Impact of AI-Based Intelligent Tutoring Systems on Student Engagement: An Empirical Data Study

Abstract

This study examines the impact of AI-based Intelligent Tutoring Systems (ITS) on student engagement using an empirical, quasi-experimental research design. A total of 240 undergraduate students were assigned to a traditional-instruction control group or an experimental group that received AI-ITS-supplemented instruction over an eight-week academic term. Engagement was measured across behavioral, emotional, and cognitive dimensions using a validated self-report instrument and platform-generated interaction logs. Students in the AI-ITS condition demonstrated significantly higher engagement scores across all three dimensions compared with the control group, and their engagement trajectory increased steadily across the intervention period, whereas the control group's engagement declined modestly. These findings extend prior research on adaptive learning technologies and provide empirical support for the proposition that AI-based tutoring systems can meaningfully enhance multiple facets of student engagement in higher-education settings. Implications for instructional design, study limitations, and directions for future research are discussed.