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| Content Provider | ACM Digital Library |
|---|---|
| Author | Wei, Koh Pang Le, Huy Chia, Daniel Papadopoulos, Kathryn Kulkarni, Chinmay Koller, Daphne Klemmer, Scott R. Cheng, Justin |
| Copyright Year | 2014 |
| Abstract | Peer and self-assessment offer an opportunity to scale both assessment and learning to global classrooms. This article reports our experiences with two iterations of the first large online class to use peer and self-assessment. In this class, peer grades correlated highly with staff-assigned grades. The second iteration had 42.9% of students’ grades within 5% of the staff grade, and 65.5% within 10%. On average, students assessed their work 7% higher than staff did. Students also rated peers’ work from their own country 3.6% higher than those from elsewhere. We performed three experiments to improve grading accuracy. We found that giving students feedback about their grading bias increased subsequent accuracy. We introduce short, customizable feedback snippets that cover common issues with assignments, providing students more qualitative peer feedback. Finally, we introduce a data-driven approach that highlights high-variance items for improvement. We find that rubrics that use a parallel sentence structure, unambiguous wording, and well-specified dimensions have lower variance. After revising rubrics, median grading error decreased from 12.4% to 9.9%. |
| Starting Page | 1 |
| Ending Page | 31 |
| Page Count | 31 |
| File Format | |
| ISSN | 10730516 |
| e-ISSN | 15577325 |
| DOI | 10.1145/2505057 |
| Volume Number | 20 |
| Issue Number | 6 |
| Journal | ACM Transactions on Computer-Human Interaction (TOCHI) |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2013-12-01 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | MOOC Peer assessment Design assessment Design crit Massive online classroom Online education Qualitative feedback Self-assessment Studio-based learning |
| Content Type | Text |
| Resource Type | Article |
| Subject | Human-Computer Interaction |
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