Exploring the impact of AI-Powered Learning Tools on students engagement and academic performance: A systemic review of moderating factors

Abstract

The increasing rate of embracing artificial intelligence (AI) in higher institutions of learning globally has generated significant debate concerning its impact on student engagement and academic performance. While AI-powered tools promise personalized learning and greater efficiency, their effectiveness is highly dependent upon several moderating factors. An in-depth systematic review was deplored to investigate the relationship between AI-powered learning tools, student engagement, and academic performance, focusing on the moderating roles of perceived ease of use (PEOU), frequency of AI tool use, instructor training and support (IT&S), and student digital literacy levels. The detailed review synthesized existing literature to address vital research questions, exploring how these moderating factors influence the technology's effectiveness. The findings confirmed PEOU as the most significant predictor of positive student attitudes, while a higher frequency of AI tool use consistently correlates with better engagement and academic outcomes. Crucially,IT&S serves as the indispensable bridge, enabling instructors transition to studentcentred models and effectively manage AI's ethical and logistical demands. However, the in-depth review suggests that digital literacy plays a complex, but an indirect role: though it is necessary for technical competence, it does not automatically ensure greater academic engagement, suggesting a persistent need for motivationalapproaches. These findings highlight the need for balanced AI incorporation that prioritize both academic success and student well-being. This review contributes key insights for policymakers and developers seeking to enhance AI-powered learning environments