Mi, Fei, and Boi Faltings. "Adaptive sequential recommendation for discussion forums on MOOCs using context trees." Proceedings of the 10th international conference on educational data mining. 2017.

As MOOCs gain popularity, discussion forums play a vital role in knowledge exchange between students and instructors. Adapting recommendation systems to rapidly evolving forum content and shifting student preferences is crucial. This study treats the forum recommendation problem as a sequence prediction task and compares various methods, including a novel approach called context tree (CT). The CT method outperforms traditional recommendation techniques by better adapting to changes in forum content and student interests, emphasizing the need for adaptive systems in dynamic online learning environments.