Bruner’s enactive stage and Montessori’s materials both understand that abstract concepts must be grounded in physical experience before symbols can carry weight. The touchscreen skips that stage entirely — and the learning data are beginning to show it.
On 2 December 2024 I gave three workshops at HfMT Köln’s Thementag on AI and music education. The handouts covered data protection, AI tools for students, and AI in teaching. This post is the argument behind them — focused on the curriculum question that none of the tools answer on their own: what should change, and what should not?
A third post in the networked music performance series. Technical latency is solved. Institutional infrastructure has a name. What students actually learn — and what conservatoire curricula consistently get wrong about teaching it — turns out to be a different problem entirely.
Every ensemble faces the same physical problem: N oscillators with slightly different natural frequencies trying to synchronise through a shared coupling channel. The Kuramoto model — developed by a statistical physicist to describe fireflies, neurons, and power grids — applies directly to musicians. It predicts a phase transition between incoherence and synchrony, quantifies why latency destroys networked ensemble performance, and connects to recent EEG studies of inter-brain synchronisation.