Redefining Inclusive Learning in the Age of AI: A Qualitative Study of University Lecturers’ Perspectives - Artipah Artipah; Erma Damayanti; Ditta Mustika Rakhmawati; Deny Gunawan Susandi (ULIL ALBAB : Jurnal Ilmiah Multidisiplin, 2026)
The growing integration of artificial intelligence (AI) in higher education has reshaped teaching and learning practices, yet its implications for inclusive learning remain underexplored. This study investigates how university lecturers conceptualize and enact inclusive learning within AI-mediated educational contexts. Employing a qualitative interpretive approach, data were collected through semi-structured interviews and reflective accounts from lecturers in English education and mathematics with experience using AI in teaching. Data were analyzed using reflexive thematic analysis to identify recurring patterns across participants’ perspectives. The findings indicate that inclusion is understood not merely as accommodation but as a pedagogical commitment to access, participation, and meaningful learning. Three interrelated themes emerged: the reframing of inclusion in AI-supported learning, the dual role of AI as both an enabler and a constraint, and the central role of lecturers as pedagogical and ethical mediators. The study reveals that AI does not inherently promote inclusivity; rather, its educational impact depends on how it is interpreted and enacted by lecturers. This study proposes an AI-Mediated Inclusive Learning Framework, emphasizing that inclusive learning in the age of AI is a pedagogical and ethical achievement rather than a technological outcome.