The Growth of Contemporary Music Subject and the Reform of Music Teaching in Universities

• Published in: International journal of web-based learning and teaching technologies Vol. 19; no. 1; pp. 1 - 15
• Main Authors: Zhao, Binbin, Razzouk, Rim
• Format: Journal Article
• Language: English
• Published: Hershey IGI Global 2024
• Subjects: Algorithms; Art Expression; Collaboration; Colleges & universities; Data mining; Education; Educational Change; Educational Resources; Equipment and supplies; Identity formation; Influence of Technology; Instructional Materials; Internet; Learning; Methods; Music; Music Education; Music in education; Music Teachers; Music Theory; Musical Instruments; Musical performances; Periodicals; Recommender systems; Reforms; School Culture; Social Development; Sparse matrices; Sparsity; Student Characteristics; Students; Study and teaching; Talent Development; Teachers; Teaching; Technical services; Universities; Universities and colleges; World Problems
• ISSN: 1548-1093; 1548-1107
• DOI: 10.4018/IJWLTT.338362

In order to promote the growth of contemporary music and the reform of music, this article designs an improved collaborative filtering (CF) algorithm to solve the problem of sparse matrix in traditional recommendation algorithms. The data matrix is dimensionally reduced to find the nearest neighbor, so as to realize personalized recommendation of music teaching resources in colleges and universities. The test results show that the accuracy of the proposed teaching resource recommendation algorithm is improved by 22.56% compared with the traditional CF algorithm. The improved CF algorithm can provide more accurate prediction, and the recommendation effect of the improved algorithm is better than the original algorithm, which can effectively avoid the sparse matrix problem faced by the CF algorithm, and provide technical support for the development of contemporary music discipline and the reform of music discipline.