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Qualitative data analysis

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Qualitative data analysis

  1. 1. QUALITATIVE DATA ANALYSIS A/Professor Denis McLaughlin School of Educational Leadership
  2. 2. QUALITATIVE DATA ANALYSIS You have a book of readings with relevant extracts from the following books. They must be read 1. Dey, I (1993) Qualitative data analysis, London: Routledge 2. Miles, M & Huberman, A (1984). Qualitative data analysis, Newbury park: Sage 3. Miles, M & Huberman, A (1994). Qualitative data analysis : An expanded source book (2nd edition), Thousand Oakes: Sage 4. Coffey, A. & Atkinson, P.(1996).Making sense of qualitative data, Thousand Oaes: Sage 5. Marshall, C. & Rossman, G. (1989).Designing qualitative research. Newbury Park: Sage 6. Tesch, R. (1990). Qualitative research, New York: Falmer Press 7. Creswell, J. (1998). Qualitative inquiry and research design, Thousand Oaks: Sage 8. Creswell, J. (2002). Analyzing and interpreting qualitative data (pp256- 283). In J Creswell, Educational research, Thousand Oaks: Sage 9. Maykut, P. & Morehouse, R. (1994) Qualitative data analysis: using the constant comparative method , In P. Maykut & R. Morehouse, Beginning qualitative research, London Falmer Press
  3. 3. RESEARCH STRATEGY IDENTIFICATION RESEARCH PROBLEM RESEARCH PURPOSE RESEARCH QUESTIONS ISSUES TO BE EXPLORED APPROPRIATE TECHNIQUES
  4. 4. OVERVIEW OF QUALITATIVE ANALYSIS Data Collectio n Data display Data reduction Conclusions: drawing / verifying (Miles & Huberman, 1984; 1994)
  5. 5. INTERACTIVE PROCESS OF DATA ANALYSIS Data collection Data display Reflection on Data Data Coding Generation of Themes Story interpretation Research Conclusions SIMULTANEOUSITERATIVE Data distillation (reduction
  6. 6. QUALITATIVE ANALYSIS (Dey, 1993) describing ClassifyingConnecting
  7. 7. Qualitative analysis as an iterative spiral Dey, 1993
  8. 8. DATA ANALYSIS PROCEDURES In this section of your Design chapter mention the following characteristics of the process Data analysis is an eclectic process (Tesch,1990) 1. Occurs simultaneously and iterative with data collection, data interpretation and report writing (Creswell, 2002; Miles & Huberman, 1984) 2. Is based on the on data reduction and interpretation -decontextualisation & recontextualisation (Marshall & Rossman, 1989; Tesch, 1990)
  9. 9. 2. Data Analysis Procedures 3. Represents information in matrices-displays of information , spatial format that presents information systematically to reader 1. (Miles and Huberman, 1984) A I page example of this must be placed in this chapter eventually • Display categories by informants, sites and other … • Tables of tabular information showing relationships among categories of information 4. Identifies the coding procedure to be used to reduce information to themes / categories (Read Tesch, 1990, pp142-145).
  10. 10. Categorisation and Themes 1. Constant comparative content analysis 2. Themes generated from the literature review 3. Themes embedded in instrument questions 4. Themes embedded in research questions 5. Combination of any of above
  11. 11. DATA ORGANISATION(Miles & Huberman, 1994) DEVELOP MATRICES : VISUAL IMAGES OF INFORMATION Comparison tables –themes, participants, sites Heirarchical trees visually representing themes & their relations Figures in boxes to indicate the processes, time sequence, evolution of themes Organising the data by type interviews, observations, documents Organising by participants or sites combinations See Michael Dredge’s Power point at the end of this sequence on this issue 
  12. 12. DATA ANALYSIS MANUAL LESS THAN 500 PAGES OF TRANSCRIPTS OR FIELD NOTES WANT TO “FEEL” CLOSE TO DATA CANNOT AFFORD TO HAVE ALL INTERVIEWS TRANSCRIBED (4 HRS TO TRANSCRIBE 1 HR TAPE INTERVIEW) COMPUTER MORE THAN 500 PAGES OF DATA CAN AFFORD PROGRAM AND TRANSCRIBER ATLAS.ti QSR N5 (NUD8IST 5.0) NVivo Ethnograph WinMAX HyperResearch
  13. 13. CODING DATA (see Tesch, pp142 -145) 1. Get sense of whole: read all carefully 2. Pick one document “what is its underlying meaning” write thoughts themes in margin 3. Do this for several informants; Cluster together similar topics; arrange topics into major topics, unique topics, left overs 4. Revisit data with topics; Abbreviate the topics as codes; Re-analyse. Do new codes emerge? 5. Turn topics into themes 6. Reduce number of themes by grouping similar themes 7. Diagrammatize the basics of the numbers 5 & 6 8. Finalise abbreviations- alphabetise codes 9. Perform preliminary analysis on material belonging to each theme 10. If necessary, recode existing data Always include in your design chapter a page of text (exhibit 4.x) illustrating the how you code the text
  14. 14. Read text data Divide text into segments of information Code segments Reduce Codes Collapse codes into themes Many pages of texts Many segments of texts 30 – 40 codes Codes reduced to 20 Codes reduced to 5 -7 themes CODING PROCESS (Creswell, 2002) (Matrix example)
  15. 15. Description of Data Analysis (Matrix example) Initial data analysis Major and minor topics Theme 1 Theme 2 Theme 3 Theme 4 Final interpretation In your analysis chapter you would present a diagram such as this at the beginning but with actual contextual material to illustrate the flow of your analysis. You would “flag” this overview in your Design chapter and refer specifically to it Stage 1 Data collection, display reflection Stage 2 Data coding & distillation Stage 3 Generation of key themes Stage 4 Story report & conclusions
  16. 16. Data Collection Techniques Stages for Data Collection (Matrix example) Exploratory Phase Step 1a: Initial Exploratory Survey – Conducted in 1998 1st Visit to PNG; Meet various stakeholders – SSSP graduates, personnel from tertiary institutions, NDOE, parents etc Step 1b: Analyze responses for trends and patterns Step 2: Select stratified sample from step 1 according to predetermined criteria for individual interviews •recipients in employment •recipients at universities •recipients at vocational institutions Individual In-depth Interviews Focus Groups Step 3: Interview selected sample Step 4: Focus groups at universities and colleges Step 5: Analyse data collected in step 3 and 4 Step 6: Interview selected officials, personnel from tertiary institutions, employers, parents & guardians Documentary & Final analysis Step 7: Analyse official interviews Step 8: Analyse interviews of secondary sources Step 9: Document analysis Step 10 Final analysis

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