Precision education in the algorithmic age: Toward a conceptual framework for personalized learning in higher education

Resumen

This article presents the design and implementation of Kahbom, a low-cost, game- Precision education in the algorithmic age has gained increasing relevance as higher education institutions seek to respond more effectively to student diversity, learning variability, and evolving demands for personalized teaching. Assisted by artificial intelligence, this emerging approach moves beyond traditional standardization by enabling more adaptive, data-informed, and responsive learning environments. This conceptual analysis examines precision education as a developing educational framework shaped by the integration of artificial intelligence, learning analytics, adaptive systems, and pedagogical decision-making. The article identifies its defining attributes, including personalization, predictive support, timely intervention, and continuous adjustment to learners’ needs, progress, and contexts. It also discusses key antecedents, such as technological infrastructure, ethical governance, data literacy, and faculty preparedness, as well as its potential outcomes for engagement, equity, and academic success. The paper argues that AI-assisted precision education should be understood as a human-centered and ethically guided framework that strengthens, rather than replaces, pedagogical judgment in higher education.