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  1. Qualitative Data Analysis Within and Across Settings June 9, 2013 Toronto Reed Early Independent consultant

  2. Part 1 QDA Methods • Outcomes – learners understand the origin and current practice of QDA methods in general, grounded theory in particular, and possible applications of the methods.

  3. 1.      Methods a.      useful for inductive researchb.      useful in naturalistic inquiryc.      qualitative methods growing consensusd.      collection ↔ analysis ↔ collection

  4. 2.      Qualitative Data (QD) a.      open b.      exploratoryc.      useful when questions not yet definedd.      allows insights

  5. 3.      Overview of QDA

  6. 4.      QDA cycle

  7. 5.      overview of process

  8. 6.      Work plan of research process

  9. 7.      Characteristics of QDA a.      constructivist - many meaningsb.      context bound i.e. “cast of thousands"c.      uses inflection i.e. "THIS was good."d.      can be sorted in many ways e.      QD by itself has meaning i.e “apple”

  10. 8.      Sources of QD a.      interviewsb.      focus Groupsc.      field observations (GPS data)d.      survey comments e.      historical recordsf.       secondary datag.      photos, paintings, songs ...

  11. 9.      Types of QD a.    structured text writings, stories, survey comments, news articles, books etc b.    unstructured text transcription, open interviews, focus groups, conversation c.    audio recordings, as above, music d.    visual recordings, graphics, art, pictures e.    location specific dataGoogle Earth, GPS

  12. 10. Principles of QDA a.      Data entry (gathering)b.     Comprehending (immersion)c.      Synthesizing (sifting)d.      Theorizing (sorting)e.      Re‑Contextualizing (emerging theory)

  13. 11. Data entry (analogous demo) a.      not easily mechanizedb.      important part of processc.      often done by analystd.      concurrent with analysis e.      transcribe thoroughly, ASAP f.      write memos (reflect)g.      coding (start with few)

  14. 12. Comprehending (immersion) a.      begin while entering data b.      start QDA immediatelyc.      “live with it”d.      line by line examinatione.      create new questions for collection

  15. 13. Synthesizing (sifting) “quotes” (decontextualize) a.      use inductive categoriesb.      find common threadsc.      compare transcriptsd.      aggregate stories

  16. 14. Theorizing (sorting) “coding” a.      ask questions of the datab.      find alternative explanationsc.      allow sufficient time d.      be open to insights

  17. 15. Re‑Contextualizing a.      develop theoretical “elegance”b.      apply to other settingsc.      examine fit to literature/researchd.      describe emerging theory

  18. 16. Data Management Principles a.      stay close to the datab.      be sensitive to emergent theoryc.      allow recontextualizingd.      it is a non‑linear process

  19. 17. QDA method options – everyday analogues Content Analysis - like movie ratings by the censorship bd Grounded Theory – like a mystery solved by ordinary citizens Matrix Analysis – like a map’s matrix of campsite services Phenomenology – like a movie documentary

  20. 18.        Displaying results (computer methods) •  display code frequencies and charts (in QDA Miner)

  21. Exercise 1: Quotes, Codes & Memos

  22. Grounded Theory a. Primary documents (comprehending) • immerse in the primary documents • begin as data are collected • read/view/listen to the data

  23. b.      Quotations (synthesizing) • select and mark salient quotations/passages • compare each line to other data

  24. c.      Coding (theorizing) • assign codes in margin • group, sort, categorize codes into families • collect new data based on emerging theory, memos, codes

  25. d.      Memos (aids in all processes) • record insights on memos or post-it notes ie: ideas for emerging theories, thematic ideas, linked memos (Exercise 1)

  26. e.      Network (re-contextualize) • create network (mind map) • add and arrange network nodes • (quotes, memos and codes) • collect more data as needed (Exercise 2)

  27. Exercise 2: Grounded Theory and Network Mapping

  28. f. Generate theory • Make a matrix of themes (rows) by roles (cols) • Fill in cells with either a selected quote or “*” to indicate missing data. • Look for patterns, empty cells, areas of convergence. • Generate an explanation and provide a short quote to support your "theory". (optional Exercise)

  29. 20. Methods Matched to Type of Data a. structured text content and matrix analysis etc b. unstructured text i.e. narratives, open interviews phenomenology, grounded theory etc c. audio i.e. interviews, anecdotes, “stories”, music matrix analysis, grounded theory etc • visuali.e. graphics, art, pictures matrix analysis, grounded theory etc

  30. 21. Methods Matched to Principle Task a.      describe content analysis … b. explain / predictmatrix analysis … c.      derive new ideas and insights  phenomenology … d.      test significance matrix analysis, quantitative … e.      map theoretical relation grounded theory, mapping…

  31. run crosstab (matrix) codes and variables (QDA Miner)

  32. Alternate Exercise: Theorizing Using Matrix Analysis

  33. Code network map (Atlas-ti)

  34. Code Network MapMulti-Dimensional Scaling (QDA Miner Concept Systems)

  35. Q&A Questions and answers

  36. 23. Some QDA Methods matched to Software 1.Content Analysis Word, QDA Miner, Excel, Atlas-ti 2.Matrix analysis NVivo, QDA Miner 3.Grounded Theory Mapping Atlas-ti, QDA Miner 4.Phenomenology - using mind maps Inspiration, Visio 5. Concept Mapping Concept Systems, QDA Miner

  37. 24. QDA software • QDA Miner inclWordStat-SimStat(Provalis, CAN) • Atlas-ti Scientific Software (GER) • NVivo (QSR, AU) • Inspiration (USA) • Concept Mapping (Concept Systems USA) • MS Excel, SPSS (USA)

  38. Handouts Handout 1. Summary of Manual and Software Qualitative Methods Handout 2. Website, Software and Internet Resources The above and these slides are available at http://www3.telus.net/reedearly/shared/

  39. Don’t forget the workshop evaluation… rearly@telus.net http://www3.telus.net/reedearly/shared/