Artificial Intelligence in Science Learning within the Framework of Situated Learning Theory: A Qualitative Investigation of Teachers’ Perspectives

Abstract

This study explores how artificial intelligence (AI) tools influence science learning, classroom interaction, and teachers’ evolving roles in K-12 education through the lens of Situated Learning Theory (SLT). While prior research has emphasized AI’s potential to enhance STEM learning, few studies have grounded these effects in established learning theories. Drawing on semi-structured interviews and open-ended questionnaires with fourteen Chinese science teachers across elementary to high school levels, this study investigates how AI integration shapes students’ learning processes and outcomes, social construction, and teachers’ pedagogical identities. Findings reveal that AI technologies—particularly virtual labs, simulations, and intelligent tutoring systems—enhance students’ conceptual understanding, foster higher-order scientific skills, and cultivate scientific identity by enabling contextualized, low-risk and inquiry-based participation. AI-supported collaboration also deepened classroom interaction, promoting joint meaning-making and peer learning. Moreover, teachers’ roles shifted from knowledge transmitters to facilitators, co-investigators, and ethical supervisors, highlighting emerging responsibilities in guiding students’ responsible use of AI. By integrating SLT with AI in science education, this study extends theoretical understanding of how digital tools mediate authentic participation and boundary crossing in learning. It also underscores the indispensable human dimension of teaching in the age of intelligent technology.