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Visualizing Topics and Opinions Helps Students Interpret Large Collections of Peer Feedback for Creative Projects

Transactions on Human-Computer Interaction (TOCHI)

Publication date: June 10, 2023

Patrick Crain, Jaewook Lee, Yu-Chen Yen, Joy Kim, Alyssa Aiello, Brian Bailey

We deployed a feedback visualization tool to learn how students used the tool for interpreting feedback from peers and teaching assistants. The tool visualizes the topic and opinion structure in a collection of feedback and provides interaction for reviewing providers’ backgrounds. A total of 18 teams engaged with the tool to interpret feedback for course projects. We surveyed students (N = 69) to learn about their sensemaking goals, use of the tool to accomplish those goals, and perceptions of specific features. We interviewed students (N = 12) and TAs (N = 2) to assess the tool’s impact on students’ review processes and course instruction. Students discovered valuable feedback, assessed project quality, and justified design decisions to teammates by exploring specific icon patterns in the visualization. The interviews revealed that students mimicked strategies implemented in the tool when reviewing new feedback without the tool. Students found the benefits of the visualization outweighed the cost of labeling feedback.

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Research Area:  Adobe Research iconHuman Computer Interaction