title: A model for student action prediction in 3D virtual environments for procedural training
creator: Riofrío Luzcando, Diego
creator: Ramírez Rodríguez, Jaime
subject: Computer Science
description: This paper presents a predictive student actionmodel, 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 con- sidering 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 stu- dent and the total time that each student spent to complete the entire practice. Next, for each cluster an extended au- tomata is created, which allows us to generate predictions more reliable to each student type. In turn, the action pre- diction based on this model helps an intelligent tutoring sys- tem to generate students? feedback proactively.
publisher: E.T.S. de Ingenieros Informáticos (UPM)
rights: https://creativecommons.org/licenses/by-nc-nd/3.0/es/
date: 2015
type: info:eu-repo/semantics/conferenceObject
type: Presentation at Congress or Conference
source: EDM 2015: proceedings of the 8th International Conference on Educational Data Mining | 8th International Conference on Educational Data Mining | 26-29 Jun 2015 | Madrid, España
type: PeerReviewed
format: application/pdf
language: eng
relation: http://www.educationaldatamining.org/EDM2015/index.php?page=proceedings
rights: info:eu-repo/semantics/openAccess
identifier: https://oa.upm.es/41758/