Optimized Cohort Creation for Hybrid Online Design-learning During COVID-19

Sheng Lun (Christine) Cao; Laleh Behjat

Download Paper | Permalink

Conference: 2021 ASEE Virtual Annual Conference Content Access
Location: Virtual Conference
Publication Date: July 26, 2021
Start Date: July 26, 2021
End Date: July 19, 2022
Conference Session: Impact of COVID-19 on Design Education 2
Tagged Division: Design in Engineering Education
Page Count: 27
DOI: 10.18260/1-2--37548
Permanent URL: https://peer.asee.org/37548
Download Count: 551

Paper Authors

biography

Sheng Lun (Christine) Cao University of Calgary

visit author page

Sheng Lun (Christine) Cao is a second-year Master of science student with Dr. Laleh Behjat at the Schulich School of Engineering, University of Calgary. Her research combines engineering design education with techniques from Electronic Design Automation (EDA). Christine also works as a an engineering education research assistant for Dr. Elena Rangelova and Dr. Ivan Detchev.

visit author page

biography

Laleh Behjat P.Eng. University of Calgary

visit author page

Dr. Laleh Behjat is a Professor in the Department of Electrical and Computer Engineering at the University of Calgary. Her research interests include designing computer chips, electronic design automation and developing software for computer hardware. She has won several awards for her work on the development of software tools for computer engineering. In addition, Dr. Behjat has a passion for increasing the status of women in science, technology, engineering and mathematics (STEM). Dr. Behjat was the recipient of the 2015 Association of Professional Engineers and Geoscientists of Alberta (APEGA) Women in Engineering Champion Award. She currently serves as the NSERC Chair for Women in Science and Engineering in the Prairie Region of Canada.

visit author page

Download Paper | Permalink

Abstract

The unprecedented global pandemic, COVID-19, significantly disrupted the higher education sector, forcing both institutions and their educators to rethink modes of content delivery. As COVID-19 restrictions slowly lift, many institutions are operating a hybrid course delivery structure: online lectures and small groups of in-person, hands-on learning sessions. To limit the further spread of the virus during in-person components, a cohort learning model is proposed. The cohort model would better comply with the Center for Disease Control and Prevention’s reopening guideline [1], and limit viral spreading through the model’s small and static nature. Furthermore, cohort-based learning can promote a sense of community and facilitate identity-building in online spaces [2]. A similar cohort model was implemented as learning communities within a second-year integrated electrical engineering program, prior to COVID-19 [3]. The experimental course utilized the learning communities to great success, especially in promoting active learning during the engineering design module.

The goal of this study is to identify the optimal student cohort configuration for an engineering department. An anonymized dataset of 81 electrical engineering students’ Fall 2020 semester enrollment records, obtained from the university registrar, forms the student network. Two clustering algorithms, Best Choice [3] and Modified Hyperedge Coarsening [4] (techniques adapted from integrated circuit design and automation), are implemented to evaluate the dataset and create cohorts. The ideal cohort is no larger than ten students, to prevent instances of large gatherings of students. The resulting cohorts are evaluated based on cohort members’ number of possible interactions external to their cohort. The Best Choice algorithm yielded more uniform cohorts that are less connected with other clusters. Results showed the cohort model to be a viable method of grouping students to limit cross-cohort transmission.

The future of engineering design education will have to be more agile in order to embrace active learning. Using cohort-based learning enables creative modes of content delivery, extending beyond the traditional lectures-based teaching environments. Cohorts could create a sense of community learning as well as function as a basis for novel integrated and flipped teaching pedagogy. Future studies are necessary to examine these cohorts in a real-classroom setting.

Bibliography

[1] Center for Disease Control and Prevention, "Interim Guidance for Child Care Programs," 2020. [Online]. Available: http://cdn.cnn.com/cnn/2020/images/04/30/reopening.guidelines.pdf. [Accessed 5 October 2020]. [2] D. Conrad, "Building and Maintaining Community in Cohort-Based Online Learning," Journal of Distance Education, vol. 20, no. 1, pp. 1 - 20, 2005. [3] Redacted [4] C. Alpert, A. Kahng, G.-J. Nam, S. Reda and P. Villarrubia, "A semi-persistent clustering technique for VLSI circuit placement," in ISPD '05: Proceedings of the 2005 international symposium on physical design, 2005. [5] S. K. Lim, Practical Problems in VLSI Physical Design, Atlanta: Springer, 2008.

Citation
Format

Cao, S. L. C., & Behjat, L. (2021, July), Optimized Cohort Creation for Hybrid Online Design-learning During COVID-19 Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. 10.18260/1-2--37548

TY - CPAPER
AB - The unprecedented global pandemic, COVID-19, significantly disrupted the higher education sector, forcing both institutions and their educators to rethink modes of content delivery. As COVID-19 restrictions slowly lift, many institutions are operating a hybrid course delivery structure: online lectures and small groups of in-person, hands-on learning sessions. To limit the further spread of the virus during in-person components, a cohort learning model is proposed. The cohort model would better comply with the Center for Disease Control and Prevention’s reopening guideline [1], and limit viral spreading through the model’s small and static nature. Furthermore, cohort-based learning can promote a sense of community and facilitate identity-building in online spaces [2]. A similar cohort model was implemented as learning communities within a second-year integrated electrical engineering program, prior to COVID-19 [3]. The experimental course utilized the learning communities to great success, especially in promoting active learning during the engineering design module.

The goal of this study is to identify the optimal student cohort configuration for an engineering department. An anonymized dataset of 81 electrical engineering students’ Fall 2020 semester enrollment records, obtained from the university registrar, forms the student network. Two clustering algorithms, Best Choice [3] and Modified Hyperedge Coarsening [4] (techniques adapted from integrated circuit design and automation), are implemented to evaluate the dataset and create cohorts. The ideal cohort is no larger than ten students, to prevent instances of large gatherings of students. The resulting cohorts are evaluated based on cohort members’ number of possible interactions external to their cohort. The Best Choice algorithm yielded more uniform cohorts that are less connected with other clusters. Results showed the cohort model to be a viable method of grouping students to limit cross-cohort transmission.

The future of engineering design education will have to be more agile in order to embrace active learning. Using cohort-based learning enables creative modes of content delivery, extending beyond the traditional lectures-based teaching environments. Cohorts could create a sense of community learning as well as function as a basis for novel integrated and flipped teaching pedagogy. Future studies are necessary to examine these cohorts in a real-classroom setting.

Bibliography

[1] Center for Disease Control and Prevention, &quot;Interim Guidance for Child Care Programs,&quot; 2020. [Online]. Available: http://cdn.cnn.com/cnn/2020/images/04/30/reopening.guidelines.pdf. [Accessed 5 October 2020].
[2] D. Conrad, &quot;Building and Maintaining Community in Cohort-Based Online Learning,&quot; Journal of Distance Education, vol. 20, no. 1, pp. 1 - 20, 2005.
[3] Redacted
[4] C. Alpert, A. Kahng, G.-J. Nam, S. Reda and P. Villarrubia, &quot;A semi-persistent clustering technique for VLSI circuit placement,&quot; in ISPD &#39;05: Proceedings of the 2005 international symposium on physical design, 2005.
[5] S. K. Lim, Practical Problems in VLSI Physical Design, Atlanta: Springer, 2008.

AU - Sheng Lun (Christine) Cao
AU - Laleh Behjat P.Eng.
CY - Virtual Conference
DA - 2021/07/26
PB - ASEE Conferences
TI - Optimized Cohort Creation for Hybrid Online Design-learning During COVID-19
UR - https://peer.asee.org/37548
DO - 10.18260/1-2--37548
ER -