qualitative data analysis
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QUALITATIVE DATA ANALYSIS
A/Professor Denis McLaughlin
School of Educational Leadership
QUALITATIVE DATA ANALYSISYou have a book of readings with relevant extracts from the following books.
They must be read1. Dey, I (1993) Qualitative data analysis, London: Routledge2. Miles, M & Huberman, A (1984). Qualitative data analysis, Newbury park:
Sage3. Miles, M & Huberman, A (1994). Qualitative data analysis : An expanded
source book (2nd edition), Thousand Oakes: Sage4. Coffey, A. & Atkinson, P.(1996).Making sense of qualitative data,
Thousand Oaes: Sage5. Marshall, C. & Rossman, G. (1989).Designing qualitative research.
Newbury Park: Sage6. Tesch, R. (1990). Qualitative research, New York: Falmer Press7. Creswell, J. (1998). Qualitative inquiry and research design, Thousand
Oaks: Sage8. 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
RESEARCH STRATEGY IDENTIFICATIONRESEARCH PROBLEM
RESEARCH PURPOSE
RESEARCH QUESTIONS
ISSUES TO BE EXPLORED
APPROPRIATE TECHNIQUES
OVERVIEW OF QUALITATIVE ANALYSIS
Data Collection
Data display
Data reduction
Conclusions: drawing / verifying
(Miles & Huberman, 1984; 1994)
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
QUALITATIVE ANALYSIS (Dey, 1993)
describing
ClassifyingConnecting
Qualitative analysis as an iterative spiralDey, 1993
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)
2. Data Analysis Procedures
3. Represents information in matrices-displays of information , spatial format that presents information systematically to reader
3. (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).
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
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
DATA ANALYSIS
MANUALLESS THAN 500 PAGES OF TRANSCRIPTS OR FIELD NOTESWANT TO “FEEL” CLOSE TO DATACANNOT AFFORD TO HAVE ALL INTERVIEWS TRANSCRIBED(4 HRS TO TRANSCRIBE 1 HR TAPE INTERVIEW)
COMPUTERMORE THAN 500 PAGES OF DATACAN AFFORD PROGRAM AND TRANSCRIBERATLAS.tiQSR N5 (NUD8IST 5.0)NVivoEthnographWinMAXHyperResearch
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
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)
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 1Data collection, displayreflection
Stage 2 Data coding & distillation
Stage 3
Generation of key themes
Stage 4Story report & conclusions
Data Collection Techniques
Stages for Data Collection (Matrix example)
Exploratory Phase
Step 1a: Initial Exploratory Survey – Conducted in 19981st 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 employmentrecipients at universitiesrecipients at vocational institutions
IndividualIn-depth InterviewsFocus 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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