abstract

The Online Transition of Two CS Courses in Response to COVID-19

Authors:

Mohammed F. Farghally,

Clifford A. ShafferAuthors Info & Claims

SIGCSE '21: Proceedings of the 52nd ACM Technical Symposium on Computer Science Education

Page 1251

https://doi.org/10.1145/3408877.3439571

Published: 05 March 2021 Publication History

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Abstract

COVID-19 caused universities to switch from traditional face-to-face (F2F) course delivery to completely online in Spring 2020. This transition took place on short notice in the middle of the semester. We present results from surveys of students in two CS courses offered at Virginia Tech. Results indicate differing perceptions in the two courses regarding the usefulness of course components before and after the transition for each course. A logistic regression model indicates that for each course, different course components both before and after the transition significantly affect students' preferences for course modality.

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B. Means, Y. Toyama, R. Murphy, M. Baki, et al. The effectiveness of online and blended learning: A meta-analysis of the empirical literature. Teachers College Record, 115(3):1--47, 2013.

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T. Nguyen. The effectiveness of online learning: Beyond no significant difference and future horizons. MERLOT J. Online Learning & Teaching, 11(2):309--319, 2015.

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Cited By

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Latulipe CDe Jaeger AMerkle LDoyle MSheard JSoh LDorn B(2022)Comparing Student Experiences of Collaborative Learning in Synchronous CS1 Classes in Gather.Town vs. ZoomProceedings of the 53rd ACM Technical Symposium on Computer Science Education - Volume 110.1145/3478431.3499383(411-417)Online publication date: 22-Feb-2022
https://dl.acm.org/doi/10.1145/3478431.3499383
Maier MCzibula GOneţ-Marian Z(2021)Towards Using Unsupervised Learning for Comparing Traditional and Synchronous Online Learning in Assessing Students’ Academic PerformanceMathematics10.3390/math92228709:22(2870)Online publication date: 11-Nov-2021
https://doi.org/10.3390/math9222870

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The Online Transition of Two CS Courses in Response to COVID-19

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Published In

SIGCSE '21: Proceedings of the 52nd ACM Technical Symposium on Computer Science Education

March 2021

1454 pages

ISBN:9781450380621

DOI:10.1145/3408877

General Chairs:
Mark Sherriff
University of Virginia, USA
,
Laurence D. Merkle
Air Force Institute of Technology, USA
,
Program Chairs:
Pamela Cutter
Kalamazoo College, USA
,
Alvaro Monge
California State University, Long Beach, USA
,
Judithe Sheard
Monash University, Australia

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 05 March 2021

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SIGCSE '21

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SIGCSE

SIGCSE '21: The 52nd ACM Technical Symposium on Computer Science Education

March 13 - 20, 2021

Virtual Event, USA

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Overall Acceptance Rate 1,595 of 4,542 submissions, 35%

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SIGCSE Virtual 2024

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1st ACM Virtual Global Computing Education Conference

December 5 - 8, 2024

Virtual Event , NC , USA

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Cited By

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Latulipe CDe Jaeger AMerkle LDoyle MSheard JSoh LDorn B(2022)Comparing Student Experiences of Collaborative Learning in Synchronous CS1 Classes in Gather.Town vs. ZoomProceedings of the 53rd ACM Technical Symposium on Computer Science Education - Volume 110.1145/3478431.3499383(411-417)Online publication date: 22-Feb-2022
https://dl.acm.org/doi/10.1145/3478431.3499383
Maier MCzibula GOneţ-Marian Z(2021)Towards Using Unsupervised Learning for Comparing Traditional and Synchronous Online Learning in Assessing Students’ Academic PerformanceMathematics10.3390/math92228709:22(2870)Online publication date: 11-Nov-2021
https://doi.org/10.3390/math9222870

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