Research On Effective Teaching Of Elementary School Mathematics Classroom Based On Association Rules

Today,with the rapid development of education,China's higher education has become popularized from the elite and has become popular.More and more students are entering the higher education stage,and the needs of learning are also different,showing a diversified trend..In most of the university's teaching and training programs,most of the curriculum systems have a large amount of courses,less class hours,and unreasonable curriculum content.Most of the theoretical courses contain both theoretical and practical content.Under the constraints of realistic conditions and the traditional concept of education,most teachers still follow the large~scale teaching form of unified progress and unified standards.Therefore,the university classroom learning mode can not meet the needs of all college students' individualized and diversified learning.Students learn during the learning process.The effect is also difficult to guarantee.In the current university teaching practice,because the teachers do not understand the actual situation of the students,they usually evaluate the students with the index of academic achievement.This evaluation method is not only comprehensive for the students,but also easy for students to produce a feeling of being tired of learning.This paper designs and implements a personalized learning model for college students based on clustering integration algorithm,and applies and practices the personalized learning model.The main work includes: by using the classification algorithm in data mining,the student classification method based on clustering integration algorithm is proposed,the student classification process is designed,the students are scientifically classified based on the individualized data of the students,and the teaching is personalized.For the students of H University 2017 education technology majors and the "programming language design" course as an example,the application of personalized learning model and personalized learning practice.Experiments show that the individualized learning mode of college students based on clustering integration algorithm is more conducive to students' mastery and learning of knowledge,and it is easier for learners to get better learning results.Throughthe analysis of teaching effects,the application of personalized learning based on clustering integration algorithm has achieved certain results,providing students with the most suitable education,and providing powerful data support for personalized learning research and teaching in the future.