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Artificial Intelligence in Physics Education Research in Two Decades: A Bibliometric Study from Scopus Database
Abstract
Physics education has witnessed a surge in research exploring the integration of Artificial Intelligence (AI) technologies, aiming to optimize instructional strategies and promote student engagement. This study aims to conduct a comprehensive bibliometric analysis of studies related to AI in physics education, identifying trends, patterns, and future research directions in this emerging field. A systematic literature search was conducted on the Google Scholar database, employing specific keywords and inclusion criteria. Data analysis was facilitated by Biblioshiny and VOSviewer software tools. The analysis revealed a growing interest in AI applications in physics education, with a notable increase in publications from 2020 to 2023. Key topics included chatbot applications, assessment methods, computational approaches, virtual simulations, and AI integration in learning. The overlay visualization depicted the evolution of research, highlighting the emergence of pre-trained language models, misconception detection, and natural language processing in recent years. The findings underscore the potential of AI technologies to revolutionize physics education, offering opportunities for personalized learning experiences, automated assessment, and innovative teaching approaches. Future studies should focus on developing adaptive assessment systems, exploring AI-driven tools for promoting problem-solving and scientific attitudes, and investigating the seamless integration of AI technologies in physics classrooms. Additionally, interdisciplinary collaborations among researchers, educators, and technology experts could accelerate the development of cutting-edge AI solutions tailored to physics education.
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References
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DOI: https://doi.org/10.26618/jpf.v12i2.14745
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