Application de la theorie des ensembles flous a l'elaboration d'un modele pour predire la reussite dans une ecole de genie a partir du score a une epreuve diagnostique

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Universite de Montreal (Canada), 2007 - 186 pages
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Current theories on measure and evaluation have remained hitherto relatively limited in their ability to deal with the interpretation of scores in comparison with a criterion-based reference. Indeed, the traditional success/failure diagnosis outcome, which consists of comparing a gross score with a threshold score, is an incomplete model. However, the fuzzy sets theory adds further nuance to this model by adding a second parameter which shows the link between the gross score and the degree of certainty behind a success diagnosis. Thus, the obtained data is classified in a fuzzy set ---no need to resort to an interval scale for that matter. Furthermore, the data processing is performed by operations onto fuzzy sets and the true value of inclusion of a subset within a set so as to yield inferences of logical implication rules the like of "If the student was diagnosed positively, then he will succeed."

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