The preceding pages offer only a glimpse into the potential of using random elements in teaching improvisation and bridging the gap between human interaction and playing with a machine. Each of the topics (rhythm, harmony, etc.) could be investigated separately and would require focus groups and extensive testing.
The rhythm exercises, with random elements very similar to those found in video games (which use random events at the core of gameplay), seem the most promising with regard to recent research.1 Other studies point to the potential of using games for rhythmic training.2
I created some of these exercises for my own practice during the two years of MA study and devised other exercises for beginning and intermediate students. While the novelty effect was real and the ease of use and learning objectives were well understood, the main weak point is the amount of time required to create each exercise. The creation steps are as follows, not counting the initial development required to arrive at a working system:
This amount of work would increase when recording real musicians. The input/output ratio needs to be further critically investigated. The system is also well-suited to a collaborative and remote working approach.
A positive and very rewarding aspect of this research was the challenge and enjoyment of creating exercises that use these random elements. Reviewing and inventing typical jazz improvisation exercises—from simple scale and arpeggio practice to more complex upper structure concepts—was rewarding and shone new light on exercises that might often seem repetitive or even stale. Play-along exercises could be made more engaging even through minimal random variations.
Bégel, V., Loreto, I. D., Seilles, A., & Bella, S. D. (2017). Music Games: Potential Application and Considerations for Rhythmic Training. Frontiers in Human Neuroscience, 11. https://doi.org/10.3389/fnhum.2017.00273 ↩︎
Duffy, S., & Pearce, M. (2018). What makes rhythms hard to perform? An investigation using Steve Reich’s Clapping Music. PLOS ONE, 13, 1–33. https://doi.org/10.1371/journal.pone.0205847 ↩︎