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, Lishan Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations


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.

Original languageEnglish (US)
Title of host publicationIntelligent Tutoring Systems - 12th International Conference, ITS 2014, Proceedings
Number of pages6
ISBN (Print)9783319072203
StatePublished - 2014
Event12th International Conference on Intelligent Tutoring Systems, ITS 2014 - Honolulu, HI, United States
Duration: Jun 5 2014Jun 9 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8474 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference12th International Conference on Intelligent Tutoring Systems, ITS 2014
Country/TerritoryUnited States
CityHonolulu, HI


  • affect
  • architecture
  • component-based
  • meta-tutoring
  • tutoring

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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