Évaluation d’un programme de développement professionnel en santé publique : le laboratoire de promotion de la santé

Il y a quelques décennies, l’émergence du discours de la promotion de la santé infléchissait un nouveau tournant à la santé publique, orientant sa pratique vers l’action communautaire, participative et intersectorielle. Parallèlement, au Québec, la réforme du système de santé de 2004 réorganisait le niveau de gouverne locale à travers la création des centres de santé et de services sociaux (CSSS). Ceux-ci doivent articuler les secteurs des soins et de la santé publique à travers un continuum de services qui va de la promotion de la santé aux soins palliatifs. Ces changements ont des implications majeures pour les acteurs de la santé et de la santé publique, qui doivent composer avec de nouveaux rôles professionnels et de nouvelles stratégies d’action. Le développement professionnel est considéré comme un levier potentiel pour soutenir ces changements. En 2009, une équipe de la Direction de la santé publique de l’Agence de santé et des services sociaux de Montréal concevait un programme de développement professionnel appelé le Laboratoire de promotion de la santé. Ce programme mise sur une approche d’apprentissage de groupe pour permettre aux professionnels des CSSS de développer de nouvelles compétences, une pratique réflexive ainsi que de nouvelles pratiques de promotion de la santé. Basée sur une méthodologie générale qualitative et une approche d’évaluation collaborative, cette thèse utilise plusieurs stratégies d’investigation afin d’évaluer le Laboratoire de promotion de la santé sous trois angles, qui renvoient à sa conceptualisation, à son implantation et à ses effets. Plus spécifiquement, elle vise à : (1) examiner la plausibilité de la théorie d’intervention du programme; (2) décrire et comprendre les processus d’apprentissage d’équipe ainsi que les facteurs qui les influencent; et (3) explorer, du point de vue des participants, les effets réflexifs du Laboratoire. Afin de répondre à ces objectifs, la thèse mobilise diverses perspectives théoriques liées à l’apprentissage individuel, d’équipe et organisationnel. Les résultats des analyses démontrent que : (1) malgré quelques améliorations possibles, le modèle du programme est généralement bien conçu pour parvenir aux résultats visés; (2) l’implantation de ce modèle dans deux sites a donné lieu à des processus d’apprentissage d’équipe différents, bien que conditionnés par des facteurs communs liés aux participants, à l’équipe, au contexte organisationnel et à l’implantation du programme; (3) tel que visé, les participants des deux sites ont développé de la réflexivité vis-à-vis leur pratique et leur rôle professionnel – cette réflexivité adoptant une fonction formative ou critique en regard de l’expérience professionnelle. Ces résultats soulignent le potentiel que représente l’évaluation de la théorie d’intervention pour améliorer la conceptualisation d’un programme de développement professionnel, ainsi que l’intérêt et la pertinence d’évaluer les processus d’apprentissage au niveau de l’équipe dans le cadre d’une approche collective de développement professionnel. De plus, ils appuient l’importance de l’apprentissage réflexif pour l’amélioration des pratiques et l’engagement social des professionnels. En ce sens, ils proposent différentes avenues qui ont le potentiel de consolider les capacités de la main-d’œuvre de santé publique et d’influer conséquemment sur son efficacité à améliorer la santé des collectivités dans le prochain siècle.

Analysis of System Signals Based on Cross Recurrence Method for System Dynamics Characterization

Natural systems are inherently non linear. Recurrent behaviours are typical of natural systems. Recurrence is a fundamental property of non linear dynamical systems which can be exploited to characterize the system behaviour effectively. Cross recurrence based analysis of sensor signals from non linear dynamical system is presented in this thesis. The mutual dependency among relatively independent components of a system is referred as coupling. The analysis is done for a mechanically coupled system specifically designed for conducting experiment. Further, cross recurrence method is extended to the actual machining process in a lathe to characterize the chatter during turning. The result is verified by permutation entropy method. Conventional linear methods or models are incapable of capturing the critical and strange behaviours associated with the dynamical process. Hence any effective feature extraction methodologies should invariably gather information thorough nonlinear time series analysis. The sensor signals from the dynamical system normally contain noise and non stationarity. In an effort to get over these two issues to the maximum possible extent, this work adopts the cross recurrence quantification analysis (CRQA) methodology since it is found to be robust against noise and stationarity in the signals. The study reveals that the CRQA is capable of characterizing even weak coupling among system signals. It also divulges the dependence of certain CRQA variables like percent determinism, percent recurrence and entropy to chatter unambiguously. The surrogate data test shows that the results obtained by CRQA are the true properties of the temporal evolution of the dynamics and contain a degree of deterministic structure. The results are verified using permutation entropy (PE) to detect the onset of chatter from the time series. The present study ascertains that this CRP based methodology is capable of recognizing the transition from regular cutting to the chatter cutting irrespective of the machining parameters or work piece material. The results establish this methodology to be feasible for detection of chatter in metal cutting operation in a lathe.

Simulación del proceso de investigación durante la realización del ciclo de prácticas

Las sesiones de laboratorio ofrecen la posibilidad de simular a pequeña escala el proceso de investigación. En una actividad formativa basada en la metodología PBL (Problem Based Learning), cada grupo de alumnos recibe el encargo de comprobar de manera experimental el efecto de una sustancia sobre el crecimiento de una población de la planta acuática Lemna minor. Después de completar el diseño experimental y llevar a cabo el ensayo, los alumnos deben redactar un informe final en formato póster de forma que presenten sintéticamente los objetivos del ensayo, el procedimiento experimental seguido, los resultados obtenidos y las conclusiones alcanzadas. La actividad finaliza con la presentación de todos los pósters en una sesión específica. Esta práctica docente ha permitido detectar algunos déficits formativos en nuestros alumnos que han motivado la implementación de estrategias correctoras

La Metodologia d'aprenentatge basat en problemes com a pràctica docent en fase experimental dins la xarxa d'innovació docent de la UdG

Aquesta comunicació exposa l’experiència desenvolupada a través de la xarxa d’Innovació Docent (XID) d’Aprenentatge Basat en Problemes (ABP) de la nostra Universitat. La xarxa d’ABP forma part d’una proposta d’innovació docent endegada per l’ICE el curs 2009-2010 dins un conjunt d’iniciatives entre les que hi ha altres xarxes. Els membres de la xarxa d’ABP pertanyem a diferents disciplines: Ciències de la Salut, Socials, Educació i Enginyeria. El grup es va organitzar a partir d’una coordinació que, alhora, es vehiculava amb les altres xarxes d’innovació docent de l’ICE. A banda de les sessions presencials, es van utilitzar altres formes de comunicació i relació, a través de la plataforma Moodle i el correu electrònic

Tensor regression based on linked multiway parameter analysis

Classical regression methods take vectors as covariates and estimate the corresponding vectors of regression parameters. When addressing regression problems on covariates of more complex form such as multi-dimensional arrays (i.e. tensors), traditional computational models can be severely compromised by ultrahigh dimensionality as well as complex structure. By exploiting the special structure of tensor covariates, the tensor regression model provides a promising solution to reduce the model’s dimensionality to a manageable level, thus leading to efficient estimation. Most of the existing tensor-based methods independently estimate each individual regression problem based on tensor decomposition which allows the simultaneous projections of an input tensor to more than one direction along each mode. As a matter of fact, multi-dimensional data are collected under the same or very similar conditions, so that data share some common latent components but can also have their own independent parameters for each regression task. Therefore, it is beneficial to analyse regression parameters among all the regressions in a linked way. In this paper, we propose a tensor regression model based on Tucker Decomposition, which identifies not only the common components of parameters across all the regression tasks, but also independent factors contributing to each particular regression task simultaneously. Under this paradigm, the number of independent parameters along each mode is constrained by a sparsity-preserving regulariser. Linked multiway parameter analysis and sparsity modeling further reduce the total number of parameters, with lower memory cost than their tensor-based counterparts. The effectiveness of the new method is demonstrated on real data sets.

On Compositional Modelling

Many solutions to AI problems require the task to be represented in one of a multitude of rigorous mathematical formalisms. The construction of such mathematical models forms a difficult problem which is often left to the user of the problem solver. This void between problem solvers and the problems is studied by the eclectic field of automated modelling. Within this field, compositional modelling, a knowledge-based methodology for system modelling, has established itself as a leading approach. In general, a compositional modeller organises knowledge in a structure of composable fragments that relate to particular system components or processes. Its embedded inference mechanism chooses the appropriate fragments with respect to a given problem, instantiates and assembles them into a consistent system model. Many different types of compositional modeller exist, however, with significant differences in their knowledge representation and approach to inference. This paper examines compositional modelling. It presents a general framework for building and analysing compositional modellers. Based on this framework, a number of influential compositional modellers are examined and compared. The paper also identifies the strengths and weaknesses of compositional modelling and discusses some typical applications.

Determinação da solução ótima do problema de fluxo de potência ótimo via análise de sensibilidade

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Trabalhando com estratégias de ensino-aprendizado por descoberta na área da saúde: a problematização e a aprendizagem baseada em problemas.

Considering the changes in teaching in the health field and the demand for new ways of dealing with knowledge in higher learning, the article discusses two innovative methodological approaches: problem-based learning (PBL) and problematization. Describing the two methods' theoretical roots, the article attempts to identify their main foundations. As distinct proposals, both contribute to a review of the teaching and learning process: problematization, focused on knowledge construction in the context of the formation of a critical awareness; PBL, focused on cognitive aspects in the construction of concepts and appropriation of basic mechanisms in science. Both problematization and PBL lead to breaks with the traditional way of teaching and learning, stimulating participatory management by actors in the experience and reorganization of the relationship between theory and practice. The critique of each proposal's possibilities and limits using the analysis of their theoretical and methodological foundations leads us to conclude that pedagogical experiences based on PBL and/or problematization can represent an innovative trend in the context of health education, fostering breaks and more sweeping changes.

Um novo jogo para o estudo do raciocínio combinatório e do cálculo de probabilidade

We present an educational proposal for the study of combinatorial reasoning and calculation of probabilities based on a game and problem solving methodology, aiming to support the teaching of mathematical content. A review of the literature related to the teaching and learning of the concepts of combinatorial reasoning and probability is presented. The game is original, using a board game similar to Tic-tac-toe, and the movements of its parts have some similarities, in particular those made with the rook and pawn pieces of the game of chess. We formulate various activities (problems) involving the game which, in the process of solving them, using the problem solving methodology and with the appropriate intervention of the teacher, encourage students to develop strategies for counting, an indispensable tool in the initial study of Combinatorial Analysis and Calculation of Probabilities.

A heuristic algorithm based on multi-assignment procedures for nurse scheduling

This paper tackles a Nurse Scheduling Problem which consists of generating work schedules for a set of nurses while considering their shift preferences and other requirements. The objective is to maximize the satisfaction of nurses' preferences and minimize the violation of soft constraints. This paper presents a new deterministic heuristic algorithm, called MAPA (multi-assignment problem-based algorithm), which is based on successive resolutions of the assignment problem. The algorithm has two phases: a constructive phase and an improvement phase. The constructive phase builds a full schedule by solving successive assignment problems, one for each day in the planning period. The improvement phase uses a couple of procedures that re-solve assignment problems to produce a better schedule. Given the deterministic nature of this algorithm, the same schedule is obtained each time that the algorithm is applied to the same problem instance. The performance of MAPA is benchmarked against published results for almost 250,000 instances from the NSPLib dataset. In most cases, particularly on large instances of the problem, the results produced by MAPA are better when compared to best-known solutions from the literature. The experiments reported here also show that the MAPA algorithm finds more feasible solutions compared with other algorithms in the literature, which suggest that this proposed approach is effective and robust. © 2013 Springer Science+Business Media New York.

Geração automática de estereomodelos a partir de imagens digitais georreferenciadas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Aprendizado baseado em problemas, um novo conceito para a formação do designer e a sustentabilidade

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Avaliação dos princípios ergonômicos na prática odontológica

Pós-graduação em Odontologia Preventiva e Social - FOA

Concepções sobre a aprendizagem baseada em problemas: um estudo de caso na FAMEMA

Pós-graduação em Educação - FFC

Panorama da educação fundamental e média no Brasil: o modelo da aprendizagem baseada em problemas como experiência na prática docente

O presente documento atualiza os dados que revelam o perfil atual do ensino fundamental e médio no Brasil, re-visitando os bancos de dados de instituições oficiais (INEP e IBGE). Nós encontramos coincidências suspeitas que relacionam concentração de renda e abstinência educacional, como combustíveis que realimentam o ciclo da miséria em nosso país. Aspectos qualitativos da escola brasileira também foram levantados para que pudéssemos compreender as dificuldades do fazer educacional no Brasil e acenar com possibilidades concretas de mudança. Nós também investigamos, através da metodologia de estudo de caso, dois cursos de férias para implementar e avaliar a Aprendizagem Baseada em Problemas (ABP). As aulas foram direcionadas a professores e alunos do Ensino Médio. Através da observação direta e de inferências obtidas a partir de questionários aplicados a alunos e professores, antes e depois de cada um dos cursos (em 2004 e 2005), mediu-se o impacto da ABP sobre alunos e professores. Os resultados revelaram várias dificuldades e perplexidades demonstradas por professores e alunos, tais como a dificuldade em relacionar experimentos e conteúdos dos livros didáticos, a abstinência quase completa em experimentação e sua relação com o Método Científico, dificuldades de discernir entre hipótese e fato, etc. A Aprendizagem Baseada em Problemas foi aceita por todos (estudantes e professores) como uma possível maneira de mudar as aulas de Ciências e a Biologia. Contudo, sua ampla disseminação vai exigir capacitação em larga escala, gestão e liderança para iniciar o processo de mudança, aumentos de salários, e melhor infra-estrutura das escolas para experimentação. Utilizando metodologias semelhantes à ABP, como alternativa para capacitação, as universidades que desenvolvem atividades de pesquisa precisam ser diretamente envolvidas no processo através de fomento dirigido para a renovação. Um pacto educacional precisa ser construído para reformar o fazer educacional, e essa ação deve incluir Administradores e Professores das escolas de ensino fundamental e médio, Secretários de Educação (do Estado e do Município), Governos de Estado e do Município, Ministérios da Educação e da Ciência e Tecnologia, Universidades e Agências de Fomento para que o esforço possa ganhar dimensões nacionais.