Academic literature on the topic 'Apprentissage'
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Journal articles on the topic "Apprentissage"
Cantin, Gabrielle, and Adèle Chené-Williams. "L’intégration des apprentissages : du pourquoi au comment." Revue des sciences de l'éducation 4, no. 3 (October 9, 2009): 375–87. http://dx.doi.org/10.7202/900086ar.
Full textBischoff, Thomas. "Apprentissage." Revue Médicale Suisse 18, no. 767 (2022): 210–11. http://dx.doi.org/10.53738/revmed.2022.18.767.210a.
Full textHamida, Soufiane, Bouchaib Cherradi, Abdelhadi Raihani, and Hassan Ouajji. "Evaluation des apprentissages au sein d’un environnement de type MOOC adaptatif." ITM Web of Conferences 39 (2021): 03005. http://dx.doi.org/10.1051/itmconf/20213903005.
Full textGarcias, Frédéric, Cédric Dalmasso, and Jean-Claude Sardas. "Tensions paradoxales autour des apprentissages : exploration, exploitation et apprentissage d'exploitation." M@n@gement 18, no. 2 (2015): 156. http://dx.doi.org/10.3917/mana.182.0156.
Full textAndlauer, Leticia. "Apprentissages informels au sein des communautés de joueurs en ligne." Diversité 185, no. 1 (2016): 167–72. http://dx.doi.org/10.3406/diver.2016.4323.
Full textHarris, Ruth. "D’un apprentissage passif à un apprentissage actif." Recherche et pratiques pédagogiques en langues de spécialité - Cahiers de l'APLIUT 13, no. 4 (1994): 20–30. http://dx.doi.org/10.3406/apliu.1994.3368.
Full textFournier, Helene, and Rita Kop. "DE NOUVELLES DIMENSIONS À L’AUTO-APPRENTISSAGE DANS UN ENVIRONNEMENT D’APPRENTISSAGE EN RÉSEAU." Canadian Journal for the Study of Adult Education 26, no. 1 (February 18, 2014): 35–55. http://dx.doi.org/10.56105/cjsae.v26i1.3028.
Full textVieille-Grosjean, Henri, and Gabriel Di Patrizio. "Apprendre à l’âge adulte : entre imitation et émancipation." Phronesis 4, no. 1 (June 18, 2015): 40–50. http://dx.doi.org/10.7202/1031203ar.
Full textNDOUMATSEYI BOTONGOYE, Landry. "Médiation des simulateurs pour l’apprentissage de l’activité de diagnostic en automobile." LAKISA, Revue des Sciences de l’Éducation 2, no. 4 (November 5, 2023): 29–37. https://doi.org/10.55595/lakisa.v2i4.68.
Full textClémence, Alain, Jean-Claude Deschamps, and Patricia Roux. "La perception de l'entrée en apprentissage." L’Orientation scolaire et professionnelle 15, no. 4 (1986): 311–30. http://dx.doi.org/10.3406/binop.1986.1605.
Full textDissertations / Theses on the topic "Apprentissage"
Roussel, Jacques. "Evaluation et apprentissage : l'evaluation en arithmetique au cycle des apprentissages." Toulouse 2, 1989. http://www.theses.fr/1989TOU20062.
Full textTeachers hope for a theory of evaluation that precsibes means and conditions of correct evaluation. Epistemological treatment of didactic evaluationshows that all standard conception entail the destruction of its object: relativism, differenciation and diversity are the essential properties of the treatment of pupils' answers. That view is applied to evaluation in arithmetic in the beginners'classes. The hypothesis of "answering evaluation", linked to the "answering teching", a theory developed by l. Not, explains two facts: the preservation of the propose of didactic evaluation, i. E. The appropriation of knowledge, its structure and genesis; the protection against a cheating operator that pretends to turn an answer into a result. When the conditions of answering evaluation are not observed, evaluation becomes a pseudo or a meta-evaluation. The proof is established after a critical review of recent papers about the didactics of arithmetic and an analysis of a variety of non didactic evaluation. The purpose of the thesis was to examine two possibilities : the practice of evaluation by the teacher in the class-room and the content of the training of teachers for evaluation
Venturini, Gilles. "Apprentissage adaptatif et apprentissage supervise par algorithme genetique." Paris 11, 1994. http://www.theses.fr/1994PA112016.
Full textMoradi, Fard Maziar. "Apprentissage de représentations de données dans un apprentissage non-supervisé." Thesis, Université Grenoble Alpes, 2020. http://www.theses.fr/2020GRALM053.
Full textDue to the great impact of deep learning on variety fields of machine learning, recently their abilities to improve clustering approaches have been investi- gated. At first, deep learning approaches (mostly Autoencoders) have been used to reduce the dimensionality of the original space and to remove possible noises (also to learn new data representations). Such clustering approaches that utilize deep learning approaches are called Deep Clustering. This thesis focuses on developing Deep Clustering models which can be used for different types of data (e.g., images, text). First we propose a Deep k-means (DKM) algorithm where learning data representations (through a deep Autoencoder) and cluster representatives (through the k-means) are performed in a joint way. The results of our DKM approach indicate that this framework is able to outperform similar algorithms in Deep Clustering. Indeed, our proposed framework is able to truly and smoothly backpropagate the loss function error through all learnable variables.Moreover, we propose two frameworks named SD2C and PCD2C which are able to integrate respectively seed words and pairwise constraints into end-to-end Deep Clustering frameworks. In fact, by utilizing such frameworks, the users can observe the reflection of their needs in clustering. Finally, the results obtained from these frameworks indicate their ability to obtain more tailored results
Boucheron, Stéphane. "Apprentissage et calculs." Montpellier 2, 1988. http://www.theses.fr/1988MON20251.
Full textBoucheron, Stéphane. "Apprentissage et calculs." Grenoble 2 : ANRT, 1988. http://catalogue.bnf.fr/ark:/12148/cb376121172.
Full textSalomon, Antoine. "Apprentissage stratégique statistique." Paris 13, 2010. http://www.theses.fr/2010PA132039.
Full textThis thesis studies strategic interaction between several agents who are facing an exploration vs. Exploitation dilemma. In game theory, this situation is well described by models of bandit games. Each player faces a two-arm bandit machine, one arm being safe, the other being risky. At each stage of the game, each player has to decide which arm he uses. If he chooses the risky arm (exploration), he gets a random payoff which gives him partial information on the rentability of his machine. If he chooses the safe arm, he gets a known payoff, but possibly less than what he could have got from exploration. The rentability of the machine depends on an unknown state of the nature, which can be learnt from exploration. Learning is a strategic issue: for instance a player could benefit from others' information without taking risks himself. We study Nash equilibria of such games. We mainly wonder if equilibria are efficient: does a player gain significanlty more from strategic interaction than he would alone? Is there some kind of cooperation that helps getting more information? Do players manage to have a good knowledge of the state of the nature? This depends on what agents are able to see from each other (actions and/or payoffs), and also on how the types of the machines are correlated. We will also study the way equilibria are evolving when the number of players get large. In particular, we wonder if this increase leads to better pieces of information, and better gains
Dinh, Quang-Thang. "Apprentissage statistique relationnel : apprentissage de structures de réseaux de Markov logiques." Phd thesis, Université d'Orléans, 2011. http://tel.archives-ouvertes.fr/tel-00659738.
Full textLaronze, Florian. "Apprentissage à distance, apprentissage gamifié : identification des facteurs de la réussite universitaire." Electronic Thesis or Diss., Bordeaux, 2024. http://www.theses.fr/2024BORD0445.
Full textRecently, the President of France Université emphasised that ‘the ultimate objective of the French university is to integrate those who want to enrol and to ensure that they succeed’. Certainly exacerbated by the major health crisis caused by the Covid-19 pandemic, a high proportion of students are experiencing serious difficulties, with significant repercussions for their mental health. In addition, just over a quarter of students enrolled on a Licence degree complete their three-year programme. Given these facts, the need for a better understanding of the factors that determine success at university is a major challenge for our society. Also associated with the health crisis, the practice of distance learning, and in particular its synchronous mode (e.g. Zoom), has boomed worldwide and seems destined to become a common mode of learning. Coupled with this development of distance learning, but also with the technological revolution and pedagogical considerations aimed at encouraging student engagement during lessons, recent years have also seen the rise of digital and gamified teaching tools (e.g. mobile quiz applications, virtual reality environments for educational purposes, etc.). In this general context, the aim of my thesis is to gain a better understanding of the impact of distance learning and gamified digital tools on academic success (e.g. emotions felt, motivation, grades, etc.). As part of the national ‘Université Atypie Friendly’ project, which aims to promote the academic inclusion of young adults with Autism Spectrum Disorder, this thesis will also seek to identify the most relevant digital tools and pedagogical practices for this specific audience
Solnon, Matthieu. "Apprentissage statistique multi-tâches." Phd thesis, Université Pierre et Marie Curie - Paris VI, 2013. http://tel.archives-ouvertes.fr/tel-00911498.
Full textKocák, Tomáš. "Apprentissage séquentiel avec similitudes." Thesis, Lille 1, 2016. http://www.theses.fr/2016LIL10230/document.
Full textThis thesis studies several extensions of multi-armed bandit problem, where a learner sequentially selects an action and obtain the reward of the action. Traditionally, the only information the learner acquire is about the obtained reward while information about other actions is hidden from the learner. This limited feedback can be restrictive in some applications like recommender systems, internet advertising, packet routing, etc. Usually, these problems come with structure, similarities between users or actions, additional observations, or any additional assumptions. Therefore, it is natural to incorporate these assumptions to the algorithms to improve their performance. This thesis focuses on multi-armed bandit problem with some underlying structure usually represented by a graph with actions as vertices. First, we study a problem where the graph captures similarities between actions; connected actions tend to grand similar rewards. Second, we study a problem where the learner observes rewards of all the neighbors of the selected action. We study these problems under several additional assumptions on rewards (stochastic, adversarial), side observations (adversarial, stochastic, noisy), actions (one node at the time, several nodes forming a combinatorial structure in the graph). The main contribution of this thesis is to design algorithms for previously mentioned problems together with theoretical and empirical guaranties. We also introduce several novel quantities, to capture the difficulty of some problems, like effective dimension and effective independence number
Books on the topic "Apprentissage"
Michèle, Kail, Fayol Michel 1947-, and Hickmann Maya, eds. Apprentissage des langues. Paris: CNRS, 2009.
Find full textGoupil, Georgette. L 'apprentissage cognitif. Laval, Qué: Université du Québec, 1996.
Find full textScheinert, David. L' apprentissage inutile. Bruxelles: Société de commercialisation des Editions J. Antoine, 1985.
Find full textAnnie, Guédez. Compagnonnage et apprentissage. Paris: Presses universitaires de France, 1994.
Find full textBerbaum, Jean. Apprentissage et formation. 4th ed. Paris: Presses universitaires de France, 1994.
Find full textBook chapters on the topic "Apprentissage"
Hartmann, Werner, Michael Näf, and Raimond Reichert. "Apprentissage par la découverte." In Enseigner l’informatique, 95–103. Paris: Springer Paris, 2012. http://dx.doi.org/10.1007/978-2-8178-0262-6_16.
Full textGaté, Jean-Pierre. "Apprentissage." In L'ABC de la VAE, 79–80. Érès, 2009. http://dx.doi.org/10.3917/eres.bouti.2009.01.0079.
Full textde Maillard, Jacques. "Apprentissage." In Dictionnaire des politiques publiques, 62–68. Presses de Sciences Po, 2019. http://dx.doi.org/10.3917/scpo.bouss.2019.01.0062.
Full textde Maillard, Jacques. "Apprentissage." In Dictionnaire des politiques publiques, 68–75. Presses de Sciences Po, 2014. http://dx.doi.org/10.3917/scpo.bouss.2014.01.0068.
Full textde Maillard, Jacques. "Apprentissage." In Dictionnaire des politiques publiques, 68–75. Presses de Sciences Po, 2010. http://dx.doi.org/10.3917/scpo.bouss.2010.01.0068.
Full textJeanguiot, Nicole. "Apprentissage." In Les concepts en sciences infirmières, 72–74. Association de Recherche en Soins Infirmiers, 2012. http://dx.doi.org/10.3917/arsi.forma.2012.01.0072.
Full textHaeberli, Philippe. "2. Temps des apprentissages, apprentissage des temps." In Questions de temporalité, 95–107. Presses universitaires du Septentrion, 2007. http://dx.doi.org/10.4000/books.septentrion.14322.
Full text"3 APPRENTISSAGE." In Psychologie, 48–67. EDP Sciences, 2023. http://dx.doi.org/10.1051/978-2-7598-3097-8.c004.
Full textRoger, Lucie. "Apprentissage professionnel." In Dictionnaire des concepts de la professionnalisation, 67–71. De Boeck Supérieur, 2022. http://dx.doi.org/10.3917/dbu.jorro.2022.01.0067.
Full textDurocher, Éric. "Apprentissage collaboratif." In Repères contemporains pour l’éducation aux sciences et à la technologie, 7–13. Les Presses de l’Université de Laval, 2020. http://dx.doi.org/10.1515/9782763749570-002.
Full textConference papers on the topic "Apprentissage"
Delisle, Sylvain, Sylvain Létourneau, and Stan Matwin. "Expérimentation en apprentissage d'heuristiques pour l'analyse syntaxique." In the 17th international conference. Morristown, NJ, USA: Association for Computational Linguistics, 1998. http://dx.doi.org/10.3115/980451.980896.
Full textDelisle, Sylvain, Sylvain Létourneau, and Stan Matwin. "Expérimentation en apprentissage d'heuristiques pour l'analyse syntaxique." In the 36th annual meeting. Morristown, NJ, USA: Association for Computational Linguistics, 1998. http://dx.doi.org/10.3115/980845.980896.
Full textFourcade, A. "Apprentissage profond : un troisième oeil pour les praticiens." In 66ème Congrès de la SFCO. Les Ulis, France: EDP Sciences, 2020. http://dx.doi.org/10.1051/sfco/20206601014.
Full textVillard, Marie-Aline. "Commentaire de la postface de Mouvements d’Henri Michaux : déplacement, (dés)apprentissage, écart." In Penser le mouvement. Fabula, 2015. http://dx.doi.org/10.58282/colloques.2593.
Full textPreiss, R., and M. Gabrea. "Modelisation du canal telephonique pstn et apprentissage multireferences en reconnaissance robuste de la parole." In 2006 Canadian Conference on Electrical and Computer Engineering. IEEE, 2006. http://dx.doi.org/10.1109/ccece.2006.277295.
Full textMarin, Brigitte, and Jacques Crinon. "Approches des genres dans l'enseignement apprentissage de la production verbale écrite à l'école élémentaire française." In 2ème Congrès Mondial de Linguistique Française. Les Ulis, France: EDP Sciences, 2010. http://dx.doi.org/10.1051/cmlf/2010207.
Full textCHTIOUI, Researcher Jamila. "HOW CAN STUDY GROUPS BE MADE EFFECTIVE AT UNIVERSITY?" In IV. International research Scientific Congress of Humanities and Social Sciences. Rimar Academy, 2023. http://dx.doi.org/10.47832/ist.con4-2.
Full textMarnet, Béatrice. "Les expressions idiomatiques et l’approche actionnelle – L'apprentissage du français langue étrangère à travers les unités phraséologiques qui ont pour thème l'eau." In XXV Coloquio AFUE. Palabras e imaginarios del agua. Valencia: Universitat Politècnica València, 2016. http://dx.doi.org/10.4995/xxvcoloquioafue.2016.3799.
Full textCordier, Thibault, Fabrice Lefèvre, Tanguy Urvoy, and Lina Maria Rojas-Barahona. "Et la robustesse ?... bordel ! Comment les stratégies de dialogue par apprentissage structuré résistent aux bruits des entrées ?" In XXXIVe Journées d'Études sur la Parole -- JEP 2022. ISCA: ISCA, 2022. http://dx.doi.org/10.21437/jep.2022-53.
Full textGhedhahem, Zeineb. "Cap sur le premier MOOC FOFLE en Afrique francophone pour se (re)mettre à flot." In XXV Coloquio AFUE. Palabras e imaginarios del agua. Valencia: Universitat Politècnica València, 2016. http://dx.doi.org/10.4995/xxvcoloquioafue.2016.3049.
Full textReports on the topic "Apprentissage"
Lopes, Helena. La Dimension Apprentissage de la Relation de Travail. DINÂMIA'CET-IUL, 1995. http://dx.doi.org/10.7749/dinamiacet-iul.wp.1995.04.
Full textMelloni, Gian. Le leadership des autorités locales en matière d'assainissement et d'hygiène : expériences et apprentissage de l'Afrique de l'Ouest. Institute of Development Studies (IDS), January 2022. http://dx.doi.org/10.19088/slh.2022.002.
Full textChambers, Robert, Naomi Vernon, and Jamie Myers. L’apprentissage rapide par l’action pour la programmation de l’assainissement et l’hygiène. The Sanitation Learning Hub, Institute of Development Studies, September 2020. http://dx.doi.org/10.19088/slh.2020.010.
Full textMotulsky, Aude, Jean Noel Nikiema, Philippe Després, Alexandre Castonguay, Martin Cousineau, Joé T. Martineau, Cécile Petitgand, and Catherine Régis. Promesses de l’IA en santé - Fiche 2. Observatoire international sur les impacts sociétaux de l’intelligence artificielle et du numérique, March 2022. http://dx.doi.org/10.61737/votf6751.
Full textBrinkerhoff, Derick W., Sarah Frazer, and Lisa McGregor. S'adapter pour apprendre et apprendre pour s'adapter : conseils pratiques tirés de projets de développement internationaux. RTI Press, January 2018. http://dx.doi.org/10.3768/rtipress.2018.pb.0015.1801.fr.
Full textCanto, Patricia, ed. Apprentissages au regard des initiatives de fomentation de la collaboration transfrontaliere: une expérience au cœur de l’eurorégion Nouvelle-Aquitaine, Euskadi, Navarre. Universidad de Deusto, 2022. http://dx.doi.org/10.18543/ctih9147.
Full textComment combler le déficit d’engagement communautaire sur le marché du carbone: Exploration d’un fonds commun pour l’assistance juridique et technique communautaire. Rights and Resources Initiative, February 2025. https://doi.org/10.53892/voyf3520.
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