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Qualitative Analysis

Qualitative Analysis. Information Studies Division Research Workshop Elisabeth Logan. What is Qualitative Research?. Interpretation of the “social” world. - How Understood - How Experienced - How Environments are Produced

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Qualitative Analysis

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  1. Qualitative Analysis Information Studies Division Research Workshop Elisabeth Logan

  2. What is Qualitative Research? • Interpretation of the “social” world. - How Understood - How Experienced - How Environments are Produced • Addresses issues not well analysed through statistical techniques - How, not what or how much *

  3. Qualitative Data Collection • Data generation flexible & from real world context. - Rich - Contextual - Detailed • Participant Observation • In-depth Interviews *

  4. Qualitative Data Analysis • Observations, transcripts, videos of a process. - Holistic, descriptive, and explanatory - Some quantification, but statistical analysis not central - Aims for an understanding of human behavior in a given context

  5. Qualitative Studies: Example I • How skilled and novice searchers navigate in a commercial electronic database. - Task assignment - Interview - “Think aloud” - Observation - Recording - Interactions - Post-search Interviews

  6. Study Example I • Data Analysis - Navigation process - Description of activities - “Think aloud” statements - Problem areas - Expressed degree of satisfaction - Results evaluation

  7. Study Example II • Inter-library cooperation among a group of small town libraries - In-depth interviews with librarians and staff - Planned question format - Open-ended conversations - Tape recording - Assessment of current status of cooperation

  8. Study Example II • Data Analysis - Detailed analysis of transcripts - Categories identified and coded - Interpretation of transcribed results - Evaluated in light of stated interest in cooperative activities - Software available for identification & coding

  9. Qualitative Research Processes Different from quantitative research - Planning and Designing - Sampling and Selecting - Sorting and Organizing Data - Analyzing and Explaining

  10. Planning and Designing 1. What is the nature of the social reality I want to investigate? - Fundamentally different from determining “A Topic” - Broader concept that invites alternate points of view (people, interactions, processes, patterns, cultures) 2. What would provide evidence of these realities? - Nature of evidence; not how to collect it - How social phenomena can be known or demonstrated *

  11. Planning and Designing 3. What is my targeted area of interest? - Search behavior; interlibrary cooperation attitudes 4. What are my research questions? - What is the intellectual puzzle I want to explain? 5. What do I hope to obtain from this research? - A degree or contribution to fundamental knowledge?

  12. Selecting and Sampling 1. Qualitative Analysis does not generally use statistical sampling -Theoretical sampling or purposive sampling - Builds in characteristics to help you develop and test your theory (explanations) - Samples chosen on the basis of your research question - Objectivity defended in final outcome *

  13. Selecting and Sampling 2. Some practical considerations - Sample size - Samples for social comparisons - Defining “key” comparisons - Sampling frames not appropriate or non- existent - Availability - Feasibility: money and time *

  14. Data Organization 1. Recognizing and reading the data! - Many ways to do this: chronological, thematic, etc - What to include as “data” - Literal interpretation or interpretive or reflexive (includes your role)

  15. Data Organization 2. Determining indexing categories: - Iteration is crucial in qualitative data analysis - Categories appropriate and consistent (NU*DIST available in our lab) 3. Using non-cross sectional organization - identify segments for specialized analysis - appropriate for studying units separately

  16. Explanations and Data Analyses 1. What Explanations and Analyses can be built from the data? - Comparisons among key components - Tracing developments - Descriptive explanations - Predictive explanations - Theorizing

  17. Explanations and Data Analyses 2. Does the data and data analysis support the explanations? - Comparisons need data on the key components - Developments need data on stages, etc - Descriptive explanations need credible factors and support data - Predictions are very tricky from any analysis - “Grounded theory” produced from qualitative analysis.

  18. Qualitative Research: Summary • Natural setting the source of data; researcher is the instrument • Research is descriptive & anecdotal • Concerned with “process” not product • Inductive analysis • Meaning or “sense-making” important • Masses of data are usually obtained

  19. Considerations:Qualitative Analysis • How is this different from quantitative research? Must they be separate? • Is this research really “scientific”? • Can findings be generalized? • What about researcher bias? • What IS the goal of qualitative research?

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