Research Progress of Generative Artificial Intelligence in Secondary School Chemistry Teaching

Abstract

As a cutting-edge branch of artificial intelligence technology, generative artificial intelligence (GenAI) is effecting a profound transformation in secondary - school chemistry education. This study undertakes a systematic review of 31 related research papers to analyze the current application of GenAI in chemistry teaching. Through discussing four key dimensions—homework and assessment optimization, experimental teaching innovation, instructional design empowerment, and personalized learning support—the research not only unveils the underlying mechanisms of technological empowerment but also grapples with practical challenges such as data security and algorithmic bias. It ultimately proposes development paths including building human-machine collaborative teaching paradigms and cultivating critical thinking. The findings demonstrate that GenAI bolsters the personalization and efficacy of chemistry instruction via intelligent content generation, contextualized interaction design, and precise data feedback. However, the study emphasizes the necessity to address time constraints in technology application while preserving the rational essence of education.