Classification Hiérarchique Implicative et Cohésitive selon la mesure MGK - Application en didactique de l'informatique

Abstract : Statistical Implcative Analysis (SIA) is a data analysis tool initially dedicated to research in didactic disciplines. In this thesis we realize the implementation on a programming language of the new dendrogram construction algorithms representing the cohesive and implicative hierarchical classification according to the new cohesion based on MGK. This work also includes the use of the software tool thus developed on data, allowing us to analyze curricula of computer science in the Anglo-Saxon model, compared to the computer science curriculum of ENSET. The analysis obtained allowed us to create and adapt a new curriculum of computer science, and more particularly the algorithmic and programming in second class at the College of Madagascar. As, youth training requires a new thinking approach « modelling, algorithmic and organizational » that is a computer thinking related to the science of information processing. This computer program is in this case taken as a prerequisite for students who would like to continue the computer science course at the higher level. We also propose in this work some algorithmic and programming learning methods using the SCRATCH software taking into account the two components that seem to us inevitable, « Community and ICT » in the pedagogical system.
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https://tel.archives-ouvertes.fr/tel-02172222
Contributor : Hery Frédéric Rakotomalala <>
Submitted on : Wednesday, July 3, 2019 - 3:51:29 PM
Last modification on : Tuesday, September 17, 2019 - 10:37:35 AM

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Hery Frédéric Rakotomalala. Classification Hiérarchique Implicative et Cohésitive selon la mesure MGK - Application en didactique de l'informatique. Education. Université d'Antanarivo, 2019. Français. ⟨tel-02172222⟩

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