Cited by 119Online Learning and AnalyticsEthics and Social Impacts of AIDigital Education and Society

Ethical issues in learning analytics: a review of the field

Tzimas, Dimitrios, Demetriadis, Stavros·2021·Educational Technology Research and Development

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Registry

Crossref · 10.1007/s11423-021-09977-4

Cites

120 of 120 references verified0 citation errors · 0 not checkable

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  • The use of AI and learning analytics in education entails a massive amount of personal data generated, captured, and analyzed to optimize learning experiences.

    “This digital revolution in education, particularly the use of AI and learning analytics in the field of education, entails a massive amount of personal data generated, captured, and analyzed to optimize learning experiences (Tzimas & Demetriadis, 2021; Pardo & Siemens, 2014).”

    From Ethical principles for artificial intelligence in education (2023) · cites this paper as Tzimas & Demetriadis, 2021

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Authors
Tzimas, D., & Demetriadis, S.
Affiliations
Aristotle University of Thessaloniki (GR)
Corresponding author
Tzimas, Dimitrios
Venue
Educational Technology Research and Development
Published
2021-03-05
Volume
69
Issue
2
Pages
1101-1133
ISSN
  • 1042-1629 (ISSN-L)
  • 1556-6501
OpenAlex
W3134656961
Cited by
119
References
123
Citations by year
2026: 20 · 2025: 37 · 2024: 22 · 2023: 26 · 2022: 11 · 2021: 3
FWCI
13.12
Type
journal article
Language
en
Open access
closed
Locations
Educational Technology Research and Development (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
  • Physical Sciences › Computer Science › Information Systems › Digital Education and Society
Keywords
learning analytics, ethics of learning analytics, educational data, big data in education, moral norms, code of practice, educational stakeholders, responsible data use, instructional design model

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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