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Proof of Concept: An Algorithm for Consideration of Students’ Personalities in Team Formation

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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

Student Division Technical Session 6

Tagged Division

Student

Page Count

18

DOI

10.18260/1-2--37618

Permanent URL

https://peer.asee.org/37618

Download Count

273

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Paper Authors

biography

Jeong Hin Chin University of Michigan

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Bachelor of Science in Statistics and Data Science, Statistics Department, College of Literature, Science and the Arts.

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biography

Herbert Li University of Michigan

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A student studying at the University of Michigan. Majoring in Computer Science and Data Science. Passionate in data analytics and inspired to utilize data to find more useful discoveries.

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biography

Robin Fowler University of Michigan

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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. She is also one of the faculty innovators behind Tandem, a tool to support teams with equity in teamwork.

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Abstract

Team-based pedagogy is common across engineering, especially in introductory courses and senior design projects. Although team-based learning provides students with many benefits, not all students benefit equally from it. Due to the fact that students of a team may come from vastly different backgrounds (academically and non-academically), faculty members find it difficult to predict barriers to team success. Better prediction of student and team outcomes would allow for better pedagogical decision-making in the formation and support of team-based learning. This methodological paper describes a dataset including student personality and team preference inputs, self-and-peer-assessments of teamwork, and perceptions of teamwork outcomes. We use student- and team-level inputs to consider students’ likelihood of dominating group discussions. Using such information, we propose a method for clustering students for analysis with the aim of finding ways to group students into teams more effectively to help achieve their particular goals or alleviate their concerns.

Chin, J. H., & Li, H., & Fowler, R. (2021, July), Proof of Concept: An Algorithm for Consideration of Students’ Personalities in Team Formation Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. 10.18260/1-2--37618

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