Facing Big Data Information Fusion and Data Mining Technology to Construct College Physical Education Teaching Evaluation System

Abstract

The purpose is to enrich the evaluation system of physical education (PE) teaching in colleges and universities and to improve PE teaching methods and improve teaching quality. Based on big data information fusion and data mining technology, firstly, the related theories of teaching evaluation are analyzed and expounded, as well as the characteristics and principles of the construction of college PE teaching evaluation system. Secondly, from the perspective of evaluation index system of sports teachers’ teaching and students’ sports teaching, the content and evaluation index of college sports teaching evaluation are analyzed under the background of big data information fusion and data mining by questionnaire survey. Combined with model test, the results show that traditional college sports teacher pays more attention to the design and teaching methods of PE and ignore the learning process of students. The evaluation process of PE ignores the individual differences of students, the feedback method lacks openness, and the evaluation process is isolated. Based on the big data technology and teaching evaluation theory, the evaluation index is designed for PE teaching in colleges and universities. The average value of the first layer indexes is above 4, and the coefficient of variation is less than 0.2, which can basically reflect the content of PE teaching evaluation and provide some reference for the research of PE teaching evaluation.