Cited by 34Ethics and Social Impacts of AIOnline Learning and AnalyticsArtificial Intelligence in Education

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Assessing Algorithmic Fairness in Automatic Classifiers of Educational Forum Posts

Sha, Lele, Rakovic, Mladen, Whitelock-Wainwright, Alexander, Carroll, David, Yew, Victoria M., Gasevic, Dragan, Chen, Guanliang·2021·Lecture Notes in Computer Science

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Crossref · 10.1007/978-3-030-78292-4_31

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3 of 3 references verified0 citation errors · 0 not checkable

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  • Several studies highlight the risks of underperforming or biased AI models, which can negatively impact human learning and perpetuate systemic biases.

    “Several studies highlight the risks of underperforming or biased AI models, which can negatively impact human learning and perpetuate systemic biases, such as gender, racial, and social class biases [87,88].”
  • Two studies have suggested that potential bias and discrimination issues may occur if adopting a model that is accurate but unfair.

    “Apart from issues with adopting inaccurate models, two studies have suggested that potential bias and discrimination issues may occur if adopting a model that is accurate but unfair (Merine & Purkayastha, 2022;Sha et al., 2021).”

Citations

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Research works printed but not linked: 47

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Metadata

Authors
Sha, L., Rakovic, M., Whitelock-Wainwright, A., Carroll, D., Yew, V. M., Gasevic, D., & Chen, G.
Affiliations
Monash University (AU)
Corresponding author
Chen, Guanliang
Venue
Lecture Notes in Computer Science
Published
2021
Volume
12748 LNAI
Pages
381-394
ISSN
  • 0302-9743 (ISSN-L)
  • 1611-3349
OpenAlex
W3165938262
Cited by
34
References
3
Citations by year
2026: 3 · 2025: 8 · 2024: 9 · 2023: 7 · 2022: 6 · 2021: 1
FWCI
5.20
Type
conference paper
Language
en
Open access
closed
Locations
  • Lecture notes in computer science (publishedVersion)
  • HAL (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
  • Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
  • Social Sciences › Education › Artificial Intelligence in Education
Keywords
algorithmic fairness, sex bias, English as a second language, data sampling, online learning analytics

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