Agile Teaching Framework for Music Education Software Development Curriculum Based on Deep Learning

Abstract

Music learning is changing as a result of high-quality instruction, progressing from shallow to deep learning over time. In-depth learning is a revolutionary teaching paradigm that focuses entirely on the perception and investigation of music by students, allowing them to completely experience the allure of music. It can assist students not only to learn more about music and improve their skills but also to grow their music literacy and improve their musical talent. In this study, a deep-learning-based agile teaching framework is proposed for music education software development courses. The framework is built on the Internet of Things (IoT), and each device is considered an IoT device. Data is recorded and transmitted via the IoT network using the wireless sensor network (WSN). With the use of a genetic algorithm, the WSN Randomized Search Method is employed to execute intelligent music data transfer. For online classes, various music datasets are used, and the performance is examined. The findings of this study demonstrate that the proposed method is effective in teaching music education to students.