Artificial Intelligence in Music Education.
Systematic Analysis of Computational Research
Keywords:
Artificial intelligence, Atenttion to diversity, Musical education, Computational research, PRISMAAbstract
This study presents a systematic review of research published between 2015 and 2024 on the application of artificial intelligence (AI) in music education, with special attention to its potential to address student diversity. The main objective is to offer a comprehensive view of computational resources and their usefulness in processes such as composition, music analysis, auditory recognition, and learning personalization. The methodology is based on PRISMA guidelines, applying rigorous inclusion and exclusion criteria. A search was conducted in academic databases such as Web of Science, JSTOR, Scopus, and ERIC-EBSCO, using combinations of keywords related to AI, music education, and attention to diversity. After eliminating duplicates and applying the defined filters, eleven studies that met the established requirements were selected. The most notable conclusion is the potential of AI to enrich music teaching and its interest in inclusive reinforcement and in the personalization of the learning process. It is also worth noting that, as motivating and attractive as the benefits of AI may be, this study shows that teaching is necessary and irreplaceable.
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