Implementing AI-Enabled Learning Management System for Colleges of Education in Kwara State: Insights from a Systematic Review

Abstract

The integration of Artificial Intelligence (AI) into Learning Management Systems (LMS) presents significant opportunities for enhancing teaching and learning in higher education. However, the extent to which these technologies are understood, adopted, and effectively implemented in Colleges of Education in Nigeria remains uncertain. The study adopts a systematic review methodology, drawing on recent literature (2019–2025) from major academic databases. Findings reveal that awareness of AI technologies among lecturers and students is increasing; however, such awareness is largely general and not specifically linked to AI-enabled LMS functionalities. The extent of adoption is found to be low to moderate, with most institutions utilising LMS platforms primarily for basic instructional purposes, while advanced AI features such as adaptive learning, predictive analytics, and automated assessment remain underutilised. The study further identifies key challenges hindering effective implementation, including inadequate technological infrastructure, limited digital and AI competencies, insufficient funding, resistance to change, and the absence of clear institutional policies. In response, the study develops a conceptual framework that highlights the interaction between enabling factors, system features, implementation processes, and expected outcomes. The study concludes that while AI-enabled LMS has the potential to significantly improve teaching effectiveness and learning outcomes, its successful integration requires strategic investment in infrastructure, capacity building, and policy development.