The Practice and Application of Philosophical Thought of Music Education in the Information Age in the Education of College Music Curriculum

Abstract

Taking the philosophical view of music education as an entry point, this paper investigates the relevance of music education and philosophical thought from three aspects, focusing on the compatible philosophical view of music. Based on the random forest algorithm under machine learning, the music data samples are classified, and the algorithm is chosen to be optimized and improved when the dimension of music features is high. Using the extreme gradient boosting algorithm, the model is penalized to avoid the phenomenon of overfitting during the operation process. The RF-XGBoost hybrid music recommendation algorithm is proposed to help students learn personalized music by combining the two models mentioned above. Utilize ICT integration technology to combine music education and information technology in order to create the M-ICTPACK model. Create music simulation experiments to evaluate the impact of the music recommendation model proposed in this paper. Based on the idea of music education and philosophy, design music teaching content that meets the needs of students in colleges and universities and analyze its impact. The results show that in the music simulation recommendation effect, the smallest gap between the recommended musicians and the type of interest of the students is only 0.00001. The same student scores differently in music skills in different periods of music learning, and after 9 months of learning, except for the learning interest score of 79.365, the scores of all other aspects are more than 80. This paper proposes more effective philosophical ideas for music education in music curriculum education.

Keywords

• random forest
• extreme gradient boosting
• rf-xgboost hybrid recommendation algorithm
• mictpack model
• music curriculum education
• 94a08