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Développement d'une ontologie pour l'analyse d'observables de l'apprenant dans le contexte d'une tâche avec des robots modulaires

Lisa Roux 1 Margarida Romero 1 Frédéric Alexandre 2 Thierry Viéville 2, 1 Chloé Mercier 2
1 LINE - Laboratoire d'Innovation et Numérique pour l'Education
UNS - Université Nice Sophia Antipolis (... - 2019), UCA - Université Côte d'Azur : URE201622216H
2 Mnemosyne - Mnemonic Synergy
LaBRI - Laboratoire Bordelais de Recherche en Informatique, Inria Bordeaux - Sud-Ouest, IMN - Institut des Maladies Neurodégénératives [Bordeaux]
Abstract : The aim of this document is to present the design of an ontology allowing to carry out a modeling of the learner, the task and the observables during a learning activity, in order to develop a model applicable to the observed learning analytics which can be exploited to analyze them with computational approaches. The challenge here is to work from a relatively small batch of data (a few dozen to compare with the thousands of data used with classic statistical methods), highly structured, therefore to introduce a maximum of a priori information upstream to the analysis in order the results to be meaningful. The learner is modeled on the basis of knowledge from the educational science and cognitive neurosciences, including machine learning formalisms, in the very precise framework of a task, named CreaCube, related to initiation to computational thinking presented as an open-ended problem, which involves solving a problem and appealing to creativity. This document presents these elements and discusses the exploration and exploitation issues, the different goals (for example of performance, speed or mastery of the task), before relating this to the different types of memory and discussing the basics of problem solving, including engaging in a learning activity. It then describes the very precise construction of an ontology which formalizes this process of task resolution and knowledge construction, taking into account the stimuli received, the discovery of affordances, the setting of hypotheses, clearly distinguished from the notion of belief, without forgetting contextual knowledge. The production is shared as a free and open resource, and both the implications and the perspectives of this pioneering work of formalizing such a human learning task are discussed in conclusion. This research report and ontology corresponds to the short Post Doc research work of Lisa Roux, who is also the main author of the document, supervised by Margarida Romero and Frédéric Alexandre and was carried out within the framework of the Aex AIDE project supported by the Otesia Observatory of Technological, Economic and Societal impacts of Artificial Intelligence and Digital Technology.
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Submitted on : Wednesday, February 24, 2021 - 1:50:41 PM
Last modification on : Friday, January 21, 2022 - 3:11:48 AM


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  • HAL Id : hal-03013685, version 2


Lisa Roux, Margarida Romero, Frédéric Alexandre, Thierry Viéville, Chloé Mercier. Développement d'une ontologie pour l'analyse d'observables de l'apprenant dans le contexte d'une tâche avec des robots modulaires. [Rapport de recherche] RR-9376, Inria. 2020, pp.48. ⟨hal-03013685v2⟩



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