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.
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Acknowledgements
This work has been partially funded by the Agencia Estatal de Investigación (AEI) and Fondo Europeo de Desarrollo Regional (FEDER) within the MERINET project: TIN2016-76843-C4-2-R (AEI/FEDER, EU). Sonia G. Sosa-León thanks the support granted by PRODEP (México) through a scholarship with folio UNISON-344. Julio Waissman thanks the Universidad Castilla - La Mancha for its funding through the support program for visiting professors.
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Sosa-León, S., Waissman, J., Olivas, J.A., Prieto, M.E. (2018). Estimation of Skill Level in Intelligent Tutoring Systems Using a Multi-attribute Methodology. In: Mata-Rivera, M., Zagal-Flores, R. (eds) Telematics and Computing . WITCOM 2018. Communications in Computer and Information Science, vol 944. Springer, Cham. https://doi.org/10.1007/978-3-030-03763-5_22
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DOI: https://doi.org/10.1007/978-3-030-03763-5_22
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