Barriers of Mathematical Language Representation of College Students Based on Data Mining

Abstract

With the innovation and development of computer application technology, colleges have further accelerated the process of information construction, and data mining has gradually become one of the most active research fields in education and teaching big data analysis. As a public basic course, college mathematics has many problems, such as a large number of students, high learning failure rate, and many learning disabilities. Stolyar, a famous mathematical educator of the former Soviet Union, said that mathematical teaching is also the teaching of mathematical language. Therefore, it plays a significant role in mathematics teaching to train students to skillfully use mathematical language to represent mathematical problems and enhance the students’ ability of solving problems with mathematical methods. Based on the existing circumstances of students’ mathematical language representation obstacles, this thesis deeply discusses the influencing factors of students’ performance, constructs a decision tree model of the main factors affecting students’ performance according to the decision tree arithmetic in data mining technology, and predicts the level of curriculum obstacles according to the model, so as to help teachers adjust teaching reasonably, and guide students to overcome the obstacles of mathematical language representation.