Abstract
AbstractIn this article, we discuss the use of bipartite network analysis to understand and improve interdisciplinary teaching practice. We theorize mathematics and biology as part of a coevolving mutualistic ecosystem. As part of an interdisciplinary teaching initiative, we inventoried mathematics topics appearing in the marine biology classroom and their associated marine context. We then apply techniques of mutualistic bipartite networks analysis to this system to understand the use of mathematical concepts in a marine biology classroom. By analyzing the frequency and distribution of mathematics topics, we see that a variety of mathematical concepts are used across the course with most appearing only a few times. While this is an inherent trait of mutualistic coevolutionary networks, it can create a logistical challenge to supporting mathematics in the marine biology classroom. We find that marine biology topics containing the most mathematics are either close to the instructor’s research area or were introduced through externally developed educational resources. Finally, we analyze groups of topics that appear connected to each other more frequently to inform both interdisciplinary education development as well as disciplinary support. We also suggest ways to use network metrics to track interdisciplinary connections over time, helping us understand the impact of interventions on interdisciplinary teaching practice.
Publisher
Cold Spring Harbor Laboratory
Reference56 articles.
1. Teaching quantitative ecology online: An evidence-based prescription of best practices;Ecology and Evolution,2020
2. Akman, O. , Eaton, C. D. , Hrozencik, D. , Jenkins, K. P. , & Thompson, K. V. (2020). Building Community-Based Approaches to Systemic Reform in Mathematical Biology Education. Bulletin of Mathematical Biology, 82(8).
3. American Association for the Advancement of Science [AAAS]. (2011). Vision and change in undergraduate biology education: a call to action. American Association for the Advancement of Science, Washington, DC. visionandchange.org/finalreport.
4. Colleagues as change agents: How department networks and opinion leaders influence teaching at a single research university;CBE-Life Sciences Education,2016
5. Network analysis of knowledge construction in asynchronous learning networks;Journal of Asynchronous Learning Networks,2003
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