Citation:
Muñoz-Merino, P. J., Ganzález Novillo, R. y Delgado Kloos, C. (2018). Assessment of skills and adaptive learning for parametric exercises combining knowledge spaces and item response theory. Applied Soft Computing, 68, pp. 110-124.
xmlui.dri2xhtml.METS-1.0.item-contributor-funder:
Comunidad de Madrid Ministerio de Economía y Competitividad (España)
Sponsor:
This work was supported by the Smartick company (project entitled “ANÁLISIS, EVOLUCIÓN, PROPUESTAS DE MEJORA y DESARROLLO DEL SISTEMA DE APRENDIZAJE ADAPTATIVOY ANALÍTICA DEL APRENDIZAJE DE LA PLATAFORMA SMARTICK”), by the Madrid Regional Government(eMadrid project, grant number S2013/ICE-2715), and by the Spanish Ministry of Economy and Competiveness (Smartlet project,grant number TIN2017-85179-C3-1-R) funded by the Agencia Estatal de Investigación (AEI) and Fondo Europeo de Desarrollo Regional (FEDER).
Project:
Comunidad de Madrid. S2013/ICE-2715 Gobierno de España. TIN2017-85179-C3-1-R
Many computer systems implement different methods for the estimation of students' skills and adapt the generated exercises depending on such skills. Knowledge Spaces (KS) is a method for curriculum sequencing but fine-grained decisions for selecting next exercMany computer systems implement different methods for the estimation of students' skills and adapt the generated exercises depending on such skills. Knowledge Spaces (KS) is a method for curriculum sequencing but fine-grained decisions for selecting next exercises among the candidates are not taken into account, which can be obtained with the application of techniques such as Item Response Theory (IRT).[+][-]