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Anonymous Online Peer Review for Innovation-Based Learning

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Conference

2021 ASEE Virtual Annual Conference Content Access

Location

Virtual Conference

Publication Date

July 26, 2021

Start Date

July 26, 2021

End Date

July 19, 2022

Conference Session

Assessment in Multidisciplinary Learning Environment

Tagged Division

Multidisciplinary Engineering

Page Count

16

DOI

10.18260/1-2--36686

Permanent URL

https://peer.asee.org/36686

Download Count

35

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Paper Authors

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Ryan Striker P.E. North Dakota State University Orcid 16x16 orcid.org/0000-0001-9058-5636

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Ryan Striker is a life-long learner. Ryan has over a decade of professional experience designing embedded electronic hardware for industrial, military, medical, and automotive applications. Ryan is currently pursuing a PhD in Electrical and Computer Engineering at North Dakota State University. He previously earned his MS in Systems Engineering from the University of Saint Thomas and his BS in Electrical Engineering from the University of Minnesota.

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Mary Pearson North Dakota State University

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Mary is a Ph.D. candidate in biomedical engineering with research focused in the area of bioelectromagnetics, specifically designing electronics that can be used as medical devices. She obtained her B.S. and M.S. degrees at NDSU in electrical and computer engineering. Mary is also interested in STEM education research.

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Ellen M. Swartz North Dakota State University

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Ellen Swartz is currently pursuing a M.S. degree in Biomedical Engineering at North Dakota State University. Her research interests include STEM education, innovation-based learning, and agent-based modeling of complex adaptive systems. She previously received her B.S. degree from North Dakota State University in Electrical and Computer Engineering.

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Enrique Alvarez Vazquez North Dakota State University Orcid 16x16 orcid.org/0000-0002-7257-0817

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Enrique is an experienced Systems Engineer with a demonstrated history of working in the electrical and electronic manufacturing field. Highly skilled in Embedded Devices, Software Engineering, and Electronics. He is a strong information technology professional with two MSc's and working on a Doctor of Philosophy - PhD focused in Electrical Engineering from North Dakota State University.

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Lauren Singelmann North Dakota State University Orcid 16x16 orcid.org/0000-0003-3586-4266

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Lauren Singelmann is a PhD Student in Electrical and Computer Engineering at North Dakota State University. Her research interests are innovation-based-learning, educational data mining, and K-12 Outreach. She works for the NDSU College of Engineering as the K-12 Outreach Coordinator where she plans and organizes outreach activities and camps for students in the Fargo-Moorhead area.

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Stanley Shie Ng Biola University Orcid 16x16 orcid.org/0000-0003-3021-8206

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Stanley Ng received his BS in Biomedical Engineering from University of California Irvine and MS in Biomedical Diagnostics from Arizona State University. He serves as faculty and director of engineering programs at Biola University. Currently, he is pursuing a Ph.D. in Engineering and STEM Education at North Dakota State University.

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Abstract

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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