Practical Teaching and Intellectualization of University Courses Based on the Maximum Information Entropy Model

Abstract

Abstract Traditional teaching has become a thing of the past, the integration of technology and the classroom has brought about significant changes in education, and the role of information entropy in teaching has gradually manifested itself. In this paper, the behavioral time occupancy of the teaching process of university courses is viewed as a probability distribution event combined with the Lagrange multiplier method to solve the maximum entropy value in the distribution of practical teaching behavior. The practice depth value of classroom behavior can be calculated using the interaction behavior coefficient and interaction behavior entropy. Apply the information entropy to the practical teaching analysis of university courses, verify the practical effect of university courses from different sides, and carry out intelligent course construction according to the current situation of students’ learning behavior. The results show that the average score of class 3 in the practical analysis ability assessment is 4.021, which indicates that the practical analysis ability of students in the class meets the standard, and the students’ practical execution should be mainly cultivated in the later practical teaching. 67.1% of students believe that the intelligent classroom has improved their performance over the traditional classroom according to the intelligent course model.