ARTIFICIAL INTELLIGENCE-BASED COGNITIVE MECHANISMS FOR LEARNING FOLK PEDAGOGY IN MODERN EDUCATION: A SYNTHESIS REVIEW

Abstract

This synthesis review examines how artificial intelligence (AI)–enabled cognitive mechanisms can support learning folk pedagogy—culturally rooted, informal, and widely distributed practices through which communities teach and learn—within modern education. Drawing on interdisciplinary sources spanning AI-driven pedagogy, dialogic and blended learning, hybrid intelligence, inclusive education, and AI governance, the study identifies: (a) key cognitive mechanisms through which AI can scaffold folk-pedagogical learning (personalization, dialogic interaction, simulation-based practice, and collaborative knowledge-building), (b) instructional design principles for integrating AI while preserving human-centered and culturally responsive pedagogy, and (c) ethical and governance requirements (privacy, bias mitigation, integrity, accountability) to ensure equitable implementation. The synthesis highlights convergences across domains and clarifies tensions between automation and mentorship, personalization and cultural fidelity, and innovation and governance. The findings support a nuanced approach in which AI augments—rather than replaces—human mentorship and community knowledge practices.