Apprentissage automatique à partir de traces multi-sources hétérogènes pour la modélisation de connaissances perceptivo-gestuelles

Abstract : Perceptual-gestural knowledge is multimodal : they combine theoretical and perceptual and gestural knowledge. It is difficult to capture in Intelligent Tutoring Systems. In fact, its capture in such systems involves the use of multiple devices or sensors covering all the modalities of underlying interactions. The "traces" of these interactions -also referred to as "activity traces"- are the raw material for the production of key tutoring services that consider their multimodal nature. Methods for "learning analytics" and production of "tutoring services" that favor one or another facet over others, are incomplete. However, the use of diverse devices generates heterogeneous activity traces. Those latter are hard to model and treat.My doctoral project addresses the challenge related to the production of tutoring services that are congruent to this type of knowledge. I am specifically interested to this type of knowledge in the context of "ill-defined domains". My research case study is the Intelligent Tutoring System TELEOS, a simulation platform dedicated to percutaneous orthopedic surgery.The contributions of this thesis are threefold : (1) the formalization of perceptual-gestural interactions sequences; (2) the implementation of tools capable of reifying the proposed conceptual model; (3) the conception and implementation of algorithmic tools fostering the analysis of these sequences from a didactic point of view.
Document type :
Theses
Complete list of metadatas

Cited literature [172 references]  Display  Hide  Download

https://tel.archives-ouvertes.fr/tel-01370337
Contributor : Abes Star <>
Submitted on : Thursday, September 22, 2016 - 1:54:07 PM
Last modification on : Thursday, October 11, 2018 - 8:48:02 AM

File

TOUSSAINT_2015_archivage.pdf
Version validated by the jury (STAR)

Identifiers

  • HAL Id : tel-01370337, version 1

Collections

Citation

Ben-Manson Toussaint. Apprentissage automatique à partir de traces multi-sources hétérogènes pour la modélisation de connaissances perceptivo-gestuelles. Intelligence artificielle [cs.AI]. Université Grenoble Alpes, 2015. Français. ⟨NNT : 2015GREAM063⟩. ⟨tel-01370337⟩

Share

Metrics

Record views

1024

Files downloads

703