Assessing differences in flow state induced by an adaptive music learning software
This work addresses the challenge of enhancing flow state in beginner musicians using adaptive technology, representing an incremental improvement in educational tools.
The study tackled the problem of making music learning more enjoyable by applying flow theory and game design principles to an adaptive software, finding that feedback and difficulty scaling helped achieve flow, with effects more pronounced for participants with more music experience.
Technology can facilitate self-learning for academic and leisure activities such as music learning. In general, learning to play an unknown musical song at sight on the electric piano or any other instrument can be quite a chore. In a traditional self-learning setting, the musician only gets feedback in terms of what errors they can hear themselves by comparing what they have played with the score. Research has shown that reaching a flow state creates a more enjoyable experience during activities. This work explores whether principles from flow theory and game design can be applied to make the beginner's musical experience adapted to their need and create higher flow. We created and evaluated a tool oriented around these considerations in a study with 21 participants. We found that provided feedback and difficulty scaling can help to achieve flow and that the effects get more pronounced the more experience with music participants have. In further research, we want to examine the influence of our approach to learning sheet music.