CYAIJun 10

Why does AI unlock new possibilities in STEM education? A Bibliometric Analysis of Trends and Future Agenda

arXiv:2607.05412
Originality Synthesis-oriented
AI Analysis

For STEM education researchers, this study maps the field's evolution but offers only descriptive trends without quantitative performance gains.

This bibliometric analysis of 242 publications (2015-2025) reveals that AI in STEM education has evolved from intelligent tutoring systems to LLM-driven inquiry-based learning and computational thinking, with AI providing intelligent scaffolding that lowers knowledge understanding thresholds.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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