The field of biochemistry provides a critical foundation for students as they pursue careers in diverse fields, such as health care, and basic and applied research. To master core biochemical concepts, students must integrate background knowledge in biology, chemistry, physics, and mathematics as they learn about the dynamic structures and processes that constitute biochemical systems. Students often struggle with mechanistic reasoning, as evidenced by their inability to connect structures to functions and to properly attribute causality within decentralized systems. Hence, the ability to properly visualize and model biochemical systems represents an important means to advance student learning. Unfortunately, the traditional biochemistry classroom provides limited opportunities for students to engage with concepts in realistic and interactive ways, as primarily static, two-dimensional images and diagrams are used as teaching tools within passive, lecture-based environments. This project will transform biochemistry instruction by developing a series of easily-incorporated modules that make use of dynamic physical and computational models. These modules will focus on helping students develop their understandings of the direct relationships between macromolecular structure and function as well as the dynamic coordination of metabolic systems. At a larger level, this project will help establish new paradigms in biochemistry teaching and learning, and significantly enhance the training of the next generation of STEM professionals.
The goals of this project are: (i) to develop dynamic, structural three-dimensional (3D) models and implement these into modules for biochemistry courses to improve understanding about the complex 3D structures critical to life; (ii) to develop computational models of metabolic networks and implement these into modules for biochemistry courses to improve understanding of biochemical systems concepts; and (iii) to determine the impact of the physical and computational modules on student learning of key learning objectives. The 3D models will be developed using the cost-accessible 3D printing technology and the computational models will be built on an open-source software platform called Cell Collective, developed by one of the project's co-PIs. This platform provides a unique interactive environment for students to explore the relationships and dynamics of complex systems in ways that are not available in other simulations, and resembling authentic science practice as articulated by Vision and Change. These modules and their associated materials will be made available on-line, and dissemination efforts, including a workshop, will help propagate their use at many institutions.
