MATEMATİK EĞİTİMİNDE YAPAY ZEKA: EĞİLİMLER, ROLLER VE GELECEK YÖNELİMLERİ ÜZERİNE SİSTEMATİK BİR İNCELEME

Öz

Günümüzde yapay zekâ teknolojilerinin eğitim ortamlarına entegrasyonu, özellikle matematik öğretimi bağlamında köklü dönüşümler yaratmaktadır. Bu sistematik literatür incelemesi, 2020–2025 yılları arasında yayımlanan çalışmaları analiz ederek yapay zekâ (YZ) teknolojilerinin matematik eğitimine entegrasyonuna dair eğilimleri, üstlenilen rolleri ve gelecekteki araştırma ihtiyaçlarını belirlemeyi amaçlamaktadır. Scopus ve ERIC veri tabanlarında PRISMA yönergeleri doğrultusunda yürütülen tarama sonucunda 87 nitelikli makale incelenmiştir. İçerik analiziyle elde edilen bulgular, matematik eğitiminde YZ (MEYZ) rollerinin beş ana kategori altında toplandığını göstermektedir: öğrenci öğrenmesi, öğretmen odaklı uygulamalar, materyal hazırlama, araç odaklı değerlendirmeler ve veri odaklı çalışmalar. Öğrenci öğrenmesi rolü en baskın kategori olup, özellikle bireyselleştirilmiş öğrenme, anlık geri bildirim ve motivasyon artışı gibi işlevlerle öne çıkmıştır. Bu kategoride en sık kullanılan YZ araçları Akıllı Özel Ders Sistemleri (ITS) ve Büyük Dil Modelleri (LLM) olmuştur. Araştırma tasarımları açısından karma yöntem çalışmaları ağırlık kazanırken, örneklem düzeyinde üniversite öğrencilerine odaklanan çalışmalar çoğunluktadır. Öte yandan, okul öncesi gruplar, öğretmen eğitimi ve ölçme gibi içerik alanları araştırmalarda oldukça sınırlı temsil edilmiştir. Çalışmanın sonuçları, MEYZ alanındaki araştırmaların giderek çeşitlendiğini, ancak öğretmen merkezli uygulamalar, veri analitiği kullanımı ve pedagojik materyal geliştirme gibi kritik alanlarda derinlemesine çalışmalara ihtiyaç olduğunu ortaya koymaktadır.

Anahtar Kelimeler

• Matematik eğitimi
• Sistematik literatür incelemesi
• Yapay zeka
• Eğitim teknolojileri
• Pedagojik entegrasyon

ARTIFICIAL INTELLIGENCE IN MATHEMATICS EDUCATION: A SYSTEMATIC REVIEW OF TRENDS, ROLES AND FUTURE DIRECTIONS

Öz

The integration of artificial intelligence (AI) technologies into educational settings is currently creating profound transformations, particularly in the context of mathematics instruction. This systematic literature review aims to identify the trends, assumed roles, and future research needs regarding the integration of AI technologies into mathematics education by analyzing studies published between 2020 and 2025. Following the PRISMA guidelines, 87 high-quality articles were examined through a screening process conducted in the Scopus and ERIC databases. The findings obtained through content analysis show that the roles of AI in mathematics education (AIME) are grouped under five main categories: student learning, teacher-oriented practices, material development, tool-based evaluations, and data-driven studies. The student learning role emerged as the most dominant category, especially standing out with functions such as personalized learning, real-time feedback, and increased motivation. In this category, the most frequently used AI tools were Intelligent Tutoring Systems (ITS) and Large Language Models (LLMs). In terms of research design, mixed-method studies were predominant, and most of the sample groups focused on university students. On the other hand, preschool groups, teacher training, and content areas such as assessment were found to be significantly underrepresented in the literature. The results of the study indicate that research in the field of AIME is becoming increasingly diversified; however, there is still a critical need for in-depth studies in areas such as teacher-centered practices, data analytics usage, and the development of pedagogical materials.

Anahtar Kelimeler

• Mathematics education
• Systematic literature review
• Artificial intelligence
• Educational technologies
• Pedagogical integration

Kaynakça

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