July 26, 2021
July 26, 2021
July 19, 2022
This paper presents a distributed, scalable, student-driven method to provide timely, nuanced, unbiased, and personalized feedback to students learning in diverse self-defined project teams. We report on a new implementation of anonymous peer review within a custom-made online learning management system designed to support Innovation-Based Learning. The system automatically and anonymously assigns multiple students to review each work product of their peers. Students benefit doubly from peer review. First, students receive more feedback more quickly with more personalization compared to instructor-reviewed or computer scored activities. More importantly, new opportunities for learning are created when students assume the role of reviewer; they must analyze the work of others, provide technical justification for their review comments, and communicate professionally. Peer review also benefits the instructor and institution as it addresses scalability challenges for non-routine assignments and qualitative evaluation. We describe how the peer review workflow was implemented, and we evaluate peer review effectiveness in terms of the quantity of peer reviews performed and whether peer review increased the odds of an item subsequently receiving instructor approval. Student opinions of peer review were also gathered in an end-of-semester survey. The implementation was a mixed success; lessons-learned and subsequent improvements are also reported.
Striker, R., & Pearson, M., & Swartz, E. M., & Alvarez Vazquez, E., & Singelmann, L., & Ng, S. S. (2021, July), Anonymous Online Peer Review for Innovation-Based Learning Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. 10.18260/1-2--36686
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