Why does AI unlock new possibilities in STEM education? A Bibliometric Analysis of Trends and Future Agenda
Jesse Yusuf Chan, Mengyao Chen, Yang Hong, Ziyun Song, Haoming Wang, Xianlong Xu
Abstract
STEM education faces challenges in personalization and interdisciplinary integration. AI technology has brought new possibilities, but the mechanisms by which AI reshapes the STEM education ecosystem require systematic investigation. This study employs bibliometric methods to analyze 242 publications from 2015-2025, constructing knowledge maps to reveal the evolutionary trajectory. The findings show that the field has transformed from intelligent tutoring systems to inquiry-based learning and computational thinking cultivation driven by LLMs. AI's key contribution lies in providing intelligent scaffolding that lowers the threshold for understanding knowledge. In this sense, AI is a core driving force promoting its shift from knowledge transmission to capability development.
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Classified with taxonomy v2 on Sat, 5 Sept 2026.