Learning content sequencing in an educational environment according student needs
Ana M. Iglesias, Paloma Martı́nez, Ricardo Aler, Fernando Fernández · 2004
Abstract. One of the most important issues in educational systems is to define effective teaching policies according to the students learning characteristics. This paper proposes to use the Reinforcement Learning (RL) model in order for the system to learn automatically sequence of contents to be shown to the stu-dent, based only in interactions with other students, like human tutors do. An initial clustering of the students according to their learning characteristics is proposed in order the system adapts better to each student. Experiments show convergence to optimal teaching tactics for different clusters of simulated stu-dents, concluding that the convergence is faster when the system tactics have been previously initialised. 1