1. Quality Indicators of Rigor in Qualitative Methods & Analysis Dr. Louise McCuaig Dr. Sue Sutherland

2. Qualitative Research  Qualitative researchers aim to gather an in- depth understanding of human behavior and the reasons that govern such behavior.  Investigates the why and how of decision making, not just what, where, when.  Often smaller, but focused, samples are selected rather than large samples.  Qualitative methods rarely claim to generalize findings to other populations. It produces information on the particular cases studied. More general conclusions are only propositions (informed assertions).

3.  Cases (participants) selected purposefully, according to whether or not they typify certain characteristics/contextual locations.  Researcher lens - researchers reflect on their role in the research process & make this clear in the analysis.  Interpretive - Make meaning of the data collected  Holistic & contextual analysis of data rather than being reductionistic and isolationist. Nevertheless, systematic & transparent approaches to analysis are almost always regarded as essential for rigor.  Inductive analysis – data drives the Research Questions, the hypotheses (assertions), & conclusions made.  Deductive analysis – theoretical concepts drive analysis Qualitative Research – Inductive

4. 4 Hot Topic: What are the implications of a global and local reinvigorated commitment to religion for HPE? RELIGION, CITIZEN’S BODIES AND SCHOOL HPE: EXPLORING YOUNG PEOPLE’S PERCEPTION OF HPE AND RELIGIOUS MESSAGES FOR GOOD LIVING 1.Ethical Substance - what part of myself should I address? 2.Mode of Subjection - why should I engage in such a work? [Obligation] 3.Forms of Elaboration of the self - what tools are available to me? [Principles and practices] 4.Telos - what kind of person do I want to be, or what kind of life do I want to lead? [Goals]  DEDUCTIVE OR INDUCTIVE ????

5. Alignment World view Research Questions Research Design Data Collection/Data Gathering Data Analysis

6. 6 Research Questions Purpose statement is clear and precise outlining the intent of the study Clear research questions that align with the world view and theory used as the lens for the study

7. RELIGION, CITIZEN’S BODIES AND SCHOOL HPE: Research Questions 1.How do religious-based practices for good living align with HPE? 2.How do religious young people navigate the practices of healthy living? 3.To what extent do the principles and practices of young people’s faith serve as a strengths-based resource for healthy living? 4.What are the implications for HPE in schools?

8. 8 Methods Design Researcher subjectivity/Reflexivity Context/setting Participants Data Collection Data Analysis Trustworthiness

9. 9 Design Interpretive Symbolic interactionism Ethnography Phenomenology Case study Auto-ethnography Grounded theory

10. Reflexivity Ways that research is shaped by the particular perspectives, interests, and biography of the researcher. Reflect on how own biography and assumptions influence the entire research process Important to state this for the reader – help them to understand where you are coming from and what assumptions, experience, or influence you bring to the study

11. 11 Context Detailed description of where the study took place. Help the reader understand the nature of the environment. Country, geographic region, Urban, suburban, rural Location – e.g. school, childcare, youth sport Other relevant information such as socio- cultural factors

12. 12 Methods Participants Detailed description of participants age, gender, ethnicity, income level, sports experience, home environment etc Description of characteristics relevant to study Sampling What sampling procedures are used in the study Purposeful, case study, snowball, etc.

13. 13 Data Collection What are the data collection tools? Do they align with the researchers’ world view, research design, research questions? Discussed in sufficient detail to fully understand what happened, with whom, and when in terms of data collection Describe each data collection method in detail How conducted When collected Who

14. 14 Design & Analysis Aligned with world view, theory, research design

15. 15 Trustworthiness Credibility Transferability Dependability Confirmability

16. 16 Trustworthiness  Credibility (internal validity in Quantitative terms)  Data collection methods described in detail  Entre and time at site– includes prior to the study  Triangulation of data - how established  Rapport with participants allows for honest answers  Negative case analysis or disconfirming evidence  Peer debriefing  Member checking – transcripts and analysis  Researcher’s reflexivity –  Researcher subjectivity

17. 17 Trustworthiness Transferability (external validity/generalization) Thick rich description of Context, Setting, Participants, Data collection methods, Timeline, Interpretations Data excerpts

18. 18 Trustworthiness Dependability (reliability) Research design and implementation – in detail what you did and when Data gathering – what you did and when to collect the data Reflective appraisal of study

19. 19 Trustworthiness Confirmability (objectivity) Triangulation Researcher subjectivity/reflexivity Audit trail – trace the course of the research step by step – data collection, analysis, process, timeline etc

20. Data Analysis  Analysis  Process of systematically searching and arranging all of your data to allow you to come up with findings  Interpretation  Developing ideas about your findings and relating back to the literature

21. Data Analysis  Don’t wait until all your data is collected  Ongoing analysis of the data will help to focus future data collection, raise new insights you want to explore, help you to realize areas that need more probing/data.  Inductive or deductive process

22. Beginning the Data Analysis Process  Read, read, read, and read some more all of your data corpus  Organize how best suits you  Software packages – e.g. NVIVO  Hands on with the data – use of post its, cards, print outs  Hands on  Print out your data with two columns and room between lines to allow for coding.  One column has the data  Second column allows room for your initial interpretation of the data

23. Beginning the Coding Process  In the data, words, phrases, behavior, etc repeat or stand out  Begin to find a label of phrase that represents these piles to separate them from other piles  Develop a list of coding categories – this can be driven by your questions, theoretical approach etc  Constantly revisit data chunks when new codes arise

24. Beginning the Coding Process  Constantly revisit data chunks when new codes arise  Disconfirming evidence or negative case  As codes develop begin to look for codes that fit together into larger concepts/thoughts – begin transforming codes into initial theme  Constantly revisit your themes as you move through the process

25. Coding Family  Kinds of codes – broad areas to consider in your coding  Testing theory use codes from the theory (deductive) – apply the theory to the data  Setting/context codes  Information on the setting, participants etc  Definition of the situation codes  How subjects define setting or topics etc  Perspectives held by subjects  Ways of thinking of some or all of participants

26. Coding Family  Subject’s ways of thinking about people and objects  Subjects understanding of each other, outsiders, objects that make up their world  Process codes  Categorize sequencing of events, changes over time, etc  Activity codes  Regularly occurring kinds of behavior – student smoking, joking, lunch, warm up, game etc

27. Themes  Themes develop from your coding process  Could be related to RQ’s, theory, what you see in the data  Use of themes and sub-themes  Must be related to the purpose of your study!

28. Rigor  Outline what you did in your data analysis  Research journal for reflexivity on the whole research process  Coding book - codes and possible initial interpretation  Audit trail