The Design and Application of Smart Classroom Teaching Mode in Higher Vocational Education Based on Deep Learning
Rongxia Wang, Weihuang Yang · 2022
The impact of new technology on higher vocational education(HVE) has attracted the attention of many domestic scholars. The current direction of education informatization research is mostly smart classrooms. Therefore, schools will inevitably promote education informatization through the use of smart classrooms, and smart classrooms with classroom teaching(CT), teacher-student activities, and Internet + education will also become the core. This article uses experimental analysis and questionnaire survey methods to experiment on the design and application of the intelligent CT model of deep learning in HVE, compare and analyze the learning effects of the experimental and control classes of computer professional courses, and investigate and analyze their attitudes to the application of the intelligent classroom model. The experimental survey results show that the outstanding students in the experimental class has more students than that in the control class, and the learning effect is better than the traditional mode in the smart CT mode of deep learning, and most students in the experimental class prefer the use of the smart classroom mode. It can be concluded that it is necessary to study the design and application of the intelligent CT model of deep learning in HVE. In the intelligent classroom teaching system, data mining, K-means algorithm and MapReduce framework are comprehensively applied. By analyzing various behavioral data of students in school, the potential value behind these data is mined, so as to improve the construction of intelligent classroom and promote the improvement of higher vocational education.