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How COVID-19 Affected Computer Science MOOC Learner Behavior and Achievements: A Demographic Study

Authors:

Ronisha Carter,

Shigeru MiyagawaAuthors Info & Claims

L@S '22: Proceedings of the Ninth ACM Conference on Learning @ Scale

Pages 345 - 349

https://doi.org/10.1145/3491140.3528328

Published: 01 June 2022 Publication History

Abstract

Learner data from multiple instances of two introductory Python MOOCs, offered before and during the COVID-19 pandemic, were analyzed to see if and how learner behavior and overall learning outcomes changed during the pandemic. We found a surge in interest during the pandemic, but the certification rate fell short of the pre-pandemic average. Moreover, this drop in certification rate is more noticeable for the advanced course in the sequence, and is more pronounced in groups traditionally underrepresented in computer-science and coding communities. Additionally, we analyzed learners' interaction with one another on the course discussion forum, and performed a sentiment analysis of the forum comments using natural language processing, which revealed behavioral trends that differed significantly during the pandemic.

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Cited By

Chrysafiadi KVirvou MTsihrintzis G(2023)A Fuzzy-Based Evaluation of E-Learning Acceptance and Effectiveness by Computer Science Students in Greece in the Period of COVID-19Electronics10.3390/electronics1202042812:2(428)Online publication date: 13-Jan-2023
https://doi.org/10.3390/electronics12020428
Yee MRoy APerdue MCuevas CQuigley KBell ARungta AMiyagawa S(2023)AI-assisted analysis of content, structure, and sentiment in MOOC discussion forumsFrontiers in Education10.3389/feduc.2023.12508468Online publication date: 15-Sep-2023
https://doi.org/10.3389/feduc.2023.1250846
Blundo CLoia VOrciuoli F(2023)A Time-Aware Approach for MOOC Dropout Prediction Based on Rule Induction and Sequential Three-Way DecisionsIEEE Access10.1109/ACCESS.2023.332320211(113189-113198)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3323202
Show More Cited By

Index Terms

How COVID-19 Affected Computer Science MOOC Learner Behavior and Achievements: A Demographic Study
1. Applied computing
  1. Education
    1. E-learning

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Published In

cover image ACM Other conferences

L@S '22: Proceedings of the Ninth ACM Conference on Learning @ Scale

June 2022

491 pages

ISBN:9781450391580

DOI:10.1145/3491140

General Chair:
René F. Kizilcec
Cornell University, USA
,
Program Chairs:
Katie Davis
University of Washington, USA
,
Xavier Ochoa
New York University, USA

Copyright © 2022 Owner/Author.

This work is licensed under a Creative Commons Attribution International 4.0 License.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 June 2022

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United States Air Force Research Laboratory

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L@S '22

L@S '22: Ninth (2022) ACM Conference on Learning @ Scale

June 1 - 3, 2022

NY, New York City, USA

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Overall Acceptance Rate 117 of 440 submissions, 27%

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Cited By

Chrysafiadi KVirvou MTsihrintzis G(2023)A Fuzzy-Based Evaluation of E-Learning Acceptance and Effectiveness by Computer Science Students in Greece in the Period of COVID-19Electronics10.3390/electronics1202042812:2(428)Online publication date: 13-Jan-2023
https://doi.org/10.3390/electronics12020428
Yee MRoy APerdue MCuevas CQuigley KBell ARungta AMiyagawa S(2023)AI-assisted analysis of content, structure, and sentiment in MOOC discussion forumsFrontiers in Education10.3389/feduc.2023.12508468Online publication date: 15-Sep-2023
https://doi.org/10.3389/feduc.2023.1250846
Blundo CLoia VOrciuoli F(2023)A Time-Aware Approach for MOOC Dropout Prediction Based on Rule Induction and Sequential Three-Way DecisionsIEEE Access10.1109/ACCESS.2023.332320211(113189-113198)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3323202
Bothe MMeinel C(2022)Stay at Home and Learn: Did the COVID-19 Pandemic Influence Mobile Learning in MOOCs?2022 IEEE Learning with MOOCS (LWMOOCS)10.1109/LWMOOCS53067.2022.9927873(85-90)Online publication date: 29-Sep-2022
https://doi.org/10.1109/LWMOOCS53067.2022.9927873

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