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Ethical issues in learning analytics: a review of the field
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“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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Metadata
- 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
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Social Sciences › Education › 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
About these checks
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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