Transforminɡ Rural Education: AI and Autonomy in Readinɡ and Writinɡ
DOI:
https://doi.org/10.64325/IJIP.v3i1.52Keywords:
artificial intelligence, self-directed learning, communicative skills, English as a foreign language, pedagogical innovationAbstract
This study presents a narrative literature review with thematic synthesis, guided by SANRA and by Braun and Clarke. It examines how artificial intelligence (AI)—intelligent tutoring, learning analytics, and natural language processing—can promote autonomy in English reading and writing among eighth-grade students in rural Colombia. Publications (2019–2025) were reviewed in SciELO, Dialnet, Redalyc, and Latin American repositories; Google Scholar was used only for alerts and gray literature. From 847 records, 25 documents were selected after applying inclusion/exclusion criteria. The findings were organized around three axes: (1) intelligent diagnosis, (2) personalized learning pathways, and (3) intelligent support, which together form a model for teaching English in rural areas. The evidence suggests that AI strengthens personalization and self-directed learning when integrated with pedagogical frameworks such as SAMR, TPACK, and TPD, avoiding technocentric approaches. Barriers persist (intermittent connectivity, limited infrastructure, and insufficient teacher training) that hinder its implementation. It is concluded that AI can increase autonomy and motivation if integrated with a contextually and culturally relevant pedagogy. It is recommended to adopt the model gradually: starting with an assessment of low data consumption, prioritizing teacher training, and establishing partnerships to ensure minimum viable connectivity.
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Copyright (c) 2026 Maruen Elías Neɡrete Berdella (Author)
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