Yapay Zekâ Destekli Öğrenmenin Öğrenci Motivasyonuna Etkisi

ABSTRACT

Artificial intelligence (AI) applications are increasingly being incorporated into contemporary educational environments, offering the potential to personalize and make learning processes interactive. Students are more likely to exhibit higher motivation in digital environments where they can interact, receive instant feedback, and learn at their own pace. This study examines the effects of AI-supported learning environments on learning motivation of middle school students. The research was conducted using a pretest-posttest control group experimental design. The study group consisted of 60 7th grade students. For four weeks, AI-supported learning materials and feedback were provided to the experimental group, while the control group received instruction based on the existing constructivist-centered approach. Datas were collected using the "Learning Motivation Scale for Middle School Students," and ANCOVA and effect size calculations were used in the analysis. The findings indicate that AI-supported learning significantly increases students' intrinsic motivation, interest, and self-regulation dimensions, in particular. The results demonstrate that AI-based instructional practices are a powerful tool in instructional design. AI-supported learning tools should be used as a supplementary tool in classroom instruction. This can increase productivity, especially in courses with intensive feedback. Personalized learning paths should be developed for students with low motivation, and AI's adaptive features should be utilized.

Keywords: Artificial Intelligence, Student Motivation, Experimental Research, Educational Technology