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  5. Variations in Sense of Belonging in Undergraduate Computing Students Through the COVID-19 Pandemic
 
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Variations in Sense of Belonging in Undergraduate Computing Students Through the COVID-19 Pandemic

Author(s)
Runa, Shamima Nasrin  
Becker, Brett A.  
Mooney, Catherine  
Uri
http://hdl.handle.net/10197/25283
Date Issued
2022-09-01
Date Available
2024-01-22T16:56:22Z
Abstract
Student sense of belonging, or belongingness, is important and has been associated with motivation, persistence, and other outcomes. However, belongingness varies according to factors such as race/ethnicity and gender [2]. In previous work, there have been statistically significant differences in the belongingness of computing students identifying as women and as part of a minority [2]. During the COVID-19 pandemic there was a reduction in the belongingness of students identifying as men, and those not identifying as being part of a minority, and an increase in the belongingness of women identifying as a minority [3]. Our current work shows that the belongingness of men and women not identifying as being part of a minority has not returned to pre-pandemic levels, despite returning to campus, and a further statistically significant drop in the belongingness of men who identify as part of a minority. This work shows that further efforts need to be made to restore student belongingness to pre-pandemic levels and may yield insight into how events affect belongingness.
Type of Material
Conference Publication
Publisher
ACM
Copyright (Published Version)
2022 the Authors
Subjects

Belongingness

Inclusion

Sense of Belonging

Underrepresentation

DOI
10.1145/3555009.3555029
Language
English
Status of Item
Peer reviewed
Journal
UKICER '22: Proceedings of the 2022 Conference on United Kingdom & Ireland Computing Education Research
ISBN
9781450397421
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
File(s)
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UKICER_poster_2022.pdf

Size

334.15 KB

Format

Adobe PDF

Checksum (MD5)

ee3bc3ac9fa2f92e7d171766914e99ca

Owning collection
Computer Science Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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