Critically slow learning in flashcard learning models

Algorithmic education theory examines, among other things, the trade-off between reviewing old material and studying new material: time spent learning the new comes at the expense of reviewing and solidifying one’s understanding of the old. This trade-off is captured in the “Slow Flashcard System” (SFS) - a system that has been studied not only for its applications in educational software but also for its critical properties; it is a simple discrete deterministic system capable of remarkable complexity, with standing conjectures regarding its longterm behavior. Here, we introduce a probabilistic model of SFS and further derive a continuous time, continuous space partial differential equation model. These two models of SFS shed light on the longterm behavior of SFS and open new avenues of research.