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A Model for Student Action Prediction in 3D Virtual Environments for Procedural Training
Year:2015
Research Areas
  • Information technology and adata processing
Information
Abstract
This paper presents a predictive student action model, which uses student logs generated by a 3D virtual environment for procedural training to elaborate summarized information. This model can predict the most common behaviors by considering the sequences of more frequent actions, which is useful to anticipate common student? errors. These logs are clustered based on the number of errors made by each student and the total time that each student spent to complete the entire practice. Next, for each cluster an extended automata is created, which allows us to generate predictions more reliable to each student type. In turn, the action prediction based on this model helps an intelligent tutoring system to generate students? feedback proactively.
International
Si
Congress
8th International Conference on Educational Data Mining EDM 2015
960
Place
Madrid, España
Reviewers
Si
ISBN/ISSN
978-84-606-9425-0
Start Date
26/06/2015
End Date
29/06/2015
From page
614
To page
615
Proceedings of the 8th International Conference on Educational Data Mining
Participants
  • Autor: Diego Riofrío Luzcando (UPM)
  • Autor: Jaime Ramirez Rodriguez (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Interacción Persona Ordenador y Sistemas Interactivos Avanzados
  • Departamento: Lenguajes y Sistemas Informáticos e Ingeniería de Software
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