In the process of "artificial intelligence+education" to open a new education model, teaching concepts and learning objectives have also changed. Learning objectives have changed from superficial learning such as memorization and understanding to high-level abilities such as transfer and application, complex problem solving, reflection and evaluation. Therefore, effective use of smart classrooms to strengthen deep learning in the teaching process has become a key measure to improve the quality of talent training at present and even in the future. However, through literature review, interviews with teachers and students in smart classroom teaching, and listening in class, the author found that there are problems in classroom teaching, such as low level of cognitive ability training and low participation of students, which restrict the development of smart teaching and the effectiveness of in-depth learning. In view of this, this research adopts the experimental research method to apply the constructed smart classroom teaching model to the practical teaching of College English in Grade 2019 of A University. The experimental data were collected by the method of survey and research, and paired sample T test was conducted on the collected questionnaire data, and the analysis was conducted from the aspects of students' performance, deep learning ability, learning process, emotional experience, etc. The results show that the classroom teaching mode constructed in this study can effectively improve the course performance of college students, and students have good learning process experience and emotional experience.

Yuyun Shao and Yali Zhu. College English Teaching Model Based on Deep Learning and Artificial Intelligence. International Journal of Neural Network (2020), Vol. 1, Issue 2: 17-24. https://doi.org/10.38007/NN.2020.010203.

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