The in-depth application of big data technology to the information classroom of music education in colleges and universities can help education managers accurately grasp the dynamics of students’ thoughts and behaviors so as to clarify the direction and focus of education management. This paper takes the intelligent body as the “new subject” in the information classroom, integrates the “knowledge structure”, and provides an opportunity for students to realize their creative learning potential. It interprets the concept of big data from multiple perspectives and grasps the application of big data technology in the field of education. The entropy analysis method is used to depict the discrete degree of learning time and achievement in the information-driven classroom of college music education. K-means and Apriori association rule algorithms in big data technology are integrated into the college music information technology classroom to visualize learning behavior data in the classroom. Through the analysis of learning behavior data, it was found that the distribution of students’ scores in the informatized classroom is mainly between 70 and 90 points, and the teaching effect is better. Students generally have “delayed” in completing homework, and the learning effect is positively correlated with the number of logins and the time of informatized learning. The results of the study have certain reference significance for realizing the goal of education information technology construction in colleges and universities.