The Intersection of Technology and Art: A Study on AI-Driven CTCL Music Teaching Paradigm

Abstract

This research investigates the influence of the AI-supported CTCL teaching model on students' music literacy, focusing on its practical application in music education. The study involved 88 music majors, whose abilities were analyzed using the radial basis function (RBF) algorithm. The comparison between the experimental and control groups focused on music interest and core musical skills. The results demonstrate that the experimental group showed marked improvements in areas such as music aesthetics, artistic expression, creative practice, and cultural comprehension. These findings affirm the CTCL teaching model’s effectiveness in boosting students' music literacy across multiple dimensions. Particularly, the model excels at cultivating artistic creativity and enriching students' cultural understanding. This study underscores the importance of merging the CTCL model with AI algorithms, revealing its positive influence on students' musical development and providing valuable insights for enhancing music education practices.