Mastery of quantitative skills is increasingly critical for student success in life sciences, but few curricula adequately incorporate quantitative skills. Quantitative Biology at Community Colleges (QB@CC) is designed to address this need by building a grassroots consortium of community college faculty to 1) engage in interdisciplinary partnerships that increase participant confidence in life science, mathematics, and statistics domains; 2) generate and publish a collection of quantitative skills–focused open education resources (OER); and 3) disseminate these OER and pedagogical practices widely, in turn expanding the network. Currently in its third year, QB@CC has recruited 70 faculty into the network and created 20 modules. Modules can be accessed by interested biology and mathematics educators in high school, 2-year, and 4-year institutions. Here, we use survey responses, focus group interviews, and document analyses (principles-focused evaluation) to evaluate the progress in accomplishing these goals midway through the QB@CC program. The QB@CC network provides a model for developing and sustaining an interdisciplinary community that benefits participants and generates valuable resources for the broader community. Similar network-building programs may wish to adopt some of the effective aspects of the QB@CC network model to meet their objectives.

Vol. 22, No. 2

June 01, 2023

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History

Submitted: 16 September 2021

Revised: 13 January 2023

Accepted: 20 January 2023

Information

© 2023 J. Esquibel et al. CBE—Life Sciences Education © 2023 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 4.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/4.0).

The authors recognize members of the NIMBioS Quantitative Biology at Community Colleges Working Group for their substantial contributions to the RCN-UBE QB@CC grant, including Lisa Corwin, Melissa Aikens, Linda Grisham, Greg Wiggins, and Tony Weisstein. Their work on the survey and matrix, as well as the thoughtful discussions in the working group, were the foundation for QB@CC network activities. The authors also thank NIMBioS for supporting the working group. The authors thank Tara Graham (BioQUEST staff) for her help with Figure 1B. Finally, the authors thank all the network participants for their time and effort to make the QB@CC project successful. This work was supported by NSF award no. 1919613. Any opinions, findings, conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the NSF.

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