A computational approach has become an indispensable tool in materials science research and related industry. At the University of Illinois, Urbana-Champaign, our team at the Department of Materials Science and Engineering (MSE), as part of a Strategic Instructional Initiatives Program (SIIP), has integrated computation into multiple MSE undergraduate courses over the last years. This has established a stable environment for computational education in MSE undergraduate courses through the duration of the program. To date, all MSE students are expected to have multiple experiences of solving practical problems using computational modules before graduation. In addition, computer-based techniques have been integrated into course instruction through iClicker, lecture recording, and online homework and testing. In this paper, we seek to identify the impact of these changes beyond courses participating in the original SIIP project. We continue to keep track of students’ perception of the computational curriculum within participating courses. Furthermore, we investigate the influence of the computational exposure on students’ perspective in research and during job search. Finally, we collect and analyze feedback from department faculty regarding their experience with teaching techniques involving computation.
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Computational Curriculum for MatSE Undergraduates and the Influence on Senior Classes
Computational materials modeling has been emerging as a very important aspect in materials science research. At the University of Illinois, Urbana-Champaign, our faculty team at the Department of Materials Science and Engineering, as part of the Strategic Instructional Initiatives Program (SIIP) of the university, have integrated comprehensive computational modules into multiple MatSE undergraduate courses and have created a collaborative teaching environment to improve these modules iteratively. Each year, a dedicated teaching assistant has been involved to communicate between faculty members, to ensure the quality of the computational modules, and to offer additional office hours. After three years of effort, we have now established a stable and systematic environment for computational education in MatSE undergraduate courses. The students initially involved in the program are now approaching their senior years. Thus we now investigate the influence of the computational experience in the SIIP classes on the performance of the students in the senior classes. In this paper, we present the recent progress of our computational curriculum and we focus on the influence of the program on the performance of students in senior computational modelling classes and senior classes with computational modules.
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- Award ID(s):
- 1654182
- NSF-PAR ID:
- 10093478
- Date Published:
- Journal Name:
- ASEE Annual Conference proceedings
- ISSN:
- 1524-4644
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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A computational approach has become an indispensable tool in materials science research and related industry. At the University of Illinois, Urbana-Champaign, our team at the Department of Materials Science and Engineering (MSE), as part of a Strategic Instructional Initiatives Program (SIIP), has integrated computation into multiple MSE undergraduate courses over the last years. This has established a stable environment for computational education in MSE undergraduate courses through the duration of the program. To date, all MSE students are expected to have multiple experiences of solving practical problems using computational modules before graduation. In addition, computer-based techniques have been integrated into course instruction through iClicker, lecture recording, and online homework and testing. In this paper, we seek to identify the impact of these changes beyond courses participating in the original SIIP project. We continue to keep track of students' perception of the computational curriculum within participating courses. Furthermore, we investigate the influence of the computational exposure on students' perspective in research and during job search. Finally, we collect and analyze feedback from department faculty regarding their experience with teaching techniques involving computation.more » « less
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