6009 - Week 9.docx - Week 9 Qualitative Data Analysis for...

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Week 9: Qualitative Data Analysis for Program Evaluation 9.2 Qualitative Data Analysis The Goal of Qualitative Data Analysis Discover something new Perform interpretive analysis Identify the meaning of what is seen and heard Interpret the data o Step back to see the bigger picture o Relate the description to the theme of the evaluation question o Step. In to see the details The Meaning of Analysis A systematic process of coaxing the collected data to reveal their characteristics and patterns A data-led, and therefore data-limited, activity An ongoing process throughout the data collection for the study activity o Recognize what has been learned o Identify areas that need enhanced focus o Recognized new areas that should be developed An integral part of the overall design of the study and the plan for data collection A Common Approach to Analysis Organize the raw data (transcripts, notes) Preserve the data by entering it into a defined system Identify the system for coding (hand coding, ATLAST.ti, NVivo, etc) Search for meaning in the data (divide and categorize for thematic analysis) Interpret the meaning of the data Draw conclusions Qualitative Data Mostly textual (derived from interviews and existing documents) May be photos or audio recordings Data variables are also qualitative in nature The Data Analysis Spiral Qualitative data analysis is cyclical, reflexive and iterative Researchers continually compare the interaction between theory and data Researchers test the interpretation of the data against alternative explanations Researchers can attain a level of generalizability, depending on the linkages between the theory and the conceptual framework (how well is it working?) Four Approaches to Qualitative Analysis 1. Thematic content analysis: uses predefined themes and content 2. Grounded theory: intentional leack of preconveived ideas
Week 9: Qualitative Data Analysis for Program Evaluation 3. Framework analysis 4. Narrative analysis Thematic Content Analysis Categorizes the content of the data on the basis of recurrent themes Identifies patterns of themes in the answers of respondents Grounded Theory Good for when enough data don’t exist to build a theory Used when researcher wants to systematically develop a theory that explains a process, action or interaction Good for when an explanatory theory doesn’t exist or doesn’t fit the observations Analysis Goes Beyond Coding Theory codes Coding theory coding enables categorization of vast quantities of research data qualitaitive data analysis extends beyond the coding of the data coding is gounded in theory coding and analysis processes can lead to theory validation and (possibly) revision Theory + data = good (qualitative) research data needs to be grounded by theory, which may then permit generalizations to be made about populations beyond the immediate study group qualitative analysis must be conceptually dense and should examine the linkages and

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