A System Architecture for Affective Meta Intelligent Tutoring Systems

Javier Gonzalez-Sanchez, Maria Elena Chavez-Echeagaray, Kurt VanLehn, Winslow Burleson, Sylvie Girard, Yoalli Hidalgo-Pontet et al.

Intelligent Tutoring Systems (ITSs) constitute an alternative to expert human tutors, providing direct customized instruction and feedback to students. ITSs could positively impact education if adopted on a large scale, but doing that requires tools to enable their mass production. This circumstance is the key motivation for this work. We present a component-based approach for a system architecture for ITSs equipped with meta-tutoring and affective capabilities. We elicited the requirements that those systems might address and created a system architecture that models their structure and behavior to drive development efforts. Our experience applying the architecture in the incremental implementation of a four-year project is discussed.

The final publication is available at Springer via https://doi.org/10.1007/978-3-319-07221-0_67.