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Student Perceptions of the Complete Online Transition of Two CS Courses in Response to the COVID-19 Pandemic

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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

Studies of Shifting In-person Courses to Online and Students' Online Behavior

Tagged Division

Educational Research and Methods

Page Count

17

Permanent URL

https://peer.asee.org/37755

Download Count

74

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Paper Authors

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Mohammed F. Farghally Virginia Polytechnic Institute and State University

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Mohammed F. Farghally received his PhD from Virginia Tech in 2016. He recently joined the computer science department at Virginia Tech as a visiting assistant professor. Starting in Fall 2021, Dr. Farghally will join the computer science department at Virginia Tech as a collegiate assistant professor. Dr. Farghally's background includes extensive teaching experience and significant contributions to the computer science education research. Dr. Farghally's work is mainly directed towards developing innovative technologies to help students better understand abstract CS concepts. Furthermore, Dr. Farghally is interested in analyzing students interactions with online eTextbook material to better understand students' learning behaviors.

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Mostafa Kamel Osman Mohammed Virginia Polytechnic Institute and State University; Assiut University Orcid 16x16 orcid.org/0000-0002-0652-2817

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Mostafa Mohammed is a PhD candidate at Virginia Tech. He is planning to defend his dissertation on June 2021, Mostafa’s background includes extensive teaching experience and significant contributions to the computer science education research. Mostafa’s work is mainly directed towards developing eTextbooks with different teaching technologies to help students better understand abstract CS concepts. His PhD is about Teaching Formal Languages through Visualizations, MachineSimulations, Auto-Graded Exercises, and Programmed Instruction.

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Hamdy F. F. Mahmoud Virginia Polytechnic Institute and State University; Assiut University Orcid 16x16 orcid.org/0000-0001-8378-2965

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Hamdy F. F. Mahmoud is a collegiate assistant professor in the Department of Statistics at Virginia Tech, and he has held an assistant professor position at Assiut University in Egypt. He earned master's and doctoral degrees in statistics from Virginia Tech. Mahmoud’s research interest mainly focuses on developing statistical models, especially in semi and nonparametric statistics and regression, and applying different types of data, such as but not limited to teaching, epidemiology, spatial, spatially-temporally, and environmental data.

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Margaret O'Neil Ellis Virginia Polytechnic Institute and State University

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Associate Professor of Practice, Computer Science Department, Virginia Tech

My research interests include examining ways to improve engineering educational environments to facilitate student success, especially among underrepresented groups.

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Derek A. Haqq Virginia Polytechnic Institute and State University

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Derek Haqq received his MSc in Computer Science from The University of The West Indies in 2009. He is currently a PhD student at Virginia Tech. Research Interests include Technology in Teaching and Learning, Technologies to support Relational Maintenance, Technology-Mediated Recreation, and Technology on the Trail.

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Molly Rebecca Domino Virginia Polytechnic Institute and State University

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Currently a second year Ph.D candidate at Virginia Tech

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Brett D. Jones Virginia Polytechnic Institute and State University

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Brett D. Jones is a full Professor of Educational Psychology in the School of Education at Virginia Tech (www.theMUSICmodel.com). He has held faculty positions as an educational psychologist at Duke University, the University of South Florida St. Petersburg, and Virginia Tech. He has taught 24 different types of university courses related to motivation, cognition, and teaching strategies. Dr. Jones has also conducted workshops and invited presentations at many universities and has presented about 130 research papers at conferences. His research, which includes examining instructional methods that support students’ motivation and learning, has led to more than 100 refereed journal articles, several book chapters, and three books. He has received three grants from the National Science Foundation for a total of over $2 million to conduct his research.

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Clifford A. Shaffer Virginia Polytechnic Institute and State University

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Dr. Shaffer received his PhD in Computer Science from University of Maryland, College Park in 1986. He is currently Professor of Computer Science at Virginia Tech, where he has been since 1987. He directs the OpenDSA project, whose goals include developing a complete online collection of interactive tutorials for data structures and algorithms courses. His research interests are in Digital Education, Algorithm Visualization, Algorithm Design and Analysis, and Data Structures.

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Abstract

Student perceptions of the complete online transition of two CS courses in response to the COVID-19 pandemic

Due to the COVID-19 pandemic, universities across the globe switched from traditional Face-to-Face (F2F) course delivery to completely online. Our university declared during our Spring break that students would not return to campus, and that all courses must be delivered fully online starting two weeks later. This was challenging to both students and instructors.

In this evidence-based practice paper, we present results of end-of-semester student surveys from two Spring 2020 CS courses: a programming intensive CS2 course, and a senior theory course in Formal Languages and Automata (FLA). Students indicated course components they perceived as most beneficial to their learning, before and then after the online transition, and preferences for each regarding online vs. F2F. By comparing student reactions across courses, we gain insights on which components are easily adapted to online delivery, and which require further innovation. COVID was unfortunate, but gave a rare opportunity to compare students’ reflections on F2F instruction with online instructional materials for half a semester vs. entirely online delivery of the same course during the second half. The circumstances are unique, but we were able to acquire insights for future instruction. Some course components were perceived to be more useful either before or after the transition, and preferences were not the same in the two courses, possibly due to differences in the courses. Students in both courses found prerecorded asynchronous lectures significantly less useful than in-person lectures. For CS2, online office hours were significantly less useful than in-person office hours, but we found no significant difference in FLA. CS2 students felt less supported by their instructor after the online transition, but no significant difference was indicated by FLA students. FLA students found unproctored online exams offered through Canvas more stressful than in-person proctored exams, but the opposite was indicated by CS2 students. CS2 students indicated that visual materials from an eTextbook were more useful to them after going online than before, but FLA students indicated no significant difference.

Overall, students in FLA significantly preferred the traditional F2F version of the course, while no significant difference was detected for CS2 students. We did not find significant effects from gender on the preference of one mode over the other.

A serendipitous outcome was learning that some changes forced by circumstance should be considered for long term adoption. Offering online lab sessions and online exams where the questions are primarily multiple choice are possible candidates. However, we found that students need to feel the presence of their instructor to feel properly supported.

To determine what course components need further improvement before transitioning to fully online mode, we computed a logistic regression model. The dependent variable is the student's preference for F2F or fully online. The independent variables are the course components before and after the online transition. For both courses, in-person lectures were a significant factor negatively affecting students' preferences of the fully online mode. Similarly, for CS2, in-person labs and in-person office hours were significant factors pushing students’ preferences toward F2F mode.

Farghally, M. F., & Mohammed, M. K. O., & Mahmoud, H. F. F., & Ellis, M. O., & Haqq, D. A., & Domino, M. R., & Jones, B. D., & Shaffer, C. A. (2021, July), Student Perceptions of the Complete Online Transition of Two CS Courses in Response to the COVID-19 Pandemic Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. https://peer.asee.org/37755

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