Artificial Intelligence in Music Education: A Critical Review

Holland, Simon (2000). Artificial Intelligence in Music Education: A Critical Review. In: Miranda, Eduardo Reck ed. Readings in Music and Artificial Intelligence. Contemporary Music Studies. Routledge, pp. 239–274.

DOI: https://doi.org/10.4324/9780203059746

Abstract

This paper reviews the principal approaches to using Artificial Intelligence in Music Education. Music is a challenging domain for Artificial Intelligence in Education (AI-ED) because music is, in general, an open-ended domain demanding creativity and problem-seeking on the part of learners and teachers. In addition, Artificial Intelligence theories of music are far from complete, and music education typically emphasises factors other than the communication of ‘knowledge’ to students. This paper reviews critically some of the principal problems and possibilities in a variety of AI-ED approaches to music education. Approaches considered include: Intelligent Tutoring Systems for Music; Music Logo Systems; Cognitive Support Frameworks that employ models of creativity; highly interactive interfaces that employ AI theories; AI-based music tools; and systems to support negotiation and reflection. A wide variety of existing music AI-ED systems are used to illustrate the key issues, techniques and methods associated with these approaches to AI-ED in Music.

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