Teaching Computation in Neuroscience: Notes on the 2019 Society for Neuroscience Professional Development Workshop on Teaching
The Journal of Undergraduate Neuroscience Education (JUNE)
The 2019 Society for Neuroscience Professional 1Development Workshop on Teaching reviewed current tools, approaches, and examples for teaching computation in neuroscience. Robert Kass described the statistical foundations that students need to properly analyze data. Pascal Wallisch compared MATLAB and Python as programming languages for teaching students. Adrienne Fairhall discussed computational methods, training opportunities, and curricular considerations. Walt Babiec provided a view from the trenches on practical aspects of teaching computational neuroscience. Mathew Abrams concluded the session with an overview of resources for teaching and learning computational modeling in neuroscience.
Society for Neuroscience, teaching workshop, professional development, computational neuroscience, coding, programming, MATLAB, Python, modeling
© 2021 Faculty for Undergraduate Neuroscience
Grisham, William; Abrams, Mathew; Babiec, Walt E.; Fairhall, Adriene L.; Kass, Robert E.; Wallisch, Pascal; and Olivo, Richard F., "Teaching Computation in Neuroscience: Notes on the 2019 Society for Neuroscience Professional Development Workshop on Teaching" (2021). Biological Sciences: Faculty Publications, Smith College, Northampton, MA.
Archived as published. Open access article.