Leveraging Peer Feedback to Improve Visualization Education

January 12, 2020 Β· Declared Dead Β· πŸ› IEEE Pacific Visualization Symposium

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Authors Zachariah Beasley, Alon Friedman, Les Piegl, Paul Rosen arXiv ID 2001.07549 Category cs.HC: Human-Computer Interaction Cross-listed cs.CY Citations 10 Venue IEEE Pacific Visualization Symposium Last Checked 4 months ago
Abstract
Peer review is a widely utilized pedagogical feedback mechanism for engaging students, which has been shown to improve educational outcomes. However, we find limited discussion and empirical measurement of peer review in visualization coursework. In addition to engagement, peer review provides direct and diverse feedback and reinforces recently-learned course concepts through critical evaluation of others' work. In this paper, we discuss the construction and application of peer review in a computer science visualization course, including: projects that reuse code and visualizations in a feedback-guided, continual improvement process and a peer review rubric to reinforce key course concepts. To measure the effectiveness of the approach, we evaluate student projects, peer review text, and a post-course questionnaire from 3 semesters of mixed undergraduate and graduate courses. The results indicate that course concepts are reinforced with peer review---82% reported learning more because of peer review, and 75% of students recommended continuing it. Finally, we provide a road-map for adapting peer review to other visualization courses to produce more highly engaged students.
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