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Teaming is a core part of engineering education, especially in the first and last years of engineering when project work is a prevalent focus. The literature on the effects of working in diverse teams is mixed. Negative findings include decreased affect, increased frustration, and sustained conflict in teams. Positive findings include increased productivity, production of high quality products, and divergent-thinking and idea generation. Given these mixed findings, it becomes important to not only understand the practical outputs of working in diverse teams, but also how the experience of working in diverse teams influences whether students see themselves as engineers and whether or not they feel they belong in engineering. Our project, Building Supports for Diversity through Engineering Teams, investigates how students’ attitudes towards diversity influence how students experience work in diverse teams through addressing two main research questions: 1) What changes occur in students’ diversity sensitivity, multicultural effectiveness, and engineering practices as a result of working in diverse teams? 2) How do students’ perceptions of diversity, affect, and engineering practices change because of working on diverse teams? Using a multi-method approach, we deployed survey instruments to determine changes in student’s attitudes about teaming, diversity sensitivity, and openness attitudes. We also observed students working in teams and interviewed these students about their perceptions of diversity and experiences in their teams. Preliminary results of the quantitative phase show that variance in students’ attitudes about diversity significantly increase over the semester, further reflecting the mixed results that have been seen previously in the literature. Additionally, Social Network Analysis was used to characterize the social structure practices of a multi-section, large-enrollment first-year engineering course. This reveals the underlying social structure of the environment, its inclusiveness, and how diverse students work with others on engineering. Initial results indicate that students are included in social networks regardless of gender and race. Preliminary results of the qualitative phase, using Interpretive Phenomenological Analysis, have yielded relationships between student’s definitions, valuation, and enactment of diversity in engineering spaces. Individual student’s incoming attitudes of diversity and previous experiences interact with practical needs in first-year engineering classrooms to create different microclimates within each team. These microclimates depict tensions between what instructors emphasize about diversity, stereotypes of engineering as focused on technical instead of social skills, and pragmatic forces of “getting the job done.” This knowledge can help explain some of the complexity behind the conflicting literature on diversity in teams. Ultimately, this research can help us understand how to build inclusive and diverse environments that guide students to learn how to understand their own complex relationship, understanding, and enactment of diversity in engineering. By understanding how students make sense of diversity in engineering spaces, educators and researchers can figure out how to introduce these concepts in relevant ways so that students can inclusively meet the grand challenges in engineering. This curriculum integration, in turn, can improve team interactions and the climate of engineering for underrepresented groups.
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Forming Diverse Teams From Sequentially Arriving People
Abstract Collaborative work often benefits from having teams or organizations with heterogeneous members. In this paper, we present a method to form such diverse teams from people arriving sequentially over time. We define a monotone submodular objective function that combines the diversity and quality of a team and proposes an algorithm to maximize the objective while satisfying multiple constraints. This allows us to balance both how diverse the team is and how well it can perform the task at hand. Using crowd experiments, we show that, in practice, the algorithm leads to large gains in team diversity. Using simulations, we show how to quantify the additional cost of forming diverse teams and how to address the problem of simultaneously maximizing diversity for several attributes (e.g., country of origin and gender). Our method has applications in collaborative work ranging from team formation, the assignment of workers to teams in crowdsourcing, and reviewer allocation to journal papers arriving sequentially. Our code is publicly accessible for further research.
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- Award ID(s):
- 1728086
- PAR ID:
- 10211403
- Date Published:
- Journal Name:
- Journal of Mechanical Design
- Volume:
- 142
- Issue:
- 11
- ISSN:
- 1050-0472
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1115/1.4046998
