Integrating Model-Based Approaches Into a Neuroscience Curriculum—An Interdisciplinary Neuroscience Course in Engineering
Year: 2018
Type: article
Abstract: Contribution: This paper demonstrates curricular modules that incorporate engineering model-based approaches, including concepts related to circuits, systems, modeling, electrophysiology, programming, and software tutorials that enhance learning in undergraduate neuroscience courses. These modules can also be integrated into other neuroscience courses. Background: Educators in biological and physical sciences urge incorporation of computation and engineering approaches into biology. Model-based approaches can provide insights into neural function; prior studies show these are increasingly being used in research in biology. Reports about their integration in undergraduate neuroscience curricula, however, are scarce. There is also a lack of suitable courses to satisfy engineering students' interest in the challenges in the growing area of neural sciences. Intended Outcomes: (1) Improved student learning in interdisciplinary neuroscience; (2) enhanced teaching by neuroscience faculty; (3) research preparation of undergraduates; and 4) increased interdisciplinary interactions. Application Design: An interdisciplinary undergraduate neuroscience course that incorporates computation and model-based approaches and has both software- and wet-lab components, was designed and co-taught by colleges of engineering and arts and science. Findings: Model-based content improved learning in neuroscience for three distinct groups: 1) undergraduates; 2) Ph.D. students; and 3) post-doctoral researchers and faculty. Moreover, the importance of the content and the utility of the software in enhancing student learning was rated highly by all these groups, suggesting a critical role for engineering in shaping the neuroscience curriculum. The model for cross-training also helped facilitate interdisciplinary research collaborations.
Source: IEEE Transactions on Education
Institution: University of Missouri
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
SDG: Quality education
Open Access status: green
Awards: REU Site: Summer Research Projects in Neuroscience, INTEGRATING MODELING AND LABORATORY SESSIONS IN NEUROSCIENCE, Interdisciplinary Training in Computational Neuroscience for Researchers from Graduate and Medical Students to Junior Faculty, CRCNS: Modeling Acquisition and Extinction of Fear Memories in Amygdala Circuits, Interdisciplinary Training in Neuroscience for Faculty and Undergraduates from 2- and 4-year Institutions, G7727099618, REU Site: Summer Research Projects in Neuroscience
OpenAlex ID: W2911733318