Adaptive Digital Modules and Artificial Intelligence in Physics Education: Bibliometric Analysis Using Scopus Data - Abdul Muhyi; Bambang Heru Iswanto; Yuli Rahmawati; Firmanul Catur Wibowo (Universitas Lambung Mangkurat, 2025)
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