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Contributions à l'amélioration de génération des bases des règles d'association MGK-valides et applications en didactique des mathématiques

Abstract : The Statistical Implicative Analysis (SIA) is a very suitable tool for discovering causes and effects in discipline education research . With SIA, the analysis of our data such obtained after an experiment has shown that the simultaneous and balanced use of ICT and blackboard or whiteboard is a fructufull way we can use to achieve the teaching mathematics objectives. The reliability of results of data analysis strongly depends on the used mathematical tool. In case of the SIA, it depends on the quality of the used measurements. We choose dealing with both measurement Support and MGK, because the unique active component of MGK is implicative, such property being requered in SIA. The number of valid rules by any measure can be very huge because of many redundant rules. This situation complicates interpretation. Generating a minimum set of rules containing all the most informative rules that are commonly called bases of the rules is a benefit way to around this drawback. With couple of measurement Support-MGK, we defined the new concept of bases and semi-bases of rules. Then we proposed bases and semi-bases extraction algorithms.
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https://tel.archives-ouvertes.fr/tel-02114765
Contributor : Harrimann Ramanantsoa <>
Submitted on : Monday, April 29, 2019 - 8:20:31 PM
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Harrimann Ramanantsoa. Contributions à l'amélioration de génération des bases des règles d'association MGK-valides et applications en didactique des mathématiques. Statistiques [math.ST]. Université d'Antananarivo, 2016. Français. ⟨tel-02114765⟩

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