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Impact of Transitions between Online and Offline Learning During COVID-19 on Computational Curricular Reform: Student Perspective

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Conference

2022 ASEE Annual Conference & Exposition

Location

Minneapolis, MN

Publication Date

August 23, 2022

Start Date

June 26, 2022

End Date

June 29, 2022

Conference Session

Materials Division Technical Session 3

Page Count

21

DOI

10.18260/1-2--41676

Permanent URL

https://sftp.asee.org/41676

Download Count

235

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Paper Authors

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Yang Dan University of Illinois at Urbana - Champaign

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Yang Dan is a Ph.D. candidate and research assistant of the Department of Materials Science and Engineering, University of Illinois at Urbana-Champaign. He is the computational teaching assistant of the department for academic year 2021-2022, and participated in the teaching activities, surveys and researches regarding computations in several undergraduate courses. Yang holds a Bachelor of Science degree in physics from Peking University, P. R. China, with research interest in computational and theoretical condensed matter and materials physics. Working under the supervision of Prof. Dallas R. Trinkle, Yang is currently doing research on modeling defects in materials, alloys and magnetism in materials using first-principles tools.

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Andre Schleife

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André Schleife is a Blue Waters Associate Professor of Materials Science and Engineering and his degrees in physics are from the Friedrich-Schiller University in Jena, Germany (Diploma, 2006; Ph.D. 2010). He was a Directorate Postdoctoral Researcher at Lawrence Livermore National Laboratory (2011–2013). At UIUC, which he joined in 2013, he received the NSF CAREER award, the ONR YIP award, and was an ACS PRF Doctoral New Investigator before being promoted to Associate Professor in 2020.
Research in André’s group revolves around excited electronic states, optical properties, and real-time dynamics arising from coupling to phonons and magnons. He uses and implements accurate quantum-mechanical first-principles methods within many-body perturbation and time-dependent density functional theory on high-performance super computers.
André is an editor for a journal and engages in the APS National Mentoring Community and the U.S.-Africa Initiative. At UIUC he is part of the Diversity and Inclusion committee. He actively organizes national and international activities and workshops, and tutorials, focus topics, and invited symposia to advance and connect our community. He enjoys time outdoors as a private pilot and is passionate about cutting-edge data visualization using raytracing and virtual reality.

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Dallas Trinkle University of Illinois at Urbana - Champaign

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Ivan Racheff Professor and Associate Head of Materials Science and Engineering at Univ. Illinois, Urbana-Champaign

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Pinshane Huang University of Illinois at Urbana - Champaign

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Cecilia Leal

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Abstract

Computational methods have gained importance and popularity in both academia and industry for materials research and development in recent years. Since 2014, our team at University of Illinois at Urbana-Champaign has consistently worked on reforming our Materials Science and Engineering curriculum by incorporating computational modules into all mandatory undergraduate courses. The outbreak of the COVID-19 pandemic disrupted education as on-campus resources and activities became highly restricted. Here we seek to investigate the impact of the university moving online in Spring 2020 and resuming in-person instructions in Fall 2021 on the effectiveness of our computational curricular reform from the students' perspective. We track and compare feedback from students in a representative course MSE 182 for their computational learning experience before, during and after the pandemic lockdown from 2019 to 2021. Besides, we survey all undergraduate students, for their online learning experiences during the pandemic. We find that online learning enhances the students' belief in the importance and benefits of computation in materials science and engineering, while making them less comfortable and confident to acquire skills that are relatively difficult. In addition, early computational learners are likely to experience more difficulties with online learning compared to students at late stages of their undergraduate education, regardless of the computational workload. Multiple reasons are found to limit the students' online computational learning, such as insufficient support from instructors and TAs, limited chances of peer communication and harder access to computational resources. Therefore, it is advised to guarantee more resources to students with novice computational skills regarding such limiting reasons in the future when online learning is applied.

Dan, Y., & Schleife, A., & Trinkle, D., & Huang, P., & Leal, C. (2022, August), Impact of Transitions between Online and Offline Learning During COVID-19 on Computational Curricular Reform: Student Perspective Paper presented at 2022 ASEE Annual Conference & Exposition, Minneapolis, MN. 10.18260/1-2--41676

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