Student-centric ethical frameworks for AI-driven education: Participatory consent and data ownership in a global perspective

Deckker, Dinesh and Sumanasekara, Subhashini (2025) Student-centric ethical frameworks for AI-driven education: Participatory consent and data ownership in a global perspective. International Journal of Science and Research Archive, 15 (3). pp. 1491-1503. ISSN 2582-8185

The integration of artificial intelligence (AI) into educational systems has transformed pedagogical practices; however, it has also intensified concerns regarding privacy, consent, and data governance, particularly for students. This narrative review examines the ethical challenges posed by AI in education from a student-centred perspective. It focuses on two critical dimensions: participatory consent and data ownership. Drawing on interdisciplinary literature from 2015 to 2025, the study synthesises global perspectives on student rights, cultural variance in data ethics, and emerging governance models. The review adopts a narrative methodology to analyse peer-reviewed articles, policy reports, and theoretical frameworks. Key findings highlight the inadequacy of current consent practices, the marginalisation of student voice, and the dominance of institution- or developer-centric ethical standards. The review identifies alternative models of ethical engagement, including dynamic consent, Indigenous data sovereignty frameworks, and culturally responsive design approaches. It concludes that ethical AI in education requires a paradigm shift—from compliance-based mechanisms to relational, justice-oriented frameworks that centre students as rights-bearing participants. By integrating perspectives from the Global South, Indigenous epistemologies, and critical pedagogy, this review contributes to the development of ethical frameworks that are inclusive, pluralistic, and empowering.