An Invitation to Modeling

As part of an working group at the National Institute for Mathematical and Biological Synthesis (NIMBioS), I joined an an interdisciplinary group of biologists, mathematicians, mathematical biologists, and education researchers who came together to address the challenges of teaching modeling. This working group provided the opportunity over two years to explore the education research on modeling, share how modeling is applied and taught in our various disciplines, and examine our individual teaching experiences for best practices. In the process, members of the group became more thoughtful in our practice and have developed more granular, nuanced, and inclusive definitions of models and modeling in a broad sense, and mathematical modeling in particular (Eaton et al., 2019; doi: 10.1080/10511970.2018.1489318). This has led to insight about how we might improve our approach to teaching with models in biology courses (Dahlquist et al., 2017; doi: 10.7287/peerj.preprints.3215v1). Models and the process of modeling are fundamental to the discipline of biology, and therefore should be incorporated into undergraduate biology courses. Models are ubiquitous in biology, including representations of the process of science itself. We advocate for a model of the process of science that highlights parallel tracks of mathematical and experimental modeling investigations. With this recognition, we suggest ways in which instructors can call students’ attention to biological models more explicitly by using modeling language, facilitating metacognition about the use of models, and employing model‐based reasoning. We then provide guidance on how to begin to engage students in the process of modeling, encouraging instructors to scaffold a progression to mathematical modeling. I will discuss how I use this framework in a lower division sophomore‐level Cell Function course and upper division courses in Molecular Biology, Bioinformatics, and Biomathematical modeling. We suggest that by making even a small shift in the way models and modeling are discussed in the classroom, students gain understanding of key biological concepts, practice realistic scientific inquiry, and build quantitative and communication skills. Support or Funding Information This work was conducted as part of the “Unpacking the Black Box: Teaching Quantitative Biology” Working Group at the National Institute for Mathematical and Biological Synthesis (NIMBioS), sponsored by the National Science Foundation through NSF Award #DBI‐1300426, with additional support from The University of Tennessee, Knoxville. Working group members included: Melissa L. Aikens, Joseph T. Dauer, Samuel S. Donovan, Carrie Diaz Eaton, Hannah Callender Highlander, Kristin P. Jenkins, John R. Jungck, M. Drew LaMar, Glenn Ledder, Robert L. Mayes, and Richard C. Schugart.