CSTAR Seminar on Secondary Data Analysis. June 19 th 2012 Choosing Software for Qualitative Data Analysis version 2

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Deborah Shields
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ended questions in questionnaires Research diaries, fieldnotes Film, video, diagrams, observational data Photographs, handwritten documents,

1 CHOOSING SOFTWARE FOR QUALITATIVE DATA ANALYSIS Dr. Kalpana Shankar School of Information and Library Studies, UCD QUALITATIVE DATA Types of data may include: Semi-structured interviews Open ended questions in questionnaires Research diaries, fieldnotes Film, video, diagrams, observational data Photographs, handwritten documents, paintings/artwork ROLE OF SOFTWARE IN RESEARCH Project management tool Data storage, code storage, memos and comments can be stored in one place Flexibility Use of tools should depend upon: Research questions and aims Constrains Methodological and analytical approach 1

2 COMPUTER ASSISTED QUALITATIVE DATA ANALYSIS (CAQDAS) Suites of software to help researchers do some/all/most of the following: Code data (thematic, demographic, other) Text searches Data organization/project management Data segmentation Writing tools for memos, commentary, annotation Outputs of searches in bibliographies, codebooks, memos QUALITATIVE DATA ANALYSIS TOOLS Useful for managing transcription, linking documents, coding, affiliated documents, and preliminary writing Factors in choice: Mac, PC, both, or online/web-based Number of researchers using the tools Nature of data (text, video, audio, diagram) Price Pros/cons DIFFERENCES AMONG SOFTWARE PACKAGES Architecture/platform Data formatting Multimedia handling Coding schema Querying possibilities Output options Cost 2

3 EXTRA FEATURES Facilitating teamwork Integration of quantitative data Multimedia data handling (including transcription) Tools for navigating data without coding Integration and organization of outside materials articles, documents, etc Quantifying qualitative data NEW ANALYTICAL POSSIBILITIES Convergences of qualitative data and GIS (geographical information systems) Multi stream video data Real time collaboration Data visualization Mapping and networks Charts Matrices Data exchange in structured formats CODE BASED APPROACHES TO ANALYSIS Allow both externally generated codebook and coding on the fly (exploratory analysis) Automatic coding Within and between case analysis (useful for secondary data analysis) Intercoder reliability easier to calculate Coding can be used for other purposes Literature reviews, reflective analysis Generating outputs 3

NON CODE BASED APPROACHES Software to manage the project Discourse/narrative/conversation analysis Interaction analysis DISADVANTAGES Distance from data

4 NON CODE BASED APPROACHES Software to manage the project Discourse/narrative/conversation analysis Interaction analysis DISADVANTAGES Distance from data Different security/privacy issues with respect to data management Temptation to let software do the work Integrating into existing workflow/changing workflow 4

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6 CHOOSING A PACKAGE (LOTS OF RESOURCES OUT THERE) Institutional license and support Price!! Platform(s) Time to learn software Kinds and amounts of data Methodology Preferred style of analysis Thematic, coding Language and terminology analysis Annotation and memoing needs Team versus individual work EXAMPLES Atlas.ti (PC but can be installed on Intel Mac) Nvivo (UCD has and supports) MaxQDA (PC) Transana (video) Dedoose (Web based, low cost) WeftQDA (Open source, PC/Linux) TAMS Analyzer (Open source, Mac OSX and Linux) CONCLUSIONS When choosing a package, consider platform, size of research team, kinds of data you are working with, user community/license, and most important, your methodology Don t let the tool drive your data analysis! 6

Qualitative Data Analysis Software. A workshop for staff & students School of Psychology Makerere University

Qualitative Data Analysis Software A workshop for staff & students School of Psychology Makerere University (PhD) January 27, 2016 Outline for the workshop CAQDAS NVivo Overview Practice 2 CAQDAS Before