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Memorias de investigación
Artículos en revistas:
Predicting Student Actions in a Procedural Training Environment
Año:2017
Áreas de investigación
  • Informática aplicada
Datos
Descripción
Data mining is known to have a potential for predicting user performance. However, there are few studies that explore its potential for predicting student behavior in a procedural training environment. This paper presents a collective student model, which is built from past student logs. These logs are firstly grouped into clusters. Then an extended automaton is created for each cluster based on the sequences of events found in the cluster logs. The main objective of this model is to predict the actions of new students for improving the tutoring feedback provided by an intelligent tutoring system. The proposed model has been validated using student logs collected in a 3D virtual laboratory for teaching biotechnology. As a result of this validation, we concluded that the model can provide reasonably good predictions and can support tutoring feedback that is better adapted to each student type.
Internacional
Si
JCR del ISI
Si
Título de la revista
Ieee Transactions on Learning Technologies
ISSN
1939-1382
Factor de impacto JCR
1,22
Información de impacto
Datos JCR del año 2013
Volumen
DOI
10.1109/TLT.2017.2658569
Número de revista
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1
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Participantes
  • Autor: Diego Riofrío Luzcando (UPM)
  • Autor: Jaime Ramirez Rodriguez (UPM)
  • Autor: Marta Berrocal Lobo (UPM)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Departamento: Sistemas y Recursos Naturales
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