RESEARCH TRENDS OF ARTIFICIAL INTELLIGENCE IN SCIENCE EDUCATION: A SCOPUS-BASED BIBLIOMETRIC MAPPING USING VOSVIEWER
Abstract
The rapid advancement of Artificial Intelligence (AI) has significantly transformed educational practices, particularly in science education, through the integration of intelligent technologies such as machine learning, natural language processing, and ChatGPT. These technologies have enabled more adaptive, personalized, and technology-enhanced learning experiences. However, comprehensive mapping of emerging research trends and thematic developments in AI-based science education remains limited. Therefore, this study aims to analyze publication trends, identify dominant research themes, and explore the development of AI technologies in science education through a bibliometric approach. This study employed bibliometric analysis using data collected from the Scopus database. A total of 270 English-language journal articles published between 2018 and 2025 were analyzed using VOSviewer software. The findings identified 102 keywords grouped into six major clusters, including (1) science education and teaching, (2) computing and education, (3) learning outcomes and educational applications, (4) language models and emerging AI technologies, (5) machine learning and intelligent systems, and (6) interdisciplinary and technology-enhanced education. Recent studies increasingly focus on ChatGPT, generative artificial intelligence, and machine learning, indicating a shift from traditional AI applications toward adaptive and intelligent learning environments. The findings also reveal that AI research in science education is becoming increasingly interdisciplinary and technology driven. This study contributes to providing a comprehensive overview of research development and offers insights into future directions for AI implementation in science education.
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DOI: https://doi.org/10.17509/e.v25i2.99912
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