A Systematic Review of AI Integration in STEM Education: Motivation, Engagement, Efficiency, and Adaptivity (Stage 2, 10:53 AM)

• In Event: e-Lightning Ed-Talk Session 16 - Stage 2

Abstract

This systematic review examines the integration of Artificial Intelligence (AI) in K–12 STEM education based on the impacts of four dimensions: motivation, engagement, efficiency, and adaptivity. The review highlights AI’s potential to personalize learning, enhance inquiry-based engagement, streamline instructional processes, and support differentiated instruction. Findings reveal that engagement was the most consistently reported benefit, followed by efficiency, with motivation and adaptivity showing promising but context-dependent outcomes. The dual-perspective approach from both student and teacher experiences emphasizes the importance of pedagogical design and educator agency in AI implementation. This review offers evidence-based insights for educators and policymakers aiming to harness AI for equitable and effective STEM learning.

Author

• Chenxi Zhou, The George Washington University