Alor que pour les deux dernières nous avons souvent

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deux premières unités, les conceptions dominantes ont un aspect, soit descriptif, soit formel et calculatoire. Alors que pour les deux dernières, nous avons souvent constaté une confusion entre la lecture et l’interprétation des RGDS. Les résultats concernant les élèves ont mis en évidences différents modes de lecture et d’interprétation des RGDS. Parmi ces derniers ‘’le mode discret’’, ‘’le mode ordinal’’, ‘’le mode fonctionnel’’, ‘’le mode direct’’ et le ‘’mode fonctionnel’’. Ces modes de lecture et d’interprétation des RGDS, engendrent des difficultés associées aux différents aspects de compréhension de ces dernières. Les aspects concernés sont l’aspect structurel, l’aspect sémiotique, l’aspect descriptif et l’aspect fonctionnel. Les autres difficultés sont liées au rôles de
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60 destructeur visuel, que peut jouer le graphique. Nous avons aussi pu constater que chacune des RGDS traitées est caractérisée par un type particulier de difficultés ou par la dominance d'un aspect particulier de compréhension. Ainsi pour l'histogramme et le diagramme en bâtons, ce sont surtout les difficultés engendrées par le mode "ordinal", liées aux aspects structurel et descriptif, qui dominent. Alors que le diagramme circulaire est caractérisé surtout par les difficultés engendrées par son rôle destructeur, dû à la domination de ses aspects iconique et spatial et à leur interférence avec les constituants du contexte de la situation. Liliana Tauber (2001). La construcción del significado de la distribución normal a partir de actividades de análisis de datos [Building the meaning of normal distributions from data analysis activities]. PhD. University of Sevilla. Supervisors: Carmen Batanero and Victoria Sánchez. In this research we are interested in the teaching and learning of normal distributions in an introductory data analysis course. The research is based on a theoretical framework where two different dimensions (institutional and personal) of meaning and understanding are considered for mathematical objects. We are interested in the following questions: 1. What is the institutional reference meaning of the normal distribution in a traditional introductory course of data analysis? In Chapter 4 we describe an empirical analysis of 11 University textbooks, from which we determine the main elements of meaning (problems, practices to solve these problems, representations, concepts, properties and types of arguments) that are presented in these textbooks in relation to the normal distribution. 2. How should the teaching of normal distribution be organised to take into account the use of computers? A teaching sequence of the normal distribution, which takes into account the result of the previous analysis and which incorporates the use of computers is described in Chapter 5. The main differences introduced by the use of computers as regards the reference meaning and the student’s predicted activities in the different tasks are analysed.
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