Stoddard, E. L., & Pfeifer, G. (2018, April), Working Toward More Equitable Team Dynamics: Mapping Student Assets to Minimize Stereotyping and Task Assignment Bias  Paper presented at 2018 CoNECD - The Collaborative Network for Engineering and Computing Diversity Conference, Crystal City, Virginia. 10.18260/1-2--29598

\bibitem{asee_peer_29598}
  Stoddard, E. L., \& Pfeifer, G. (2018, April), \emph{Working Toward More Equitable Team Dynamics: Mapping Student Assets to Minimize Stereotyping and Task Assignment Bias}
  Paper presented at 2018 CoNECD - The Collaborative Network for Engineering and Computing Diversity Conference, Crystal City, Virginia.
  10.18260/1-2--29598

Elisabeth (Lisa) Stoddard and Geoff Pfeifer.  "Working Toward More Equitable Team Dynamics: Mapping Student Assets to Minimize Stereotyping and Task Assignment Bias".  2018 CoNECD - The Collaborative Network for Engineering and Computing Diversity Conference, Crystal City, Virginia, 2018, April.  ASEE Conferences, 2018.  https://peer.asee.org/29598 Internet.  23 Apr, 2024

\bibitem{asee_peer_29598}
  Elisabeth (Lisa) Stoddard and Geoff Pfeifer.
  "Working Toward More Equitable Team Dynamics: Mapping Student Assets to Minimize Stereotyping and Task Assignment Bias".
  \emph{2018 CoNECD - The Collaborative Network for Engineering and Computing Diversity Conference, Crystal City, Virginia, 2018, April}.
  ASEE Conferences, 2018.
  https://peer.asee.org/29598 Internet.  23 Apr, 2024

@INPROCEEDINGS{asee_peer_29598
author = "Elisabeth (Lisa) Stoddard and Geoff Pfeifer"
title = "Working Toward More Equitable Team Dynamics: Mapping Student Assets to Minimize Stereotyping and Task Assignment Bias"
booktitle = "2018 CoNECD - The Collaborative Network for Engineering and Computing Diversity Conference"
year = "2018"
month = "April"
address = "Crystal City, Virginia"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/29598}
number = {10.18260/1-2--29598}
}

TY  - CPAPER
AB  - Today’s STEM students will enter a diverse workforce and need to be prepared to work with people of diverse backgrounds. Research shows diverse teams are better at innovating and solving STEM-related problems, precisely because there are a diversity of perspectives and backgrounds that are brought to bear in working on these issues (Philips, Liljenquist, Neale, 2010; Rock, Grant, and Grey 2016). However, this assumes those working on teams can take advantage of that diversity and are not hampered by racial, gender, and other forms of bias. Recent studies show that issues of bias and stereotyping on student teams is prominent, particularly in STEM fields (Wolfe, Powell, Schisserman, and Kirshon, 2016). This results in reduced learning opportunities for all students, with compounded harms to the self-efficacy and retention rates of female students, students of color, and other underserved populations. We have created a set modules and resources for WPI’s first year, project-based seminar program (the Great Problems Seminars program) that attempt to help STEM students and faculty work through these issues with the goal of creating effective, equitable, and inclusive teams. This paper/presentation will detail the structure of these modules, some of the results from a study done in connection with them, and what we have learned along the way.  


References: 

Phillips, Katherine W., Katie A. Liljenquist, and Margaret Neale. “Better Decisions Through Diversity” Kellogg Insight. October 2010. 

Rock, David, Heidi Grant, and Jacqui Grey. “Diverse Teams Feel Less Comfortable- and That’s Why They Perform Better” in Harvard Business Review, September 2016.

Wolfe, Joanna, Beth Powell, Seth Schlisserman, Alexandra Kirshon. “Teamwork in Engineering Undergraduate Classes: What Problems Do Students Experience” Proceedings of the 123rd Annual Conference of the Association of Engineering Education (June) 2016.  

AU  - Elisabeth (Lisa) Stoddard
AU  - Geoff Pfeifer
CY  - Crystal City, Virginia
DA  - 2018/04/29
PB  - ASEE Conferences
TI  - Working Toward More Equitable Team Dynamics: Mapping Student Assets to Minimize Stereotyping and Task Assignment Bias
UR  - https://peer.asee.org/29598
DO  - 10.18260/1-2--29598
ER  -