The Impact of AI, Digital Learning, and Blended Approaches on Student Engagement for Inclusive Education

Abstract

Grounded in technology-enhanced learning and inclusive pedagogy frameworks, this study examines the influence of Artificial Intelligence (AI), Digital Learning Technologies (DLT), and Blended Learning (BL) on Inclusive Education (IE), with Student Engagement (SE) serving as a mediator variable. Data were collected through a structured questionnaire administered to university students in Pakistan (N = 750) across five higher education institutions. The measurement model demonstrated acceptable reliability and validity (Cronbach's α > 0.60; CR > 0.70), and the structural model was assessed using Partial Least Squares Structural Equation Modelling (PLS-SEM) in SmartPLS 4. The model demonstrated strong predictive accuracy, accounting for 51.8% of the variance in Inclusive Education (R2 = 0.518). Results showed that AI-driven adaptive systems, digital platforms, and blended instructional approaches enhance accessibility, personalize learning, and increase student participation. Mediation analysis confirms that Student Engagement (SE) mediates the relationship between technology use and improved educational outcomes. However, persistent challenges include inadequate digital infrastructure, unequal access, limited teacher training, and concerns about privacy and algorithmic bias. This research presents a novel, integrated framework that advances our understanding of how technology-driven approaches support inclusive education in a developing-country context. Future studies should validate this framework across diverse educational contexts and employ longitudinal designs to capture long-term impacts.