A paradigm shift has occurred in research in the natural and social sciences, but this change has not reached the classroom in a systematic way. Computational modeling has transformed the way science is done and is now a full partner to experimentation and theory in most disciplines. Despite its importance, students in the sciences do not know the basics of modeling, make fundamental errors in application, and are ill-prepared to solve complex, cross-disciplinary problems using modeling as a tool. Oberlin College proposes to change this and is well positioned to do so. By introducing dynamic systems modeling into introductory courses in 11 science disciplines, the College will expose the majority of its eventual science majors to these powerful techniques at least twice in their first two years of study. When coupled with follow-up efforts at the intermediate and advanced level, the College will transform the way that most science students view complex problem solving. Oberlin will be aided in this effort by faculty and graduate students from the Center for the Study of Complex Systems at the University of Michigan, building on a vibrant relationship between the institutions. Established connections with two nationally recognized modeling experts will help to anchor the effort and give it external perspective. More than a dozen Oberlin faculty have been active in this area in recent years, and they will be among the initial cohort through which this systemic change will be accomplished. The group of faculty engaged in computational modeling will expand through the wide range of grant activities. By using dynamic systems modeling, the College will achieve its five goals for this project: integrating computational thinking into the science curriculum; developing a cohort of faculty experienced in teaching and using modeling techniques; developing a new tool for teaching computational modeling; providing cross-disciplinary teaching and curriculum development opportunities for graduate students and a postdoctoral researcher; and assessing, revising, and disseminating the most successful components.
As the undergraduate institution that leads the nation in students who go on to get Ph.Ds, Oberlin?s project in modeling pedagogy will have a powerful multiplier effect as its graduates enter academia and other high-impact careers, carrying the new modeling paradigm with them. This cohort of young scientists will have an important effect since computational thinking is the key to complex problem solving in such diverse fields as public health, economics, climate change, and biotechnology. Students who have worked with models throughout their science education will be well equipped to tackle both societal and cutting edge scientific problems. This project will also produce a key piece of publicly available software for use in modeling pedagogy and research. Other products will include pedagogical modeling units across the 11 disciplines involved in this effort, and these will be disseminated through standard channel
