Exploration of an Interdisciplinary Teaching Model in Primary Schools Supported by Generative Artificial Intelligence

Abstract

With the rapid advancement of generative artificial intelligence (Generative AI) technology, its potential for application in the educational field is becoming increasingly evident, demonstrating significant innovative value, particularly in interdisciplinary teaching at the primary school level. This paper explores the application models of generative AI in primary school interdisciplinary teaching and analyzes its functions in areas such as teaching support, content generation, and evaluation feedback. Generative AI can dynamically generate personalized learning content based on students' learning needs and provide teachers with precise instructional guidance through intelligent analysis, thereby enhancing teaching effectiveness and fostering the development of students' interdisciplinary thinking. Interdisciplinary teaching not only facilitates the integration and innovation of student knowledge but also cultivates their critical thinking and problem-solving abilities. The findings of this study indicate that generative AI can effectively promote classroom interaction, optimize the learning environment, and guide students in forming autonomous learning and interdisciplinary thinking patterns. In the future, with the continuous progress of artificial intelligence technology, generative AI will play an even greater role in the field of education, driving profound transformations in educational models.