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Descripción
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| This 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. | |
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Internacional
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Si |
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Nombre congreso
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2nd EAI International Conference on e-Learning e-Education and Online Training |
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Tipo de participación
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960 |
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Lugar del congreso
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Novedrate, Italia |
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Revisores
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Si |
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ISBN o ISSN
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978-3-319-28882-6 |
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DOI
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10.1007/978-3-319-28883-3_25 |
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Fecha inicio congreso
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16/09/2015 |
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Fecha fin congreso
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18/09/2015 |
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Desde la página
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200 |
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Hasta la página
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207 |
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Título de las actas
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E-Learning, E-Education, and Online Training Volume 160 of the series Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering |