Artificial Intelligence for Physics Education in STEM Classrooms: A Narrative Review within a Pedagogy Technology Policy Framework
Abstract
Purpose of the study: This study seeks to consolidate existing global research on the incorporation of Artificial Intelligence (AI) into school-level STEM education, with a particular emphasis on physics teaching and learning in primary and secondary settings, to delineate principal trends, recognize emerging opportunities, and underscore ongoing challenges in pedagogy and learning.
Methodology: A narrative literature review was performed utilizing Google Scholar and Scopus to identify significant studies published from 2015 to 2025. The selection emphasized peer-reviewed journal articles and conference proceedings that concentrate on the pedagogical, technological, and policy aspects of AI in STEM education.
Main Findings: The analysis indicates that artificial intelligence is transforming STEM education via intelligent tutoring systems, adaptive learning platforms, automated assessments, and virtual laboratories. These technologies improve personalization, engagement, and inquiry-based learning, yet they also present ethical dilemmas concerning bias, privacy, and equity. A novel conceptual framework that integrates pedagogy, technology, and policies is proposed to direct future research and practice.
Novelty/Originality of this study: This study presents a novel three-dimensional framework that interconnects pedagogy, technology, and policy as mutually reinforcing components in AI-enhanced STEM education. The model presents a novel analytical framework for assessing existing initiatives and outlines a strategy for creating inclusive and sustainable AI-enhanced learning environments.
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