Artificial Intelligence for Enhancing Science Education: A Decade of Trends, Themes, and Global Insights (2013-2023)

Artificial intelligence is gaining attention as a catalyst for science education. As the field continues to evolve, it is crucial to understand its current research priorities and recognize key contributors. Notably, despite its growing importance, gaps remain in comprehensive reviews describing contemporary perspectives on AI's role in science education. This research review uses bibliometric analysis to highlight the state of AI in science education research from 2013 to 2023, tracing its evolution and revealing recurring themes and priorities. This study uncovers four key insights. First, research in this field has transitioned from initial exploration to rapid development. Second, five distinct research trajectories have emerged, each with a specific focus. Keywords like artificial intelligence, machine learning, education, deep learning, and students form the hotspots of academic research. Third, fifteen research topics, such as science education, artificial intelligence, learning analytics, and online learning, have gained prominence, each representing a unique area of focus. These themes range from different AI technologies enhancing science education to transforming classroom teaching methods. The evolution of these research themes reflects the dynamic nature of science education research, with certain clusters showing sustained academic interest since 2013. Finally, a diverse ecosystem of researchers, institutions, countries, and literature has emerged, contributing to various research priorities. This review enhances our understanding of AI's role in science education and provides a valuable resource for researchers, educators, and policymakers.