Évolution des projets de formation de futurs enseignants du primaire au contact de situations probabilistes

Il semble y avoir des attentes réciproques non comblées en formation initiale à l’enseignement des mathématiques. Cherchant à comprendre la genèse de ces attentes, nous nous sommes intéressée à la vision que les étudiants nourrissent des phénomènes d’enseignement. Ayant postulé que les étudiants ont une vision déterministe de ces phénomènes, et considérant que leur anticipation oriente leur projet de formation, nous nous sommes attaquée au problème de la rencontre des projets des étudiants et des formateurs. Deux objectifs généraux ont été formulés : le premier concerne la description des projets de formation des étudiants tandis que le second concerne l’expérimentation d’une séquence de situations susceptible de faire évoluer leurs projets. Cette recherche a été menée auprès de 58 étudiants du baccalauréat en enseignement en adaptation scolaire et sociale d’une même université, lesquels entamaient leur formation initiale à l’enseignement des mathématiques. Afin d’explorer les projets qu’ils nourrissent a priori, tous les étudiants ont complété un questionnaire individuel sur leur vision des mathématiques et de leur enseignement et ont participé à une première discussion de groupe sur le sujet. Une séquence de situations probabilistes leur a ensuite été présentée afin d’induire une complexification de leur projet. Enfin, cette expérimentation a été suivie d’une seconde discussion de groupe et complétée par la réalisation de huit entretiens individuels. Il a été mis en évidence que la majorité des étudiants rencontrés souhaitent avant tout évoluer en tant qu’enseignant, en développant leur capacité à enseigner et à faire apprendre ou comprendre les mathématiques. Bien que certaines visées se situent dans une perspective transmissive, celles-ci ne semblent pas représentatives de l’ensemble des projets "visée". De plus, même si la plupart des étudiants rencontrés projettent de développer des connaissances relatives aux techniques et aux méthodes d’enseignement, la sensibilité à la complexité dont certains projets témoignent ne permet plus de réduire les attentes des étudiants à l’endroit de leur formation à la simple constitution d’un répertoire de techniques d’enseignement réputées efficaces. En ce qui a trait aux modes d’anticipation relevés a priori, nos résultats mettent en relief des anticipations se rattachant d’abord à un mode adaptatif, puis à un mode prévisionnel. Aucune anticipation se rattachant à un mode prospectif n’a été recensée a priori. La séquence a permis aux étudiants de s’engager dans une dialectique d’action, de formulation et de validation, elle les a incités à recourir à une approche stochastique ainsi qu’à porter un jugement de probabilité qui prenne en compte la complexité de la situation. A posteriori, nous avons observé que les projets "visée" de certains étudiants se sont complexifiés. Nous avons également noté un élargissement de la majorité des projets, lesquels considèrent désormais les autres sommets du triangle didactique. Enfin, des anticipations se rattachant à tous les modes d’anticipation ont été relevées. Des anticipations réalisées grâce à un mode prospectif permettent d’identifier des zones d’incertitude et de liberté sur lesquelles il est possible d’agir afin d’accroître la sensibilité à la complexité des situations professionnelles à l’intérieur desquelles les futurs enseignants devront se situer.

Resilient Navigation through Probabilistic Modality Reconfiguration

This paper proposes an approach to achieve resilient navigation for indoor mobile robots. Resilient navigation seeks to mitigate the impact of control, localisation, or map errors on the safety of the platform while enforcing the robot’s ability to achieve its goal. We show that resilience to unpredictable errors can be achieved by combining the benefits of independent and complementary algorithmic approaches to navigation, or modalities, each tuned to a particular type of environment or situation. In this paper, the modalities comprise a path planning method and a reactive motion strategy. While the robot navigates, a Hidden Markov Model continually estimates the most appropriate modality based on two types of information: context (information known a priori) and monitoring (evaluating unpredictable aspects of the current situation). The robot then uses the recommended modality, switching between one and another dynamically. Experimental validation with a SegwayRMP- based platform in an office environment shows that our approach enables failure mitigation while maintaining the safety of the platform. The robot is shown to reach its goal in the presence of: 1) unpredicted control errors, 2) unexpected map errors and 3) a large injected localisation fault.

Probabilistic design of retaining walls.

Retaining walls are one of the important structures in nearshore environment and are generally designed based on deterministic approaches. The present paper focuses on the reliability assessment of cantilever retaining walls with due consideration to the uncertainties in soil parameters. Reliability analysis quantifies the level of reliability associated with designs and the associated risk. It also gives the formalisation of a design situation that is normally recognised by experienced designers and provides a greater level of consistency in design. The results are also examined in terms of a simple cost function. The study shows that sliding mode is the critical failure mode and the consequent failure costs are also higher. The study also shows that provision of shear key results in improved reliability and reduction in expected costs.

Probabilistic reasoning of inconsistent belief in protocol analysis

Security protocols have been recently found with subtle flaws due to incomplete or ambiguous specification. Although formal methods have remarkably assisted in protocol analysis, they ignores the effect of hostile/uncertain environment, which might lead to inconsistent belief that can be held by principals in delivered messages. This discrepant belief may prevent us from representing the insecurity and uncertainty in a real trading situation. Unfortunately, the current approaches lack the ability to handle the inconsistent belief. This article presents a probabilistic method, which intuitively measures the belief from different principals that can be put on the goal of the protocol. The experiments demonstrate our method is useful to enhance the protocol analysis.

Probabilistic approach for longitudinal ventilation system design in fire situations

The main objective of ventilation systems in tunnels is to reach the highest possible safety level both in service and fire situation; being the fire one, the most relevant when designing the system. When designing a longitudinal ventilation system, the methodology to evaluate the capacity of the system is similar both in service and fire situation, with the exception of the chimney effect and the phenomena of thermal transfer which is responsible or the changes in the density of the air. When facing the dimensioning task for longitudinal ventilated tunnels, although similar methodologies are used in different countries, specific hypothesis (aerodynamic, thermal properties, traffic) even if discussed in the literature or current practice, are not usually detailed in the regulations or recommendations. The aim of this paper is to propose a probabilistic approach to the problem which would allow the designer, and the tunnel owner, to understand the uncertainty and sensibility adopted in the results and, eventually, identify possible ways of optimizing the ventilation solution to be adopted.

The effect of gender context on children's social behaviour in a limited resources situation : an observational study

Knowing when to compete and when to cooperate to maximize opportunities for equal access to activities and materials in groups is critical to children's social and cognitive development. The present study examined the individual (gender, social competence) and contextual factors (gender context) that may determine why some children are more successful than others. One hundred and fifty-six children (M age=6.5 years) were divided into 39 groups of four and videotaped while engaged in a task that required them to cooperate in order to view cartoons. Children within all groups were unfamiliar to one another. Groups varied in gender composition (all girls, all boys, or mixed-sex) and social competence (high vs. low). Group composition by gender interaction effects were found. Girls were most successful at gaining viewing time in same-sex groups, and least successful in mixed-sex groups. Conversely, boys were least successful in same-sex groups and most successful in mixed-sex groups. Similar results were also found at the group level of analysis; however, the way in which the resources were distributed differed as a function of group type. Same-sex girl groups were inequitable but efficient whereas same-sex boy groups were more equitable than mixed groups but inefficient compared to same-sex girl groups. Social competence did not influence children's behavior. The findings from the present study highlight the effect of gender context on cooperation and competition and the relevance of adopting an unfamiliar peer paradigm when investigating children's social behavior.

High-level concept annotation using ontology and probabilistic inference

Image annotation is a significant step towards semantic based image retrieval. Ontology is a popular approach for semantic representation and has been intensively studied for multimedia analysis. However, relations among concepts are seldom used to extract higher-level semantics. Moreover, the ontology inference is often crisp. This paper aims to enable sophisticated semantic querying of images, and thus contributes to 1) an ontology framework to contain both visual and contextual knowledge, and 2) a probabilistic inference approach to reason the high-level concepts based on different sources of information. The experiment on a natural scene database from LabelMe database shows encouraging results.

Mid-level concept learning with visual contextual ontologies and probabilistic inference for image annotation

To date, automatic recognition of semantic information such as salient objects and mid-level concepts from images is a challenging task. Since real-world objects tend to exist in a context within their environment, the computer vision researchers have increasingly incorporated contextual information for improving object recognition. In this paper, we present a method to build a visual contextual ontology from salient objects descriptions for image annotation. The ontologies include not only partOf/kindOf relations, but also spatial and co-occurrence relations. A two-step image annotation algorithm is also proposed based on ontology relations and probabilistic inference. Different from most of the existing work, we specially exploit how to combine representation of ontology, contextual knowledge and probabilistic inference. The experiments show that image annotation results are improved in the LabelMe dataset.

Survival Power: An Empirical Analysis of Power in a Life and Death Situation

This paper seeks to identify what antecedents of power make it more or less likely for people to survive in a life-threatening situation.In particular, we look at the Titanic disaster as the life or death situation. Maritime disasters can be interpreted as quasi-natural experiments because every person is affected by the shock. True human nature becomes apparent in such a dangerous situation. Five antecedents of power are distinguished: physical strength, economic resources, nationality, social and moral factors. This empirical analysis supports the notion that power is a key determinant in extreme situations of life or death.

Probabilistic world modeling for distributed team planning

This paper describes an application of decoupled probabilistic world modeling to achieve team planning. The research is based on the principle that the action selection mechanism of a member in a robot team can select an effective action if a global world model is available to all team members. In the real world, the sensors are imprecise, and are individual to each robot, hence providing each robot a partial and unique view about the environment. We address this problem by creating a probabilistic global view on each agent by combining the perceptual information from each robot. This probabilistic view forms the basis for selecting actions to achieve the team goal in a dynamic environment. Experiments have been carried out to investigate the effectiveness of this principle using custom-built robots for real world performance, in addition, to extensive simulation results. The results show an improvement in team effectiveness when using probabilistic world modeling based on perception sharing for team planning.

Probabilistic visual recognition of artificial landmarks for simultaneous localization and mapping

Probabilistic robotics, most often applied to the problem of simultaneous localisation and mapping (SLAM), requires measures of uncertainly to accompany observations of the environment. This paper describes how uncertainly can be characterised for a vision system that locates coloured landmark in a typical laboratory environment. The paper describes a model of the uncertainly in segmentation, the internal camera model and the mounting of the camera on the robot. It =plains the implementation of the system on a laboratory robot, and provides experimental results that show the coherence of the uncertainly model,

Noblesse oblige? Determinants of survival in a life and death situation

This paper explores what determines the survival of people in a life–and-death situation. The sinking of the Titanic allows us to inquire whether pro-social behavior matters in such extreme situations. This event can be considered a quasi-natural experiment. The empirical results suggest that social norms such as ‘women and children first’ are persevered during such an event. Women of reproductive age and crew members had a higher probability of survival. Passenger class, fitness, group size, and cultural background also mattered.