Research on smart classroom learning paths and effect testing and evaluation technology based on machine learning algorithm

With the maturity and popularization of artificial intelligence technology, all fields in the country have begun to transform towards intelligent and smart applications. This paper establishes a smart classroom learning path based on machine learning based on bottleneck issues such as the difficulty in systematically, completely, and accurately quantifying the subject ability objectives in the construction of smart learning models, the difficulty in obtaining learning behavior data, and the lack of training in learners' problem-solving abilities and creative thinking abilities., and finally combined with the algorithm model, this result was applied in specific classrooms. Finally, through statistical analysis, the average accuracy reached more than 85%. It provides a foundation for the application of artificial intelligence in the field of education and the development of smart learning, and provides a reference for subsequent research on smart learning models.