July 12, 2025

Ethical Dimensions of Artificial Intelligence in Educational Technology and Policy: A Global Bibliometric Analysis (2020–2025)

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Bibliometric analysis identifies critical ethical issues in AI application within education, indicating gaps in research on privacy and equity.

MAIN FINDING: Essential ethical issues include data privacy, integrity in academia, and justice in AI application.
KEY EVIDENCE: Analysis of 342 articles shows gaps in research on topics like algorithmic bias and child-centered ethics.
APPROACH: The bibliometric approach employed VOSviewer software to study citation patterns and keyword trends.
SIGNIFICANCE: This research emphasizes the need for policy-focused AI ethics in educational technology to ensure equitable advancement.

Rismani et al. (2025) studied this question.

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Bibliometric analysis identifies critical ethical issues in AI application within education, indicating gaps in research on privacy and equity.