Systematic Review of Studies on the Use of Artificial Intelligence in Science Education

Abstract

This study aims to systematically review research conducted between 2018 and 2024 on the use of artificial intelligence (AI) in science education. Within the scope of the research, the Scopus, Web of Science, ERIC, TR Dizin, ScienceDirect, Google Scholar, and ProQuest databases were searched, and 60 articles that met the specified criteria were included in the analysis. Using content analysis, the selected publications were categorized according to publication year, key concepts, research method, study group, data collection tools, and data analysis techniques. The findings show that the highest number of studies on the use of AI in science education was conducted in 2024. It was determined that qualitative methods were predominantly adopted in the studies and that the interview technique was the most frequently used data collection tool. While the majority of the study groups consisted of students and teachers, content analysis was found to be widely preferred in data analysis. These results reveal that AI integration in science education is increasing and that qualitative research is coming to the fore in the field. The study aims to provide a comprehensive overview of current trends in AI applications in science education and to serve as a guide for future research. In this field, where student and teacher perspectives are particularly prominent, it may be recommended to increase the number of studies using quantitative and mixed methods.

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