Qualitative Research Computer as Research Assistant

Workshop Goals  Demostrate qualitative collection using WebCT.  Exporting raw data from WebCT.  Demostrate import, organization and coding of data in N6.  Briefly discuss analysis of data in N6.  Demostrate qualitative collection using WebCT.  Exporting raw data from WebCT.  Demostrate import, organization and coding of data in N6.  Briefly discuss analysis of data in N6.

First Steps  Determine if your research questions and methodology fit with electronic research (my example).  Become familiar with the online format and asynchronous discussion.  Human Subjects Review - qualitative research and electronic collection.  Determine questioning strategy and collection strategy. Example  Determine if your research questions and methodology fit with electronic research (my example).  Become familiar with the online format and asynchronous discussion.  Human Subjects Review - qualitative research and electronic collection.  Determine questioning strategy and collection strategy. Example

Data Collection Strategy StageCollection FormatAnalysis GoalDuration Stage 1: Identifying categories private asynchronous 1-on1 discussion open coding generate categories generate properties and dimensions Collection: 1-2 Weeks Analysis: 2 Weeks Stage 2: Identify core category & construct model public asynchronous group discussion axial coding interconnect categories causal conditions build “ core ” category Collection: 1-2 Weeks Analysis: 2 Weeks Stage 3: Review/refine model public synchronous show model and gather input selective coding build story of how categories relate discursive theoretical propositions address research questions Collection: 2 Weeks Analysis: 2 Weeks+

Advantages/Disadvantages AdvantagesDisadvantages Programs provide file systems that assist researchers in storing and organizing large amounts of textual data. Most programs are complex, and their manuals not very helpful, meaning it takes nonproductive time to learn to use them to their full advantage. Computers can save time and reduce drudgery, especially in the areas of coding, retrieving, displaying, counting and sorting. Researchers may make analytic decisions based on what the computer can do rather than what should be done. Computers force researchers to be organized and to plan well, thus encouraging systematic approaches to analysis. Computer use may encourage researchers to lose sight of the contexts of the study and the data set as a whole. Most analysis programs force researchers to study data line by line, ensuring a more careful reading of the data. As categories are set within computer programs, researchers may be reluctant to rethink or change them. Some programs can create graphic displays from analyses that would take much longer and/or require expertise. Data and completed analysis can potentially be lost through technical failures and human errors.

Next Steps  Organize your discussion board appropriately. (example)  Begin first cycle of questioning - exporting data from WebCT for hardcopy and into N6. (demo)  Open coding in N6 - developing categories, properties and dimensions (how important and why?).  Organize your discussion board appropriately. (example)  Begin first cycle of questioning - exporting data from WebCT for hardcopy and into N6. (demo)  Open coding in N6 - developing categories, properties and dimensions (how important and why?).

Coding Illustration

Analysis  Coding in N6 (Free Nodes)  Free Nodes become Tree Nodes (demo)  Tree Nodes often emerge from a central theme.  Tree Nodes are the major themes containing your research variables.  Research variables are supported via text searching. (demo)  Naming conventions/memos are important!  Coding in N6 (Free Nodes)  Free Nodes become Tree Nodes (demo)  Tree Nodes often emerge from a central theme.  Tree Nodes are the major themes containing your research variables.  Research variables are supported via text searching. (demo)  Naming conventions/memos are important!

Questions/Your Problems  Conclusive remarks - good match, time saver, data as-is, searching capabilities for analysis.  Discuss some of your research problems and/or concerns.  Thank you very much!  Conclusive remarks - good match, time saver, data as-is, searching capabilities for analysis.  Discuss some of your research problems and/or concerns.  Thank you very much!