Research on music teaching content design based on intelligent algorithm optimization under constructivism theory

As an important learning theory, constructivism has received more and more attention and has been widely used in various teaching fields. Under the guidance of constructivism theory, a student-centered music teaching model is constructed to optimize music teaching content with the help of intelligent algorithms from music learner profiling and learning resource design. The K-means are optimized using the topological distance theory, which is used in the characterization of music learners, followed by the use of an improved collaborative filtering recommendation algorithm to realize the recommendation of music resources based on learner characterization. Experiments are conducted with students of a music college as an example, and it is found that the sample students prefer learning resources in the form of videos and are mostly of the type of reflectors (28%), which can be classified into three types of good (46%), excellent (39%) and poor (16%) music learners. The students who used the recommended model of this paper to assist their learning had the most significant change in their music knowledge level after the experiment, with an improvement of 5.3 points, and the best satisfaction evaluation results. Based on the analysis of learners’ characteristics, the use of intelligent algorithms to optimize learning resources in music teaching can promote improvement in music teaching quality.