Integrating interactive computational modeling in biology curricula

• Published in: PLoS computational biology 2015-03, Vol.11 (3), p.e1004131-e1004131
• Main Authors: Helikar, Tomáš, Cutucache, Christine E, Dahlquist, Lauren M, Herek, Tyler A, Larson, Joshua J, Rogers, Jim A
• Format: Article
• Language: English
• Subjects: Biology; Biology - education; Biomedical research; Cell cycle; Classrooms; Computational biology; Computational Biology - education; Computer Simulation; Core curriculum; Curriculum; Curriculum development; Education; Educational technology; Humans; Learning; Methods; Models, Immunological; Science education; Software; Studies; Study and teaching; Teaching methods
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1004131

While the use of computer tools to simulate complex processes such as computer circuits is normal practice in fields like engineering, the majority of life sciences/biological sciences courses continue to rely on the traditional textbook and memorization approach. To address this issue, we explored the use of the Cell Collective platform as a novel, interactive, and evolving pedagogical tool to foster student engagement, creativity, and higher-level thinking. Cell Collective is a Web-based platform used to create and simulate dynamical models of various biological processes. Students can create models of cells, diseases, or pathways themselves or explore existing models. This technology was implemented in both undergraduate and graduate courses as a pilot study to determine the feasibility of such software at the university level. First, a new (In Silico Biology) class was developed to enable students to learn biology by "building and breaking it" via computer models and their simulations. This class and technology also provide a non-intimidating way to incorporate mathematical and computational concepts into a class with students who have a limited mathematical background. Second, we used the technology to mediate the use of simulations and modeling modules as a learning tool for traditional biological concepts, such as T cell differentiation or cell cycle regulation, in existing biology courses. Results of this pilot application suggest that there is promise in the use of computational modeling and software tools such as Cell Collective to provide new teaching methods in biology and contribute to the implementation of the "Vision and Change" call to action in undergraduate biology education by providing a hands-on approach to biology.