IMPLEMENTATION OF ARTIFICIAL INTELLIGENCE AS A DIDACTIC TOOL IN RURAL SCHOOLS IN COLOMBIA

Abstract

The essay analyzes the implementation of artificial intelligence (AI) as a didactic tool in rural schools in Colombia, starting from gaps that affect access, quality, and relevance. Through a review of theoretical frameworks, regulatory guidelines, and international experiences, it examines AI’s potential to personalize learning, support multigrade classrooms, provide adaptive feedback, detect dropout risk, and optimize resources under limited connectivity. The central proposition holds that AI can contribute to educational justice if its integration is critical, ethical, and context-sensitive, guided by digital equity and cultural relevance. AI is conceived as a repertoire of intelligent tutors, learning analytics, natural language processing, and conversational agents designed with offline-first and low-resource criteria to enhance teacher scaffolding and strengthen formative assessment. The text acknowledges risks: algorithmic biases, automation that displaces pedagogical judgment, gaps in teacher uptake, and regulatory shortcomings in privacy and transparency. To address them, the proposal is organized into five pillars: resilient infrastructure and connectivity; situated teacher training and support; open, contextualized technological development; community participation; and data governance with child protection measures. A gradual roadmap is outlined with evaluable pilots, indicators for learning, school retention, and teacher well-being, algorithmic audits, and remediation mechanisms. The conclusions emphasize that AI neither replaces the pedagogical relationship nor solves structural deficits; nevertheless, it can catalyze improvements when aligned with the curriculum and sustainable policies. Finally, a collaborative research agenda is proposed to document effects and design community-based solutions.