Personnel
Overall Objectives
Research Program
Application Domains
Highlights of the Year
New Software and Platforms
New Results
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
Dissemination
Bibliography
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Section: Bilateral Contracts and Grants with Industry

Bilateral Grants with Industry

Intelliquiz Carnot Project

Participants : Oscar Rodríguez Rocha, Catherine Faron Zucker.

Partner: GAYAtech/QWANT.

This project started in March 2017. It is a joint project with Gayatech (now acquired by QWANT) on the automatic generation of quizzes from the Web of Data. It is a continuation of a former collaborative project with GAYAtech on the recommendation of pedagogical resources based on ontology-based modelling and processing.

Based on example quizzes extracted from the famous game Les Incollables card game, we are proposing an approach to develop quizzes from a domain ontology and we are experimenting on the geographical domain for primary school students.

Inria LabCom EduMICS

Participants : Catherine Faron Zucker, Geraud Fokou Pelap, Olivier Corby, Fabien Gandon, Alain Giboin.

Partner: Educlever.

EduMICS (Educative Models Interactions Communities with Semantics) is a joint laboratory (LabCom, 2016-2018) between the Wimmics team and the Educlever company. Adaptive Learning, Social Learning and Linked Open Data and links between them are at the core of this LabCom. The purpose of EduMICS is both to develop research and technologies with the ultimate goal to adapt educational progressions and pedagogical resource recommendation to learner profiles.

During the first year of the project we worked on developing light-weight ontologies and thesaurus to capture the Educlever ontological knowledge and we annotated the pedagogical resources of the Educlever solution. Then we developed a benchmark and showed that Semantic Web solutions can be deployed within their industrial context. In the continuation of this first step of the project, we will show the added value of Semantic Web modelling enabling ontology-based reasoning on the acquired knowledge graph.