Üniversitelerde Kişiselleştirilmiş Öğrenme ve Yenilikçi Öğretim Yaklaşımları: Yapay Zeka Destekli Fen Eğitimi

Yıl 2025, Cilt: 16 Sayı: Özel Sayı: Türkiye’de Yükseköğretimin Yeniden Yapılandırılması: Yeniklikler, Sorunlar ve Çözüm Önerileri Kongresi, 165 - 192, 06.11.2025

Mahmut Sami Kılıç , M. Said Doğru , Fatih Yüzbaşıoğlu

Öz

Bu çalışma, mevcut literatürden yararlanarak üniversite fen bilimleri eğitiminde yapay zeka destekli kişiselleştirilmiş öğrenme uygulamalarını ve bunların yenilikçi öğretim yaklaşımlarıyla entegrasyonunu analiz etmeyi amaçlamaktadır. Çalışma, yapay zekanın öğrenme ortamlarını nasıl dönüştürdüğünü, bireysel öğrenci ihtiyaçlarına göre öğrenme süreçlerini nasıl optimize ettiğini ve öğretmenlerin pedagojik yaklaşımlarını nasıl etkilediğini incelemektedir. Kullanılan metodoloji, ilgili literatürün derinlemesine bir analizi olup, yapay zeka destekli sistemlerin fen eğitimindeki rolünü ve kişiselleştirilmiş ve uyarlanabilir öğrenme sistemlerinin etkinliğini değerlendirmiştir. Bulgular, yapay zekanın kavramsal anlama ve problem çözme becerilerini geliştirdiğini, ancak literatürde uzun vadeli etki, ölçeklenebilirlik, farklı sosyoekonomik bağlamlarda uygulanabilirlik ve öğretim üyelerinin dijital pedagojik yeterlilikleri konusunda önemli boşluklar ve çelişkiler kaldığını göstermektedir. Dahası, öğrenci özerkliği ve yapay zekaya aşırı güvenme riski konusunda daha fazla araştırmaya ihtiyaç duyulduğunu vurgulamaktadır. Bu boşlukları gidermek için kapsamlı ampirik çalışmalar, disiplinlerarası iş birlikleri ve öğrenci özerkliğini destekleyen tasarımlar önerilmektedir.

Anahtar Kelimeler

Yapay zeka , Kişiselleştirilmiş öğrenme , Yenilikçi öğrenme , Fen eğitimi

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

Öz

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.

Anahtar Kelimeler

Artificial intelligence , Personalized learning , Science education , Innovative learning

Kaynakça

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