Session 13 – Part 2: Devin W. Silvia (USA)

Devin W. Silvia (USA)

Evaluating media claims about sustainability through the use of large data sets – Vince Geiger (Australia)

One of the core missions of Michigan State University’s Department of Computational Mathematics, Science and Engineering (CMSE) is to provide education in computational modeling and data science to MSU’s undergraduate and graduate students. In this presentation, I will describe our creation of CMSE 201, “Introduction to Computational Modeling and Data Analysis,” which is intended to be a standalone course teaching undergraduate students (both STEM and non-STEM) core concepts in data analysis, data visualization, and computational modeling. I will discuss the rationale behind the “flipped classroom” instructional model that we have been using and explain the course’s design principles and implementation. The concepts and skills students learn in this course can be used by other disciplines as the foundation for integrating computing across the curricula in undergraduate degree programs. 

Devin is the Director of Undergraduate Studies and a teaching specialist in the Department of Computational Mathematics, Science and Engineering at Michigan State University (MSU). He received his PhD in Astrophysical and Planetary Sciences from the University of Colorado where he worked as a computational astrophysicist running simulations aimed at understanding various facets of chemical evolution in the universe. He then worked as a National Science Foundation Astronomy and Astrophysics postdoctoral fellow at MSU before joining the ranks of the CMSE faculty in 2017. Most recently, Devin has been pursuing computing education research in an effort to better understand how students learn to do computational and data science and help inform pedagogical approaches in these disciplines. As part of this effort, Devin co-leads the Computing Education Research Lab at MSU.

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