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Best Practices and Lessons Learned on Organizing Effective Cohort-based Undergraduate Summer Research during COVID-19

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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

CIT Division Technical Session #7

Page Count

13

DOI

10.18260/1-2--41712

Permanent URL

https://peer.asee.org/41712

Download Count

481

Paper Authors

biography

Daqing Hou

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professor of software engineering at Clarkson University

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biography

Yu Liu Clarkson University

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Dr. Yu Liu is an Assistant Professor in the Department of Electrical and Computer Engineering at Clarkson University. Prior to joining Clarkson University, he was a research scientist at the Canadian Nuclear Laboratories (CNL) from 2013 through 2017. In addition, he was employed at Motorola as a senior software engineer from 2003 through 2007, and IBM from 2011 through 2013. He received his B.S. and M.S. degrees from Sichuan University in 2000 and 2003, respectively, and his Ph.D. degree from Southern Illinois University Carbondale in 2011. His research interests include high-performance computing, computer architectures, real-time systems, and wireless sensor networks. He has published over 30 peer-reviewed research papers.

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Abstract

This paper summarizes the best practices and lessons learned from organizing an effective remote REU Site during COVID-19. Our REU Site is a three-year program that is designed to offer closely-mentored summer research experience to a cohort of ten students in each of the three years. COVID-19 has disrupted our site by forcing us to split our second cohort to two groups, two students in summer 2020 and seven students in summer 2021. However, the experience that we gained in summer 2020 by mentoring the two students virtually online has provided us with the confidence that a virtual REU Site with a larger group can be as effective as in person and on campus. To further improve the quality of our REU Site in the on-line mode, we have applied multiple novel practices. Specifically, before the start of the 2021 REU site we as the site co-directors proactively worked with mentors to better understand the needs of the defined research projects. Subsequently, we tailored the topics covered by the crash course of our site to the needs of the research projects as well as purposefully increasing active learning activities and student interactions. In lieu of the previous in-person bond building activity (a two-day high rope course in a nearby camp), we added virtual scavenger image hunt in orientation and game nights every Wednesday. During the ten weeks, we also organized a half-hour daily check-in and check-out in the morning and afternoon respectively, through which students got ample opportunities to speak in a group setting about their own accomplishments and challenges for the day as well as their plans for the next day. Moreover, a PhD pathways panel and several professional development seminars on Graduate School and the research process were successfully organized to motivate students to pursue a research career. To facilitate communication, our site adopted multiple software tools (slack, google calendar, zoom, and moodle). An independent evaluator evaluated our program through online pre- and post-program surveys for both students and mentors as well as a focus group discussion with students. The evaluation report indicates significant improvement from the summer 2021 site regarding student satisfaction compared to the previous summer 2019 on-site program. Detailed quantitative analysis and lessons learned from the report will be presented in this paper to offer valuable experience and best practices for organizing effective cohort-based undergraduate research programs.

Hou, D., & Liu, Y. (2022, August), Best Practices and Lessons Learned on Organizing Effective Cohort-based Undergraduate Summer Research during COVID-19 Paper presented at 2022 ASEE Annual Conference & Exposition, Minneapolis, MN. 10.18260/1-2--41712

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