Repositioning STEM Education in the Context of Generative Artificial Intelligence: A Review Focusing on Critical Thinking and Problem Solving

Abstract

In recent years, a wealth of studies have explored the integration of generative artificial intelligence (AI) into classroom teaching within China’s education sector. To clarify the overall biases embedded in existing scholarship, this review sorts out Chinese and English journal articles published between 2022 and 2026, and compares divergent research priorities between Chinese and international academic communities. Most domestic studies on generative AI-enabled STEM education center on developing intelligent teaching tools and constructing digital classroom environments, while only a handful of top-tier theoretical discussions address the reconstruction of educational objectives and the cultivation of higher-order thinking competencies. Collectively, current research exhibits a pronounced bias that prioritizes technological advancement over the core essence of education. Against this notable research gap, the present study identifies critical thinking and problem-solving capabilities as the two core educational objectives for STEM classrooms. It further proposes actionable implementation strategies across four dimensions: classroom instruction, project design, assessment systems, and AI usage governance, offering practical references for digital STEM teaching in primary, secondary and tertiary institutions nationwide. This review is structured around five core components: prevailing pain points in real-world classroom practice, gaps in the extant literature, literature sorting methods adopted, key research findings, and theoretical as well as instructional implications.