Adaptive Digital Modules and Artificial Intelligence in Physics Education: Bibliometric Analysis Using Scopus Data

Abdul Muhyi; Bambang Heru Iswanto; Yuli Rahmawati; Firmanul Catur Wibowo

doi:10.20527/jipf.v9i3.15607

Adaptive Digital Modules and Artificial Intelligence in Physics Education: Bibliometric Analysis Using Scopus Data

Abdul Muhyi, Bambang Heru Iswanto, Yuli Rahmawati, Firmanul Catur Wibowo

Abstract

This research aims to analyze global trends in the development of adaptive digital modules based on artificial intelligence (AI) in fluid physics learning through a bibliometric approach. As the 21st-century demand for critical thinking skills and technological understanding grows, AI-based modules are becoming increasingly relevant in supporting differentiated learning. However, a comprehensive mapping of scientific publications in this field remains limited, leading to gaps in understanding current research directions and potential collaboration opportunities. This research uses bibliometric software to identify publication patterns, researcher collaboration networks, and key trends in the development of AI-based physics learning modules. The data used is taken from the Scopus database and includes related publications from 2019 to 2024. The research method involves two main steps: data collection of publications using the keywords "adaptive digital module AND AI AND physics education" and metadata analysis to identify research trends and researcher collaborations. The analysis results show a significant increase in the number of publications on AI-based adaptive learning, particularly from countries such as China, the United States, and India. The findings also indicate that the main research topics include the development of AI technology to support adaptive learning, as well as the effectiveness of digital modules in the context of physics education. This research reveals the importance of international collaboration in the development of AI-based adaptive modules and recommends the use of other bibliometric methods as well as the expansion of database coverage for future research. Furthermore, this research provides important insights for the development of more effective learning strategies through AI technology in physics education.

Keywords

Adaptive digital modules; Artificial intelligence; Bibliometric analysis; Physics education

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References

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DOI: https://doi.org/10.20527/jipf.v9i3.15607