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Autor/inn/enLi, Chenglu; Xing, Wanli; Leite, Walter L.
TitelToward Building a Fair Peer Recommender to Support Help-Seeking in Online Learning
QuelleIn: Distance Education, 43 (2022) 1, S.30-55 (26 Seiten)Infoseite zur Zeitschrift
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ZusatzinformationORCID (Li, Chenglu)
ORCID (Xing, Wanli)
ORCID (Leite, Walter L.)
Weitere Informationen
Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN0158-7919
DOI10.1080/01587919.2021.2020619
SchlagwörterPeer Relationship; Help Seeking; Electronic Learning; Distance Education; Discussion Groups; Algebra; College Students; Equal Education; Prediction; Artificial Intelligence; Disproportionate Representation; Gender Differences; Age Differences; Florida
AbstractHelp-seeking is a valuable practice in online discussion forums. However, the asynchronicity and information overload of online discussion forums have made it challenging for help seekers and providers to connect effectively. This study formulated a new method to provide fair and accurate insights toward building a peer recommender to support help-seeking in online learning. Specifically, we developed the fair network embedding (Fair-NE) model and compared it with existing popular models. We trained and evaluated the models with a large dataset consisting of 187,450 discussion post-reply pairs by 10,182 Algebra I online learners from 2015 to 2020. Finally, we examined models with representation fairness, predictive accuracy, and predictive fairness. The results showed that the Fair-NE can achieve superior fairness in genders and races while retaining competitive predictive accuracy. This study marks a paradigm change from previous investigation and evaluation of fair artificial intelligence to proactively build fair artificial intelligence in education. (As Provided).
AnmerkungenRoutledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2024/1/01
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