Interdisciplinary Training in Neuroscience for Faculty and Undergraduates from 2- and 4-year Institutions

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This Improving Undergraduate STEM Education (IUSE) project from the University of Missouri - Columbia addresses the need for professional development for biological sciences faculty in the area of computational neuroscience. Computational neuroscience is an emerging area that studies brain function in terms of the information processing properties of the structures that make up the nervous system. It is an interdisciplinary science that links the diverse fields of neuroscience, cognitive science, and psychology with electrical engineering, computer science, mathematics, and physics. While leading biology educators call for strong interdisciplinary curricula that include physical science, information technology, and mathematics, many biological and behavioral scientists lack adequate training in the quantitative sciences, limiting their understanding and use of tools from this area. Similarly, engineers and quantitative scientists lack the training in biological sciences and neuroscience necessary to understand the details of the diverse systems in biology, and facilitate improved interactions with biologists to develop relevant and advanced computational tools.The PI team is building on the knowledge they have gained through their prior NSF-funded work in the development of a computational neuroscience course, as well as on their seven years of experience providing a professional development workshop entitled "Hardware and Software Experiments to Teach Undergraduate Neuroscience." The workshops offered through this project are enhancing the teaching expertise of faculty in neuroscience at both 2- and 4-year institutions. Faculty-student teams participate in one-week workshops that include instructional methodologies emphasizing computation via free software experiments. Bringing this expertise back to their home institutions, workshop participants are increasing the number and diversity of undergraduates studying computational neuroscience. In addition, an intensive two-week curriculum development course will be offered to four faculty-student teams. These rigorous workshops provide training in mathematics, software, teaching, and development of curricular modules in computational neuroscience and include a one-year long support program for faculty-student teams as they develop and implement software modules into their curriculum. In the course of the project, the PI team is also augmenting our knowledge of obstacles to the implementation of effective instructional practices by carrying out studies to identify barriers to student learning and to faculty professional development and implementation of effective teaching practices. Understanding these impediments will facilitate development of strategies to overcome them so that effective instructional practices can be more widely adopted in the nation's institution of higher education.