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WORK IN PROGRESS: Computational Modules for the MatSE Undergraduate Curriculum

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Collection

2016 ASEE Annual Conference & Exposition

Location

New Orleans, Louisiana

Publication Date

June 26, 2016

Start Date

June 26, 2016

End Date

August 28, 2016

ISBN

978-0-692-68565-5

ISSN

2153-5965

Conference Session

Computers in Education Division Poster Session

Tagged Division

Computers in Education

Tagged Topic

Diversity

Page Count

10

DOI

10.18260/p.27214

Permanent URL

https://peer.asee.org/27214

Download Count

32

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Paper Authors

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Rachael Alexandra Mansbach University of Illinois, Urbana-Champaign Orcid 16x16 orcid.org/0000-0002-6738-1261

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Rachael A Mansbach is a PhD candidate in physics at the University of Illinois, Urbana-Champaign. She received her BA in physics from Swarthmore College in 2007. Currently, she works as a graduate research assistant in the Ferguson Lab at UIUC, studying the aggregation of optoelectronic peptides using computational simulations. She is also the computational teaching assistant for the SIIP program in Materials Science and Engineering.

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Geoffrey L. Herman University of Illinois, Urbana-Champaign Orcid 16x16 orcid.org/0000-0002-9501-2295

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Dr. Geoffrey L. Herman is a visiting assistant professor with the Illinois Foundry for Innovation in Engineering Education at the University of Illinois at Urbana-Champaign and a research assistant professor with the Department of Curriculum & Instruction. He earned his Ph.D. in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign as a Mavis Future Faculty Fellow and conducted postdoctoral research with Ruth Streveler in the School of Engineering Education at Purdue University. His research interests include creating systems for sustainable improvement in engineering education, promoting intrinsic motivation in the classroom, conceptual change and development in engineering students, and change in faculty beliefs about teaching and learning. He serves as the webmaster for the ASEE Educational Research and Methods Division.

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Matthew West University of Illinois, Urbana-Champaign

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Matthew West is an Associate Professor in the Department of Mechanical Science and Engineering at the University of Illinois at Urbana-Champaign. Prior to joining Illinois he was on the faculties of the Department of Aeronautics and Astronautics at Stanford University and the Department of Mathematics at the University of California, Davis. Prof. West holds a Ph.D. in Control and Dynamical Systems from the California Institute of Technology and a B.Sc. in Pure and Applied Mathematics from the University of Western Australia. His research is in the field of scientific computing and numerical analysis, where he works on computational algorithms for simulating complex stochastic systems such as atmospheric aerosols and feedback control. Prof. West is the recipient of the NSF CAREER award and is a University of Illinois Distinguished Teacher-Scholar and College of Engineering Education Innovation Fellow.

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Dallas R. Trinkle University of Illinois, Urbana-Champaign

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Dallas R. Trinkle is an associate professor in Materials Science and Engineering at Univ. Illinois, Urbana-Champaign. He received his Ph.D. in Physics from Ohio State University in 2003. Following his time as a National Research Council postdoctoral researcher at the Air Force Research Laboratory, he joined the faculty of the Department of Materials Science and Engineering at Univ. Illinois, Urbana-Champaign in 2006. He was a TMS Young Leader International Scholar in 2008, received the NSF/CAREER award in 2009, the Xerox Award for Faculty Research at Illinois in 2011, the AIME Robert Lansing Hardy Award in 2014, co-chaired the 2011 Physical Metallurgy Gordon Research conference, and became a Willett Faculty Scholar at Illinois in 2015. His research focuses on defects in materials using density-functional theory, and novel techniques to understand problems in mechanical behavior and transport.

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Andrew Ferguson University of Illinois, Urbana-Champaign Orcid 16x16 orcid.org/0000-0002-8829-9726

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Andrew Ferguson is Assistant Professor of Materials Science and Engineering, and an Affiliated Assistant Professor of Chemical and Biomolecular Engineering, and Computational Science and Engineering at the University of Illinois at Urbana-Champaign. He received an M.Eng. in Chemical Engineering from Imperial College London in 2005, and a Ph.D. in Chemical and Biological Engineering from Princeton University in 2010. From 2010 to 2012 he was a Postdoctoral Fellow of the Ragon Institute of MGH, MIT, and Harvard in the Department of Chemical Engineering at MIT. He commenced his appointment at Illinois in August 2012. His research interests lie at the intersection of materials science, molecular simulation, and machine learning, with particular foci in the design of antiviral vaccines and self-assembling colloids and peptides. He is the recipient of a 2015 ACS OpenEye Outstanding Junior Faculty Award, a 2014 NSF CAREER Award, a 2014 ACS PRF Doctoral New Investigator, and was named the Institution of Chemical Engineers North America 2013 Young Chemical Engineer of the Year. - See more at: https://www.asee.org/public/person#sthash.rlsVDJOX.dpuf

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Andre Schleife University of Illinois, Urbana-Champaign

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André Schleife is a Blue Waters Assistant Professor in the Department of Materials Science and Engineering at the University of Illinois at Urbana-Champaign. He obtained his Diploma and Ph.D. at Friedrich-Schiller-University in Jena, Germany for his theoretical work on transparent conducting oxides. Before he started at UIUC he worked as a Postdoctoral Researcher at Lawrence Livermore National Laboratory on a project that aimed at a description of non-adiabatic electron ion dynamics. His research revolves around excited electronic states and their dynamics in various materials using accurate computational methods and making use of modern super computers in order to understand, for instance, how light is absorbed in photo-voltaic materials.

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Abstract

There is consensus among US Materials Science and Engineering departments (driven by discussions with government, academic, and national lab stakeholders) that undergraduates require a deeper understanding of computational tools. The 2011 White House Materials Genome Initiative to accelerate the development of new materials asserts that computer-aided materials design--and training of the next generation workforce in computer-aided design--is vital to national competitiveness and welfare. Skills in computational materials modeling and design are desirable to employers hiring our graduates into industrial R&D and product development positions (e.g., Ford Motor Company, Boeing, John Deere), national labs, and academic research positions. To address these growing needs, our faculty team has developed and deployed a series of computational modules throughout the introductory coursework for our Materials Science and Engineering curriculum.

These modules have been delivered through context-rich collaborative solving sessions in a number of courses. During these sessions students work in teams to complete a worksheet that contains a single, longer disciplinary problem that ties to that week's topic. These worksheets are pulled from real world examples to showcase more in-depth applications of the material and engage students in problem solving and teamwork. Students follow up team worksheets with a individual weekly report. These worksheets and reports require students to use computational tools to help them perceive the usefulness and relevance of these tools for the coursework. Additional office hours are offered with a computational teaching assistant (who is trained to work with a few different classes using the computational modules in class) to support students using these computational tools. Our current enrollment is 110-120 students per class, and we offer three recitation sections capped at 40 students each.

This work has been championed by faculty working within a Community of Practice, implementing curricular changes collaboratively to improve the sustainability of the effort. The implementation of these computational modules has expanded to increase the number of courses using modules and the number of faculty developing and delivering them. In this paper, we will share more details about the modules and present results on the effectiveness of the Community of Practice model for implementing curricular changes in a sustainable manner.

ASEE holds the copyright on this document. It may be read by the public free of charge. Authors may archive their work on personal websites or in institutional repositories with the following citation: © 2016 American Society for Engineering Education. Other scholars may excerpt or quote from these materials with the same citation. When excerpting or quoting from Conference Proceedings, authors should, in addition to noting the ASEE copyright, list all the original authors and their institutions and name the host city of the conference. - Last updated April 1, 2015