Artificial Intelligence for Inclusive Learning in Islamic Higher Education: Evidence from Uzbekistan on Educational Equity and Student Engagement

Nilufar Parda Omonova (Chirchik State Pedagogical University, Chirchik, Uzbekistan)
Shaxnoza Saitkarimovna Nurmatova (Uzbekistan National Pedagogical University named after Nizami, Tashkent, Uzbekistan)
Shukhrat Kosimovich Mukhammedov (Samarkand State Pedagogical Institute, Samarkand, Uzbekistan)
Iqbolxon Abduraxmanova (Tashkent State Medical University, Tashkent, Uzbekistan)
Aziza Abdullayevna Olimova (University of Tashkent for Applied Sciences, Tashkent, Uzbekistan)
Shohruh Tajibaev (Bukhara State University, Bukhara, Uzbekistan)
Gavxar Saparovna Abdullaeva (Chirchik State Pedagogical University, Chirchik, Uzbekistan)
Dilnoza Xushvaktovna Ernazarova (Tashkent International University of Chemistry, Samarkand, Uzbekistan)

Jurnal Pendidikan Islam
Vol 12 No 2 (2026): Jurnal Pendidikan Islam

The growing adoption of Artificial Intelligence (AI) in education has created new opportunities to strengthen inclusive pedagogical practices that accommodate diverse learner needs. However, empirical evidence concerning the role of AI in supporting inclusive learning within Islamic higher education remains limited. This study investigates the effects of AI-supported inclusive learning on academic achievement, learner participation, accessibility, motivation, and instructional effectiveness in Islamic higher education institutions in Uzbekistan. Employing a convergent mixed-method design, the study involved 96 students and 12 teachers who participated in an eight-week intervention. Quantitative data were collected through pretest–posttest assessments, engagement and motivation questionnaires, technology acceptance surveys, and system analytics, while qualitative data were obtained through classroom observations and semi-structured interviews. The findings revealed that students exposed to AI-supported inclusive learning achieved significantly higher academic outcomes and demonstrated stronger engagement, greater accessibility, enhanced autonomy, and more positive perceptions of inclusion than those receiving conventional instruction. Additionally, teachers also reported improvements in instructional efficiency, progress monitoring, and differentiated learning support. Drawing on principles of Universal Design for Learning, Self-Determination Theory, and Islamic educational concepts of tarbiyah, ta’lim, and ta’dib, the findings suggest that AI can support more responsive, equitable, and learner-centered educational practices when integrated within coherent pedagogical frameworks. This study contributes to the growing scholarship on inclusive pedagogy in Islamic higher education by demonstrating how AI-supported learning environments can promote educational equity, meaningful participation, and sustainable quality education in diverse learning contexts.