Research on the Construction of VR Teaching Resource Library for Animation Major in Higher Vocational Colleges Based on Big Data Analysis

In order to further improve the utilization efficiency of VR teaching resources for animation major in higher vocational colleges and perfect the resource library, a personalized teaching resource recommendation algorithm for big data background is proposed, and a personalized teaching resource recommendation list is generated by predicting students' interest. The experimental results show that the average accuracy of the personalized teaching resource recommendation algorithm proposed in this paper is 12.17%, the average recall rate is 25.88%, and the average F1 value is 12.35%, which are significantly higher than those of the traditional user-based collaborative filtering recommendation algorithm and item-based collaborative filtering recommendation algorithm. In addition, as the number of recommended resources increases, the F1 value of the proposed algorithm increases continuously and stably. It can be seen that the personalized teaching resource recommendation algorithm designed in this paper has the best recommendation effect.