Exploring the Application of Generative Artificial Intelligence to Support Pre-Class Preparation in County-Level High School Chemistry

Xinhui Yu; Guofang Zuo

doi:10.70088/2kxfas03

Authors

Xinhui Yu School of Chemical Engineering and Technology, Tianshui Normal University, Tianshui, China Author
Guofang Zuo School of Chemical Engineering and Technology, Tianshui Normal University, Tianshui, China Author

DOI:

https://doi.org/10.70088/2kxfas03

Keywords:

generative ai, chemistry education, educational technology, independent learning, instructional design

Abstract

In the pre-class preview stage of chemistry education within county-level high schools, several pedagogical challenges are commonly observed, including insufficient resource support, highly formalized preview activities, and the persistent difficulty teachers face in promptly assessing students' learning statuses. Generative artificial intelligence (AI), which excels in dynamic content creation, offers a promising solution by providing timely feedback, constructing diversified learning scenarios, and organizing a comprehensive educational environment. Consequently, this advanced tool introduces innovative strategies for optimizing the pre-class preview paradigm in chemistry instruction. Grounded in the authentic teaching conditions of county-level high school chemistry courses, this study systematically explores the application value of generative AI in pre-class preparatory activities. Drawing upon AI-TPACK theory, constructivist learning theory, and distributed cognition theory, we propose a practical application model encompassing task release, intelligent preview, learning situation diagnosis, and seamless classroom integration. This comprehensive model diversifies pre-study materials, cultivates students' problem-finding habits, and significantly enhances independent learning capabilities, while simultaneously allowing educators to dynamically adjust classroom instruction based on empirical pre-study data. However, the practical deployment of this intelligent tool presents potential risks, such as students directly copying standard answers, developing an overreliance on AI, and encountering factual errors or informational omissions in AI-generated content. To mitigate these issues, educators must strategically position generative AI as an auxiliary teaching instrument, design preview tasks emphasizing the cognitive learning process, and rigorously verify students' preview outcomes during classroom sessions to provide targeted, effective guidance.

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