TY - JOUR
T1 - Computational curriculum for MatSE undergraduates
AU - Kononov, Alina
AU - Bellon, Pascal
AU - Bretl, Timothy
AU - Ferguson, Andrew L.
AU - Herman, Geoffrey L.
AU - Kilian, Kristopher Alan
AU - Krogstad, Jessica A.
AU - Leal, Cecilia
AU - Maass, Robert
AU - Schleife, Andre
AU - Shang, Jian Ku
AU - Trinkle, Dallas R.
AU - West, Matthew
N1 - Funding Information:
This material is based upon work supported by the National Science Foundation (Grant No. DMR-1554435) and by a National Science Foundation CAREER Award to A. L. F. (Grant No. DMR-1350008). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.
Funding Information:
Professor Kristopher Kilian received B.S. and M.S. degrees in Chemistry from the University of Washington in 1999 and 2003 respectively. He worked for Merck Research Labs in the Methods Development group from 2000-2004 before travelling to Sydney, Australia to do his PhD with Justin Gooding at the University of New South Wales. In 2007, he joined the laboratory of Milan Mrksich at the University of Chicago as a NIH postdoctoral fellow to investigate new methods for directing the differentiation of stem cells. Kris joined the faculty of the University of Illinois at Urbana-Champaign as Assistant Professor of Materials Science and Engineering in 2011. Kris is a 2008 recipient of the NIH Ruth L. Kirchstein National Research Service Award, and a 2015 recipient of the National Science Foundation’s CAREER award. His research interests include the design and development of model extracellular matrices for stem cell engineering and fundamental studies in cell biology.
Publisher Copyright:
© American Society for Engineering Education, 2017.
PY - 2017/6/24
Y1 - 2017/6/24
N2 - Computational materials modeling and design has emerged as a vital component of materials research and development in academic, industrial, and national lab settings. In response, US Materials Science and Engineering (MatSE) departments and the federal government recognize the need to incorporate computational training into undergraduate MatSE education. Our faculty team at the University of Illinois at Urbana-Champaign (UIUC) is addressing this growing need with a comprehensive computational component integrated into the MatSE curriculum. Throughout their coursework, undergraduates complete a series of computational modules of progressing complexity, each module modeling the principles taught in its containing course. Computational lectures accompany most modules and further illustrate how computational methods solve real-life science and engineering problems. The computational curriculum is supported by a dedicated teaching assistant who helps with module development, delivers computational lectures, and offers additional office hours. Now, three years since initial implementation, multiple student cohorts have experienced the computational curriculum at all course levels. In this paper, we present new results on the efficacy of the computational curriculum and share more information about our continued efforts to improve the computational modules, lectures, and their integration within the broader MatSE curriculum.
AB - Computational materials modeling and design has emerged as a vital component of materials research and development in academic, industrial, and national lab settings. In response, US Materials Science and Engineering (MatSE) departments and the federal government recognize the need to incorporate computational training into undergraduate MatSE education. Our faculty team at the University of Illinois at Urbana-Champaign (UIUC) is addressing this growing need with a comprehensive computational component integrated into the MatSE curriculum. Throughout their coursework, undergraduates complete a series of computational modules of progressing complexity, each module modeling the principles taught in its containing course. Computational lectures accompany most modules and further illustrate how computational methods solve real-life science and engineering problems. The computational curriculum is supported by a dedicated teaching assistant who helps with module development, delivers computational lectures, and offers additional office hours. Now, three years since initial implementation, multiple student cohorts have experienced the computational curriculum at all course levels. In this paper, we present new results on the efficacy of the computational curriculum and share more information about our continued efforts to improve the computational modules, lectures, and their integration within the broader MatSE curriculum.
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U2 - 10.18260/1-2--28060
DO - 10.18260/1-2--28060
M3 - Conference article
AN - SCOPUS:85030544210
SN - 2153-5965
VL - 2017-June
JO - ASEE Annual Conference and Exposition, Conference Proceedings
JF - ASEE Annual Conference and Exposition, Conference Proceedings
T2 - 124th ASEE Annual Conference and Exposition
Y2 - 25 June 2017 through 28 June 2017
ER -