From Heterogeneous Multisource Traces to Perceptual-Gestural Sequences: the PeTra Treatment Approach

  • Ben-Manson Toussaint
  • Vanda Luengo
  • Francis Jambon
  • Jérôme Tonetti
Conference paper

DOI: 10.1007/978-3-319-19773-9_48

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9112)
Cite this paper as:
Toussaint BM., Luengo V., Jambon F., Tonetti J. (2015) From Heterogeneous Multisource Traces to Perceptual-Gestural Sequences: the PeTra Treatment Approach. In: Conati C., Heffernan N., Mitrovic A., Verdejo M. (eds) Artificial Intelligence in Education. AIED 2015. Lecture Notes in Computer Science, vol 9112. Springer, Cham

Abstract

This paper presents PeTra, a framework proposed for representing and treating multi-source heterogeneous traces from simulated learning environments. We tested our proposition on traces from TELEOS, a simulation-based ITS dedicated to percutaneous orthopedic surgery. This ITS captures learners interactions from three different and independent sources. The conducted experiment demonstrated that the sequences generated by PeTra fostered efficiently: 1) the learning analytics task of evaluating the influence of visual perceptions on learners’ errors; 2) the extraction of interesting association rules potentially reusable for tutoring services production. However, its genericity has not been tested and it will need to be evaluated at a larger scale.

Keywords

Intelligent Tutoring Systems Knowledge modeling Perceptual-gestural knowledge Educational data mining Heterogeneous traces 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Ben-Manson Toussaint
    • 1
    • 2
  • Vanda Luengo
    • 1
  • Francis Jambon
    • 1
  • Jérôme Tonetti
    • 3
  1. 1.Université Grenoble AlpesSt-Martin D’HèresFrance
  2. 2.Ecole Supérieure D’Infotronique D’HaïtiPort-Au-PrinceHaïti
  3. 3.Département Orthopédie-TraumatologieCHU de GrenobleLa TroncheFrance

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