AI-SUPPORTED LEARNING AND MOTIVATIONAL DYNAMICS IN ISLAMIC HIGHER EDUCATION - Muhammad Abdul rouf; Rizki Gangsar Septiono; Risma Latiful Azza; Khikmatul Rosida (Universitas Islam Negeri Mataram, 2026)
Artificial intelligence (AI) is increasingly used in higher education to support personalised learning, feedback, translation, assignment preparation, and independent study. However, its role in Islamic higher education requires closer attention because AI use may support student motivation while also creating dependency on algorithmic guidance. This study examines AI-supported learning at Institut Agama Islam Urwatul Wutsqo Jombang, focusing on student engagement, motivational ambivalence, lecturer mediation, and learner autonomy. Using a qualitative case study design, data were collected from 52 participants, consisting of 40 students, eight lecturers, and four academic leaders across four study programmes. Semi-structured interviews, classroom observations, and document analysis were used to understand how AI was experienced in academic learning. The findings show that AI helped students clarify concepts, review learning materials, prepare assignments, translate texts, and access immediate feedback. These practices supported perceived competence and visible engagement. However, AI also created motivational tension when students relied on automated prompts to decide what to study or how to complete tasks. Lecturer mediation emerged as the key condition that helped students verify AI-generated responses, maintain academic responsibility, and use AI critically. The study concludes that AI-supported learning in Islamic higher education should strengthen student competence without weakening autonomy.