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Relatório de estágio de mestrado em Ensino do 1.º e 2.º Ciclo do Ensino Básico, O presente relatório insere-se, no âmbito do Mestrado em Ensino do 1º e 2º Ciclo do Ensino Básico, concretamente na componente do estágio da UC Prática de Ensino Supervisionada. O projeto desenvolvido durante a permanência nas escolas do 1º e 2º CEB, teve como principal objetivo, a evolução das ideias dos alunos sobre a temática Flutuação e os Micróbios, respetivamente. No 1º.Ciclo a principal estratégia levada a cabo na intervenção educativa baseou-se num conjunto de atividades laboratoriais do tipo Prevê-Observa-Explica-Reflete (POER), enquanto que no 2º. Ciclo as atividades foram pensadas e organização segundo o paradigma de Mudança Conceptual. Em ambos os ciclos pretendia-se, conhecer as ideias prévias dos alunos sobres as temáticas em estudo, assim como promover a prática do ensino laboratorial, cujo objetivo fundamental foi percecionar a evolução das ideias dos alunos, acerca das temáticas propostas através da implementação das atividades laboratoriais. A intervenção no 1º CEB os alunos parece ter desenvolvido o conceito de flutuação/afundamento. Já na intervenção no 2º CEB foi possível detetar uma evolução das ideias relativas ao conceito de “micróbio”., The present study is part of the framework for Masters in Education of 1st and 2nd Cycles of Primary School, specifically in the academic training of Supervised Teaching Practices UC. The developed project during the stay in the 1st and 2nd Cycles aimed the development of student´s knowledge about fluctuation and microbes, respectively. In the 1st Cycle the main strategy carried out in the educational intervention was based on a set of hands-on laboratory Predict-Observe-Explain-Reflect (POER) type activities, whereas in the 2nd Cycle were developed activities based on Conceptual Change paradigm. For both 1st and 2nd cycles was intended to know the student´s previous knowledge about the subjects under this study and promote the practice of laboratory teaching whose main goal was get a feeling of the progress of student´s ideas about the proposed subjects through the implementation of laboratory activities. In the 1st Cycle intervention, students proved to have developed the double concept of floating/sinking, whereas in the 2nd Cycle intervention was possible to detect a progress on the ideas regarding to “microbe” concept.

This study examines the statistical power levels presented in the dissertations completed in the field of educational leadership or educational administration. Eighty out of 221 reviewed dissertations were analyzed and overall statistical power levels were calculated for 2,629 significance tests. The statistical power levels demonstrated in the dissertations were satisfactory for detecting Cohen's large effect (d=0.80) and medium effect (d=0.50) but quite low for small effect (d=0.20). Therefore, the authors of analyzed dissertations had a very low probability of finding true significance when looking for Cohen's small effect. Accessed 19,703 times on https://pareonline.net from September 20, 2005 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right.

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Dans ce texte, nous analysons les développements récents de l’économétrie à la lumière de la théorie des tests statistiques. Nous revoyons d’abord quelques principes fondamentaux de philosophie des sciences et de théorie statistique, en mettant l’accent sur la parcimonie et la falsifiabilité comme critères d’évaluation des modèles, sur le rôle de la théorie des tests comme formalisation du principe de falsification de modèles probabilistes, ainsi que sur la justification logique des notions de base de la théorie des tests (tel le niveau d’un test). Nous montrons ensuite que certaines des méthodes statistiques et économétriques les plus utilisées sont fondamentalement inappropriées pour les problèmes et modèles considérés, tandis que de nombreuses hypothèses, pour lesquelles des procédures de test sont communément proposées, ne sont en fait pas du tout testables. De telles situations conduisent à des problèmes statistiques mal posés. Nous analysons quelques cas particuliers de tels problèmes : (1) la construction d’intervalles de confiance dans le cadre de modèles structurels qui posent des problèmes d’identification; (2) la construction de tests pour des hypothèses non paramétriques, incluant la construction de procédures robustes à l’hétéroscédasticité, à la non-normalité ou à la spécification dynamique. Nous indiquons que ces difficultés proviennent souvent de l’ambition d’affaiblir les conditions de régularité nécessaires à toute analyse statistique ainsi que d’une utilisation inappropriée de résultats de théorie distributionnelle asymptotique. Enfin, nous soulignons l’importance de formuler des hypothèses et modèles testables, et de proposer des techniques économétriques dont les propriétés sont démontrables dans les échantillons finis., In this text, we review recent developments in econometrics from the viewpoint of statistical test theory. We first review some basic principles of philosophy of science and statistical theory, emphasizing parsimony and falsifiability as criteria for evaluating models, test theory as a formalization of the falsification principle for probabilistic models, and the logical foundation of basic notions in test theory (such as the level of a test). We then show that some of the most frequently used statistical and econometric methods are fundamentally inappropriate for the problems and models considered, while several hypotheses, for which test procedures are commonly proposed, are not testable at all. Such situations lead to ill-defined statistical problems. We analyze several cases of such problems : (1) building confidence intervals in structural models where identification problems may be present; (2) the construction of tests for nonparametric hypotheses, including procedures robust to heteroskadasticity, non-normality or dynamic specification. We point out that these difficulties often originate from the ambition to weaken regularity conditions typically required by statistical analysis, and from an inappropriate use of asymptotic distributional theory. Finally, we underscore the importance of formulating testable hypotheses and models, and of developing econometric methods with provable finite-sample properties. Keywords: econometrics; statistics; testing; philosophy of science; falsifiability; Popper; parsimony; identification; weak instruments; nonparametric model; time series; autoregressive model; heteroskedasticity; unit root; robust method; non-normality; ill-defined problem