Ethics of Student Data Use in AI-Based EdTech Platforms

Published Paper PDF: View PDF

Gaurav Iyer

Independent Researcher

Tamil Nadu, India

Abstract
The rapid integration of Artificial Intelligence (AI) into educational technology (EdTech) platforms has ushered in a new era of personalized learning, real‑time feedback, and data‑driven decision‑making. By leveraging vast troves of student data—including demographic information, performance metrics, behavioral logs, and even affective indicators—AI systems can tailor instruction to individual learning styles, identify at‑risk learners, and optimize pedagogical approaches at scale. However, alongside these pedagogical benefits arise profound ethical challenges concerning privacy, autonomy, equity, and accountability. This enhanced abstract elaborates on the multifaceted ethical landscape, detailing the technological mechanisms of data collection and analysis, the varied stakeholder perspectives on consent and control, and the regulatory frameworks that aim to safeguard student rights. Drawing on a comprehensive mixed‑methods study—comprising a systematic literature review, stakeholder surveys with over 330 participants, and in‑depth policy analysis—this manuscript uncovers key deficiencies in current practice: opaque consent procedures that leave students and guardians uninformed; inconsistent anonymization techniques that expose re‑identification risks; algorithmic biases that can entrench existing inequities; and governance gaps that undermine transparent oversight. The findings underscore a pressing need for layered, interactive consent interfaces; advanced privacy‑preserving technologies such as federated learning and differential privacy; equity audits embedded in development lifecycles; and participatory data stewardship councils that bring together educators, learners, developers, and policymakers. By articulating concrete recommendations for ethically aligned design, this work provides a roadmap for EdTech innovators and institutional leaders to reconcile the competing imperatives of educational innovation and student rights protection, ensuring that AI’s transformative potential is realized in ways that are transparent, fair, and accountable.

Keywords
AI-Based EdTech, Student Data Ethics, Privacy, Informed Consent, Data Governance

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