Mengoptimalkan Pembelajaran yang Didukung AI Melalui Self-Determination Theory: Mengintegrasikan Psychological Needs dan Nilai-Nilai Pendidikan Islam - Retno Aqimnad Dinana; Abdul Muhid; Arif Nur Rofiq (UIN Sultan Aji Muhammad Idris Samarinda, 2026)
The rapid development of Artificial Intelligence (AI) has transformed educational practices by providing more personalized, adaptive, and efficient learning experiences. However, the use of AI does not automatically improve learning achievement because it has the potential to cause dependence on technology, cognitive offloading, the illusion of competence, and reduced social interaction among students. Previous research generally examines these issues from the perspective of educational technology or educational psychology, while integration with Islamic education values ​​is still limited. This study aims to analyze the optimization of AI-based learning achievement through the integration of Self-Determination Theory (SDT) and Islamic Education. This study uses a qualitative approach with a literature study method. Data were collected from books and scientific journal articles, then analyzed descriptively through conceptual synthesis with SDT as the main theoretical foundation. The results of the study indicate that AI can support learning achievement by fulfilling students' psychological needs, namely autonomy, competence, and relatedness, supported by self-regulated learning, metacognition, cognitive load, and self-efficacy. Islamic education enriches these three dimensions through the values ​​of tarbiyah (Islamic education), ta'lim (Islamic study), ta'dib (Islamic guidance), itqan (Islamic guidance), and ta'awun (Islamic covenant). Therefore, the use of AI not only encourages academic achievement but also character development, moral responsibility, and spiritual awareness. Therefore, optimizing AI-based learning achievement requires integrating psychological and Islamic educational perspectives so that AI can function as a pedagogical instrument that supports holistic learning.