Automating Project Team Formation with Heterogeneous Project Preferences and Skill Mix Constraints

Joseph Anthony Donndelinger; Adam Weaver; James Carlton Bates; Timothy Russell

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Conference: ASEE 2021 Gulf-Southwest Annual Conference
Location: Waco, Texas
Publication Date: March 24, 2021
Start Date: March 24, 2021
End Date: March 26, 2021
Page Count: 19
DOI: 10.18260/1-2--36362
Permanent URL: https://peer.asee.org/36362
Download Count: 368

Paper Authors

biography

Joseph Anthony Donndelinger Baylor University orcid.org/0000-0002-0421-1556

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Mr. Donndelinger joined Baylor University’s School of Engineering and Computer Science as a Clinical Associate Professor after 23 years of experience in the automotive and cutting tool industries. During his 16 years as a Senior Researcher at General Motors’ Global Research and Development Center, Mr. Donndelinger served as Principal Investigator on 18 industry-university collaborative projects focusing primarily on conducting interdisciplinary design feasibility assessments across the engineering, marketing, finance and manufacturing domains. Prior to this, he held positions in New Product Development at Ford Motor Company and Onsrud Cutter. He currently serves as lead instructor for the Baylor Engineering Capstone Design program and teaches additional courses in the areas of Engineering Design, Technology Entrepreneurship, and Professional Development. Mr. Donndelinger has published three book chapters in addition to 30 articles in peer-reviewed journals and conference proceedings and has been awarded two United States patents. Mr. Donndelinger earned an M.S. in Industrial Engineering and a B.S. in Mechanical Engineering from the University of Illinois at Urbana-Champaign.

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Timothy is a Ph.D. student in Mechanical Engineering at Baylor University and a Teacher's Aid for Senior Design. His research focus is on mechanical and thermal property prediction in large-area additive manufacturing and he has been published in the Journal of Composites Science. He has a B.S. in Mathematics from Ouachita Baptist University and a master's in Mechanical Engineering from Baylor. Timothy sits on the Honor Council at Baylor and is the president of the student chapter of the Society of Plastics Engineers.

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Abstract

It is well established that design team composition is a significant driver of both team member engagement and design project success. Off-the-shelf solutions are available for automating the process of forming design teams with balanced skill mix and diversity profiles. These systems have been successfully applied both at our institution and others to improve student engagement and team performance in design projects with homogenous project opportunities and skill mix requirements (i.e. when forming multiple teams of similar composition to address a common design challenge). However, it has proven challenging to apply available off-the-shelf solutions to form design teams in our Capstone Design program due to heterogeneity in both project opportunities (each project team addresses a unique design challenge) and required skill mixes (which vary by project opportunity).

In this paper, we discuss the development and application of a heuristic optimization algorithm that extends the capabilities of existing off-the-shelf project team formation systems, which effectively balance team sizes and diversity profiles within teams, to incorporate students’ individual project preferences and project-specific skill mix constraints. Comparing results of applying this algorithm for Capstone Design project team formation with results of applying off-the-shelf solutions for team formation in other design courses with homogenous project opportunities and skill mix requirements, we find that our algorithm satisfies project-specific skill mix constraints and effectively matches students to preferred project opportunities (consistently matching more than 5/6 of students on one of their Top 3 project choices) while offering comparable performance to off-the-shelf project team formation systems in terms of balancing team sizes and diversity profiles within teams. Consistent with findings in prior research, our data indicate that balancing the sizes and diversity of project teams favorably impacts team performance (measured by scores on course assignments) and student engagement (measured by peer evaluations). We are seeking additional insights into these phenomena by incorporating new descriptive variables such as students’ project preferences in analyses of Capstone Design project team performance.

Citation
Format

Donndelinger, J. A., & Weaver, A., & Bates, J. C., & Russell, T. (2021, March), Automating Project Team Formation with Heterogeneous Project Preferences and Skill Mix Constraints Paper presented at ASEE 2021 Gulf-Southwest Annual Conference, Waco, Texas. 10.18260/1-2--36362

TY  - CPAPER
AB  - It is well established that design team composition is a significant driver of both team member engagement and design project success. Off-the-shelf solutions are available for automating the process of forming design teams with balanced skill mix and diversity profiles. These systems have been successfully applied both at our institution and others to improve student engagement and team performance in design projects with homogenous project opportunities and skill mix requirements (i.e. when forming multiple teams of similar composition to address a common design challenge). However, it has proven challenging to apply available off-the-shelf solutions to form design teams in our Capstone Design program due to heterogeneity in both project opportunities (each project team addresses a unique design challenge) and required skill mixes (which vary by project opportunity).

In this paper, we discuss the development and application of a heuristic optimization algorithm that extends the capabilities of existing off-the-shelf project team formation systems, which effectively balance team sizes and diversity profiles within teams, to incorporate students’ individual project preferences and project-specific skill mix constraints. Comparing results of applying this algorithm for Capstone Design project team formation with results of applying off-the-shelf solutions for team formation in other design courses with homogenous project opportunities and skill mix requirements, we find that our algorithm satisfies project-specific skill mix constraints and effectively matches students to preferred project opportunities (consistently matching more than 5/6 of students on one of their Top 3 project choices) while offering comparable performance to off-the-shelf project team formation systems in terms of balancing team sizes and diversity profiles within teams. Consistent with findings in prior research, our data indicate that balancing the sizes and diversity of project teams favorably impacts team performance (measured by scores on course assignments) and student engagement (measured by peer evaluations). We are seeking additional insights into these phenomena by incorporating new descriptive variables such as students’ project preferences in analyses of Capstone Design project team performance.

AU  - Joseph Anthony Donndelinger
AU  - Adam Weaver
AU  - James Carlton Bates
AU  - Timothy Russell
CY  - Waco, Texas
DA  - 2021/03/24
PB  - ASEE Conferences
TI  - Automating Project Team Formation with Heterogeneous Project Preferences and Skill Mix Constraints
UR  - https://peer.asee.org/36362
DO  - 10.18260/1-2--36362
ER  -