Estimation of skill level in intelligent tutoring systems using a multi-attribute methodology

Sonia Sosa-León, Julio Waissman*, José A. Olivas, Manuel E. Prieto

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

For the ideal functioning of an intelligent tutoring system it is essential to be able to estimate the level of skill of the students according to complex learning objectives. We propose an architecture for the evaluation of the student’s skill level, based on the multi-attribute utility theory, using as aggregation operator the Choquet integral. The method takes into account the learning objectives raised by the decision maker (academics, school teachers, heads of institutions, etc.) represented by complex relationships that can be found among the criteria considered for the evaluation.

Original languageEnglish
Title of host publicationTelematics and Computing - 7th International Congress, WITCOM 2018, Proceedings
EditorsMiguel Felix Mata-Rivera, Roberto Zagal-Flores
PublisherSpringer Verlag
Pages259-269
Number of pages11
ISBN (Print)9783030037628
DOIs
StatePublished - 2018
Event7th International Congress of Telematics and Computing, WITCOM 2018 - Mazatlán, Mexico
Duration: 5 Nov 20189 Nov 2018

Publication series

NameCommunications in Computer and Information Science
Volume944
ISSN (Print)1865-0929

Conference

Conference7th International Congress of Telematics and Computing, WITCOM 2018
Country/TerritoryMexico
CityMazatlán
Period5/11/189/11/18

Bibliographical note

Publisher Copyright:
© Springer Nature Switzerland AG 2018.

Keywords

  • Choquet integral
  • Intelligent tutoring systems
  • MAUT

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