Supporting music production education through Artificial Intelligence tools

Educating musicians in music production necessitates student engagement with a wide range of music technologies. It also involves the development of specific knowledge regarding techniques, theoretical application and the technical operation of these tools. Supporting students to navigate the complexities of engagement with such a diverse range of practice-based activities is relevant to supporting music production education. Developing a range of strategies to support student learning can be beneficial to curriculum delivery design. The fluidity of learning enabled through online access to on-demand information extends the scope of possibility regarding when and where learning occurs. Engagement with using music technology tools can involve knowledge and skill development as part of the process of music production. In practice-based activities like music production, the processes of learning and creating have become interchangeable. Previous studies have investigated how just-in-time resources can be utilised to support music production education using mobile or other information technologies. Just-in-time resources can improve student engagement by making learning more accessible, personalised and relevant to their current focus. Generative artificial intelligence tools have exhibited potential for extending the sophistication, scope and application of engagement with just-in-time learning. The design of just-in-time learning resources that harness the power of artificial intelligence tools has enhanced the potential of supporting resources for practice-based activities like music production. This chapter revisits the key design principles of just-in-time learning identified through previous studies and discusses exploratory opportunities for just-in-time learning to be expanded by the addition of artificial intelligence tools.