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

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E-Learning, E-Education, and Online Training (eLEOT 2015)

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Abstract

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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Acknowledgements

I would like to acknowledge Secretariat of Higher Education, Science, Technology and Innovation from Ecuador (SENESCYT) for their economic support.

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Authors and Affiliations

  1. ETSI Informáticos, UPM, Madrid, Spain

    Diego Riofrío-Luzcando & Jaime Ramírez

Authors
  1. Diego Riofrío-Luzcando
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  2. Jaime Ramírez
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Correspondence to Diego Riofrío-Luzcando .

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Editors and Affiliations

  1. University of Baltimore, Baltimore, USA

    Giovanni Vincenti

  2. IBAM - Istituto per i Beni, Italian National Research Council, Roma, Italy

    Alberto Bucciero

  3. Instituto Politécnico do Porto, Porto, Portugal

    Carlos Vaz de Carvalho

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© 2016 Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Riofrío-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

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  • DOI: https://doi.org/10.1007/978-3-319-28883-3_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-28882-6

  • Online ISBN: 978-3-319-28883-3

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