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Generative AI and Agency in Education: A Critical Scoping Review and Thematic Analysis

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arxiv 2411.00631 v2 pith:SAUVCNV7 submitted 2024-11-01 cs.CY cs.AI

Jasper Roe (1) , Mike Perkins (2) ((1) James Cook University Singapore , (2) British University Vietnam) This is my paper · ORCID
classification cs.CYcs.AI
keywords agencylearnereducationalgenaireviewaccessanalysiscritical
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This scoping review examines the relationship between Generative AI (GenAI) and agency in education, analyzing the literature available through the lens of Critical Digital Pedagogy. Following PRISMA-ScR guidelines, we collected 10 studies from academic databases focusing on both learner and teacher agency in GenAI-enabled environments. We conducted an AI-supported hybrid thematic analysis that revealed three key themes: Control in Digital Spaces, Variable Engagement and Access, and Changing Notions of Agency. The findings suggest that while GenAI may enhance learner agency through personalization and support, it also risks exacerbating educational inequalities and diminishing learner autonomy in certain contexts. This review highlights gaps in the current research on GenAI's impact on agency. These findings have implications for educational policy and practice, suggesting the need for frameworks that promote equitable access while preserving learner agency in GenAI-enhanced educational environments.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. OpenAlex reports about 11 citations worldwide. Full citation record

  1. Assessment Twins: A Protocol for AI-Vulnerable Summative Assessment

    cs.CY 2025-10 conditional novelty 6.0 of 10

    A named protocol that twins AI-vulnerable assessments with a complementary low-AI-vulnerability component addressing the same outcomes, argued to enhance assessment validity.

  2. Do AI tutors empower or enslave learners? Toward a critical use of AI in education

    cs.CY 2025-07 conditional novelty 3.0 of 10

    A position paper synthesizing research to caution that unchecked AI use in education risks cognitive, emotional, and ethical harm, and recommending principles for critical AI use.

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