Kunstig intelligens i musikundervisning

Abstract

This master thesis investigates the application of Artificial Intelligence (AI) in music di-dactic practices in the Danish equivalent of primary and secondary school. The aim is to understand music teachers’ perception of music didactic practices and whether the teachers see potential in the application of AI. Furthermore, the thesis investigates to what extent AI technologies can enhance music education and students’ competencies within music. To analyse music teachers’ perception of their music didactic practice, the paper introduces Finn Holst’s (2022) understanding of music didactics with a reference to Hartmut Rosa’s (2019) theory of resonance. In addition, the thesis utilises Knud Illeris’ (2011; 2015) theories on learning and competency development. The theories on music didactics and resonance are primarily used in the analysis of transcribed interviews with three different music teach-ers, while the theories on learning and competency development are applied throughout the entire analysis, with a greater emphasis on the examination of two distinct music lessons: one involving AI and one without any AI technology. The findings indicate that AI technologies can partake in music lessons where children ac-quire competencies in music creation. Specifically, students may benefit from AI technology when learning to write songs, particularly if they lack the skills to compose chord progres-sions. Simultaneously, the interviewed music teachers seem interested in using AI technolo-gy, and they seem to perceive AI as a useful tool for various music lessons. However, the results also highlight the need for a critical approach to the implementation of AI, as it can challenge children’s learning outcomes if it replaces students' use of instruments, thereby depriving them of learning opportunities. The conclusion is that while AI can be relevant in music didactic practice, a beneficial im-plementation depends on the music teacher’s planning. When planning AI-assisted music lessons, music teachers can carefully consider the intended learning outcomes to minimise the risk of depriving students of valuable learning opportunities. Finally, learning processes regarding AI will most likely happen for students because of the rapid development and popularity of the technology, which is why the paper argues for a greater didactic interest in the involvement of AI in lessons across various subjects.

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A master thesis from Aalborg University

Kunstig intelligens i musikundervisning

[Artificial intelligence in music lessons]