Problems and Development Strategies of Music Education in Primary and Secondary Schools Based on Network Information Technology
Main Article Content
Abstract
Music education has traditionally followed a one-size-fits-all approach, often failing to address the diverse needs and preferences of individual students. A recommender system for music education is a specialized software or algorithm that helps students, educators, or music enthusiasts discover and access relevant music content, learning materials, or educational resources. This paper introduces the Graph Theory-based Information Technology(GTIT) music learning system, a revolutionary platform designed to personalize music education. The GTIT system leverages advanced technology, data-driven recommendations, and social learning networks to enhance the musical journey for students. The proposed GTIT model uses the graph theory-based music education model for the estimation of the data features with information technology. The proposed GTIT model comprises the stacked recommender model for the classification of the appropriate features in the music education data. The data for the analysis of the proposed GTIT model is collected for the existing sources. With the extracted features the recommender system is designed for the classification and recommendation of the features related to the music education. The proposed model explores the key components of the GTIT system, including the assessment of students' musical preferences, skill levels, and learning patterns. These factors are analyzed to provide tailored music recommendations that keep students engaged and motivated. Additionally, the GTIT system employs graph theory to create connections among students, fostering collaboration and social learning. Simulation results reveals that students who engage with the learning system experience significant improvements in their musical skills and knowledge. The personalized recommendations and collaborative learning environment contribute to enhanced skill development and musical progress. Moreover, the sense of community established by the system encourages peer interaction and mentorship. This paper provides a comprehensive overview of the GTIT music education system's impact on students' learning experiences, skill development, and collaborative efforts. The analysis expressed the transformative potential of personalized recommendations and networked learning environments in music education. The GTIT system serves as a model for the future of music instruction, offering a promising approach for educators and institutions seeking to provide engaging and personalized music education.
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