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Contextual Inquiry High-Level Results
Affinity | Categories | Breakdowns
In order to organized our large amounts of Contextual Inquiry data, we created post-it notes
highlighting some of the key points. Each of these post-it notes were categorized so we could tie our
conclusions directly back to specific data points. We put all of these post-it notes in a common location and sorted them as a group into specific categories to give us a better sense of the type of data we got from our research. In touching the data directly, we had the opportunity to look more carefully at each data point and get an overall sense of where the data fit into the overall picture. Just the process of creating this Affinity Diagram inspired a lot of design ideas and considerations. From here, our consolidation effort went it two different directions: Category main messages and Breakdowns. For each of the major categories listed, we have specific supporting data points. These are listed here by CI number and key fact number. Instead of video time-stamps to identify the source of the data, the index values are related to the post-it notes and the detailed CI notes. The categories from our data consolidation include:
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| © Carnegie Mellon University, Masters of Human-Computer Interaction, CitiStat project: Peter Centraf, Lisa Edelman, Lorrianne Nault, Matt Sharpe, Adrian Tang | |||||||||