Research on the Feasibility and Development of AI Application in Classroom Teaching Practice

Artificial intelligence (AI) technology injects new impetus into education reform, and its functions, such as personalized learning and intelligent evaluation, are expected to solve the problems of low efficiency and unequal resources in the traditional teaching mode. However, there are still significant bottlenecks in the practical feasibility and effectiveness of AI in the teaching classroom and its deep integration with traditional education, which restrict the full release of its educational value. Through empirical analysis, this paper reveals the current three core issues. First, the lack of support for educational resources and the gap in AI infrastructure between regions exacerbated the inequity of education; Second, there are differences in teaching feedback. AI tools are difficult to adapt to complex teaching scenes due to low adaptability of algorithms and data deviation; The third is the lack of teachers' information awareness and ability, and the dual lack of technology application ability and curriculum integration strategy. Given the above problems, this paper puts forward targeted countermeasures from three aspects: improving educational resources, improving educational feedback, and improving teachers' information awareness and ability, to provide reference for the effective application of AI technology in classroom teaching practice.