Document Type

Article

Publication Date

2026

Digital Object Identifier (DOI)

https://doi.org/10.1145/3800962

Abstract

Peer review is an underutilized yet potentially powerful strategy for fostering evaluative judgment and design literacy in visualization education. Critiquing visual work requires domain-specific competencies that extend beyond generic peer feedback; however, widely adopted platforms such as Canvas provide limited support for the cognitive and visual demands of visualization critique. We introduce VisPeerReview, a visualization-specific learning analytics dashboard (LAD) designed to scaffold peer feedback through an integrated visualization display, rubric-guided prompts, and inline annotation tools. We evaluated VisPeerReview through a three-phase mixed-methods study conducted in an undergraduate data visualization course, comparing it with Canvas’s default peer-review workflow. Drawing on interaction logs, peer-review text, and survey responses, we found that VisPeerReview elicited significantly longer and more linguistically rich feedback and was consistently preferred by students. Sentiment analysis further indicated more positive evaluative language and clearer reviewer intent under the dashboard-supported condition. Beyond tool evaluation, this study offers the first systematic comparison between Canvas and a visualization-specific LAD, demonstrating how theory-aligned instructional interface design—grounded in representational competence and learningsciences frameworks—can meaningfully improve the quality of peer feedback in computing education.

Rights Information

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

Was this content written or created while at USF?

Yes

Citation / Publisher Attribution

ACM Transactions on Computing Education, v. 26, issue 3, art. 54

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