Contributions

Laboratory members have obtained two national software copyright registration certificates

Time: 2021-08-08 17:01:21

Recently, the Ministry of Education made it clear that teachers are encouraged to teach at different levels and work at different levels. In order to help teachers to better analyze the student learning, thus achieve the goal of personalized education, realize their aptitude, our laboratory by support vector machine, artificial neural network algorithms, such as analysis of education big data, to solve the problem of performance forecast and intelligence in middle school mathematics education, teaching activities, optimize the teaching effect and improve teaching efficiency.

Laboratory members Liu Huilin, Xu Xuan, Xu Dahua and Chen Yusen took the survey data of mathematics learning in senior one as the breakthrough point, and established the prediction model of mathematics performance by using the artificial neural network algorithm. According to the prediction results, they carried out hierarchical teaching design and assigned hierarchical homework. In addition, Gao Xiaojing, a member of the laboratory, takes the optimization of teaching as the guide, combines the student information and topic information, classifies and processes the data containing various attributes by using the product kernel multi-classification support vector machine, and establishes a hierarchical model of middle school mathematics education. According to the hierarchical results of the model, hierarchical teaching and hierarchical homework are carried out for students at different levels.

The lab team applied machine learning methods to big data analysis of education to promote the deep integration of artificial intelligence and middle school mathematics education. Using artificial neural network and product kernel support vector machine in Python language environment, we developed a prediction system for middle school mathematics achievement and a hierarchical system for middle school mathematics education. Relevant research results have obtained the national computer software copyright registration certificate.



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