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Freirean Pedagogy for Equitable Assessment, Decolonial Governance, and Cognitive Wellbeing in the Age of Artificial Intelligence: A Systematic Review

Sep 2026 · F1000Research · 0 citations · 37 references

Abstract

The rapid integration of generative artificial intelligence into higher education has outpaced the development of pedagogical frameworks and institutional policies, raising fundamental questions about the purposes of education in an algorithmic age. Paulo Freire’s critical pedagogy offers a powerful lens for interrogating the epistemological, ethical, and political dimensions of AI-mediated education, yet its application remains fragmented across disciplinary boundaries. This systematic review followed the PRISMA 2020 guidelines and employed a systematic literature search across the Scopus database, supplemented by backward and forward citation tracking. The search strategy combined terms related to Freirean pedagogy and liberating education with terms related to artificial intelligence, yielding a final corpus of 15 peer-reviewed open access journal articles published between 2021 and 2026, within the 2020–2026 eligibility window. Data extraction and thematic synthesis were conducted using the PEO framework, and risk of bias was assessed using appropriate tools. The synthesis identified four thematic clusters: epistemological foundations for critiquing algorithmic neutrality; redesign of assessment and governance practices; intersectional and decolonial dimensions of algorithmic harm; and psychological consequences of cognitive offloading. Key findings reveal that uncritical AI integration reproduces the banking model of education, systematically marginalizes nondominant epistemologies, and risks eroding critical thinking through cognitive debt. A critical framework organized around recognition, voice, and power, operationalized through credibility, comprehensibility, and control, is proposed. Freirean pedagogy retains transformative relevance when translated into design principles, governance mechanisms, and evaluative criteria that challenge algorithmic reductionism and center epistemic justice, relational agency, and collective liberation. The framework offers actionable guidance for equitable assessment redesign, participatory governance, and psychologically sustaining pedagogies in AI-mediated higher education.

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