1. Quality Indicators of Rigor in Qualitative Methods & Analysis

2. Alignment World view Theoretical Framework Research Questions
Research Design
Data Generation
Data Analysis

3. World View Predict Understand Emancipate Deconstruct Positivist
Interpretive
Emancipate
Critical
Deconstruct
Poststructuralist
Postmodern

4. Theoretical Framework
Transformative Pedagogy
Pedagogies where learner searches for meaning through reflecting on values, social norms, and assumptions about educational, moral, and political issues/situations (Ukpokodu, 2009).
TP in PETE categorized as negotiated learning, storytelling, peer teaching, case studies, and place-based pedagogies (Ovens, 2017)

5. 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

6. Research Questions
The primary purpose of the study was to explore how sociocultural and social justice issues are addressed and implemented in PESP programs.
What intentional pedagogies do PESP faculty employ to educate for social justice?

7. Methods Design Researcher subjectivity/Reflexivity Context/setting
Participants
Data Generation
Data Analysis
Trustworthiness

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

9. Design Critical interpretive design
Social constructivist and transformative world views of the research team (Creswell, 2014)
Explore and understand the intentional pedagogies employed by 72 PESP/PETE faculty to educate for social justice

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. Reflexivity All members of the research team are current PESP faculty
Range from years in PETE/PESP program
From 3 different countries
Social justice (in PE/PETE/PESP) has been a strong influence for all members of the research team
All strong advocates for social justice
Published and presented on SJE

12. 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

13. Context
PETE/PESP programs from 7 different countries

14. Methods Sampling 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
Purposive, case study, snowball, etc.

15. Methods Sampling Participants Purposive sampling
72 PETE/PESP faculty members
More than 48 different PETE/PESP programs
7 different countries
Time in profession (1- 30+years)
Range of institutions
All had a terminal degree
Sampling
Purposive sampling
Participants who identified as PETE or Health Education faculty in an ITE program
Recruited by research team through research networks, conferences, and professional listserves.
Ethics – University IRB approval
Informed consent of participants

16. Data Generation What are the data generation 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 generation
Describe each data generation method in detail
How conducted
When collected
Who

17. Data Generation What are the data generation tools?
Observation – field notes
Interviews – semi-structured, face-to-face, focus group
Video/photo recall
Photo voice
Documents – curriculums, policy papers, etc.,
Journals
Reflective comments (audio, text)
Researcher Journal

18. Data Generation Data Generation
Informational survey – background information from participants
Age, gender, time in profession, educational background, employment history, social identity etc.
Semi-structured interviews
One-on-one
Face to face or skype/zoom
Range from minutes
Program documents
Researcher Journal

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

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. Data Analysis
Content analysis and constant comparative method (Corbin & Strauss, 2008)
Transcribed, open coding or line-by-line analysis = initial codes
Axial coding = collapsing initial codes into primary themes with description of theme
Researchers discussed and refined/adjusted initial themes
All transcripts reviewed to select salient quotes
Supporting documents reviewed to support and enhance description of themes

23. Trustworthiness Credibility Transferability Dependability
Confidence in the “truth” of the findings
Transferability
Findings have applicability in other contexts
Dependability
Showing that the findings are consistent and can be repeated
Confirmability
Extent to which findings are shaped by participants rather than researcher

24. Trustworthiness Credibility
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

25. Trustworthiness Transferability Thick rich description of Context,
Setting,
Participants,
Data collection methods,
Timeline,
Interpretations
Data excerpts

26. Trustworthiness Dependability
Research design and implementation – in detail what you did and when
Data generation – what you did and when to collect the data
Reflective appraisal of study

27. Trustworthiness Confirmability Triangulation Researcher reflexivity
Audit trail – trace the course of the research step by step – data collection, analysis, process, timeline etc

28. RIGOR, ALIGNMENT

29. 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

30. 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

31. Beginning the Coding Process
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

32. 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

33. 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,.

34. 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!

35. 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!