Student Action Prediction for Automatic Tutoring for Procedural Training in 3D Virtual Environments

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dc.conference.date2015-09-16
dc.conference.placeNovedrate
dc.conference.titleE-Learning, E-Education, and Online Training. eLEOT
dc.contributor.authorDiego Riofrío-Luzcando
dc.contributor.authorJaime Ramírez
dc.date.accessioned2026-02-24T14:27:00Z
dc.date.issued2016-01-14
dc.description.abstractThis paper presents a way to predict student actions, by using student logs generated by a 3D virtual environment for procedural training. Each student log is categorized in a cluster based on the number of errors and the total time spent to complete the entire practice. For each cluster an extended automata is created, which allows us to generate more reliable predictions according to each student type. States of this extended automata represent the effect of a student correct or failed action. The most common behaviors can be predicted considering the sequences of more frequent actions. This is useful to anticipate common student errors, and this can help an Intelligent Tutoring System to generate feedback proactively.
dc.description.departmentMétodos Cuantitativos
dc.identifier.citationRiofrío-Luzcando, D., Ramírez, J. (2016). Student Action Prediction for Automatic Tutoring for Procedural Training in 3D Virtual Environments. In: Vincenti, G., Bucciero, A., Vaz de Carvalho, C. (eds) E-Learning, E-Education, and Online Training. eLEOT 2015. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 160. Springer, Cham. https://doi.org/10.1007/978-3-319-28883-3_25
dc.identifier.doi10.1007/978-3-319-28883-3_25
dc.identifier.urihttps://hdl.handle.net/20.500.14861/70
dc.language.isoeng
dc.page.final207
dc.page.initial200
dc.relation.publisherversionhttps://link.springer.com/chapter/10.1007/978-3-319-28883-3_25
dc.rights.accessRightsopen access
dc.subject.keywordIntelligent Tutoring Systems
dc.subject.keywordEducational Data Mining
dc.subject.keyworde-learning
dc.subject.keywordProcedural training
dc.subject.keywordVirtual environments
dc.titleStudent Action Prediction for Automatic Tutoring for Procedural Training in 3D Virtual Environments
dc.typeconference output

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