The rapid advancement of artificial intelligence (AI) technologies has led to their increasing integration into education. High school biology experimental teaching, a critical component in cultivating students scientific literacy, is gradually investigating deeper integration with AI. This research reviews the theoretical foundations of AI in education and delineates the essential connotations of high school biology experimentation, offering a systematic analysis of the current application of AI technologies in basic education, with a focus on biology labs. Utilizing questionnaire data from teachers and students at a key high school in Zhengzhou, the research uncovers the actual adoption rate, implementation forms, and influences of AI on teaching efficiency, student comprehension, and laboratory safety. The results suggest that while certain schools have begun adopting AI-assisted tools such as virtual simulations and intelligent feedback systems, they still face considerable challenges in technological integration, infrastructure, teacher competency, and pedagogical adaptability. To tackle these challenges, this paper introduces innovative teaching models supported by AI, such as AI-driven virtual experiments and personalized learning support, and highlights the importance of sustainable professional development programs to improve biology teachers AI literacy and technical support mechanisms. The research provides theoretical insights and practical approaches for the high-quality, sustainable application of AI in high school biology experimental instruction, thereby advancing the intelligent transformation of science education.
Mingwei Zhang (Mon,) studied this question.