Research On The Innovation Path Of College Basketball Teaching Based On Big Data Analysis

Basketball, as a confrontational sport, is beneficial to improve the participants’ fitness level, flexibility, and teamwork awareness. Based on the educational big data analysis process, this paper collects the current college basketball teaching data from six dimensions, and optimizes the selection of the initial class cluster centroids of the K-means clustering algorithm, and, using the improved DT-k means clustering algorithm, carries out a cluster analysis of the college basketball teaching situation, and explores the current college basketball teaching level. On this basis, this paper designs a new model of college basketball teaching based on SPOC, and at the same time applies it to a college, and proves the teaching effect of the model through a controlled experiment. The experimental results show that the experimental group and the control group of free throw line one minute shooting test and interest in basketball sports comparison results P value is less than 0.05, proving that this paper SPOC basketball teaching mode is more conducive to improve the students’ basic basketball technical level compared with the traditional teaching mode, and more able to stimulate the students’ love for basketball as a sport. The new model of college basketball teaching based on SPOC designed in this paper is of great significance for improving the quality of college basketball teaching.