An empirical study of AI-assisted teaching method in music education based on multiple intelligences theory

被引:0
|
作者
Department of Education, Zhengzhou College of Finance and Economics, Henan, Zhengzhou [1 ]
450000, China
机构
[1] Department of Education, Zhengzhou College of Finance and Economics, Henan, Zhengzhou
来源
Appl. Math. Nonlinear Sci. | 2024年 / 1卷
关键词
CRF subwording; Multiple intelligences theory; Music education; Natural language processing; Problem recognition;
D O I
10.2478/amns-2024-3282
中图分类号
学科分类号
摘要
In the process of researching innovative methods of music teaching, this paper takes the theory of multiple intelligences as the theoretical support of AI-assisted teaching methods to assist music teaching design ideas. The multiple intelligence theory is used to propose an auxiliary Q&A system for music education. After conducting basic theoretical research on the seven dimensions of the multiple intelligence theory, the preliminary design of the auxiliary Q&A method for music education is carried out, and finally, an auxiliary Q&A system for music teaching is proposed, which mainly consists of four major modules, namely, question-answering, question-retrieval, question-browsing, and backstage management. Through empirical testing, this paper concludes that in the post-test comparison experiment of the intelligence of students in the experimental class and the control class, the experimental class students' bodily-kinesthetic intelligence and musical intelligence, etc., have been significantly improved (P<0.01). © 2024 Pengyan Chen, published by Sciendo.
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