Une démarche pour l'enseignement des réseaux et de la communication

Cet article se propose de faire le point sur l'enseignement de l'informatique dans le domaine des réseaux. Il s'appuie sur nos expériences pédagogiques post-baccalauréat dans les filières informatiques ( BTS, IUT, MIAG, MAITRISE, DEA, DESS... ).Nous décrivons dans une première partie le « concept réseau » et son rôle prépondérant dans l'informatique d'aujourd'hui. Face aux problèmes posés par ce domaine complexe, nous énonçons quelques « règles d'or » pour une approche progressive et applicative conduisant à expérimenter des systèmes de communications locaux.Nous exposons notre démarche didactique pour l'une des règles énoncées : « Apprendre la communication ». Nous l'illustrons à travers l'utilisation d'un logiciel d'enseignement assisté par ordinateur. Ce produit réalisé par notre équipe concerne le R.N.I.S. (Réseau Numérique à Intégration de Service). Il permet à un étudiant de se familiariser avec les concepts, les services, l'architecture et la mise en oeuvre d'un réseau R.N.I.S

Desenvolvimento de frameworks para a modelagem do risco de crédito por meio de algoritmos de classificação

Granting credit is a vital activity in the financial industry. For the success of financial institutions, as well as the equilibrium of the credit system as a whole, it is important that credit risk management systems efficiently evaluate the probability of default of potential debtors based on their historical data. Classification algorithms are an interesting approach to this problem in the form of Credit Scoring models. Since the emergence of quantitative analytical methods with this purpose, statistical models persist as the most commonly chosen method, given their easier implementation and inherent interpretability. However, advances in Machine Learning have developed new and more complex algorithms capable of handling a bigger amount of data, often with an increase in predictive power. These new approaches, although not always readily transferable to practical applications in the financial industry, present an opportunity for the development of credit risk modeling and have piqued the interest of researchers in the field. Nonetheless, researchers seem to focus on model performance, not appropriately setting up guidelines to optimize the modeling process or considering the present regulation for model implementation. Thereby, this dissertation establishes frameworks for consumer credit risk modeling based on classification algorithms while guided by a systematic literature review on the topic. The proposed frameworks incorporate ML techniques, data preprocessing and balancing, feature selection (FS), and hyperparameter optimization (HPO). In addition to the bibliographic research, which introduces us to the main classification algorithms and appropriate modeling steps, the development of the frameworks is also based on experiments with hundreds of models for credit risk classification, using Logistic Regression (LR), Decision Trees (DT), Support Vector Machines (SVM), Random Forest (RF), as well as boosting and stacking ensembles, to efficiently guide the construction of robust and parsimonious models for credit risk analysis in consumer lending.Agência 1A concessão de crédito é uma atividade vital da indústria financeira. Para o funcionamento e sucesso das instituições financeiras, assim como a manutenção do equilíbrio do sistema creditício, a modelagem de risco de crédito tem o papel de avaliar a probabilidade de inadimplência de potenciais devedores com base em dados históricos. Algoritmos de classificação apresentam uma abordagem interessante para esta finalidade na elaboração de modelos para Credit Scoring. Desde o surgimento das metodologias analíticas e quantitativas para esta modelagem, persistem na indústria modelos estatísticos, dotados de maior interpretabilidade e fácil implementação. Contudo, com o desenvolvimento na área de Machine Learning (ML), surgiram novos algoritmos capazes de trabalhar com um maior volume de dados e com melhor performance preditiva. Estes algoritmos, apesar de nem sempre prontamente transferíveis da academia para a indústria, apresentam uma oportunidade para o desenvolvimento da modelagem do risco de crédito, tendo consequentemente despertado um interesse de pesquisadores na área. A literatura, por sua vez, se enfoca na performance dos modelos, dificilmente estabelecendo diretrizes para a otimização do processo de modelagem ou se atentando às regulamentações vigentes para a sua aplicação prática na indústria financeira. Desta forma, esta dissertação, embasada por uma revisão sistemática de literatura, propõe frameworks para a modelagem do risco de crédito incorporando o uso de técnicas de ML, pré-processamento e balanceamento de dados, feature selection (FS) e otimização de hiper-parâmetros (OHP). Além da pesquisa bibliográfica, que possibilita uma familiarização com os principais algoritmos de classificação e as etapas de modelagem apropriadas, o desenvolvimento dos frameworks também é fundamentado pela elaboraçao de centenas de modelos para classificação do risco de crédito, partindo dos algoritmos de Regressão Logística (Logistic Regression - LR), Árvores de Decisão (Decision Trees - DT), Support Vector Machines (SVM), Random Forest (RF), assim como ensembles de boosting e stacking, para direcionar de maneira eficiente a construção de modelos robustos e parcimoniosos para a análise do risco na concessão de crédito ao consumidor

Articuler dispositifs de formation et Innovations technologiques : Repères sur des actions de pédagogie inversée

International audienceDans le contexte actuel de l’éducation, toute formation universitaire devrait traduire un besoin d’implication volontaire et responsable, de même que la nécessaire analyse des contextes et mécanismes d’apprentissage en vue de leur adaptation aux différents publics. Suivant le postulat selon lequel l’apprenant comme l’enseignant développe et exerce un savoir dans l’action et par celle-ci, nous essaierons de comprendre le fonctionnement du dispositif technique et pédagogique, en insistant sur le concept de classe inversée. En ce sens, nous aborderons la notion de ressources internes (ressources cognitives, conatives de l’apprenant) et ressources externes (ressourcesmatérielles et humaines)

Mutuality as a method: advancing a social paradigm for global mental health through mutual learning

Purpose: Calls for “mutuality” in global mental health (GMH) aim to produce knowledge more equitably across epistemic and power differences. With funding, convening, and publishing power still concentrated in institutions in the global North, efforts to decolonize GMH emphasize the need for mutual learning instead of unidirectional knowledge transfers. This article reflects on mutuality as a concept and practice that engenders sustainable relations, conceptual innovation, and queries how epistemic power can be shared. // Methods: We draw on insights from an online mutual learning process over 8 months between 39 community-based and academic collaborators working in 24 countries. They came together to advance the shift towards a social paradigm in GMH. // Results: Our theorization of mutuality emphasizes that the processes and outcomes of knowledge production are inextricable. Mutual learning required an open-ended, iterative, and slower paced process that prioritized trust and remained responsive to all collaborators’ needs and critiques. This resulted in a social paradigm that calls for GMH to (1) move from a deficit to a strength-based view of community mental health, (2) include local and experiential knowledge in scaling processes, (3) direct funding to community organizations, and (4) challenge concepts, such as trauma and resilience, through the lens of lived experience of communities in the global South. // Conclusion: Under the current institutional arrangements in GMH, mutuality can only be imperfectly achieved. We present key ingredients of our partial success at mutual learning and conclude that challenging existing structural constraints is crucial to prevent a tokenistic use of the concept

Switching back from IFRS local GAAP ::does it impact target price accuracy and analyst optimism?

Prior research shows that mandatory IFRS adoption provided some benefits for financial analysts. We extend this literature by investigating whether switching back from IFRS to local GAAP reduces these benefits. More precisely, we analyze the impact of such a switch on target price errors in Switzerland, where several firms have decided to abandon IFRS and use Swiss GAAP. Our cross-sectional analysis shows that analysts’ errors are significantly lower for firms applying IFRS. The results from our staggered difference-in-differences suggest a significant increase in the absolute target price errors after a switch from IFRS to Swiss GAAP. Thus, we conclude that target price accuracy decreases when opacity increases. However, analysts are usually more optimistic about firms using IFRS, and analyst optimism significantly decreases after a switch from IFRS to Swiss GAAP. This latter finding suggests that analysts become more prudent when opacity increases. Overall, we conclude that switching back from IFRS to local GAAP has some negative and some positive consequences for financial analysts

Utilisation d'un jeu sérieux de diagnostic dentaire

National audienceCet article relate l'introduction d'un jeu sérieux dans un module d'enseignement en d'odontologie. Après avoir détaillé le contexte pédagogique et les raisons qui ont motivé l'introduction d'un jeu sérieux, on s'attache à préciser les éléments méthodologiques qui ont permis la bonne réalisation de l'objet et à détailler les retours d'expérience qui ont validé la démarche

Former et informer à l'ère du développement durable - Enjeux de performance pour un enseignement socialement responsable (Colloque international de la CIFEODD 2018, Pondichéry, Inde)

International audienc

La classe inversée ou la réorganisation de l'espace-temps dans la dualité des paradigmes "Enseigner/apprendre"

National audienceCette communication vise à montrer comment les technologies de l’information et de la communication facilitent la mise en œuvre d’une pédagogie centrée sur l’apprenant, prenant en compte les dimensions de l’espace-temps dans sa formation. Le paradigme d'enseignement doit laisser plus de place au paradigme d'apprentissage où les aspects pédagogiques qu’ils soient transmissifs, formatifs ou immersifs ne peuvent être dissociés de l’organisation des différentes activités qu’elles se déroulent en présentiel ou à distance. Dans cet article, nous expliquerons comment le concept de classe inversée a permis d’optimiser le temps de formation en favorisant l’interaction et les échanges humains. On n'apprend plus uniquement seul chez soi mais on apprend ensemble en classe. Nous verrons aussi comment les technologies numériques de rapid learning, de quiz et/ou de jeux sérieux et l’usage de tablettes permettent de construire des modules de formation couvrant les différents aspects pédagogiques. Les expériences de classe inversée déjà menées dans des établissements scolaires et universitaires, en particulier aux Etats-Unis, au Canada et en Belgique, font leur apparition en France. Nous décrirons la mise en œuvre de ce concept ou plutôt de cette philosophie d’enseignement/apprentissage dans le cadre de modules en licence. Nous verrons comment l’usage de tablettes en classe prend sa place dans ce dispositif pour en améliorer l’interaction

Apprendre au-delà des frontières universitaires, entre mythe et réalité

International audienceLes MOOC accueillent des publics diversifiés ayant des objectifs de formation très hétérogènes. La question des effets de la formation ne peut alors obtenir une réponse que si l’évaluation est centrée sur les apprenants. Loin de faire partie d’un projet professionnel ciblé, le MOOC donne l’impression d’être dans bien des cas la porte d’entrée en formation la plus acceptable à un moment donné. Nos études sur le suivi de MOOC thématique nous permettent de développer une approche multidimensionnelle des relations : « sélections et motivations d’entrée en formation », « formation professionnelle et travail » et « croyances et représentations des apprenants sur leurs capacités d’apprentissage »

De la formation ouverte et à distance aux apprentissages collectifs médiatisés : L'exemple des MOOC

International audienceProfessionalization skills is accompanied by a diversification of training courses, dissemination methods and specialties offered on an international scale. Thisevolution contributes to an increasing distinction between the training process and itsvalidation by a diploma/degree (si universitaire). Regarding MOOCs, we question on theirperformance in terms of recognition and valorization of training courses for the learners. Maythis type of training be considered equivalent, at a time, by a learner and the professionalworld? Do not MOOCs provide additional skills and experiences recoverable in aprofessional context? All these items become a priority in the evaluation of the disseminationof learnings. In this paper, we discuss differences in the appreciation and valuation ofprofessionalization in analyzing of changes between training courses and jobs, taking intoaccount the topic multiplicity related to the performance and diversity of skills required in theprofessional context