Due to the impact of the new crown pneumonia outbreak, offline teaching was conducted to varying degrees in schools and universities nationwide in spring 2020. After the epidemic was effectively controlled, students in various schools around the country returned to school one after another, and offline teaching was resumed. In order to deeply promote it, the School of Marxism of Guangdong Second Normal College developed and built an on-campus online open course on “Outline of Modern Chinese History” and carried out the reform and practice of a hybrid teaching on the basis of abandoning traditional teaching. The reform and practice of online teaching go hand in hand. Information technology is a high-tech product; hybrid teaching is a new thing; reform of Civics and Political Science class should be combined with the actual front-line teaching, for students’ ideas and cognitive characteristics of continuous improvement and student growth. Due to some shortcomings of the process of the current teaching mode of college teaching, such as large evaluation errors and long time, the paper proposed the evaluation method of college teaching mode with the goal of improving the accuracy of college teaching mode evaluation. Firstly, we analyze the current research status of college teaching mode evaluation and find the reasons for the poor results of current college teaching mode evaluation; then, we collect the college teaching mode evaluation data, adopt deep learning algorithm to learn the college teaching mode evaluation data, and establish the college teaching mode evaluation model; finally, we conduct the application example test of college teaching mode evaluation.
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