Personalized Learning and Innovative Teaching Approaches in Universities: Artificial Intelligence-Supported Science Education

Authors : Mahmut Sami Kılıç, M. Said Doğru, Fatih Yüzbaşıoğlu

Pages : 165-192

Doi:10.58689/eibd.1754301

View : 141 | Download : 488

Publication Date : 2025-11-06

Article Type : Research Paper

Abstract :This study aims to analyze AI-supported personalized learning applications in university science education and their integration with innovative teaching approaches, drawing on existing literature. The study examines how AI transforms learning environments, optimizes learning processes based on individual student needs, and impacts teachers\\\' pedagogical approaches. The methodology employed was an in-depth analysis of relevant literature, assessing the role of AI-supported systems in science education and the effectiveness of personalized and adaptive learning systems. The findings indicate that AI enhances conceptual understanding and problem-solving skills, but significant gaps and contradictions remain in the literature regarding long-term impact, scalability, applicability across diverse socioeconomic contexts, and faculty members\\\' digital pedagogical competencies. Moreover, it emphasizes the need for further research on student autonomy and the risk of over-reliance on AI. Comprehensive empirical studies, interdisciplinary collaborations, and designs that support student autonomy are recommended to address these gaps.
Keywords : Yapay zeka, Kişiselleştirilmiş öğrenme, Yenilikçi öğrenme, Fen eğitimi

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