method
In such cases the connection between the hypothesis and the prediction is less strong. The stronger the connection that can be established, the better for the reliability of the test. Essentially, you are making an argument for the conditional statement “If H, then C,” where H is your hypothesis and C is a consequence of the hypothesis. The more solid the connection is between H and C, the stronger the overall argument will be.
In this specific case, “If H, then C” translates to “If increasing fuel octane increases fuel economy in all cars, then using higher octane fuel in your car will increase its fuel economy.” The truth of this conditional is deductively certain.
We can now test the truth of the hypothesis by testing the truth of the consequence.
Step 3: Test Whether the Consequence Occurs
Your prediction (the consequence) is that your car will get better fuel economy if you use a higher grade of fuel. How will you test this? You may think this is obvious: Just put better gas in the car and record your fuel economy for a period before and after changing the type of gas you use. However, there are many other factors to consider. How long should the period of time be? Fuel economy varies depending on the kind of driving you do and many other factors. You need to choose a length of time for which you can be reasonably confident the driving conditions are similar on average. You also need to account for the fact that the first tank of better gas you put in will be mixed with some of the lower grade gas that is still in your tank. The more you can address these and other issues, the more certain you can be that your conclusion is correct.
In this step, you are constructing an inductive argument from the outcome of your test as to whether your car actually did get better fuel economy. The arguments in this step are inductive because there is always some possibility that you have not adequately addressed all of the relevant issues. If you do notice better fuel economy, it is always possible that the increase in economy is due to some factor other than the one you are tracking. The possibility may be very small, but it is enough to make this kind of argument inductive rather than deductive.
Step 4: Reject the Hypothesis If the Consequence Does Not Occur
We now compare the results to the prediction and find out if the prediction came true. If your test finds that your car’s fuel economy does not improve when you use higher octane fuel, then you know your prediction was wrong.
Does this mean that your hypothesis, H, was wrong? That depends on the strength of the connection between H and C. If the inference from H to C is deductively certain, then we know for sure that, if H is true, then C must be true also. Therefore, if C is false, it follows logically that H must be false as well.
In our specific case, if your car does not get better fuel economy by switching to higher octane fuel, then we know for sure that it is not true that all cars get better fuel economy by doing so. However, if the inference from H to C is inductive, then the connection between H and C is less than totally certain. So if we find that C is false, we are not absolutely sure that the hypothesis, H, is false.
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Reasoning About Science: The Hypothetico–Deductive Method Section 6.4
For example, suppose that the hypothesis is that cars that use higher octane fuel will have a
higher tendency to get better fuel mileage. In that case if your car does not get higher gas
mileage, then you still cannot infer for certain that the hypothesis is false. To test that
hypothesis adequately, you would have to do a large study with many cars. Such a study
would be much more complicated, but it could provide very strong evidence that the hypothesis
is false.
It is important to note that although
the falsity of the prediction can demonstrate
that the hypothesis is false,
the truth of the prediction does not
prove that the hypothesis is true. If you
find that your car does get better fuel
economy when you switch gas, you
cannot conclude that your hypothesis
is true.
Why? There may be other factors
at play for which you have not adequately
accounted. Suppose that at the
same time you switch fuel grade, you
also get a tune-up and new tires and
start driving a completely different
route to work. Any one of these things
might be the cause of the improved gas
mileage; you cannot conclude that it is
due to the change in fuel (for this reason,
when conducting experiments it
is best to change only one variable at a
time and carefully control the rest). In
other words, in the hypothetico–deductive method, failed tests can show that a hypothesis is
wrong, but tests that succeed do not show that the hypothesis was correct.
This logic is known as falsification; it can be demonstrated clearly by looking at the structure
of the argument. When a test yields a negative result, the hypothetico–deductive method sets
up the following argument:
If H, then C.
Not C.
Therefore, not H.
You may recognize this argument form as modus tollens, or denying the consequent, which
was discussed in the chapter on propositional logic (Chapter 4). This argument form is a
valid, deductive form. Therefore, if both of these premises are true, then we can be certain
that the conclusion is true as well; namely, that our hypothesis, H, is not true. In the specific
case at hand, if your test shows that higher octane fuel does not increase your mileage, then
we can be sure that it is not true that it improves mileage in all vehicles (though it may
improve it in some).
IPGGutenbergUKLtd/iStock/Thinkstock
At best, the fuel economy hypothesis will be a strong
inductive argument because there is a chance
that something other than higher octane gas is
improving fuel economy. The more you can address
relevant issues that may impact your test results,
the stronger your conclusions will be.
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Section 6.4 Reasoning About Science: The Hypothetico–Deductive Method
Contrast this with the argument form that results when your fuel economy yields a
positive result:
If H, then C.
C.
Therefore, H.
This argument is not valid. In fact, you may recognize this argument form as the invalid deductive form called affirming the consequent (see Chapter 4). It is possible that the two premises are true, but the conclusion false. Perhaps, for example, the improvement in fuel economy was caused by a change in tires or different driving conditions instead. So the hypothetico
–deductive method can be used only to reject a hypothesis, not to confirm it. This fact has led many to see the primary role of science to be the falsification of hypotheses. Philosopher Karl Popper is a central source for this view (see A Closer Look: Karl Popper and Falsification in Science).
A Closer Look: Karl Popper and Falsification in Science
Karl Popper, one of the most influential philosophers of science to emerge from the early 20th century, is perhaps best known for rejecting the idea that scientific theories could be proved by simply finding confirming evidence—the prevailing philosophy at the time. Instead, Popper emphasized that claims must be testable and falsifiable in order to be considered scientific.
A claim is testable if we can devise a way of seeing if it is true or not. We can test, for instance, that pure water will freeze at 0°C at sea level; we cannot currently test the claim that the oceans in another galaxy taste like root beer. We have no realistic way to determine the truth or falsity of the second claim.
A claim is said to be falsifiable if we know how one could show it to be false. For instance, “there are no wild kangaroos in Georgia” is a falsifiable claim; if one went to Georgia and found some wild kangaroos, then it would have been shown to be false. But what if someone claimed that there are ghosts in Georgia but that they are imperceptible (unseeable, unfeelable, unhearable, etc.)? Could one ever show that this claim is false? Since such a claim could not conceivably be shown to be false, it is said to be unfalsifiable. While being unfalsifiable might sound like a good thing, according to Popper it is not, because it means that the claim is unscientific.
Following Popper, most scientists today operate with the assumption that any scientific hypothesis must be testable and must be the kind of claim that one could possibly show to be false. So if a claim turns out not to be conceivably falsifiable, the claim is not really scientific—and some philosophers have gone so far as to regard such claims as meaningless (Thornton, 2014).
Keystone/Getty ImagesKarl Popper, a 20th-century philosopher of science, put forth the idea that unfalsifiable claims are unscientific.
(continued)
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Section 6.4 Reasoning About Science: The Hypothetico–Deductive Method
As an example, suppose a friend claims that “everything works out for the best.” Then suppose that you have the worst month of your life, and you go back to your friend and say that the claim is false: Not everything is for the best. Your friend might then reply that in fact it was for the best because you learned from the experience. Such a statement may make you feel better, but it runs afoul of Popper’s rule. Can you imagine any circumstance that your friend would not claim is for the best? Since your friend would probably say that it was for the best no matter what happens, your friend’s claim is unfalsifiable and therefore unscientific.
In logic, claims that are interpreted so that they come out true no matter what happens are called self-sealing propositions. They are understood as being internally protected against any objections. People who state such claims may feel that they are saying something deeply meaningful, but according to Popper’s rule, since the claim could never be falsified no matter what, it does not really tell us anything at all.
Other examples of self-sealing propositions occur within philosophy itself. There is a philosophical theory known as psychological egoism, for example, which teaches that everything everyone does is completely selfish. Most people respond to this claim by coming up with examples of unselfish acts: giving to the needy, spending time helping others, and even dying to save someone’s life. The psychological egoist predictably responds to all such examples by stating that people who do such things really just do them in order to feel better about themselves. It appears that the word selfish is being interpreted so that everything everyone does will automatically be considered selfish by definition. It is therefore a self-sealing claim
(Rachels, 1999). According to Popper’s method, since this claim will always come out true no matter what, it is unfalsifiable and unscientific. Such claims are always true but are actually empty because they tell us nothing about the world. They can even be said to be “too true to be good.”
Popper’s explorations of scientific hypotheses and what it means to confirm or disconfirm such hypotheses have been very influential among both scientists and philosophers of scientists. Scientists do their best to avoid making claims that are not falsifiable.
A Closer Look: Karl Popper and Falsification in Science (continued)
If the hypothetico-deductive method cannot be used to confirm a hypothesis, how can this test give evidence for the truth of the claim? By failing to falsify the claim. Though the hypothetico–deductive method does not ever specifically prove the hypothesis true, if researchers try their hardest to refute a claim but it keeps passing the test (not being refuted), then there can grow a substantial amount of inductive evidence for the truth of the claim. If you repeatedly test many cars and control for other variables, and if every time cars are filled with higher octane gas their fuel economy increases, you may have strong inductive evidence that the hypothesis might be true (in which case you may make an inference to the best explanation, which will be discussed in Section 6.5).
Experiments that would have the highest chance of refuting the claim if it were false thus provide the strongest inductive evidence that it may be true. For example, suppose we want to test the claim that all swans are white. If we only look for swans at places in which they are known to be white, then we are not providing a strong test for the claim. The best thing to do (short of observing every swan in the whole world) is to try as hard as we can to refute the claim, to find a swan that is not white. If our best methods of looking for nonwhite swans still fail to refute the claim, then there is a growing likelihood that perhaps all swans are indeed white.
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Section 6.4 Reasoning About Science: The Hypothetico–Deductive Method
Similarly, if we want to test to see if a certain type of medicine cures a certain type of disease, we test the product by giving the medicine to a wide variety of patients with the disease, including those with the least likelihood of being cured by the medicine. Only by trying as hard as we can to refute the claim can we get the strongest evidence about whether all instances of the disease are treatable with the medicine in question.
Notice that the hypothetico–deductive method involves a combination of inductive and deductive reasoning. Step 1 typically involves inductive reasoning as we formulate a hypothesis against the background of our current beliefs and knowledge. Step 2 typically provides a deductive argument for the premise “If H, then C.” Step 3 provides an inductive argument for whether C is or is not true. Finally, if the prediction is falsified, then the conclusion—that H is false—is derived by a deductive inference (using the deductively valid modus tollens form). If, on the other hand, the best attempts to prove C to be false fail to do so, then there is growing evidence that H might be true.
Therefore, our overall argument has both inductive and deductive elements. It is valuable to know that, although the methodology of science involves research and experimentation that goes well beyond the scope of pure logic, we can use logic to understand and clarify the basic principles of scientific reasoning.
Practice Problems 6.4
1.
A hypothesis is __________.
a.
something that is a mere guess
b.
something that is often arrived at after a lot of research
c.
an unnecessary component of the scientific method
d.
something that is already solved
2.
In a scientific experiment, __________.
a.
the truth of the prediction guarantees that the hypothesis was correct
b.
the truth of the prediction negates the possibility of the hypothesis being correct
c.
the truth of the prediction can have different levels of probability in relation to the hypothesis being correct
d.
the truth of the prediction is of little importance
3.
The argument form that is set up when a test yields negative results is __________.
a.
disjunctive syllogism
b.
modus ponens
c.
hypothetical syllogism
d.
modus tollens
4.
A claim is testable if __________.
a.
we know how one could show it to be false
b.
we know how one could show it to be true
c.
we cannot determine a way to prove it false
d.
we can determine a way to see if it is true or false
(continued)
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Section 6.5 Inference to the Best Explanation
5.
Which of the following claims is not falsifiable?
a.
The moon is made of cheese.
b.
There is an invisible alien in my garage.
c.
Octane ratings in gasoline influence fuel economy.
d.
The Willis Tower is the tallest building in the world.
Practice Problems 6.4 (continued)
6.5 Inference to the Best Explanation
You may feel that if you were very careful about testing your fuel economy, you would be entitled to conclude that the change in fuel grade really did have an effect. Unfortunately, as we have seen, the hypothetico–deductive method does not support this inference. The best you can say is that changing fuel might have an effect; that you have not been able to show that it does not have an effect. The method does, however, lend inductive support to whichever hypothesis withstands the falsification test better than any other. One way of articulating this type of support is with an inference pattern known as inference to the best explanation.
As the name suggests, inference to the best explanation draws a conclusion based on what would best explain one’s observations. It is an extremely important form of inference that we use every day of our lives. This type of inference is often called abductive reasoning, a term pioneered by American logician Charles Sanders Peirce (Douven, 2011).
Suppose that you are in your backyard gazing at the stars. Suddenly, you see some flashing lights hovering above you in the sky. You do not hear any sound, so it does not appear that the lights are coming from a helicopter. What do you think it is? What happens next is abductive reasoning: Your brain searches among all kinds of possibilities to attempt to come up with the most likely explanation.
One possibility is that it is an alien spacecraft coming to get you (one could joke that this is why it is called abductive reasoning). Another possibility is that it is some kind of military vessel or a weather balloon. A more extreme hypothesis is that you are actually dreaming the whole thing.
Notice that what you are inclined to believe depends on your existing beliefs. If you already think that alien spaceships come to Earth all the time, then you may arrive at that conclusion with a high degree of certainty (you may even shout, “Take me with you!”). However, if you are somewhat skeptical of those kinds of theories, then you will try hard to find any other explanation. Therefore, the strength of a particular inference to the best explanation can be measured only in relation to the rest of the things that we already believe.
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Section 6.5 Inference to the Best Explanation
This type of inference does not occur only in unusual circumstances like the one described. In fact, we make inferences to the best explanation all the time. Returning to our fuel economy example from the previous section, suppose that you test a higher octane fuel and notice that your car gets better gas mileage. It is possible that the mileage change is due to the change in fuel. However, as noted there, it is possible that there is another explanation. Perhaps you are not driving in stop-and-go traffic as much. Perhaps you are driving with less weight in the car. The careful use of inference to the best explanation can help us to discern what is the most likely among many possibilities (for more examples, see A Closer Look: Is Abductive Reasoning Everywhere?).
If you look at the range of possible explanations and find one of them is more likely than any of the others, inference to the best explanation allows you to conclude that this explanation is likely to be the correct one. If you are driving the same way, to the same places, and with the same weight in your car as before, it seems fairly likely that it was the change in fuel that caused the improvement in fuel economy (if you have studied Mill’s methods in Chapter 5, you should recognize this as the method of difference). Inference to the best explanation is the engine that powers many inductive techniques.
The great fictional detective Sherlock Holmes, for example, is fond of claiming that he uses deductive reasoning. Chapter 2 suggested that Holmes instead uses inductive reasoning. However, since Holmes comes up with the most reasonable explanation of observed phenomena, like blood on a coat, for example, he is actually doing abductive reasoning. There is some dispute about whether inference to the best explanation is inductive or whether it is an entirely different kind of argument that is neither inductive nor deductive. For our purposes, it is treated as inductive.
Image Asset Management/SuperStockSherlock Holmes often used abductive reasoning, not deductive reasoning, to solve his mysteries.
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Section 6.5 Inference to the Best Explanation
A Closer Look: Is Abductive Reasoning Everywhere?
Some see inference to the best explanation as the most common type of inductive inference. A few of the inferences we have discussed in this book, for example, can potentially be cast as examples of inferences to the best explanation.
For example, appeals to authority (discussed in Chapter 5) can be seen as implicitly using inference to the best explanation (Harman, 1965). If you accept something as true because someone said it was, then you can be described as seeing the truth of the claim as the best explanation for why he or she said it. If we have good reason to think that the person was deluded or lying, then we are less certain of this conclusion because there are other likely explanations of why the person said it.
Furthermore, it is possible to see what we do when we interpret people’s words as a kind of inference to the best explanation of what they probably mean (Hobbs, 2004). If your neighbor says, “You are so funny,” for instance, we might use the context and tone to decide what he means by “funny” and why he is saying it (and whether he is being sarcastic). His comment can be seen as either rude or flattering, depending on what explanation we give for why he said it and what he meant.
Even the classic inductive inference pattern of inductive generalization can possibly be seen as implicitly involving a kind of inference to the best explanation: The best explanation of why our sample population showed that 90% of students have laptops is probably that 90% of all students have laptops. If there is good evidence that our sample was biased, then there would be a good competing explanation of our data.
Finally, much of scientific inference may be seen as trying to provide the best explanation for our observations (McMullin, 1992). Many hypotheses are attempts to explain observed phenomena. Testing them in such cases could then be seen as being done in the service of seeking the best explanation of why certain things are the way they are.
Take a look at the following examples of everyday inferences and see if they seem to involve arriving at the conclusion because it seems to offer the most likely explanation of the truth of the premise:

“John is smiling; he must be happy.”

“My phone says that Julie is calling, so it is probably Julie.”

“I see a brown Labrador across the street; my neighbor’s dog must have gotten out.”

“This movie has great reviews; it must be good.”

“The sky is getting brighter; it must be morning.”

“I see shoes that look like mine by the door; I apparently left my shoes there.”

“She still hasn’t called back yet; she probably doesn’t like me.”

“It smells good; someone is cooking a nice dinner.”

“My congressperson voted against this bill I support; she must have been afraid of offending her wealthy donors.”

“The test showed that the isotopes in the rock surrounding newly excavated bones had decayed X amount; therefore, the animals from which the bones came must have been here about 150 million years ago.”
These examples, and many others, suggest to some that inference to the explanation may be the most common form of reasoning that we use (Douven, 2011). Do you agree? Whether you agree with these expanded views on the role of inference or not, it clearly makes an enormous contribution to how we understand the world around us.
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Section 6.5 Inference to the Best Explanation
Form
Inferences to the best explanation generally involve the following pattern of reasoning:
X has been observed to be true.
Y would provide an explanation of why X is true.
No other explanation for X is as likely as Y.
Therefore, Y is probably true.
One strange thing about inferences to the best explanation is that they are often expressed in the form of a common fallacy, as follows:
If P is the case, then Q would also be true.
Q is true.
Therefore, P is probably true.
This pattern is the logical form of a deductive fallacy known as affirming the consequent
(discussed in Chapter 4). Therefore, we sometimes have to use the principle of charity to determine whether the person is attempting to provide an inference to the best explanation or making a simple deductive error. The principle of charity will be discussed in detail in Chapter 9; however, for our purposes here, you can think of it as giving your opponent and his or her argument the benefit of the doubt.
For example, the ancient Greek philosopher Aristotle reasoned as follows: “The world must be spherical, for the night sky looks different in the northern and southern regions, and that would be the case if the earth were spherical” (as cited in Wolf, 2004). His argument appears to have this structure:
If the earth is spherical, then the night sky would look different in the northern and southern regions.
The night sky does look different in the northern and southern regions.
Therefore, the earth is spherical.
It is not likely that Aristotle, the founding father of formal logic, would have made a mistake as silly as to affirm the consequent. It is far more likely that he was using inference to the best explanation. It is logically possible that there are other explanations for southern stars moving higher in the sky as one moves south, but it seems far more likely that it is due to the shape of the earth. Aristotle was just practicing strong abductive reasoning thousands of years before Columbus sailed the ocean blue (even Columbus would have had to use this type of reasoning, for he would have had to infer why he did not sail off the edge).
In more recent times, astronomers are still using inference to the best explanation to learn about the heavens. Let us consider the case of discovering planets outside our solar system, known as “exoplanets.” There are many methods employed to discover planets orbiting other stars. One of them, the radial velocity method, uses small changes in the frequency of light a
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Section 6.5 Inference to the Best Explanation
star emits. A star with a large planet orbiting it will wobble a little bit as the planet pulls on the star. That wobble will result in a pattern of changes in the frequency of light coming from the star. When astronomers see this pattern, they conclude that there is a planet orbiting the star. We can more fully explicate this reasoning in the following way:
That star’s light changes in a specific pattern.
Something must explain the changes.
A large planet orbiting the star would explain the changes.
No other explanation is as likely as the explanation provided by the large planet.
Therefore, that star probably has a large planet orbiting it.
The basic idea is that if there must be an explanation, and one of the available explanations is better than all the others, then that explanation is the one that is most likely to be true. The key issue here is that the explanation inferred in the conclusion has to be the best explanation available. If another explanation is as good—or better—then the inference is not nearly as strong.
Virtue of Simplicity
Another way to think about inferences to the best explanation is that they choose the simplest explanation from among otherwise equal explanations. In other words, if two theories make the same prediction, the one that gives the simplest explanation is usually the best one. This standard for comparing scientific theories is known as Occam’s razor, because it was originally posited by William of Ockham in the 14th century (Gibbs & Hiroshi, 1997).
A great example of this principle is Galileo’s demonstration that the sun, not the earth, is at the center of the solar system. Galileo’s theory provided the simplest explanation of observations about the planets. His heliocentric model, for example, provides a simpler explanation for the phases of Venus and why some of the planets appear to move backward (retrograde motion) than does the geocentric model. Geocentric astronomers tried to explain both of these with the idea that the planets sometimes make little loops (called epicycles) within their orbits (Gronwall, 2006). While it is certainly conceivable that they do make little loops, it seems to make the theory unnecessarily complex, because it requires a type of motion with no independent explanation of why it occurs, whereas Galileo’s theory does not require such extra assumptions.
Therefore, putting the sun at the center allows one to explain observed phenomena in the most simple manner possible, without making ad hoc assumptions (like epicycles) that today seem absurd. Galileo’s theory was ultimately correct, and he demonstrated it with strong inductive (more specifically, abductive) reasoning. (For another example of Occam’s razor at work, see A Closer Look: Abductive Reasoning and the Matrix.)
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Section 6.5 Inference to the Best Explanation
A Closer Look: Abductive Reasoning and the Matrix
One of the great questions from the history of philosophy is, “How do we know that the world exists outside of us as we perceive it?” We see a tree and we infer that it exists, but do we actually know for sure that it exists? The argument seems to go as follows:
I see a tree.
Therefore, a tree exists.
This inference, however, is invalid; it is possible for the premise to be true and the conclusion false. For example, we could be dreaming. Perhaps we think that the testimony of our other senses will make the argument valid:
I see a tree, I hear a tree, I feel a tree, and I smell a tree.
Therefore, a tree exists.
However, this argument is still invalid; it is possible that we could be dreaming all of those things as well. Some people state that senses like smell do not exist within dreams, but how do we know that is true? Perhaps we only dreamed that someone said that! In any case, even that would not rescue our argument, for there is an even stronger way to make the premise true and the conclusion false: What if your brain is actually in a vat somewhere attached to a computer, and a scientist is directly controlling all of your perceptions? (Or think of the 1999 movie The Matrix, in which humans are living in a simulated reality created by machines.)
One individual who struggled with these types of questions (though there were no computers back then) was a French philosopher named René Descartes. He sought a deductive proof that the world outside of us is real, despite these types of disturbing possibilities (Descartes, 1641/1993). He eventually came up with one of philosophy’s most famous arguments, “I think, therefore, I am” (or, more precisely, “I am thinking, therefore, I exist”), and from there attempted to prove that the world must exist outside of him.
Many philosophers feel that Descartes did a great job of raising difficult questions, but most feel that he failed in his attempt to find deductive proof of the world outside of our minds. Other philosophers, including David Hume, despaired of the possibility of a proof that we know that there is a world outside of us and became skeptics: They decided that absolute knowledge of a world outside of us is impossible (Hume, 1902).
However, perhaps the problem is not the failure of the particular arguments but the type of reasoning employed. Perhaps the solution is not deductive at all but rather abductive. It is not that it is logically impossible that tables and chairs and trees (and even other people) do not really exist; it is just that their actual existence provides the best explanation of our experiences. Consider these competing explanations of our experiences:

We are dreaming this whole thing.

We are hallucinating all of this.
©Warner Bros./Courtesy Everett CollectionIn The Matrix, we learn that our world is simulated by machines, and although we can see X, hear X, and feel X, X does not exist.
(continued)
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Section 6.5 Inference to the Best Explanation

Our brains are in a vat being controlled by a scientist.

Light waves are bouncing off the molecules on the surface of the tree and entering our eyeballs, where they are turned into electrical impulses that travel along neurons into our brains, somehow causing us to have the perception of a tree.
It may seem at first glance that the final option is the most complex and so should be rejected. However, let us take a closer look. The first two options do not offer much of an explanation for the details of our experience. They do not tell us why we are seeing a tree rather than something else or nothing at all. The third option seems to assume that there is a real world somewhere from which these experiences are generated (that is, the lab with the scientist in it). The full explanation of how things work in that world presumably must involve some complex laws of physics as well. There is no obvious reason to think that such an account would require fewer assumptions than an account of the world as we see it. Hence, all things considered, if our goal is to create a full explanation of reality, the final option seems to give the best account of why we are seeing the tree. It explains our observations without needless extra assumptions.
Therefore, if knowledge is assumed only to be deductive, then perhaps we do not know (with absolute deductive certainty) that there is a world outside of us. However, when we consider abductive knowledge, our evidence for the existence of the world as we see it may be rather strong.
A Closer Look: Abductive Reasoning and the Matrix (continued)
How to Assess an Explanation
There are many factors that influence the strength of an inference to the best explanation. However, when testing inferences to the best explanation for strength, these questions are good to keep in mind:

Does it agree well with the rest of human knowledge? Suggesting that your roommate’s car is gone because it floated away, for example, is not a very credible story because it would violate the laws of physics.

Does it provide the simplest explanation of the observed phenomena? According to Occam’s razor, we want to explain why things happen without unnecessary complexity.

Does it explain all relevant observations? We cannot simply ignore contradicting data because it contradicts our theory; we have to be able to explain why we see what we see.

Is it noncircular? Some explanations merely lead us in a circle. Stating that it is raining because water is falling from the sky, for example, does not give us any new information about what causes the water to fall.

Is it testable? Suggesting that invisible elves stole the car does not allow for empirical confirmation. An explanation is stronger if its elements are potentially observable.

Does it help us explain other phenomena as well? The best scientific theories do not just explain one thing but allow us to understand a whole range of related phenomena. This principle is called fecundity. Galileo’s explanation of the orbits of the planets is an example of a fecund theory because it explains several things all at once.
An explanation that has all of these virtues is likely to be better than one that does not.
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Section 6.5 Inference to the Best Explanation
A Limitation
One limitation of inference to the best explanation is that it depends on our coming up with the correct explanation as one of the candidates. If we do not think of the correct explanation when trying to imagine possible explanation, then inference to the best explanation can steer us wrong. This can happen with any inductive argument, of course; inductive arguments always carry some possibility that the conclusion may be false even if the premises are true. However, this limitation is a particular danger with inference to the best explanation because it relies on our being able to imagine the true explanation.
This is one reason that it is essential to always keep an open mind when using this technique. Further information may introduce new explanations or change which explanation is best. Being open to further information is important for all inductive inferences, but especially so for those involving inference to the best explanation.
Practice Problems 6.5
1.
This philosopher coined the term abductive reasoning.
a.
Karl Popper
b.
Charles Sanders Peirce
c.
Aristotle
d.
G. W. F. Hegel
2.
Sherlock Holmes is often said to be engaging in this form of reasoning, even though from a logical perspective he wasn’t.
a.
deductive
b.
inductive
c.
abductive
d.
productive
3.
In a specific city that happens to be a popular tourist destination, the number of residents going to the emergency rooms for asthma attacks increases in the summer. When the winter comes and tourism decreases, the number of asthma attacks goes down. What is the most probable inference to be drawn in this situation?
a.
The locals are allergic to tourists.
b.
Summer is the time that most people generally have asthma attacks.
c.
The increased tourism leads to higher levels of air pollution due to traffic.
d.
The tourists pollute the ocean with trash that then causes the locals to get sick.
4.
A couple goes to dinner and shares an appetizer, entrée, and dessert. Only one of the two gets sick. She drank a glass of wine, and her husband drank a beer. What is the most probable inference to be drawn in this situation?
a.
The wine was the cause of the sickness.
b.
The beer protected the man from the sickness.
c.
The appetizer affected the woman but not the man.
d.
The wine was rotten.
(continued)
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Section 6.5 Inference to the Best Explanation
5.
You are watching a magic performance, and there is a woman who appears to be floating in space. The magician passes a ring over her to give the impression that she is floating. What explanation fits best with Occam’s razor?
a.
The woman is actually floating off the ground.
b.
The magician is a great magician.
c.
There is some sort of unseen physical object holding the woman.
6.
You get a stomachache after eating out at a restaurant. What explanation fits best with Occam’s razor?
a.
You contracted Ebola and are in the beginning phases of symptoms.
b.
Someone poisoned the food that you ate.
c.
Something was wrong with the food you ate.
7.
In order to determine how a disease was spread in humans, researchers placed two groups of people into two rooms. Both rooms were exactly alike, and no people touched each other while in the rooms. However, researchers placed someone who was infected with the disease in one room. They found that those who were in the room with the infected person got sick, whereas those who were not with an infected person remained well. What explanation fits best with Occam’s razor?
a.
The disease is spread through direct physical contact.
b.
The disease is spread by airborne transmission.
c.
The people in the first room were already sick as well.
8.
There is a dent in your car door when you come out of the grocery store. What explanation fits best with Occam’s razor?
a.
Some other patron of the store hit your car with their car.
b.
A child kicked your door when walking into the store.
c.
Bad things tend to happen only to you in these types of situations.
9.
A student submits a paper that has an 80% matching rate when submitted to Turnitin. There are multiple sites that align exactly with the content of the paper. What explanation fits best with Occam’s razor?
a.
The student didn’t know it was wrong to copy things word for word without citing.
b.
The student knowingly took material that he did not write and used it as his own.
c.
Someone else copied the student’s work.
10.
You are a man, and you jokingly take a pregnancy test. The test comes up positive. What explanation fits best with Occam’s razor?
a.
You are pregnant.
b.
The test is correct.
c.
The test is defective.
11.
A bomb goes off in a supermarket in London. A terrorist group takes credit for the bombing. What explanation fits best with Occam’s razor?
a.
The British government is trying to cover up the bombing by blaming a terrorist group.
b.
The terrorist group is the cause of the bombing.
c.
The U.S. government actually bombed the market to get the British to help them fight terrorist groups.
Practice Problems 6.5 (continued)
(continued)
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Section 6.5 Inference to the Best Explanation
12.
You have friends and extended family over for Thanksgiving dinner. There are kids running through the house. You check the turkey and find that it is overcooked because the temperature on the oven is too high. What explanation fits best with Occam’s razor?
a.
The oven increased the temperature on its own.
b.
Someone turned up the heat to sabotage your turkey.
c.
You bumped the knob when you were putting something into the oven.
13.
Researchers recently mapped the genome of a human skeleton that was 45,000 years old. They found long fragments of Neanderthal DNA integrated into this human genome. What explanation fits best with Occam’s razor?
a.
Humans and Neanderthals interbred at some point prior to the life of this human.
b.
The scientists used a faulty method in establishing the genetic sequence.
c.
This was actually a Neanderthal skeleton.
14.
There is a recent downturn in employment and the economy. A politically far-leaning radio host claims that the downturn in the economy is the direct result of the president’s actions. What explanation fits best with Occam’s razor?
a.
The downturn in employment is due to many factors, and more research is in order.
b.
The downturn in employment is due to the president’s actions.
c.
The downturn in employment is really no one’s fault.
15.
In order for an explanation to be adequate, one should remember that __________.
a.
it should agree with other human knowledge
b.
it should include the highest level of complexity
c.
it should assume the thing it is trying to prove
d.
there are outlying situations that contradict the explanation
16.
The fecundity of an explanation refers to its __________.
a.
breadth of explanatory power
b.
inability to provide an understanding of a phenomenon
c.
lack of connection to what is being examined
d.
ability to bear children
17.
Why might one choose to use an inductive argument rather than a deductive argument?
a.
One possible explanation must be the correct one.
b.
The argument relates to something that is probabilistic rather than absolute.
c.
An inductive argument makes the argument valid.
d.
One should always use inductive arguments when possible.
18.
This is the method by which one can make a valid argument invalid.
a.
adding false supporting premises
b.
demonstrating that the argument is valid
c.
adding true supporting premises
d.
valid arguments cannot be made invalid
(continued)
Practice Problems 6.5 (continued)
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Section 6.5 Inference to the Best Explanation
19.
This form of inductive argument moves from the general to the specific.
a.
generalizations
b.
statistical syllogisms
c.
hypothetical syllogism
d.
modus tollens
Questions 20–24 relate to the following passage:
If I had gone to the theater, then I would have seen the new film about aliens. I didn’t go to the theater though, so I didn’t see the movie. I think that films about aliens and supernatural events are able to teach people a lot about what the future might hold in the realm of technology. Things like cell phones and space travel were only dreams in old movies, and now they actually exist. Science fiction can also demonstrate new futures in which people are more accepting of those that are different from them. The different species of characters in these films all working together and interacting with one another in harmony displays the unity of different people without explicitly making race or ethnicity an issue, thereby bringing people into these forms of thought without turning those away who do not want to explicitly confront these issues.
20.
How many arguments are in this passage?
a.
0
b.
1
c.
2
d.
3
21.
How many deductive arguments are in this passage?
a.
0
b.
1
c.
2
d.
3
22.
How many inductive arguments are in this passage?
a.
0
b.
1
c.
2
d.
3
23.
Which of the following are conclusions in the passage? Select all that apply.
a.
If I had gone to the theater, then I would have seen the new film about aliens.
b.
I didn’t go to the theater.
c.
Films about aliens and supernatural events are able to teach people a lot about what the future might hold in the realm of technology.
d.
The different species of characters in these films all working together and interacting with one another in harmony displays the unity of different people without explicitly making race or ethnicity an issue.
24.
Which change to the deductive argument would make it valid? Select all that apply.
a.
Changing the first sentence to “If I would have gone to the theater, I would not have seen the new film about aliens.”
b.
Changing the second sentence to “I didn’t see the new film about aliens.”
c.
Changing the conclusion to “Alien movies are at the theater.”
d.
Changing the second sentence to “I didn’t see the movie, so I didn’t go to the theater.”
Practice Problems 6.5 (continued)
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Summary and Resources
Summary and Resources
Chapter Summary
Although induction and deduction are treated differently in the field of logic, they are frequently
combined in arguments. Arguments with both deductive and inductive components
are generally considered to be inductive as a whole, but the important thing is to recognize
when deduction and induction are being used within the argument. Arguments that combine
inductive and deductive elements can take advantage of the strengths of each. They can
retain the robustness and persuasiveness of inductive arguments while using the stronger
connections of deductive arguments where these are available.
Science is one discipline in which we can see inductive and deductive arguments play out in
this fashion. The hypothetico–deductive method is one of the central logical tools of science.
It uses a deductive form to draw a conclusion from inductively supported premises. The
hypothetico–deductive method excels at disconfirming or falsifying hypotheses but cannot
be used to confirm hypotheses directly.
Inference to the best explanation, however, does provide evidence supporting the truth of a
hypothesis if it provides the best explanation of our observations and withstands our best
attempts at refutation. A key limitation of this method is that it depends on our being able to
come up with the correct explanation as a possibility in the first place. Nevertheless, it is a
powerful form of inference that is used all the time, not only in science but in our daily lives.
Critical Thinking Questions
1. You have probably encountered numerous conspiracy theories on the Internet and
in popular media. One such theory is that 9/11 was actually plotted and orchestrated
by the U.S. government. What is the relationship between conspiracy theories
and inference to the best possible explanation? In this example, do you think that
this is a better explanation than the most popular one? Why or why not?
2. What are some methods you can use to determine whether or not information
represents the best possible explanation of events? How can you evaluate sources of
information to determine whether or not they should be trusted?
3. Descartes claimed that it might be the case that humans are totally deceived about
all aspects of their existence. He went so far as to claim that God could be evil and
could be making it so that human perception is completely wrong about everything.
However, he also claimed that there is one thing that cannot be doubted: So long as
he is thinking, it is impossible for him to doubt that it is he who is thinking. Hence, so
long as he thinks, he exists. Do you think that this argument establishes the inherent
existence of the thinking being? Why or why not?
4. Have you ever been persuaded by an argument that ended up leading you to a false
conclusion? If so, what happened, and what could you have done differently to prevent
yourself from believing a false conclusion?
5. How can you incorporate elements of the hypothetico–deductive method into your
own problem solving? Are there methods here that can be used to analyze situations
in your personal and professional life? What can we learn about the search for truth
from the methods that scientists use to enhance knowledge?
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Summary and Resources
abductive reasoning See inference to the
best explanation.
falsifiable Describes a claim that is conceivably
possible to prove false. That does not
mean that it is false; only that prior to testing,
it is possible that it could have been.
falsification The effort to disprove a claim
(typically by finding a counterexample to it).
hypothesis A conjecture about how some
part of the world works.
hypothetico–deductive method The
method of creating a hypothesis and
then attempting to falsify it through
experimentation.
inference to the best explanation The
process of inferring something to be true
because it is the most likely explanation of
some observations. Also known as abductive
reasoning.
Occam’s razor The principle that, when
seeking an explanation for some phenomena,
the simpler the explanation the better.
self-sealing propositions Claims that cannot
be proved false because they are interpreted
in a way that protects them against
any possible counterexample.
Web Resources

Watch Ashford professor Justin Harrison lecture on the difference between inductive and
deductive arguments.

Shmoop offers an animated video on the difference between induction and deduction.
http://www.ac4d.com/2012/06/03/abductive-reasoning-in-airport-security-and-profiling
Design expert Jon Kolko applies abductive reasoning to airport security in this blog post.
Key Terms
Answers to Practice Problems
Practice Problems 6.1
1. d
2. a
3. b
4. b
Practice Problems 6.2
1. a
2. a
3. a
4. a
Practice Problem 6.3
1. b
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Summary and Resources
Practice Problems 6.4
1. b
2. c
3. d
4. d
5. b
Practice Problems 6.5
1. b
2. a
3. c
4. a
5. c
6. c
7. b
8. a
9. b
10. c
11. b
12. c
13. a
14. a
15. a
16. a
17. b
18. d
19. b
20. d
21. b
22. c
23. c
24. d
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What is behind these high rates of truancy and chronic absenteeism among school students?

Bullying, Peer Social Support, and Absenteeism Relationship: A Correlational Study

Concordia University-Portland

2019

Abstract

 Previous studies into the field of truancy and absenteeism in secondary schools have categorized significant truancy causes and absenteeism into four groups. Also, most of the previous studies have a longstanding view that the problematic issue of truancy exists only in one single domain which is the schools.  Scholars who have studied the effect of absenteeism and truancy in secondary school have not taken into account the existing assertions that have become a topic of discussion in various forums. These forums suggest the ways through which the simplistic thinking can be used to place severe constraints that can be used to understand the various complex ways through which a child can develop the truant behaviors that they may exhibit later in life. According to Ingul and Nordahl (2013), the simplistic thinking through which students develop the missing behaviors are always vital to understanding the primary cause of truant behaviors and solutions. Viewing the problem of school truancy must be completed as a multi-dimensional issue with a multitude of factors coming into play. The various factors that correlate to truancy as per the existing literature are known to be numerous and diverse, making truancy to be a broad topic with various causes and effects. Truancy is also believed to exist in the context of interaction which includes the interaction between the various students through which they acquire some of these characteristics. Some of the interaction effects also include the support accorded to the students from the peers, the experience the students acquire from the school environment and the settings of the community in general. The purpose of this correlational study is to determine whether a relationship exists between bullying and absenteeism in school students of age 18 and above within rural settings. Also, the study attempts to establish the relationship between peer social support and absenteeism among students of age 18 and above within rural settings.

Table of Contents

Abstract                                                                                                                                   2

Chapter One:                                                                                                                           5

Introduction                                                                                                                5

Background, Context, History, and Conceptual Framework of the Problem                        9

Problem Statement                                                                                                      12

Purpose of Proposed Study                                                                                        12

Research Questions                                                                                                     13

Hypothesis                                                                                                                  13

Rationale, Relevance, and Significance of the Proposed Study                                13

Definition of Terms                                                                                                    15

Assumptions, Delimitations, and Limitations                                                             15

Summary                                                                                                                     17

Chapter Two:  Literature Review                                                                                           17

Introduction                                                                                                                17

Conceptual Framework                                                                                               19

Behaviorism Theory                                                                                                    25

Cognitive Information Processing                                                                              26

Review of Research Literature and Methodological Literature                                 29

Review of the Methodological Findings                                                                    37

Synthesis of the Research Findings                                                                            40

Critique of the Previous Research                                                                              42

Summary                                                                                                                     46

Chapter Three:  Methodology                                                                                                 47

Introduction                                                                                                                47

Purpose of the Proposed Study                                                                                  49

Research Questions                                                                                                     50

Research Design                                                                                                         50

Target Population, Sampling Method and Related Procedures                                  52

Instrumentation                                                                                                           53

Data Collection                                                                                                           56

Operationalization of Variables                                                                                  57

Data Analysis Procedures                                                                                           59

Limitations and Delimitations of the Research Design                                              60

Limitations                                                                                                                  60

Delimitations                                                                                                               61

Validity                                                                                                                       61

Expected Findings                                                                                                      62

Ethical Issues in the Proposed Study                                                                         63

Summary                                                                                                                     63

References                                                                                                                              65                                                                                                                           Chapter One: IntroductionIntroduction

Each day, hundreds of thousands of American learners are out of school without permissible excuses, and this habit has risen to among the top ten major problems experienced by schools across the nation (DeSocio, VanCura, & Nelson, 2007). Absenteeism has been increasing. Demir and Karabeyogular (2016) in their study noted that administrative records from secondary education indicate that there is a rapid increase compared to other levels of education. For instance, in 2008-2009, the Department of Education noticed that the ratio of students who were absent for more than 20 days to all registered secondary school students was 1.1 percent. However, in 2009-2010, that ratio had risen to 4 percent (Demir & Karabeyoglu, 2016). On the contrary, the vocational and technical secondary education attendance rate rose from 1.45 percent to 4.1percent between 2008 and 2010, clearly indicating that absenteeism is a problem that is notorious to the secondary education but not to higher institutions of education (Demir & Karabeyoglu, 2016). Truancy is not only an American educational problem, but it is also a global menace. One and a half percent, 1.8 percent, 2.0 percent and 2.4 percent of the overall student population of England, Wales, Scotland, and Ulster respectively are out of class without permission, and in Scotland, five students miss school every day (Rivers, 2010).

Ironically, student attendance is one of the significant variables contributing to higher student achievement. Studies into the relationship between school attendance and academic achievement point out a strong relationship between course attendance and standardized test scores or graduate grades (Gottrified, 2009; Nichols, 2003; Roby, 2004; Sheldon, 2007). Some researchers have suggested that the levels of attendance are direct indicator as well as determinants of academic success (Sheldon, 2007). Also, research has discovered that besides low attendance being a predictor of academic success, it also predicts high-risk factors for future education (Nichols, 2003). Fundamentally, truancy and absenteeism interrupt the learning process because the educational system is established from the assumption that students will attend school, and that success solely depends on full participation in entire classes (Rivers, 2010).

Furthermore, truancy and absenteeism carry direct and indirect costs to the individuals, families, communities, and schools. Truancy or absenteeism in school, as identified above, negatively affect student learning experience whose result is a mediocre academic achievement. The adverse effect on learning is then passed on to other learners since the teachers are sometimes forced to use the additional time to compensate for those who missed the classes. Eventually, other students lose learning time, this is a major problem in interconnected courses such as mathematics (Rivers, 2010). When learners fall behind in their learning, they are likely to lose interest which increases their chances of failing (Rivers, 2010).

Additionally, absent students set a terrible example to the rest and encourage the habit of truancy and absenteeism (Rivers, 2010). Absenteeism doubles as an indicator of low academic performance as well as diminished social and life success. Absenteeism acts as a barrier to the establishment of a solid foundation concerning a sense of responsibility and discipline. The result will show-up in discipline habits and work problems in future which may ultimately translate into an inability to work, low income or total unemployment due to failure to secure a job (Rivers, 2010). Such individuals will not raise income to sustain their families and make no positive impact on the communities.

Moreover, students who experience increased truancy and absenteeism are inclined to face psychological problems such as behavioral disorders and depression (Reid, 2003). They may also get involved in criminal violence in and out of school. Absenteeism also encourages teenage pregnancy as well as drug and substance abuse (Gottfried, 2009). In a nutshell, truancy and absenteeism are considered reliable predictors of academic failure and further consequences which include risk behaviors that will eventually impact on not only the individual but also schools, families and entire communities.

What is behind these high rates of truancy and chronic absenteeism among school students? According to Zhang, Katsiyannis, Barrett, and Wilson (2007), causes of truancy fall under four categories; family factors, school, economic influences, and student variables. This research will focus on student variables and determine relationships between student bullying, peer support, and missed school days. Student variables that potentially play a role in truancy include mental and physical health problems, self-perception, substance abuse, and detachment from school. Bullying and a lack of peer support can lead to many different student issues in school. Victims of bullying tend to be insecure which provides an excuse to miss school (Reid, 1999). According to DeSocio et al. (2007), mental and physical health issues such as depression, stress disorder and anxiety among the learners contribute to absenteeism. Kowalski, Limber, and Agatston (2012) suggested that students who are victims are relieved when the school day ends, so they have absolution from the bully. Students that held low self-perceptions were most likely to be absent from school than their counterparts who held high-self-esteem. For instance, students that felt they would not graduate from high school concluded that they would not join college and hence needed not to attend school all the time (Henry, 2007). DeSocio et al. (2007) established that 30% of truants attributed their absences to detachment or disengagement from school. Learners exhibiting school disengagement are not committed to the school, hold low aspirations for their future and are overall poor achievers (Henry, 2007).

In large schools, students may feel alienated and isolated in the school setting and choose to escape such feelings by opting to stay out of such environment (Wilkins, 2008). Such students are uncomfortable with the school environment and feel devalued, unaccepted or unwanted as a result of a lack of connection to trustworthy persons within the school. In large classrooms, teachers easily fail to meet students’ diverse needs, leading to a poor student-teacher relationship. Cumulatively, these factors lead to a school climate and attitude whereby each fends for himself or herself. Henry (2007) attributed 23% of truants as a result of learners feeling unsafe in their school environment. Logically, if a student feels unsafe, uncomfortable, and insecure in a school environment, he or she will choose not to attend.

Truancy and absenteeism among secondary school students may be as a result of the four categories; family factors, school factors, economic factors, and student variables (Zhang et al. 2007) that causes truancy identified in their research. However, since the simplistic approach places severe constraints that can be used to understand the complex issues related to truancy as well as the need to view truancy as a multi-dimensional issue with a magnitude of factors, this study seeks to identify the relationship between bullying, peer support, and missed days of school. The basic data gained from this study will provide valuable information about student’s absences from school.

Bullying is a challenge with which various learning institutions are struggling to overcome. Craig and Pepler (2007) proposed that bullying at schools takes place when people are repeatedly exposed over time to negative physical and verbal activities on part of one or more learners. The relationships of bullying involve imbalance of power and strength. It involves repeated aggressive activities committed by people who have power advantages over their victims (Craig & Pepler, 2007). Application of exact definitions to bullying may be hard since bullying has transformed and continues to change in line with societal transformations. For instance, as technologies develop, new opportunities for possible bullying also develop. The idea that a behavior of a person, as described by Social Learning Theory (Clark, 2013), is learned by emulating and observing the behaviors of others are significant to this research since it can assist school districts to better comprehend why bullying may be occurring in their learning institutions, especially secondary schools and the way to deal with it.

Ingul and Nordahl (2013) noted that because experiences of social interactions can shape behavior, both the victims and the bullies are in a position of learning pro-social behaviors which are suitable for schools in case those pro-social behaviors are modeled or observed as well as openly supported and taught by educators. Today, teachers are more aware of the direct bullying effects on peer social relationships due to the augmented attention provided to victimization impacts on other in settings of the public schools. Nevertheless, educators still note: they are not ready to operate with learners who bully, having limited comprehension or knowledge of the related bullying and aggression effects on other school variables like attendance and academic achievement for both perpetrators’ and victims’ together with other victimized learners in proximity to the bullies.

Background, Context, History and Conceptual Framework of the Problem

The plethora of the literature that is available shows that the causes of truancy and absenteeism can be grouped as school sourced, teachers’ sourced, parents’ sourced, students’ sourced, and psychology sourced (Zhang et al., 2007). School-related truancy and absenteeism causes are those related to existing relationships between the teachers and the students and affect their behaviors. They also include the school factors such as school climate, attitudes, class size, school disciplinary policy on truancy, and ability to meet the diverse needs of the learners (Wilkins, 2008). In large-size schools, students often feel isolated, and to escape they choose not to attend school (Dahl, 2016). Often, these students tend to feel uncomfortable, unvalued, unwanted, insecure, and unaccepted. The students often lack connection to individuals within the school whom they can trust and turn to, in case they have a problem (Dahl, 2016). Unsafe school environment prompts learners to skip school (Henry & Yelkpieri, 2017). Where the school policy on truancy allows teachers to impose severe punishment on the truant students, the situation may even worsen further (Tobin, 2009).

Balfanz and Bynes (2012) stated that parents also play a role in encouraging school truancy in their children. Depending on the nature of the family in which a given child hails, there exist many factors which may dictate the behavior of the child. Factors such as parenting styles, the divorce, and the breakdown of parents always largely contribute to the behaviors of the children (Balfanz & Bynes, 2012). Also, parents who fail to supervise their children after school contributes to higher truancy levels (Henry & Yelkpieri, 2017). Similarly, household incomes have a bearing on truancy levels. For example, children from low-income families tend to exhibit higher truancy than their counterparts (Zhang et al., 2007).

Truancy may also arise from the student factors. Student psychology is a crucial determinant in truancy. According to Chen, Culhane, Metraux, Park, & Venable (2016), the psychological moods of the students are always the primary determinant of their decision to go to school. Enomoto (2007) mentioned that when the students feel ignored by their teachers, they lose the morale of going to school. The motivation of these students is crucial for their self-esteem which dictates their school attendance. Also, students with mental health problems such as stress disorder, depression, anxiety, and substance abuse are likely to skip school more often. Henry and Yelkpieri (2017) established that students who abused substances, such as alcohol, were more likely to skip school than their counterparts. Students are likely to become truant if they smoke cigarettes and marijuana at least once a month (Henry & Yelkpieri, 2017). Student’s self-perception also determines truancy, since those who hold lower perceptions opt to skip school more regularly than those who hold higher self-perceptions and their future (Henry & Yelkpieri, 2017).

According to Barger (2018) and Kennedy, Russom and Kevorkian (2012) today, school attendance is one of the most perplexing problems experienced in public schools across the globe. Teachers often compromise the effective discharge of their professional responsibilities by several challenges which are independent of the attendance of the students in these schools. Barger (2018) continues by saying these challenges are often differing viewpoints of what is and what is not bullying between the student and teacher. Thus, as a remedy, schools have stipulated to teach students the difference between bullying, positive advice, and helpful criticism while continuing to encourage good attendance (Barger, 2018). The effects of absenteeism are always far-reaching with significant consequences that may result in negative implications in various levels within society. Henry and Yelkpieri (2017) stated that truancy could be vital in predicting poor academic performance, maladjustment, school dropout, teenage pregnancy, delinquency, and substance abuse.

The long-term effects of truancy include marital instability, violence, job instability, incarceration, and adult criminality (Teasley, 2004). Truancy is also known to exert a negative effect on the community because of its correlation with crime, delinquency, as well as other adverse outcomes (Teasley, 2004). Truancy and absenteeism also lead to school dropouts and delinquency issues such as theft, burglary, and vandalism. Ekstrand (2015) consistently found a relationship between high rates of delinquency and truancy as well as the dropout rates. The youths that have dropped out of school and indulge in criminal activities finally end up behind bars in the United States (Dahl, 2016). They will add to the escalating number of inmates who have continued to siphon much of the public resources (Holtes, Bannink, Zwanenburg, As, Raat, & Broeren, 2015).

Predictor Variables

–          Bullying

 

 

–          Peer Social Support

Relationship:

-As bullying occurs, missed days of school increase.

-As bullying does not occur, missed days of school decrease.

-Peer Social Support is lacking, missed days of school increase.

-Peer Social Support is present, missed days of school decrease.

Criterion Variable

 

–          School absences

 

 

Figure 1. Conceptual Framework

Problem Statement

In identifying the problem of absenteeism in a County in a rural Virginia school division one must investigate some of the causes of why students miss school.  The county school division is making a focused effort to maximize student attendance and lower yearly absences (Rockingham County Public Schools Student Handbook, 2018). It is the goal of the researcher to determine if two predictor variables (bullying and peer social support) have a relationship with the criterion variable (school absences).

 

Purpose of the Proposed Study

The purpose of this quantitative correlational study is to determine whether a relationship exists between bullying and absenteeism in school students of age 18 and above within rural settings. Also, the study attempts to establish the relationship between peer social support and absenteeism among students of age 18 and above within rural settings.

The proposed study intends to use the findings and conclusions as a foundation to potentially build on another study to investigate how the two variables lead to absenteeism. The examination of each of these issues will be necessary to discern which variable plays a significant role in truancy and absenteeism among the 18-year-old secondary school students to cause a higher rate of truancy. Examining the factors will allow the researcher and the beneficiaries of the study findings to identify peculiar characteristics contributing to the significant difference in truancy and absenteeism among verified participants.

Research Questions

  1. Is there any relationship between peer social support and school absences?
  2. Is there any relationship between being bullied and school absences?

Hypotheses

H01: There is no significant relationship between peer social support and school absences.

HA1: There is a significant relationship between peer social support and school absences.

H02: There is no significant relationship between being bullied and school absences.

HA2: There is a significant relationship between being bullied and school absences.

 Rationale, Relevance, and Significance of the Proposed Study

The primary purpose of this study is to identify a possible relationship between students bullied and school absences. Also, there is possible relationship between peer social support and school absences. The objective of the research will potentially enable educational experts as well as the schools’ administration to find ways of reducing the ever-increasing rate of school absenteeism. The success or performance of the students in secondary schools has been most affected by the high level of absenteeism in different institutions (Reid, 1999). This research will act as the foundation for the future solution aimed at increasing attendance through the eradication or minimizing student absenteeism which is one of the major performance problems in secondary schools (Nichols, 2003). School absenteeism greatly affects many students and, as a result, it has been the central issue of concern to the parents, teachers, and administrators. It also has accompanying costs such as depression, unemployment, and illiteracy to the student, other students, the school and the entire community (Reid, 1999).

Furthermore, there is lack of enough studies capable of providing a solution to the school attendance problem hence the need to conduct this research. Previous studies by Sahin, Arseven, and Kilic (2016) and Fan and Wolters (2014) have examined the issue of truancy and absenteeism in general or among the entire secondary school population. With this quantitative research, the actual data will be applied to enable the educators to understand specifically two causes of attendance problems and after that find appropriate measures on how to address the problem. Of essence is to focus on the 18-year-old attendance issues and from there understand the pertinent issues such as school environment in determining truancy and attendance. An 18-year-old is typically a senior in high school and has encountered many different experiences throughout their school career.

The proposed research will be practical in that there will be no use of secondary data or qualitative studies to answer the research questions. For the proposed research, applying systematic and theoretical analysis as the methodology is essential. The raw data from the real world set up will be analysed casting no doubt on the applicability of its findings. Logically, the best solutions to a problem are those founded on the real facts in the actual setting. Therefore, by ascertaining the relationships between bullying, peer social support, and missed school days’ help identify two possible causes for truancy.

Definition of Terms

Absenteeism. Literature provides slightly varying definitions for absenteeism. Some scholars (Altinkurt, 2008; Kearney, 2008) consider absenteeism as the absence of schooling by using a verified excuse or using an unverifiable excuse. Some consider absenteeism as a general term used when referring to a general absence from school or work without any valid reason (Akbasli, Sahin, & Yilmaz, 2017). For the proposed study, the researcher defines absenteeism as the student’s absence from school because of a particular reason. The proposed study considers absenteeism as a phenomenon that result from some causes which are either related to the school, the parent or the student. Therefore, for a student to miss school there must be an underlying reason which the study wants to uncover through inquiry.

Truancy. Akbasli, et al. (2017) defined truancy as a situation whereby a learner deliberately stays away from school without permission. It is synonymous with “skipping off”, “dodging”, “going missing”, and “mitching” (Akbasli et al., 2017). The proposed study similarly defined truancy and often uses “skipping of school” to mean the same thing. Additionally, Akbasli et al. (2017) defined truancy as any intentional, unauthorized, unjustified, as well as the illegal absence of an individual from compulsory education. The absence resulting from truancy is often due to a free will of the students and is not inclusive of the legitimate absence that may arise due to an excused absence.

Assumptions, Delimitations, and Limitations

Assumptions: Researchers have any number of items in their study that they recognize as authentic (“Stating the Obvious,” n.d.). These authentic items are known as assumptions. Within the proposed study there includes some assumptions. The first assumption is that 18-year-old students have encountered experiences that lead them to miss days of school. Depending on the student, such experiences may affect the way they feel about the school, safe or unsafe. When it feels unsafe, the researcher assumes the days missed will likely be high. Every school day missed is accounted for is another assumption. In other words, every student that is absent from school has a reason either valid or invalid, but which accounts for why he or she chose to skip school. The last assumption is that schools implement general programs to deal with absenteeism without considering the main cause of the issue which may vary from one student to another. As a result, students may be punished or face a court hearing which does not address the needs and do not account for an individual’s absenteeism.

Limitations: Every study has its failings that the researcher does not have authority over (“Stating the Obvious,” n.d.). These failings are known as limitations. The proposed study survey questions have been written to aid in the collection of data on the amount of bullying and the amount of peer social support that a student experiences in high school. This means that much of the data is collected from students and their self-report concerning bullying, peer social support, and school attendance. However, the researcher will provide a definition of each variable in an attempt to limit the subjectivity of the respondent’s answers. Also, finding enough students to participate in the study may be challenging because some of them may decline to participate.

Delimitations: When developing and organizing studies researchers must define the perimeters of the study. Examples of the perimeters are the objective, variable, and research questions. The three examples are in the control of the researcher and is known as delimitations (“Stating the Obvious,” n.d.). With this study several delimitations are associated. First, information is only obtained from three of the four high schools located in the rural area of Virginia.  Secondly, the research delimited the two surveys to students that are 18 years of age and older that continue to be enrolled in school. Lastly, delimitations were not applied to other characteristics that may include special needs students, students that are on free and reduced lunch, socioeconomic status, gender or diversity of the students.

Summary

Once the proposed study is completed the researcher seeks to establish a relationship between 18-year-old students that have experienced some bullying and school absences. Additionally, the researcher seeks to establish a relationship between peer social support and school absences. Identifying and examining the main variables of bullying, peer social support, and school absences identified in the literature as possible causes for students to miss school frequently.

The researcher organized the proposed study into five chapters. The first chapter will introduce the reader of the dissertation to the research problem, research question, relevance, rationale and significance of the study. It also defines essential terms used in the study to help the reader understand what they mean in the context of the research. A literature review documents the existing literature on bullying and absenteeism in the second chapter. It enlightens the reader on what is already known about the research problems. The third chapter will focus on the proposed study’s methodologies. It shall explain the methods used by the researcher to answer the research questions. It shall also explain the approaches used to analyse and present the study findings. The fourth chapter will consist of results and discussion. In this chapter, the researcher provides the results and analysis, and then follows up by a discussion of the results. Finally, the dissertation will end with chapter five by providing conclusions and recommendations.

 

 

Chapter Two: Literature Review

Introduction

According to Mishna (2012), bullying is a form of hostility which can either be indirect or direct. Bullying occurs in an influential environment by parties engaging in verbal, mental, and physical activity. Bullying leads to absenteeism among school students. Absenteeism entails regularly staying away from school without a valid reason. Pupils who engage in truancy fail to attend classes due to fear of avoiding harassment.

Bullying is rampant among teens in the United States. A quarter of students experience bullying according to research on harassment in 2013 from the Centers for Disease Control and Prevention (CDC). 15.5% of students miss school due to harassment, while 4.1% are absent due to rational reasons (Adolesc, 2015). Furthermore, electronic bullying leads to absenteeism, according to Grinshteyn and Tony Yang (2017). Most students are absent from school because of fear. Students with chronic conditions are absent from school since they are victims of regular bullying, according to Grinshteyn and Tony Yang (2017). Interventions assists in reducing bullying rates. Integrating community efforts and school management contributes to influencing avoidance of harassment in schools. Unfortunately, several approaches which have been put in place to curb bullying in high school have been futile.

Factors that contribute to bullying in high school include cultural conditions, peer groups, family, and individual features (Mishna, 2012). Bullying is a repetitive act which is hazardous. Prejudice is a form of bullying which takes place when one is not a member of a specific gender and has different ideology concerning a particular group (Mishna, 2012). High school students torment their colleagues because they are not in the same social status, gender, and racial disparity. Moreover, high school students are victims of harassment because of having low self-esteem, lack of confidence, and absence of support from teachers.

Bullying leads to students being absent from school because they feel insecure. Research by Grinshteyn and Tony Yang (2017) shows how electronic bullying makes students engage in absenteeism more often than those who are not victims of harassment. Victims of bullying engage in binge drinking because of depression (Grinshteyn & Yang, 2017). Harassment makes students feel hopeless daily due to fear. Students who are absent due to bullying achieve poor performance. Absent students fail to attend classes with essential subjects and teachings.

Furthermore, harassment results in high levels of unhappiness, anxiety, insecurity, depression, low self-esteem, mental and physical symptoms (Gruber & Fineran, 2007). Victims of annoyance have difficulty in making friends, isolation, and weak interactions with their classmates. Victims of a bully do not build strong relations with other parties — students who encounter bullying experience high levels of despair. Harassment facilitates the development of anxiety and depression among students. Records show that 20% of school victims had a clinical range on normal anxiety and depression measure in research by Espelage and Holt (2001).

Truancy refers to any intentional, unlawful, and inexcusable absence of an individual from compulsory education (Jones, 2019). [JD1]Absence resulting from absenteeism is often not legitimate since it happens at free will. Legal procedures that emanate from absenteeism does not relate to absence due to valid reasons. Schools across the globe employ policies and measures which intervene on truancy among their students. Truancy leads to the inability to graduate and receive class credits among school students. Truant students have to make for nonattendance through fines and summer schooling.

Institutions, districts, and governments have put in place various strategies for recognizing truancy. Mechanisms collectively identify consecutive illegal absence from school as a standard definition. In a report by Baker, Sigmon, and Nugent (2001), most students practice truancy in the United States, leading to schools ranking it in their top ten challenges. Many students fail to attend classes without a valid excuse from the relevant authority. Eventually, truancy significantly contributes to undermining the educational system of the United States. Menace of truancy and absenteeism intensifies from schools to other environments. Nonetheless, absenteeism not only affects students in the United States but also affects school students in the UK countries such as Scotland, England, Ulster and Wales (Grant, 2007, Shute & Cooper, 2015, Truancy rates worst in the UK: Education, 2008).

According to Reid (2006), school attendance critical variables simplifies measuring of achievement levels among students. Students who display long-lasting absenteeism tend to practice truancy hence suggesting the need for implementation of corrective measures. Intervention which curbs truancy needs proper approach. Truancy and absenteeism have devastating impacts if no response is applicable, therefore requiring urgent supervision from specialists. Absenteeism affects the progress of students through adverse physical, social, and psychological effects. Nonattendance expresses the student’s negative emotional state about school. Moreover, absenteeism represents many different motives that the teachers, as well as parents, need to take into account (Reid, 2006).

The accomplishment of school students in their coursework depends on their daily appearance in classes as well as lesson attendance. According to Breda (2014), factors which are logical such as financial constraints, sickness, high school fees, and weather conditions attribute to absenteeism. Factors contributing to truancy in school students include social status, age, mistreatment, lacking peer social support, the arrogance of teachers, and poor school administration (Mervilde, 1981). These factors need regulation for proper tackling of truancy and absenteeism among students.

Conceptual Framework

There are various groups of absenteeism classes, which includes, school sourced, teachers’ sourced, parents’ sourced, students’ sourced, and psychology sourced (Zhang et al., 2007). School sourced absenteeism emanates from existing relationships between teachers and students, which affects their behaviors. Negative thoughts among students originate from their existing human behaviors. Students incorporate harmful intentions concerning activities within the school, incompetence of staff, and harsh supervision of a school, resulting in agitation. Students whose practices entails school sourced absenteeism eventually lose curiosity regarding school attendance, according to Williams (2002). Some school students engage in truancy due to climate settings, the extent of school, the magnitude of classes, arrogances, punishment policy at school, and pleasure. Dahl (2016), alludes that students who attend large schools may seldom experience a lack of inclusion in the affairs of their school. Unfortunately, most students avoid a feeling of non-inclusion by not attending classes. Students experiencing isolation tend to feel uncomfortable, unrecognized, unwelcome, and doubtful. In most cases of separation, students lack someone whom they can confide in to find a solution to their grievances.

Students have instructional and social needs while in large classrooms. Relationship between teachers and students is always weak since instructors cannot continually address problems of every student. According to Strand and Granlund (2013) students encounter cold school climate where each survives on their own because of feeble association with teachers. Students feel insecure in whom to confide in with their problems. Henry and Yelkpieri (2017) identify in their study that 23% of the truant students who choose to avoid attending classes is due to feeling insecure. According to Tobin (2009), administering severe punishment for truant learners in such cases can only intensify the absentee behavior. Corrective measures which impacts on the functioning of students control truancy rates rather than an intensive penalty.

Williams (1999) identifies teacher sourced absenteeism, which often comes about as an outcome of teachers’ high anticipations for their students ensuing into truancy. High expectations from teachers attribute to absenteeism in students. Students tend to attend school in cases where they encounter a positive attitude from instructors (Wadesango & Machingambi, 2011). Optimistic attitude and behaviors of teachers while inside and outside of institutions affects the personality of students. Dictatorial, high expectations, and absence of communication from tutors transpire into teacher sourced absenteeism. Teachers need to establish positive interactions with students to promote lower rates of truancy.

Parents also promote school truancy in their kids. The nature of the family of a child and many other factors influences their conduct. Childcare styles, separation of parents, and failure marriages generally contribute to behaviors of kids (Balfanz & Bynes, 2012). Pressure from family often steers truancy in students. Students depend on the support of their family to continue with education. Parents’ training, household earnings, and parental supervision affect domestic homes. Henry and Yelkpieri (2017) identify a close connection between these household factors and truant behaviors among kids. Lower education levels of fathers lead to high cases of truancy in children. Likewise, in cases where the mother is a high school dropout, truancy rates also increase. Therefore, parents ought to be careful when attending to their children. Failure of establishing a healthy and positive relationship between parents and children promotes the development of parent caused truancy.

Henry and Yelkpieri (2017) indicate that children whose parents never direct them after school are probably engaging in truancy. In their study, 29.9% of the children became truant because of lack of supervision after school for periods lasting four hours. Moreover, approximately 11.3% of the children became truant because of lack of oversight thoroughly after school. Parent supervision contributes to declining of truancy cases — children who operate under supervision practice behaviors which are desirable in their households. A comparable study by Zhang et al. (2007) links truancy in kids to levels of earnings of their homes. Kids who originate from a humble background engage in truancy and eventually end up in the juvenile justice system. Kids hailing from a prosperous household do not take part in truancy behaviors regularly.

Students engage in truancy by being absent from class without giving any justification. Students fail to attend classes because of uninteresting lessons, dislike of an instructor, fear of harassment, and lower expectations. Thus, student-initiated truancy is a result of a lack of enthusiasm for education. Psychology causes truancy among students. According to Chen et al. (2016), the psychological attitudes of students are determinants of their conclusion to go to school. Enomoto (2007) identifies that ignoring the needs of students declines their determination of attending classes. Motivating students is vital for their confidence, which facilitates their class turnout. Students who receive motivation from teachers tend to attend classes frequently. Apart from psychological problems, truancy causes physical and mental fitness problems. Behaviors of students depend on their mental state. Eventually, truants engage in abuse of drugs and substances hence dropping from school. DeSocio et al. (2007) display various psychological and physical issues that prompt school absenteeism in students. Researchers establish a relationship between family and students’ mental health condition. Boyce (2002) states psychological health conditions such as post-traumatic stress disorder, hopelessness, anxiety, and drug abuse is a pointer of a developing complication. Henry and Yelkpieri (2017), implicates those who are likely to skip classes are drug abusers such as alcoholics. Truancy leads to devastating repercussions which need measures for regulation. Employing strategic interventions reduces cases of absenteeism among students.

Additionally, Henry and Yelkpieri (2017) state that students who smoke cigarette and marijuana at least once a month are likely to practice truancy. The opinion of students about themselves is essential. Interviews concerning the probability of truant students graduating from high school and attending College shows the relationship between perception and behavior. Lower understanding enhances skipping school while high knowledge lowers truancy. Students who do not comprehend affairs at schools tend to be absent in some classes. Active students participate in diverse issues of school hence minimizing their urge for engaging in truancy. 44.5% and 30% are truancy levels of students who gave answers like “probably won’t” graduate from high school and “definitely won’t” attend college respectively (Henry & Yelkpieri, 2017). Students who lack interest develop a negative attitude which favors the formation of truancy. In summary, Henry and Yelkpieri (2017) state that most students who commit high truancy levels drop out of school. Moreover, truants lack commitment and at all times, turn out to hold low ambitions and eventually become poor go-getters. Truancy leads to high levels of school dropping if not kept under supervision.

Chronic absenteeism results in a student dropping out of school. Chen et al. (2016) denote how truancy cases resulting in dropout rates are rampant in contemporary society. Chen et al. (2016) note that truancy rates are more significant in places with diverse racial disparity with low-income earners and have many high schools. Moreover, such areas encounter high rates of truancy, leading to high dropout rates. Mickelson (2018) states some regions experience more students dropping out of school than those advancing to college.

Furthermore, areas with high rates of truancy experience high crime rates leading to more imprisonment of population. Ekstrand (2015) states a relationship among high rates of law-breaking, truancy, and dropout rates. Truancy facilitates negative behaviors which relate to criminal activities and substance abuse. Drug abuse and mob activities are forms of crime in the study. Truant students later involve themselves in illegal activities such as hijacking, robbery, and sabotage leading to confinement in juveniles. Ninety-four percent of wrongdoers in minors in Rhode Island are truants from school (Ekstrand, 2015). A study by Dahl (2016) reveals that one of the ten male dropouts or one of the four black male dropouts ends up behind bars in the United States. Confinement results from truant students engaging in illegal activities that attract law enforcement.

The study by Holtes et al. (2015) reveals that the United States houses a higher fraction of its citizens than any other country across the world. The United States spends an average of roughly $20,000 per year on each convict. Additionally, the state spends about $9,391 per learner. Research shows how it is expensive to deal with repercussions of truancy like confinement. A study by Ekstrand (2015) of South Carolina’s high school shows how dropout cases are rampant. Dropout students contribute to more senior criminal activities. Research suggests that on graduating, students contribute to the economy immensely tallying to about $8 billion over their lifespan. Students who graduate end up participating in productive activities hence generate income. Educating students is beneficial to the state than detaining them since incarceration leads to more cost, which the nation incurs in the form of billions of dollars regarding lost earnings and foregone taxes. There exists a connection between truancy, dropping out, and imprisonment, which relates to the level of education (Ekstrand, 2015). High truancy rates lead to high illiteracy levels within prisons systems of the United States. People in prison lack information regarding social norms since they were absent in classes — students who drop out lack sufficient knowledge concerning essential aspects of life skills. A study by Ekstrand (2015) shows that 75% of Americans who go to jail are ignorant. Prisoners lack requisite knowledge for the application of particular skill and expertise. Most prisoners are students who drop out of school and eventually end up breaking the law — educating people results in a decline in crime rates.

Behaviorism Theory

Behaviorism theory focuses on a logical approach in comprehending behaviors of individuals. An assumption on which behaviorism theory relies is that people exhibit diverse personality in response to certain stimuli in their surroundings (Murtonen, Gruber, & Lehtinen, 2017). Moreover, behaviorism theory suggests that an individual’s state of punishment, reinforcement, and environments results in different behavior patterns. Research demonstrates how Inheritance determines actions which individuals display. Environmental factors play a vital role in modifying the manners of people. Integration of surroundings and prevalent conditions of parties greatly influences their personality.

The behaviorist theory considers various elements of methodology, philosophy, and psychological approaches. Pioneers advocate that psychological factors influence behavioral theory in the late 19th century. Mental condition and other psychological traits play an important role in enhancing behavior forms. Depth psychology and different sorts of consciousness experience troubles in coming up with testable predictions (Stoyanov, 2017). Creators of behaviorist theory include individuals like Edward Thorndike of the 19th century. Edward emphasizes strengthening peoples’ behavior using reinforcement (“John B. Watson,” 2016).

John B. Watson develops methodological behaviorism in the 20th century hence adding more information behaviorist theory. Methodological behaviorism by Watson enforces measurable conducts and events, therefore, declining prevailing introspective (“John B. Watson,” 2016). Factors affecting change in behaviors are quantifiable and are useful during the implementation of intervention strategies. In late 1930, B. F. Skinner entails thoughts and feelings as aspects influencing individual behavior hence leading to radical behaviorism. Emotional state and opinions of people change the conduct of people in a particular environment. Watson and Pavlov concentrate on stimulus responses in standard conditioning. Skinner focuses on nature controls as well as its consequences on past experiences which attributes to prevalent conditioning. Various aspects impacts on behaviors which individuals display in response to particular stimuli. Actions originate from the incorporation of dynamic forces inhabiting a specific atmosphere.

Experiments by Skinner on inventing radical behaviorism have been successful. Skinner perceives behaviorism theory by revealing that new phenomena cultivate after new methods (Day, 2016). Researchers classify radical behaviorism depending on past events and sensitivity towards stimuli (Murtonen, Gruber, & Lehtinen, 2017). Skinner uses rats and pigeons to display responses which are significant in the operating environment (Day, 2016). Behaviorism theory comprises of radical behaviorism which groups into applied behavior analysis, which facilitates analysis of truancy behavior among high school students. Practicable behavior analysis shares ideas with radical behaviorism and human-based psychology. Implementing applied behavior analysis in hampering drug abuse reduces truancy rates among high school students. Furthermore, applied behavior is essential in nurturing positive personalities at schools, thus preventing the development of abnormal actions among students (Stoyanov, 2017). Implementing applied behavior investigation facilitates the development of intervention strategies which hampers harmful activities like truancy among students.

Cognitive information processing

Also known as information processing, cognitive theory encompasses several theoretical perspectives that focus on order and execution of intellectual events. Cognitive theory majors on how individuals interact with surroundings, acquire knowledge, and store information for future reference (Lachman, Lachman, & Butterfield, 2015). Cognitive events require parties to use experience which they have been acquiring during normal conditions. The cognitive theory views learners as active seekers of knowledge and processing of data.

Moreover, the approach depends on the ability to remember information as a significant factor. The memory of students and community at large is the primary aspect attributing to cognitive information processing. Information processing theory emulates computer metaphors such as inputs and outputs and their response — cognitive theory majors on principal factors contributing to truancy in high school. Information processing theory studies the memory system as well as other processes such as attention, chunking, rehearsal, encoding, and retrieval that stores knowledge for transfer.

Sensory memory of cognitive information processing is responsible for holding information relating to hearing and vision senses. Short-term memory refers to short working memory for processing data for response and storage. Short-term memory contains little information for a shorter period. On the other hand, long-term memory stores data permanently. Long-term memory retains data for an indefinite duration of time (Siemens, 2014).

Information processing theory suggests processing of data in a chain of information flow. There is altering of information as it flows from one stage to the next. Nonetheless, processing of information does not generally flow in a single direction. For instance, expression in a sentence by an individual depends on existing and prior knowledge. Supervisory monitors processes and keeps track of information read by an individual. Prioritization of processing information occurs unconsciously and consciously. Instructions build on already existing knowledge of learners on a given topic hence proves to be irrelevant. Prior experience enables students to make viable decisions in current affairs. Truant students miss a lot since their flow of information is incomplete. Absenteeism underpins the ability of students to compare first-hand knowledge since they lose a lot when engaging in non-attendance of classes. Truancy in high school results to discriminatory where learners select and process particular information while ignoring others simultaneously. Truant students lack interest in specific sectors but pay attention to useless knowledge hence promoting discerning actions. Selective attention depends on aspects such as awareness, similarities in competing tasks, the complexity of events, and the ability of functions to control the devotion of students (Siemens, 2014). Truant students incorporate selective attention when making judgment fostering their involvement in illegal absence.

Truant students fail to recognize the importance of going to school. Students who engage in truancy make wrong decisions concerning the attendance of classes. Thus, they fail to prioritize schoolwork leading to truancy and absenteeism. Truant students experience hardships in acquiring and applying the knowledge that they learn in classrooms leading to rapid loss of information. Rehearsal is vital in storing information while encoding enables individuals to develop ideas and concepts. Truant students fail to prepare adequately for knowledge acquisition.

Moreover, the lack of knowledge among students engaging in absenteeism facilitates deficiency of creativity. Forms of encoding available include imagery, mnemonics, concept trees, hierarchies, outlines, groupings, and organizations. Students may also have problems with retrieving information from their long-term memories. Retrieval of data from the long-term memory requires recalling, recognition, and retrieval cues. Truancy among students favors high levels of illiteracy.

This dissertation will make use of the two theories, cognitive information processing and behaviorism in explaining the causes of absenteeism among high school students. Behaviorism theory focuses on comprehending truancy behavior among students while cognitive information processing theory focuses on psychological aspects that cause absenteeism. The two arguments apply throughout the paper to establish and create a comprehension of truancy behavior among high school students.

Review of Research Literature and Methodological Literature

The United States has been enacting mandatory school attendance laws which force students to avoid absenteeism over the past years. Enactment of compulsory attendance laws for schools takes place between 1852 and 1918. Moreover, free primary education from elementary school to secondary school occurs in this period; hence, historical (Atwood & Croll, 2015). Aspiration for universal education, immigrant socialization, and quality labor forces Government to adopt laws for the provision of free primary education (Breda, 2014). Government schools across the country lead other institutions with the sole purpose of educating children and imposing existing child labor laws. Government schools protect children in preparation for independence after graduating. These schools impart knowledge in generations resulting in higher standards of living of students during adult life. Vital knowledge which students acquire subsidizes in the delivery of efficient services. Students practice what they train in school by attaining positive impacts on society. Eventually, in 1918, every state within the United States embraces compulsory school attendance laws. Mandatory school attendance laws compel parents and guardians to admit a school-aged child to school and monitor their attendance (Yang & Ham, 2017). Parents have to ensure that their students don’t miss classes according to involuntary class attendance policies. Support from parents lowers truancy rates since students encounter supervision of their academic accomplishments and class inclusion. Laws focusing on mandatory school attendance deteriorates levels of truancy. Formulating rules and policies regarding class attendance force students to participate in school affairs actively.

The compulsory school attendance laws dictate that any child absent from school without giving a valid reason is engaging in truancy (Breda, 2014; Dahl, 2016). Mandatory school attendance laws define truancy as an unlawful absence of students from school without the consent of their parents or guardians. Unfortunately, some states don’t embrace compulsory school attendance laws. Students in countries that don’t have involuntary school attendance involve in activities resulting from their absenteeism in schools. Private schools, homeschoolers, schools for people with special needs, pregnant students, and those who attend schools, yet they are jobless have to endure compulsory school attendance laws (Breda, 2014). Some factors are inevitable since they impact in reasonable absenteeism of students. According to Yang and Hall (2017), sickness, loss of an immediate family member and emergency in families are legitimate explanations for absenteeism disregarding the location of schools in the United States of America. Additionally, uncontrollable situations, expulsion, health conditions of students and parents, and safety provide a valid motive for truancy. Unavoidable circumstances among students lead to truancy and absenteeism.

Schools accept exceptional circumstances such as the temporary assignment of duties, vacations, and other special events that lead to valid causes of absenteeism. Certain conditions force students to be absent from school. The difference in the interpretation of existing laws in states causes disparities in attendance laws across the United (Sahin, Arsven, &Kilic, 2016). Distinctions in formulating rules enhance the development of different measures for assessing class attendance. For instance, most districts within the United States determine absenteeism without permission per period basis, while others consider the entire day (Wilson, Rivers, & Schultz, 2016). Differing interpretation among schools makes it difficult to make comparisons of truancy rates across the country to establish the real causes of this vice. Data from the supervision of attendance is not compatible due to different assessment procedures that schools utilize hampering interventions requiring correlation.

Various states within the country adopt a general definition of truancy, thus providing them with a specific and deliberate approach in identifying truant youths (Cox, 2017). Lack of a standard truancy rate computation in schools contributes to states employing homogenize interpretations. Thus, according to Sahin, Arseven, and Kilic (2016), mild effects of truancy in government schools of the United States is due to the lack of a standard definition and intervention. Joint intervention policy assists in tackling rampant cases of absenteeism in Government schools. However, Breda (2014), denotes how a combined effort of parents, teachers, school management, and students steer in reducing truancy rates. Collective determination of community is significant in prohibiting truancy.

Teasley (2004) states how truancy levels decline through merging efforts of individuals giving rise to strategies and interventions. According to Zhang et al. (2007), the implementation of the Check and Connect program in government institutions results in successful interference of strategies such as behavioral, instructional, and community-based interventions. However, Henry and Yelkpieri (2017), identify family and instructional intervention strategies most convenient for combating truant behaviors. Households and guidelines which students encounter play an essential role in their actions. In the study by DeSocio et al. (2007), there was an introduction of a mentor intervention program to prohibit truancy. Mentors offer pieces of advice to students hence influencing their behavior in response to certain stimuli and surroundings. Reid (2006), indicates five intervention recommendations, namely School-Based Scheme (SBS). According to Reid (2006), SBS pilot applications were successful in schools in the United Kingdom. Reid (2006) concludes how schools and districts implement ABS due to its efficiency in hampering immoral behaviors. According to Nordahl (2013), truancy behaviors in schools deteriorate due to the integration of intervention strategies. The tremendous success in reduction of truancy among students emanates from the comprehensive effort of the community in establishing suitable prevention procedures.

Lehr, Sinclair, & Christenson (2004) indicates the use of direct instruction or instructional approach in various states leads to proper training in students. Lessons on direct instruction encourage practice technique in students. Students present in classes obtain critical knowledge through written scripts, rehearsal, and brief lessons which they eventually initiate applications. According to Zhang et al. (2007), instructional experiences impact tremendously in classes like math and reading where students can receive immediate feedback on committing an offense. Students who don’t comprehend essential aspects engage in asking instructors questions. Reinforcing mode of teaching influences the confidence of instructors in administering lessons on moral behavior to students hence leading to reduction of inappropriate conducts (Zhang et al., 2007). Teachers who provide support to students influence their behavior patterns since students feel contentment.

The use of instructional interventions encourages some of the regularly absent students through praise to attend school. However, this strategy alone cannot eradicate truancy in high schools. Instructional interventions provide physical support hence influencing the psychology of students. Moreover, it’s the best mode through which government and institutions tackle absenteeism. Students heed advice from people providing instructions enabling drop-in truancy levels. Interventions verified on a behavioral basis include Functional Behavior Assessment (FBA) and Positive Behavior Support (PBS). The Positive Behavior Support (PBS) incorporates various experimentally-proven practices with a lot of support from students who exhibit challenging behaviors. PBS provides support on a personal and worldwide basis (Zhang, 2007).

On the other hand, Functional Behavior Assessment is a more individual-based intervention in comparison to Positive Behavior Support. Functional Behavior Assessment involves the method of gathering information on the function of behaviors of students. Data enhances the proficiency of student’s self-management and manners support. Substantive Behavior Assessment process entails self-evaluation, self-monitoring, and positive reinforcement. Moreover, it teaches students to be accountable for their social behaviors and academic accomplishments. Functional Behavior Assessment and Positive Behavior Support strategists are vital in the provision of a paper trail of attendance of students. Employing Functional Behavior Assessment and Positive Behavior Support Strategies ensures students attend classes regularly since information on the significance of school attendance is readily available. Students deviate from truancy when they assess positive consequences that relate to frequent class attendance.

Community-based interventions such as the Truancy Reduction Demonstration Program (TRDP) and Abolish Chronic Truancy Now (ACT Now) are the best and most prevalent interventions in combating truancy. Furthermore, funds and strength of community facilitate community-based interventions. Families of truant students receive incentives from resources kitty propelling them to attend classes. Other community-based interventions include intensive family interventions, mentoring, case management, expanding police force, and use of welfare restriction in economic sanction (Henry & Yelkpieri, 2017). Zhang et al. (2007) delude that presenting incentives to students in the form of awards and maintaining follow up through communication increases class attendance. Communities play an essential role in ensuring most students don’t miss classes.

Lack of involvement from people like law enforcement, parents, social services, family, and juvenile courts leads to failure of community-based intervention. Thus, resulting in increasing truancy rates due to unavailability of intervention actions meant to hinder immoral behaviors. A valuable community invests in youths and tackles truancy menace. Check and Connect intervention strategy prevents dropping out of students and assists in many states of the United States to inspire learners to engage in academics until they graduate (Zhang et al., 2007). Students under Check and Connect focus in accomplishing good academic grades rather than dropping out. In the Check and Connect model, individuals monitor levels of student’s commitments daily. Students facilitate inclusion of various risk factors such as skipping classes, tardiness, absenteeism, detention, grades, suspension, and accrued credits.

Individuals promote an association of the respective student with their school and their participation in learning atmospheres. Check and Connect relies on follow up nature and students engagement in suitable events. Connect aspect entails intervening on risks affecting specific task given to students. Students who face certain risks connected with various preventive strategies which hinder an increase in truancy rates. Students provide regular feedback on their progress at school through information sharing and observing intervention. Individuals discuss with students concerning the benefits of attending classes in Check and Connect. Characters incorporate problem-solving strategies which analyze potential risks that students encounter at school — implementing problem-solving strategies like FBA gears strong relationships in adults and students hence reducing chronic absenteeism among students. Students who connect with adults tend to receive positive perspectives about going to school leading to waning in drop-out levels. Positive relationship influences students to make commitments to themselves and people who are significant to them. The connection between students and their parents dramatically impacts on students’ notion of attending classes.

Family set up, and household issues affect truancy rates in students (Henry &Yelkpieri, 2017). Thus, the intervention of family is essential when establishing causes of truancy. However, according to a study by DeSocio et al. (2007), inadequate information in family-based interventions and truancy levels comparisons exists. Therefore, DeSocio et al. initiate a mentoring program that aims at improving school attendance and consequently, the academic performance of students. DeSocio et al. operate on the assumption that students who don’t attend classes experience despair and separation hence gain from personal mentors who provide attention. Mentors impact personal care virtue in students, thus prompting students to halt from engaging in unfavorable behavior patterns. Her findings indicate that fostering adult mentors attributes to the positive relationship between students and schools due to the elimination of hopelessness and anxiety. Students engage in establishing strong relationships with adults whom they confide in with their feelings and situations (DeSocio et al., 2007). Adults guide students further impacting on the sense of belonging in the community among students. Students who establish positive relationships with adults usually attend classes due to the availability of support and guidance.

Reid (2006) identifies the School-Based Scheme (SBS) program, which combats truancy in schools in the United Kingdom. SBS has a long term strategic plan that overcomes truancy through the elimination of essential attendance troubles that students encounter. SBS composes of five distinct stages in which students engage. The first stage is where the students attend at least 92% of their classes. Students don’t require any support in this stage. The second stage entails sending an initial warning letter to guardians and parents indicating the importance of regular school attendance.

Moreover, parents’ responsibilities and consequences of guardians failing to fulfill their obligations are in the second stage. The third stage comprises of students with an average of 75 – 84% attendance. This stage requires parents to attend a panel consisting of key staff members of the school, such as principal, social worker, and performance director. The main agenda of this meeting focuses on the importance of consistent class attendance. This meeting formulates plans facilitating regular participation of students.

The fourth stage comprises of students with attendance report ranging between 65-74 percent. In this stage, students and their governors appear in the governor’s attendance panel. Governor’s attendance panel consists of governor of the school, principal, social worker, teacher, and performance director (Holtes et al., 2015). Primary agenda of this meeting focuses on discussing the importance of regular attendance and developing a strategy to help students attend school frequently. Parents and guardians receive a warning and notification regarding regular class attendance of their children. The fifth stage of the process comprises of students who have an attendance register of less than 65 percent. This stage requires students and their legal guardians to attend a Local Education Authorities Panel. The Local Education Authorities Panel is similar to the District’s board of Education in the United States (Holtes et al., 2015). Board members of the meeting oversee the likely causes leading to the nonattendance of students. The meeting adjourns with a final warning to students and their guardians.

Furthermore, students’ class attendance should be 100% for two months under the monitor. Dropping of students’ performance leads to disclosure of their information to relevant authorities such as Child Protective Services (CPS) for further disciplinary measures. Unfavorable performance from students implies the presence of immoral behavior that facilitates intervention. Reid (2006) examines schools in which the program was successful and notes an increase in class attendance of about 10% during its first year of implementation. Moreover, performance and attendance increases in schools which implement the program concerning schools that don’t apply the plan. Students who undergo strict supervision opt to accomplish higher grades due to high-class attendance. Disciplinary measures enforce high standards of conduct leading to students engaging in self-control hence undermining truancy and absenteeism. School-Based Scheme instills higher supervision standards that force students to participate in activities that uphold proper values and norms in society. Moreover, students who enroll in School-Based Scheme have a positive affiliation with excellent academic grades.

Review of the methodological findings

The existing literature explores various methodological approaches that define multiple causes of the truancy in high school students. The research suggests multiple applications and consequences of programs and interventions during the studies. Most of the literature review identifies parents’ participation, community cooperation, and school administration as critical aspects influencing truancy among students. Moreover, the use of incentives and supporting students to overcome psychological problems affects truancy among scholars. Attwood and Croll (2015) suggest an ongoing evaluation as relevant in each element of the control strategy. For intervention on absenteeism to be successful, assessment of each prevention strategy is critical.

Nonetheless, most of the studies that implement truancy reduction programs fail to provide details on challenges, evaluation, and outcomes. Truancy programs evaluation focuses on aggregate information, which, in the broader perspective, lacks meaningful comparison groups. Aggregate data relies on the short-term benefits of truancy programs like reduction in absenteeism, which provides inadequate information for assessing changes that may exist in the attendance record of an individual (Blackmon & Cain, 2015). Several factors affect class attendance. However, information determining the success of intervention programs is insufficient. Therefore, changes in class attendance need collection and valuation of diverse aspects to establish factors contributing to truancy.

Research by Henry and Yelkpieri (2017) shows truancy programs relies on also short-term benefits in a meta-analysis of intervention programs that the United States uses to address school dropping, which hinders completion of high school. However, the standards of research do not relate to meta-analysis. Thus, the conclusion of the study focuses on prevention of dropouts that result from truancy. The Office of Juvenile Justice Delinquency Preventions formulates laws that significantly impact a reduction of school absenteeism. The Office of Juvenile Justice Delinquency Preventions funds programs that combat truancy in high schools. Evaluation of truancy programs provides valuable lessons like delivering student support services in preventing absenteeism, widespread mentorship intervention, and community awareness (Henry & Yelkpieri, 2017). Various stakeholders have different roles in developing strategies meant to hamper truancy. Involving law enforcers such Office of Juvenile Justice Delinquency Preventions assists in formulating laws that hinder more cases of absenteeism.

Most communities embrace truancy intervention programs hence incorporating with individual members and their families. The government supports truancy programs by providing adequate resources for identifying, locating, and transitioning the truant youths in communities. Appropriate authorities use tactics like the involvement of the police, negotiation, and suspension of missing children. Nonetheless, Attwood and Croll (2015) report that some strategies have not been successful in resolving truancy in high schools. Most communities lack relevant intervention and assessment services for truant youths in spite of indication of existing psychological problems. Community-based programs require identifying and addressing issues that children and families encounter before ultimately introducing the truancy intervention programs. Government and communities involvement in establishing intervention programs enables parties to handle truancy menace. Furthermore, parties working on reducing truancy in the community need to integrate their efforts to acquire first-hand information that deliberates on forming many solutions.

On the other hand, school-based programs reduce absenteeism and truancy through enforcing of teacher-student interactions. Positive relationships between teachers and students lead to higher lesson attendance and excellent performance among students due to one on one interaction. Students solve their problems quickly with help from instructors. School-based programs introduce school-based health care eliminating sickness excuses from becoming a primary reason for truancy in most schools. Students who fall sick get urgent treatment while in school or outside school premises if need be. Combination of school-based and the community-based programs provides a concrete intervention that assists in the reduction of truancy rates immensely. However, such programs only target truant students disregarding students who attend school frequently. Students who attend school regularly do not qualify for school-based and community-based intervention programs since their personality is conducive according to guidelines. As a result, missing students improve their performance while regular attendees’ performance remains constant. Integration of school-based and community-based programs involves the referral of parents to a mental health agency for students whose performance does not improve. However, parents resist psychological health agency recommendation since it is against their rights. Parents decline the offer to visit mental health facilities because it undermines their personality. Failure of community and school-based programs facilitates legal action hence favoring the use of law enforcement based agendas. Results from implantation of court-found and law enforcement based plans show how truancy leads to criminal activities among students later in life. Employing legal action against truant students assists in fostering behaviors which diverge from criminal events.

Synthesis of the research findings

Truancy hampers students from accomplishing their life goals according to the literature review. Literature review establishes a direct connection between school attendance of students and their achievements later in life. Absenteeism translates to no learning. Thus, no knowledge acquisition for truant students resulting in poor performance. Missing students lack the requisite knowledge and skills for accomplishing goals through the qualification of various job opportunities. Studies reveal that most of the absent students who miss more than 50% of their classes always fail in government tests and hardly manage to get good grades. Students who are sometimes lacking in qualities do not afford to achieve high academic grades. The literature review identifies numerous factors contributing to truancy among high school students such as bad influences, lack of interest in school, poor relations, bullying, student’s matters, and family factors. Furthermore, factors that cause truancy classifies into student caused truancy, school caused truancy, family caused truancy and psychological truancy.

Students make friends with others from different backgrounds while at school. Sometimes friendship often extends terrible influences on their colleagues depending on their upbringing, making it a significant cause of truancy. Interactions among students facilitate the formation of divergent views resulting in students emulating what they believe is suitable among their peers. Truant behavior can be a successful factor in relationships that upholds particular beliefs. Students who become missing as a result of lousy guidance often view truanting as a new act that can raise their status among peers. For quick acceptance in a given social group, students practice truancy. Sense of belonging many impacts on student behavior patterns. Thus, truancy prevention requires the implementation of programs and interventions. Most schools often opt for punishment such as the temporary or permanent exclusion of the student from school. However, Chen et al. (2016) mention that it is administering punishment on students further worsens truant behavior. Ekstrand (2015) suggests that establishing behavioral patterns ensures permanent abolition of a specific practice among students. Employing policies and activities that encourage upholding moral standards among students hampers truancy from intensifying. Involving students in sports helps in curbing absenteeism, especially in lousy scenarios. According to Parrish (2015), participating in sports such as soccer is useful since it makes students star on pitch. Students participating in sports encounter contentment when making judgment thus dropping on truant cases. Team games where students regularly participate in encourages students to attend school regularly. Through motivation available in teams, students gauge the confidence of attending school games hence improving in-class attendance.

Review in literature identifies a lack of interest in school as a cause of truancy. Most students don’t attend classes regularly since they are aware of what they want to engage in after completion of school. Students lose attachment to school affairs since they experience boredom resulting in truancy. Thus, they often prefer hanging out with their friends. Dahl (2016) suggests the introduction of lesson plans in schools which emphasizes the importance of acquiring skills and utilizing them beyond classrooms. Truancy results from poor relations at school. Truant students often evade going to school due to their unfortunate associations with their fellow students and teachers.

On the contrary, some teachers have the best interest of students at heart. However, students see teachers as arrogant and bullying. Positive relationships impacts on an optimistic attitude of students leading to moral upright among students who tend to engage in regular class attendance.

Mestry (2015) suggests that re-timetabling of students assists in solving a split relationship between students and teachers when students don’t work with the teacher under consideration. Peaceful pact ensues between students and instructors when learners undergo re-timetabling. School administration sets up a team meant to handle cases of bullying hence promoting safety among learners. Management upholds the protection of students by administering punishment on bullies. School management and community appoint personal mentors to enable students to share their problems hence avoiding truancy. Parents and guardians of the students uphold their responsibility in ensuring that children attend school frequently. Henry and Yelkpieri (2017) suggest that parents should not condone some reasons like unofficial holidays that makes students truant. Enforcing parent’s evening in which school emphasizes on the importance of regular class attendance and implications of being absent resolves parents caused truancy. Parents’ involvement in school affairs of their children stimulates suitable prevention intervention against absenteeism.

Critique of the previous research

The existing studies on truancy groups the behavior into four major categories. These categories include student-specific variables, family-specific settings, school-specific factors, and community influenced variables (Jaafar et al., 2013; Monahan et al., 2014). These studies introduce various interventions and programs which addresses truancy conducts among students. However, these interventions and programs focus in particular areas. Most of the literature reviews that truancy menace exists only in schools. The literature does not consider current allegations that have become a topic of argument in various forums. Forums suggest using simplistic thoughts and severe limitations to comprehend how truant behaviors develop in children and exhibit later in life. According to Ingul and Nordahl (2013), simplistic thinking through which children develop truant behaviors provides a solution to truant behaviors in schools and the juvenile justice system. Many factors attribute to school truancy (Breda, 2015; Maynard, 2016; Yang & Ham, 2017). The various factors that correlate to absenteeism have diverse causes and repercussions according to the literature review. Truancy traits among students are transferable through interactions. Interaction leads to the accordance of support from family, acquisition of experience, and creates a community atmosphere.

Previous research identifies four similar categories of truancy, including family, school, student, and community-level factors. Each of these factors is common since they have a variety of connection between aspects. The elements also reveal a mixture of characters which facilitates their success in explaining the incidences of truancy in high schools. Research by Ekstrand (2015) specifies that truancy initiates with both short and long-term challenges for the students who are prone to avoiding schools. These challenges not only affect students but also extends to their families, school, and the societies from which these students hail.

Nonetheless, Chen et al. (2016) suggest that students portray truant behaviors emanating from more profound problems, thus require the intervention of community members. Chen et al. (2016) identify that intervention by educators who embrace missing students assists family, school, and community in creating one on one relationship with students. Furthermore, a response by instructors makes students to disclose their difficulties. According to Dahl (2016), embracing truant students is essential in comprehending the level of implications brought about by truant traits.

The consequences of embracing the truant students also lead to various impacts on each truancy category. Chen et al. (2016) argue that in the first category of individual-specific outcomes, consequences group into short and long-term. Havik, Bru, and Ertesvag (2015) mention that most of the students who display truant behaviors lack ambition in life and expect much for their future. Thus, short and long-term consequences may not have any adverse effects on them. For students who might not have lost hope in their future, the most visible and immediate impact of truancy will always be on their education. Students accomplish poor performance due to lower class attendance, thus missing a lot of information (McNulty, 2016). Failures in education negatively affect occupation. Truancy persists in students leading to employment-related complications like high unemployment rates, less stable patterns in career, lower status in their professions, and weak earnings in their adult lives. Blackmon and Cain (2015) argue that truant students change due to their lazy nature hence employ the simplest and the best solutions to their problems. Missing people do their best to retain their job while giving their best during the times when they are available.

Mazerolle et al. (2017), argues that chronically truant students may always experience a variety of future relational difficulties, which may include those that form during the early stages of childcare. Missing students tend to produce a higher number of dependents leading to first marriages and consequently, a series of problems leading to marital breakdowns. Mijinyawa, Bakar, and Muhammad (2015) highlight poor health as an adverse adult outcome of chronic truancy. Chronically truant students suffer from poor psychological health during their adult stages of life due to some student caused the effects of truancy such as drug abuse. Gentle-Genitty et al. (2015) mention that chronic absenteeism leads to rehabilitation. There exists a variety of actions against the students who become truant due to substance abuse. Most of the substance abuse cases are a result of the peer pressure in their quest to be popular in school. Students also turn to drugs to relieve themselves of the painful feelings that emanate from family structures and bullying in school surroundings. Truant students are known to be poor performers in school. They turn to drug abuse and study aid drugs such as Ritalin to help them boost their performances and grades as a remedy (Virtanen et al., 2014). Moreover, students who use drugs tend to be deviant and anti-social. The personality of students who abuse substances usually has immediate results of behaviors that associate with truancy and leads to adult criminal activities.

Blackmon and Cain (2015) argue that truancy has direct impacts on educational institutions leading to loss of returns. The authors argue that school loses revenue due to a reduction in school funding from daily attendance rates of students. However, there exist laws which schools exploit to ensure every student attends classes (Solakoglu & Orak, 2016). Existing literature provides various programs and interventions which schools explore to ensure every student is present regularly. Loss of revenues in educational institutions is disastrous since it reduces the capacity of the institution to meet the educational requirements of students through service provision. Furthermore, it affects each student within the institution, regardless of his or her attendance record. Therefore, truancy results in devastating effects if no preventive intervention is made in advance.

Summary

This chapter reviews the existing literature on high school truancy. It introduces truancy and defines it as an intentional, unauthorized, unjustified, as well as the unauthorized absence of an individual from compulsory education. It also identifies the adverse physical, social, as well as the psychological effects of truancy on the students, which in turn affects their development. In this chapter, truancy emanates from school, teachers, student, and community, including parents. Existing relationships between teachers and students affect students’ behaviors hence causing School sourced absenteeism. The teacher sourced absenteeism comes about as a result of the critical nature of the teachers who always have high expectations for their students resulting in absenteeism. Students can also instate their truancy by being absent from class without giving any excuse. Parent sourced truancy has various causes such as parenting styles, a divorce of parents, and the breakdown of parents, which contributes to the behaviors of children. Absenteeism among students attributes from climate within the school, size of the school, size of classes, attitudes, discipline policy within a school, and the ability of the school to meet the diverse needs of every student. According to Henry and Yelkpieri (2017), the background of the student and other family-related issues that students often encounter are significant illustrations of truancy.

Critical elements vital for effective programming and control of truancy among students include involvement of parents, use of incentives, support, collaboration within the community, and active participation of the school administration. Various programs and interventions can be put in place by government, community, and schools to ensure students have regular attendance. This chapter reviews case studies, including the implementation of truancy programs and analyses results. Literature review reveals that most communities embrace truancy prevention programs and interventions and make them sanctions to youths and their families.

Chapter 3: Methodology

Introduction

School administrators in secondary schools are worried about students who are chronically absent from school. Many wonder what keeps students away from school while trying to understand what they can do to get students in school consistently (Liu & Loeb, 2016).  Most work on the assumption that things such as low socioeconomic status, parent non-interest in education, and suffering from parental abuse are reasons to miss school (Jacob & Lovett, 2017).  However, the need to be absent may come from another source within the walls of the school in the form of bullying or lacking social support (Kelly, n.d.).

Bullying is a problem that is hard to discover and to verify unless someone else is witnessing, it is also difficult to correctly measure its extent in schools according to (Smith, 2014).  Not only is there difficulty in determining if bullying occurs, but as an administrator, it is problematic because of trying to discipline the individual (Rigby, 2011).  Additionally, according to Smith (2014) administrators may think they understand what effects bullying has on students, even they may not be sure. Bullied students may also experience other effects such as lacking social friendships (Tariq & Tayyab, 2011).

Students who lack social support in school may feel isolated or are loners, are not interested in attending school to escape the isolation (Dahl, 2016). Administrators tend to assume when students struggle to have friends, they are less likely to want to attend school. While this study will not argue that bullying or a lack of social support causes students to miss school more frequently, its purpose is to measure whether a relationship occurs.

In this research paper, there will be the use of a correlational design, data collection techniques, and analysis processes to answer the research questions. In every study, there are essential tools that are needed to facilitate the outcome of accurate information. This research methodology covers different sections including the formulation of the research questions, identification of the research design, identification of research population and the description of the research instrumentation (Creswell, 2014). Additionally, there will be an incorporation of procedures involved in the data collection processes. In every quantitative research, the process of data analysis is important as it enables the researcher to answer the research questions by carrying out tests of a hypothesis (Sedgwick, 2014). Data analysis will be discussed based on the types of data collected. Some tests that will be undertaken include Pearson correlational assumptions and the normality assumptions. Chapter three, therefore, outlines the data collection processes and analysis with the aim of answering the research questions.

Test for Assumption for a Pearson Correlation

The most popular way of defining random events is normal distribution. The processes fit normal distribution because the two graphs are bell-shape single peaks (their means). They are symmetrical that implies that the occurrence probabilities of the two values equidistant from the means, but on their different sides are the same. Most of the values are between -1 and +1 from the mean, it is one standard deviation. In almost all of the processes there are virtually no observations farther than three standard deviations from the mean and there are no farther than two standard deviations from the mean. The assumptions behind Pearson Correlation Coefficient are forgotten given its simplicity. The Coefficient of Pearson may not be appropriate and therefore it is significant to make sure that the assumptions hold. The requirements and assumptions for computing Correlation Coefficient of Pearson are normality, linearity, and continuous variables. Normality implies that the sets of data should correlate to the estimate of the normal distribution. Most data points tend to drift close to the mean in such normally distributed data. Linearity simply implies that data the relationships between variables are linear. This can be again explored by plotting the scatter diagram. If the data fulfills the assumption of linearity, then the data points a straight-line relationships but not a curve.

Purpose of the Proposed Study

The purpose of this investigative study is to determine whether a relationship exists between bullying and absenteeism in school students of age 18 and above within rural settings. Also, the study attempts to establish the relationship between peer social support and absenteeism among students of age 18 and above within rural settings.

One of many responsibilities of a high school administrator, that encumbers several hours weekly is student attendance. Likewise, time is spent on disciplining aggressive behaviors (bullying) from students directed at other students. It is the desire of the researcher to determine if there is a relationship between the bullying and students missing school. Furthermore, generally speaking, students that are victims of bullying have common characteristics, one being a loner with limited peer social support. With the knowledge that students may lack peer social support, the researcher intends to determine if there is a relationship between the amount of peer social support and student absences.

Research Questions

For this study, the researcher strived to establish relationships between the predictor variables (amount of bullying and amount of peer social support) and the criterion variable (school absences). The research questions are aligned with the behaviorism theory through evidence that the exhibiting of students’ behaviors result from flexes from the responses of certain stimuli in their environment (Murtonen, Gruber, & Lehtinen, 2017).

The following research questions and hypotheses guided the correlational study are:

  1. To what extent is there a relationship between peer social support and school absences?
  2. To what extent is there a relationship between being bullied and school absences?

Hypotheses

H01: There is no significant relationship between peer social support and school absences.

HA1: There is a significant relationship between peer social support and school absences.

H02: There is no significant relationship between being bullied and school absences.

HA2: There is a significant relationship between being bullied and school absences.

Research Design

The study is quantitative and specifically takes on correlational research design to be utilized as a data collection strategy (Creswell, 2014). The study aims to establish the relationship between bullying and school absences as well as peer social support and school absences. Correlational research is a non-experimental technique in which researchers measure two variables (predictor and criterion), understands them and then assesses the statistical relationship that exists among the variables. The researcher is not concerned with the cause and effect of the variables, so the correlational design is an obvious choice. Every school in the rural setting has its climate, culture, and demographic makeup which makes it possible that in addition to bullying and peer social relations, other variables could influence student’s attendance. However, the researcher does not make attempts to account for extraneous factors since it is a correlational study. The advantage of a correlational design is that it measures two variables and evaluates the statistical connection (i.e., the correlation) between them mostly with minimal effort or none at all in the control of extraneous variables (Crawford, 2014).

On the other hand, the researcher decided against using the causal – comparative research design because causal –- comparative design compares two or more groups (Groves, n.d.).  Additionally, as Groves (n.d.) stated, this type of research design usually works with a situation that previously materialized. Causal –- comparative is also known as “ex post facto”, which is translated as “after the fact”. Lastly, while the correlational study tries to determine a relationship, the causal-comparative design tries to determine cause and effect. In this instance, the researcher is not interested in cause and effect (Groves, n.d.,).

For analysis, the study looks forward to statistical analysis since it needs to produce statistics that can indicate the relationships and significance of predictor and criterion variables. There is one part of data analysis to be included in the study which aims to comprehend the relationships between the variables in the study. The researcher will examine correlations among three variables: bullying, school absences, and peer social support. Data shall be collected using questionnaires that include questions depending on the two research questions which are: to what extent is there a relationship between the amount of peer social support and school absences and, to what extent is there a relationship between the amount of bulling and school absences. Selection of samples for the study population will be through a sampling of three rural high schools and purposive selection of participants to reach only those students that fall under the categories required. It is important to note that the researcher and each school reside within The Commonwealth of Virginia, that the researcher works in one of the high schools in the County and each participant will have an equal chance of being part of the sampled schools. The study needs respondents that are secondary school students who are 18 years and over and are still in school.

Target Population, Sampling Method and Related Procedures

The participants for this study will be students (aged 18 years and above) drawn from three of four different rural secondary high schools, all from a Virginia school district. Presently, there are 338 students that fit the characteristics of participation. To facilitate smooth data collection, the participants in the study will have the right to refuse to take part without any consequence if they wish. After identifying the study population, the next thing is selecting a sample of participants. A sample implies a small group from the entire population that is studied (Van Voorhis & Morgan, 2007) and is selected through a specific technique (Muthén, & Muthén, 2002). Notably, eligible participants for this study are those students that are 18 years and above, still schooling and in a rural setting. All who meet these requirements and attend one of the three county schools shall be considered for inclusion in the sample.

One week before the survey, the researcher will be in constant communication with school administrators of the three schools as the date for survey draws nearer. The school administrators will act as the researcher’s contact persons in the respective schools. This will be intended to ensure any changes in terms of time, schedule, venue, and shortlisted participants are shared between the researcher and the school administrators.

The study is a survey and needs statistical analysis. The total number of students aged 18 years and above from three secondary schools located in the Shenandoah Valley of Virginia is 338 at present. Based on that knowledge, the researcher wanted to find out how many participants are required to get results that represent the target population. By use of a sample calculator (https://www.qualtrics.com) with 80% level of confidence and a margin error of 5%, the ideal sample size will be 84 students (participants). In fact, in research, it is advisable to have a sample size that is ideal to reach reliable conclusions and recommendations that are easily generalizable (Welman, Kruger, & Mitchel, 2005). Thus, this sample is suitable for the correlational study and can aid in reaching concrete results and conclusions.

 

Instrumentation

The study will use the Olweus Bullying Questionnaire (OBQ) a self-report instrument which is a standardized, legalized, multiple-choice survey structured to assess some issues related to bullying challenges in schools. The questionnaire which is comprised of 42 questions (many of them being sub-questions) is usually used with students of varied grades (Olweus, n.d) including secondary schools, meaning it is ideal for the current study. Students usually fill in the OBQ anonymously; this means the identity of participants of the current study will remain anonymous. The OBQ which is accessible on https://www.qualtrics.com has a number of unique characteristics that will enable the researcher to collect relevant data as much as possible. These characteristics include:

  • A full definition of bullying so participants have a better understanding of how they should answer the questions.
  • A majority of the questions mention a particular period or reference time, such as “the past couple of months (after the summer/winter holiday vacation)”. This technique is believed to be an ideal duration of time for participants to recall their past experiences.
  • The response options are designed to be as specific as possible by making use of terms like “2 or 3 times a month” and “about once a week”. Response terms are meant to discourage subjective phrases like “often” and “fairly often”, which are likely to be understood differently by participating students.
  • Other than being asked two broad questions (Questions 4 and 24 in the OBQ) on being a victim of bullying and being a bully, the OBQ will also ask participants corresponding questions (Questions 5-12a) on specific types of bullying (about being bullied) and also on bullying others (Questions 25 to 32a in the OBQ).
  • The OBQ will ask straightforward questions on students’ demographics (gender, sex, ethnicity, and the school the participant attends).

The study will also use another essential instrument known as Child and Adolescent Social Support Scale (CASSS) which is a “60-item self-report rating scale that measures perceived social support for children in grades 3 through 12” (Menon & Demaray, 2013, p.50), an ideal instrument to rate the current study’s participants. CASSS assess four kinds of identified support (appraisal, emotional, informational, and instrumental) which corresponds to five different sources: parents, classmates, teachers, and close friends (Malecki, Denaray, Elliott, & Nolten, 2000).

In creating CASSS, participants will be asked to read a provided statement and input their response on a scale on whether they feel that they get that support. The development of the CASSS will allow the researcher to have a complete insight of the participants’ social support and allow the researcher to desist from looking at social support as a general term for a comprehensive and complex concept.

Gaining permission from the author of the Olweus Bullying Questionnaire the researcher sent an email describing the research and the desire to use the OBQ in search of the intended relationship.  Additionally, the researcher contacted the authors of the Child and Adolescent Social Support Scale (CASSS) by email. Once again the researchers described the research study and how the CASSS will be used to provide statistical information to help with the relationship questions. Permission to administer these questionnaires to high school students shall be sought from school administrators and students (Manson, 2002). A letter describing the intent of the research and the process of how the research is conducted is provided to each student that fits the participant criteria. Each participant has the opportunity to deny or accept the terms in which to participate. Furthermore, the researcher will need to submit a request to the Assistant Superintendent for Rockingham County for permission to enlist the students in the study. The Assistant Superintendent has requested the completed IRB application to assess whether to approve or deny permission. At the conclusion of this research, a brief description of the results will be forwarded to reviewers. The second instrument (Child and Adolescent Social Support Scale) will be utilized in this project to identify the influence of peer social support on the level of school attendance among the secondary school students of ages 18 and above. The questions in this survey relate to how these students feel regarding the treatment they receive from their peers. Items shall be recorded with scales and entered into SPSS to find correlations between the datasets attained from the collected data.

The two instruments (OBQ and CASSS) have been used previously in different studies and produced reliable findings. For example, Kyriakides, Kaloyirou and Lindsay (2006) reported that OBQ “has satisfactory psychometric properties; namely, construct validity and reliability” (p.781) while on their part, Cullum and Mayo (2015) reported that “the Child and Adolescent Social Support Scale (CASSS) for Healthy Behaviors, demonstrates adequate initial reliability and validity” (p.198). According to Mathers, Fox, and Hunn (2007), questionnaire surveys are the best tools for collecting quantitative data in research. Thus, selecting to use OBQ and CASSS survey instruments is because they are capable of producing the best quantitative data for this study.

Data Collection

On the day of the survey, two sets of surveys (OBQ and CASSS) will be administered to collect demographic data such as average days missed per month, gender, ethnicity, and age. After providing the informed consent to the participants, these two instruments will have cover pages that have an information letter on the purpose of the study and a statement that informs the respondents that by filling in and returning the survey, they have given their informed consent. As mentioned earlier, the OBQ is designed in a way that makes the questions to be as simple and straightforward as possible for the respondents. The instrument is also designed to provide relevant, reliable, and valid data. The OBQ will be administered to selected schools during school hours in the presence of one representative from each of the three participating schools. The administration of the OBQ will be done in groups of ten students. The OBQ will be administered to the students. Separate scales will be created consisting of (i) The items of the OBQ related to the amount of bullying on victims and (ii) those related to the magnitude to which students express bullying characters. Both scales will have analyzed for reliability and validity. They will also be analyzed separately for boys and girls to examine their invariance.

All selected students will be provided a separate room from the other non-participating students to avoid any potential interference to complete the questionnaires. The entire exercise for each school will take 30 to 50 minutes. The researcher, with school representative’s help, will note any strange happenings during the administration of the survey and if any issue is identified, it will be documented and be emailed to the researcher. It is normal for non-response bias (assuming some of the participants will not respond or fail to turn up) to occur in studies similar to the current one. To avoid non-response bias, the researcher will extend the survey collection period to two days so that the students can choose any of the two days to respond based on their lessons schedule. All students attending the three Virginia high schools are provided a Chromebook to use during their school years. Two links, one for each survey is provided on respondents Chromebook for them to complete the surveys. After completion of the survey exercise, the completed answers are collected through Survey Monkey.

The instrument items for measuring the level of absenteeism among the students (victims) that have been bullied include response items of school days missed or attended in the entire term. The responses will be arranged regarding the number of days they have been absent from school this year. If days are missed because a student believes they will be bullied or if they come to school because they are not getting bullied will provide answers to the research questions.

Operationalization of Variables

Demographics: For the entire study, age will be a significant factor such that all participants must be of age 18 or above. Those that do not make it to the age limit are excluded from the study (Dillman, Smyth, & Christian, 2014). In addition, school students and the schools selected will be from a rural setting

Peer social support levels: In the current context, social support will be defined as the student’s beliefs that he or she is cared for, appreciated, and respected by those belonging to his or her social setup, that boosts personal wellbeing, helps him or her inadequately managing stressors, and could protect him or her from unfavorable incidents. With that understanding, the Child and Adolescent Social Support Scale (CASSS) items will include statements detailing supportive behaviors like “My friend(s) appreciate me”. Respondents will be asked to read every single statement and specify their response by ranking the item regarding frequency and importance. For example, frequency scores will be rated based on a 4-point Likert scale whereby 1 = Never and 4 = Always. Importance scores will be rated based on a 3-point Likert scale whereby 1 = Not Important and 3 = Very Important. As mentioned earlier, each of the five subscales on the Child and Adolescent Social Support Scale will correspond to one of the social support sources (parent, classmates, a close friend, teacher, and school).

Each subscale will have 12 items that will assess the four types of social support (appraisal, emotional, informational, and instrumental). To find the frequency scores for every single subscale, the researcher will add the frequency ratings for each one of the 12 items under that subscale. By adding up, all five frequency subscale scores will give the researcher the Total Frequency score. Likewise, importance ratings for every single subscale is obtained by adding up the importance scores for the 12 items under every subscale. The added subscale importance ratings will be added to obtain the Total Importance score.

Data Analysis Procedures

The study will utilize correlational analyses for examining the relationships that exist among variables, and to apply various predictors (peer social support and bullying) for the outcome (attendance). SPSS for windows will be used for statistical analysis of the data in this study (Sedgwick, 2014). Before conducting the correlation analyses, data will be assessed against the assumptions of the Pearson correlation tests to see if they conform to them. In the first place, boxplots for every variable shall be formulated to understand the data and detect outliers which will be examined and dealt with appropriately. Second, normality tests for each variable shall be conducted as well as evaluation of kurtosis and skewness (Tabachnick & Fidell, 2013).

In the case of multivariate comparisons, scatterplots shall be generated for pairwise variable combinations. Every scatterplot will be examined for outliers and to confirm if the relationship between the two variables is showing linearity and the variance across the measures. After computation of the correlation matrix, bivariate correlations will be checked for the likelihood of forming multicollinearity issues during the regressions (Tabachnick & Fidell, 2013).

A correlational analysis will be done in that Pearson product correlation tests are calculated to assess the direction and strength of relationships existing between all variables. Correlation matrix will be developed to display the different correlation coefficients for every variable in the study. This information will be recorded in tables for purposes of the audience of this study.

Limitations and Delimitations of the Research Design

Limitations: Similar to a majority of studies, this study design has its limitations. The study is a quantitative study and thus requires an extensive sample (Creswell, 2014). However, regardless of the benefits of extensive studies, the large sample size is likely to magnify the bias linked to error emanating from sampling or study design (Kaplan, Chambers & Glasgow, 2014); therefore, this study will include 84 respondents. Other limitations on sample size are due to constraints of time and resources to engage a more extended sample. Larger samples mean more time for administering instruments and increased sums of questionnaires for distribution. Since the instruments used in this study entail self-reporting (questionnaires), a few cases of data cleaning may arise particularly in cases where one or two participants choose only to answer four or five survey questions, then such participant(s) will not positively contribute much and therefore may need to be excluded from the data set.

This study will use purposive sampling that creates a limitation of possible bias. For each survey, sampling techniques that are favorable are required to eliminate tendencies of bias. Šimundić (2013) provided that choosing a sample requires researchers to apply a method which may lead to bias-free participant samples since this can influence the findings of a project. The purposive sampling techniques are most of the time a breeding ground for research bias since it might encourage predetermination of results and conclusions. Conversely, this limitation will be eliminated by requesting the school administrators of the respective schools to select the respondents randomly as long as they meet the minimum age requirement while ensuring gender and ethnicity balance to avoid tendencies of researcher biases.

Delimitations: The delimitations of this design rotate around the topic as well as research questions. The topic of this study takes a context that has been of great concern in the U.S rural schools. This research project brings on something of such significance, and this becomes one boost for the study to run smoothly. The schools selected are those that have faced this challenge and need to find workable solutions for the matter. Therefore, truancy is a critical issue in a rural setting especially among older students, selection of schools that fall under this category and face the challenge was the best thing to do.

More so, the decision to conduct a quantitative survey with questionnaires as tools will help in extracting statistical data relevant for finding correlations among the variables (Dillman et al., 2014). The research questions could not have a better response than using questionnaire survey methods to get descriptive statistics of students who have experienced bullying and less social support for peers. Since the research questions are projected towards finding relationships between bullying, peer social support and school absences; victims will become the central focus. This decision is taken in a bid to help this vulnerable portion of students to have a productive and favorable learning environment.

Validity: Through previous studies, the validity of both OBQ according to Kyriakides et al. (2006) and CASSS according to Cullum and Mayo (2015) has been confirmed. This implies that the instruments will be administered with the knowledge that they meet acceptable standards and have the ability to collect the required data. As Manson (2002) mentioned, using instruments that have been tested improves the quality of data collected and ensures significantly reliable results and conclusions.

The validity of instruments consists of how correctly the evidence acquired represents the research variables. Reliability refers to the level to which instruments of the study generates consistent data or results after repetitive tests to create its reliability. The instrument validity was developed by supervisor of study reviewing the research. The questionnaire was pre-tried on a pilot scale via chosen participants outside the area of research to ensure reliability. The pre-testing objectives enabled for alteration of different questions to clear up, rephrase, and clarify any limitations in questionnaire before delivering them to the real respondents. The methods of quantitative studies rely on the components of reliability, validity, and objectivity in ensuring the research data trustworthiness. The credibility was created via members checking, repetitive observations, prolonged involvement and participation, debriefing of peer, and triangulation. Transferability was developed via a detailed research explanation. The process of audit enabled the researcher to establish confirmability and dependability.

Expected Findings

The study expectations are to find a substantial relationship between bullying and absenteeism and social support and absenteeism among secondary school students that are 18 and above. The researcher expects to effectively respond to the questions related to whether (1) to what extent is there a relationship between the amount of peer social support and the number of school absences? Also, (2) to what extent is there a relationship between amount of bullying and the number of school absences?

The researcher strongly believes there is a significant relationship between peer social support and the number of school absences by students, an observation verified through some studies (Rothon, Head, Klineberg, & Stansfeld, 2011; Stamm, 2007, September; Wallace, 2017). It is from this belief that the researcher expects results that point to peer social support as a factor that could help reduce chronic truancy among K-12 secondary school students.

Additionally, the researcher believes there is a significant relationship between some amount of bullying and the number of school absences by the victims above the age of 18 in a rural setting. Previous studies (Dunne, Bosumtwi-Sam, Sabates, & Owusu, 2010; Gaukler, 2015; Grinshteyn & Tony Yang, 2017) have produced findings indicating there is indeed a relationship between being bullied in school and absenteeism.

Ethical Issues in the Proposed Study

The researcher will receive an introductory letter from the university department of attachment, and this will be used to get to the field. The researcher will then obtain approvals from both the school administrations and school district before the actual data collection process. Formal applications will be sent to the schools requesting for permission to use their school and students as part of the study. Manson (2002) recommended that researchers get a consent form educational authority to take on a study project in a specified area of operation. This will enable the research to be conducted in an acceptable manner to both the researcher and the population.

In conclusion, chapter three is to act as a blueprint of how the correlational survey will be conducted. It provides a procedural structure of how data will be collected or generated and analyzed in this study. This chapter gives shape to the sample selection, data collection and generation, and data analysis as will be used in the chapters that follow to aid the arrival at firm conclusions and recommendations of the study.

 

 

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Does the average rate of babies that have had 6+ visits in their first 15 months of life differ between plan types?

SCENARIO

You are an Informatics Manager for a health plan that needs to submit their HEDIS data to NCQA next month. The health plan’s former informatics manager did not provide the CIO with a report of the HEDIS scores from the prior year. She is interested in the percent of well-child visits in the first 15 months of life (#8940) for babies covered by your plan and all cause readmission rates (#9190). However, as with any public report, the CIO asks you for an analysis of these data before it is submitted to the NCQA.

INSTRUCTIONS

Please read about the 2 HEDIS measures (Measure 8940 and Measure 9190) we will be exploring in this final project. The links to the NCQA explanations are in the module.

For this final project, each student will create a (1) three slide PowerPoint presentation and an (2) Executive Brief.

Please select a health plan that begins with the first letter of your last name. If your last name begins with F, I, X, Y, or Z then please choose a health plan that begins with the first letter of your first name. For example, I would choose between Geisinger Health Plan, one of the Group Health Cooperatives, or Gundersen Lutheran Health Plan.

 

Elements to analyze and report on:

  1. You have HEDIS data on 223 plans including yours for the well-child visit measure. You’d like to see the breakdown of how plans are doing overall. You decide to depict this through a vertical bar chart (proc gchart, vbar) depicting the percent (x axis) and frequency (y axis) of the plans for the 6+ visit rate only (variable = six_plus_visit_rate).

How does your plan compare in terms of this measure?

  1. You also want to see if the average 6+ visit rate is different across plan types, if it varies depending on if a plan is an HMO or PPO (variable =ReportingProduct). You decide to depict this through a horizontal bar chart (proc gchart, hbar). The meanrate of the variable six_plus_visit_rate will be across the x axis. This is very similar to your Q3 for PL1, because you’ll have to show the average rate across categories. 

Does the average rate of babies that have had 6+ visits in their first 15 months of life differ between plan types?

  1. You have HEDIS data on the 225 plans including yours for the all-cause readmissions measure. You’d like to see an overall breakdown of readmissions rates for the total population for all plans. You decide to depict this through a pie chart (proc gchart, pie).

How does your plan compare in terms of this measure?

  1. You’d like to create a table depicting the mean (using the proc means statement) readmission rates for females, males, and total for all the plans. You want the variable name, the sample size (N), the Mean, the Standard Deviation, and the Minimum and Maximum values. The variables you’ll use are (var = Readm_F_Total, Readm_M_Total, Readm_Total_Total).  (first check out the module for help with the syntax).

How does your plan compare in terms of this measure?

https://www.ncqa.org/hedis/measures/child-and-adolescent-well-care-visits/

https://www.ncqa.org/hedis/measures/plan-all-cause-readmissions/

Deliverables:

Create a powerpoint that has the above elements (must be copied from SAS output)

Use template and findings to write a one-page Executive Summary.