QUALITATIVE DATA ANALYSISA/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 readDey, I (1993) Qualitative data analysis, London: RoutledgeMiles, M & Huberman, A (1984). Qualitative data analysis, Newbury park: SageMiles, M & Huberman, A (1994). Qualitative data analysis : An expanded source book (2nd edition), Thousand Oakes: SageCoffey, A. & Atkinson, P.(1996).Making sense of qualitative data, Thousand Oaes: SageMarshall, C. & Rossman, G. (1989).Designing qualitative research. Newbury Park: SageTesch, R. (1990). Qualitative research, New York: Falmer PressCreswell, J. (1998). Qualitative inquiry and research design, Thousand Oaks: SageCreswell, J. (2002). Analyzing and interpreting qualitative data (pp256-283). In J Creswell, Educational research, Thousand Oaks: Sage 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 PROBLEMRESEARCH PURPOSERESEARCH QUESTIONSISSUES TO BE EXPLOREDAPPROPRIATE TECHNIQUES

OVERVIEW OF QUALITATIVE ANALYSISData CollectionData displayData reductionConclusions: drawing / verifying (Miles & Huberman, 1984; 1994)

INTERACTIVE PROCESS OF DATA ANALYSISData collection

Data displayReflection on DataData CodingGeneration of ThemesStory interpretationResearch ConclusionsSIMULTANEOUS

ITERATIVEData distillation (reduction

QUALITATIVE ANALYSIS (Dey, 1993)describingClassifyingConnecting

Qualitative analysis as an iterative spiralDey, 1993

DATA ANALYSIS PROCEDURESIn this section of your Design chapter mention the following characteristics of the processData analysis is an eclectic process (Tesch,1990)Occurs simultaneously and iterative with data collection, data interpretation and report writing (Creswell, 2002; Miles & Huberman, 1984)Is based on the on data reduction and interpretation -decontextualisation & recontextualisation (Marshall & Rossman, 1989; Tesch, 1990)

2. Data Analysis ProceduresRepresents information in matrices-displays of information , spatial format that presents information systematically to reader(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 informationIdentifies the coding procedure to be used to reduce information to themes / categories (Read Tesch, 1990, pp142-145).

Categorisation and ThemesConstant comparative content analysisThemes generated from the literature reviewThemes embedded in instrument questionsThemes embedded in research questionsCombination of any of above

DATA ORGANISATION(Miles & Huberman, 1994)DEVELOP MATRICES :VISUAL IMAGES OF INFORMATIONComparison 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 Dredges Power point at the end of this sequence on this issue

DATA ANALYSISMANUALLESS 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 carefully2. Pick one document what is its underlying meaning write thoughts themes in margin3. Do this for several informants; Cluster together similar topics; arrange topics into major topics, unique topics, left overs4. Revisit data with topics; Abbreviate the topics as codes; Re-analyse. Do new codes emerge?5. Turn topics into themes6. Reduce number of themes by grouping similar themes7. Diagrammatize the basics of the numbers 5 & 68. Finalise abbreviations- alphabetise codes9. Perform preliminary analysis on material belonging to each theme10. 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

CODING PROCESS (Creswell, 2002)(Matrix example)

Description of Data Analysis (Matrix example)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 itStage 1Data collection, displayreflection

Stage 2 Data coding & distillation

Stage 3Generation of key themes

Stage 4Story report & conclusions

Data Collection TechniquesStages for Data Collection (Matrix example)Exploratory PhaseStep 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 patternsStep 2:Select stratified sample from step 1 according to predetermined criteria for individual interviews recipients in employmentrecipients at universitiesrecipients at vocational institutionsIndividualIn-depth InterviewsFocus GroupsStep 3:Interview selected sample Step 4:Focus groups at universities and colleges Step 5:Analyse data collected in step 3 and 4Step 6:Interview selected officials, personnel from tertiary institutions, employers, parents & guardians Documentary &Final analysisStep 7:Analyse official interviewsStep 8:Analyse interviews of secondary sourcesStep 9:Document analysisStep 10Final analysis

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