This project aims to serve the national interest in excellent undergraduate STEM education by improving students' training in modeling and quantitative skills. Workforce sectors from advertising to life science research are drowning in data and lack employees with the critical thinking and technical skills to manage, process, analyze, and interpret it. Vision and Change in Undergraduate Biology Education, calls for an increase in technical and systems biology training, reflecting the shift in life science research to incorporate mathematics and computer science. Traditional methods are inadequate for teaching complex subject matter. Thus, it is increasingly important for life sciences education to evolve to equip students with skills to reason mechanistically and quantitatively, and to answer emerging life science questions. The long-term goal of this project is to transform the way biology students learn about complex living systems by enabling them to use computational modeling, both to acquire and to apply scientific knowledge. The project will build on successes from previous NSF-funded efforts that resulted in a new simulation- and modeling-based approach to learning about complex biological processes. This effort is facilitated through Cell Collective software that makes computational modeling accessible to any student and instructor, regardless of setting or prior modeling experience. This project will extend previous work involving Cell Collective by focusing on training and engaging instructors in its use with undergraduate students.
The project will develop a framework for understanding the barriers and impact of instructors deploying computational modeling and simulation lessons via Cell Collective to students across institutions with demographically diverse student populations. Teaching and learning challenges will be simultaneously addressed and minimized through new user-centric features in the Cell Collective software. Examples of features already identified include accessibility of the technology and streamlined access for students to modeling and simulation lessons across different life science courses. Furthermore, this project will provide professional development for 50-80 instructors about how to overcome challenges to integrating computational modeling and how to implement these tools in the classroom. It is expected that instructors who participate in the project will be better prepared to support the shift toward more quantitative and systems-level education in life sciences. It is also expected that the broad adoption of Cell Collective for teaching undergraduate life science topic will, over time, help to transform biology instruction so that it better prepares students to enter the modern data-driven workforce. The project thus has the potential to support United States innovation and economic growth. Resources developed in the project will be made available to researchers and instructors interested in incorporating computational modeling into their own learning technologies and methodologies. This project is supported by the NSF Improving Undergraduate STEM Education Program: Education and Human Resources, which supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
