A computational model for physics learning
Florin Bocaneala · AIP conference proceedings · 2004
In this paper we test the versatility of the neural network approach to modeling the dynamics of student learning. We choose a problem from an introductory physics class and we construct a neural network model for it. Based on this simulation, we argue for the future use of neural network models in Physics Education Research and what this approach can teach us about how physics learning takes place.