Applied Mathematics and Nonlinear Sciences
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Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 10, Issue 1


Published
on

March 19, 2025


Pages


DOI

Article

Constructing a Differentiation System for Music Teaching Based on Multiple Intelligences and Learning Style Models

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Authors

Bo Zhang Affiliation:
Art College, Puyang Vocational and Technical College, Puyang, Henan, 457000, China.


Abstract

This study aims to construct a music teaching differentiation system based on the Multiple Intelligences and Learning Styles model to accommodate the music learning needs and preferences of different students. Through the multiple intelligences theory and learning styles theory, a multidimensional teaching framework is proposed to design a music differentiation teaching strategy from the levels of music teaching materials, teaching process, and teaching assessment. The teaching experiment under the strategy was implemented in an art college, and the experiment was summarized as follows: the system constructed in this paper can improve students’ mastery of music theory knowledge, and the experimental class improves the theoretical score by 5.56 compared with the control class, which is a significant difference, and the differentiated teaching has a positive impact on the state of students’ music learning. Students’ attitude towards music learning has the strongest influence on their music ability, and its increase by one unit raises music ability by 0.521. In addition, students’ average satisfaction with differentiated teaching is 4.458, indicating that the differentiated system constructed in this paper is feasible in music teaching.


Keywords

Multiple Intelligences, Learning Styles, Differentiated System, Music Teaching, 03C65


Citation

Zhang, B. (2025). Constructing a differentiation system for music teaching based on multiple intelligences and learning style models. Applied Mathematics and Nonlinear Sciences, 10(1). https://doi.org/10.2478/amns-2025-0505

Published by: Engineering Journals

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