WIP: Identity-Based Bias in Undergraduate Peer Assessment
- Conference
- Location
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East Lansing, Michigan
- Publication Date
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July 31, 2022
- Start Date
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July 31, 2022
- End Date
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August 2, 2022
- Conference Session
- Tagged Topics
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Diversity and Works In Progress
- Page Count
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5
- DOI
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10.18260/1-2--42257
- Permanent URL
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https://peer.asee.org/42257
- Download Count
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225
Paper Authors
Madison Jeffrey University of Michigan
Madison Jeffrey is a graduate candidate in the University of Michigan's Masters in Higher Education program. With a focus on Management and Organizations, she's interested in ways in which the system of higher education can adapt to become more accessible and equitable to students. She's a research assistant at the University of Michigan's College of Engineering, where she works with a team of researchers responsible for Tandem, a software that monitors team performance to link students and instructors.
Robin Fowler University of Michigan
Robin Fowler is a lecturer in the Program in Technical Communication at the University of Michigan. She enjoys serving as a "communication coach" to students throughout the curriculum, and she's especially excited to work with first year and senior students, as well as engineering project teams, as they navigate the more open-ended communication decisions involved in describing the products of open-ended design scenarios.
Mark Mills
UM, Center for Academic Innovation
orcid.org/0000-0002-1145-9592
Mark Mills is a Data Scientist with the Center for Academic Innovation at the University of Michigan. He is responsible for leading analysis across the Center in support of its mission to leverage data for shaping innovation in higher education. Mark received his PhD from the University of Nebraska in Cognitive and Quantitative Psychology, where he studied models for classifying cognitive state from eye movements.
Abstract
Peer evaluation is a commonly used practice for group work throughout higher education as it allows students to provide and receive insight as well as provides additional information to faculty. When such peer evaluations may be taken into consideration for grades, it is especially important to look closer at the potential bias that may be present. Students may unconsciously perceive members of their group in biased ways because of ingrained gender or racial biases, potentially resulting in skewed feedback. In this project, we look at how student feedback varies for students with historically underrepresented identities. To accomplish this, we will use survey data from a software tool that monitors team members throughout the course of a project to provide a link between students and instructors. Part of this software allows team members to evaluate one another and provide feedback, including items such as reliability, effort, quality of work, and idea generation. Using hierarchical linear regression, we will investigate patterns of ratings based on identity characteristics such as gender and race (of both evaluator and evaluated) to investigate how these factors are related to evaluations.
Jeffrey, M., & Fowler, R., & Mills, M. (2022, July), WIP: Identity-Based Bias in Undergraduate Peer Assessment Paper presented at 2022 First-Year Engineering Experience, East Lansing, Michigan. 10.18260/1-2--42257
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