Assistance in Building Student Models using Knowledge Representation and Machine Learning

Sébastien Lallé 1 Vanda Luengo 2 Nathalie Guin 3
2 MeTAH
LIG - Laboratoire d'Informatique de Grenoble
3 SILEX - Supporting Interaction and Learning by Experience
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : We propose a method and a first authoring tool to assist the design and implementation of diagnostic techniques. This method is independent from the domain and allows building more than one technique at once. The method is based on knowledge representation and a semi-automatic machine learning algorithm. We tested the method in two domains, surgery and reading English. Techniques built with our method beat the majority class in terms of accuracy.
Type de document :
Communication dans un congrès
H. Chad Lane, Kalina Yacef, Jack Mostow, Philip Pavlik. AIED 2013 - 16th International Conference on Artificial Intelligence in Education, Jul 2013, Memphis, TN, United States. Springer, 7926, pp.754-757, 2013, Lecture Notes in Computer Science (LNCS). 〈10.1007/978-3-642-39112-5_105〉
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https://hal.archives-ouvertes.fr/hal-00871569
Contributeur : Denis Bouhineau <>
Soumis le : mardi 15 octobre 2013 - 18:37:57
Dernière modification le : jeudi 19 avril 2018 - 14:38:05

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Sébastien Lallé, Vanda Luengo, Nathalie Guin. Assistance in Building Student Models using Knowledge Representation and Machine Learning. H. Chad Lane, Kalina Yacef, Jack Mostow, Philip Pavlik. AIED 2013 - 16th International Conference on Artificial Intelligence in Education, Jul 2013, Memphis, TN, United States. Springer, 7926, pp.754-757, 2013, Lecture Notes in Computer Science (LNCS). 〈10.1007/978-3-642-39112-5_105〉. 〈hal-00871569〉

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