Analysis of the COVID-19 Impact on Students’ Enrollment, Performance, and Retention

Elena Filatova; Yu-Wen Chen; Hong Li

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Conference: 2023 ASEE Annual Conference & Exposition
Location: Baltimore , Maryland
Publication Date: June 25, 2023
Start Date: June 25, 2023
End Date: June 28, 2023
Conference Session: Computing and Information Technology Division (CIT) Technical Session 8
Tagged Division: Computing and Information Technology Division (CIT)
Tagged Topic: Diversity
Page Count: 15
DOI: 10.18260/1-2--42660
Permanent URL: https://peer.asee.org/42660
Download Count: 184

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Paper Authors

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Elena Filatova CUNY, New York City College of Technology

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Associate Professor at CUNY, New York City College of Technology, Department of Computer Systems Technology

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Yu-Wen Chen New York City College of Technology

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Dr. Yu-Wen Chen is an Assistant Professor in the Computer Systems Technology Department at New York City College of Technology. Dr. Chen received her Ph.D. degree in Computer Engineering from Iowa State University and an M.S. degree in Electrical Engineering from Columbia University. Dr. Chen's interdisciplinary research background includes cloud-based energy management, large-scale optimization, demand response, electric vehicle charging scheduling, mobile communication, fairness, and peer-to-peer networking. Her research interests span a range of topics in data analysis, cybersecurity, smart grid, cloud computing, optimization, communication networking, and the Internet of Things. She teaches a variety of courses related to security and digital forensics.

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Hong Li New York City College of Technology

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Hong Li is a Professor at the Computer Systems Technology Department of the New York City College of Technology, CUNY. She received her Ph.D. in Mathematics.

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Abstract

The COVID-19 pandemic brought a significant impact on society and the academic field. Many colleges and universities faced an enrollment drop during the pandemic years from the Spring of 2020. According to the Research Center's Stay Informed report series, institutions have had a total two-year enrollment drop of 4.2 percent since 2020. The Computer Systems Technology (CST) Department at New York City College of Technology (City Tech) of the City University of New York (CUNY) experienced a similar drop. At the same time, in the Spring 2020, most universities and colleges moved their teaching online. The decrease in enrollment numbers and shift to online teaching, combined with multiple reports of cheating in the wake of COVID-19, present an interesting case for studying the students' performance at different phases of COVID-19. The City Tech is a Hispanic Serving Institution (HSI), and many of our students come from low-income households and underrepresented communities which were dramatically affected by the pandemic. For the CST Department, the portions of students with economic disadvantages from the total enrolled numbers are around 72.5% in Fall 2019 and around 64% in Fall 2020. This project investigates how the changes in the learning environment (i.e., in-person to virtual and virtual to in-person) affected different student groups at City Tech at various phases of the pandemic. Our work concentrates on the students who take courses in the CST department. The analysis is performed by aggregating multiple institutional and departmental data sets from Spring 2019 to Spring 2022. The student's performance is examined for the sequence of the first three programming courses at the CST Department. It is analyzed along several dimensions, including major, gender, ethnicity, etc., throughout the different phases of the COVID-19 pandemic. This project investigates the performance of the students who take the CST courses as mandatory courses for the three CST majors as well as the performance of the students (non-CST majors) who take the CST courses as a general education computing requirement. The presented findings show the trends in courses enrollment, passing, failing, and withdrawing from the courses. In addition to a core three-course sequence, the project examines the general department retention numbers.

Citation
Format

Filatova, E., & Chen, Y., & Li, H. (2023, June), Analysis of the COVID-19 Impact on Students’ Enrollment, Performance, and Retention Paper presented at 2023 ASEE Annual Conference & Exposition, Baltimore , Maryland. 10.18260/1-2--42660

TY - CPAPER
AB - The COVID-19 pandemic brought a significant impact on society and the academic field. Many colleges and universities faced an enrollment drop during the pandemic years from the Spring of 2020. According to the Research Center&#39;s Stay Informed report series, institutions have had a total two-year enrollment drop of 4.2 percent since 2020. The Computer Systems Technology (CST) Department at New York City College of Technology (City Tech) of the City University of New York (CUNY) experienced a similar drop. At the same time, in the Spring 2020, most universities and colleges moved their teaching online. The decrease in enrollment numbers and shift to online teaching, combined with multiple reports of cheating in the wake of COVID-19, present an interesting case for studying the students&#39; performance at different phases of COVID-19. The City Tech is a Hispanic Serving Institution (HSI), and many of our students come from low-income households and underrepresented communities which were dramatically affected by the pandemic. For the CST Department, the portions of students with economic disadvantages from the total enrolled numbers are around 72.5% in Fall 2019 and around 64% in Fall 2020. This project investigates how the changes in the learning environment (i.e., in-person to virtual and virtual to in-person) affected different student groups at City Tech at various phases of the pandemic. Our work concentrates on the students who take courses in the CST department. The analysis is performed by aggregating multiple institutional and departmental data sets from Spring 2019 to Spring 2022. The student&#39;s performance is examined for the sequence of the first three programming courses at the CST Department. It is analyzed along several dimensions, including major, gender, ethnicity, etc., throughout the different phases of the COVID-19 pandemic. This project investigates the performance of the students who take the CST courses as mandatory courses for the three CST majors as well as the performance of the students (non-CST majors) who take the CST courses as a general education computing requirement. The presented findings show the trends in courses enrollment, passing, failing, and withdrawing from the courses. In addition to a core three-course sequence, the project examines the general department retention numbers.
AU - Elena Filatova
AU - Yu-Wen Chen
AU - Hong Li
CY - Baltimore , Maryland
DA - 2023/06/25
PB - ASEE Conferences
TI - Analysis of the COVID-19 Impact on Students’ Enrollment, Performance, and Retention
UR - https://peer.asee.org/42660
DO - 10.18260/1-2--42660
ER -