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.
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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. https://doi.org/10.1007/978-3-319-19773-9_48
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DOI: https://doi.org/10.1007/978-3-319-19773-9_48
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