Educational characteristics of adult students in portuguese technological schools

Despite a massive expansion of education in Portugal, since the 1970’s, educational attainment of the adult population in the country remains low. The numbers of working-age people in some form of continuing education are among the lowest, according to the OECD and EU-27 statistics. Technological Schools(TS), initially created in the 1990’s, under the umbrella of the Ministry of Economy in partnership with industry and industrial associations, aimed to prepare qualified staff for industries and services in the country, particularly in the engineering sector, through the provision of post secondary non-university programmes of studies, the CET (Technological Specialization Courses). Successful CET students are awarded a DET(Diploma of Technological Specialization), which corresponds to Vocational Qualification level IV of the EU, according to the latest alteration (2005) of the Education Systems Act (introduced in 1986). In this, CET’s are also clearly defined as one of the routes for access to Higher Education (HE), in Portugal. The PRILHE (Promoting Reflective and Independent Learning in Higher Education) multinational project, funded by the European Socrates Grundtvig Programme, aimed to identify the learning processes which enable adult students in higher education to become autonomous reflective learners and search best practices to support these learning processes. During this research, both quantitative and qualitative methods were used to determine how students organise their studies and develop their learning skills. The Portuguese partner in the project’ consortium used a two case studies approach, one with students of Higher Education Institutions and other with students of TS. This paper only applies to students of TS, as these have a predominant bias towards engineering. Results show that student motivation and professional teaching support contribute equally to the development of an autonomous and reflective approach to learning in adult students; this is essential for success in a knowledge economy, where lifelong learning is the key to continuous employment.

Methodology in the epidemiological research of respiratory diseases and environmental pollution

There are complex and diverse methodological problems involved in the clinical and epidemiological study of respiratory diseases and their etiological factors. The association of urban growth, industrialization and environmental deterioration with respiratory diseases makes it necessary to pay more attention to this research area with a multidisciplinary approach. Appropriate study designs and statistical techniques to analyze and improve our understanding of the pathological events and their causes must be implemented to reduce the growing morbidity and mortality through better preventive actions and health programs. The objective of the article is to review the most common methodological problems in this research area and to present the most available statistical tools used.

A aplicação da CIF nos programas educativos individualizados das crianças e jardim de infância

A Classificação Internacional da Funcionalidade, Crianças e Jovens (CIF-CJ), usando uma linguagem comum e universal, permite a comunicação entre os diferentes profissionais e investigadores. Sustenta-se numa abordagem biopsicossocial que pressupõe um processo interactivo da participação com os contextos de vida da criança, classificando a criança quanto à sua funcionalidade, definindo perfis de funcionalidade. A reestruturação do Programa Educativo Individual (PEI) através do decreto-lei 3/2008, passa a incluir uma terminologia da CIF-CJ, para a determinação do Perfil de Funcionalidade e Plano de Intervenção. Devido à sua pertinência e actualidade foi objectivo deste estudo fazer a análise da aplicação da CIF nos Programas Educativos Individualizados das crianças da Creche e Jardim de Infância do Cabedelo, verificando se os conteúdos dos PEI das crianças tem ligação com as componentes da CIF-CJ, se são elaborados de modo a englobarem predominantemente os constructos ligados à Actividade e Participação e ao Ambiente segundo o modelo biopsicossocial, e se os constructos identificados no Perfil de Funcionalidade surgem como alvo no Plano de Intervenção. Seleccionámos uma amostra de 15 crianças com Necessidades Educativas Especiais (NEE) com idades entre os dois e os seis anos de idade. A metodologia foi mista iniciando com um estudo qualitativo seguido de uma metodologia quantitativa. Assim procedeu-se a uma análise de conteúdo dos PEI’s, utilizando as linking rules para os relacionar com a CIF-CJ, e posteriormente efectuou-se uma análise de frequências com recurso à estatística descritiva. Os resultados indicam existir uma ligação dos conteúdos dos PEI’s com os componentes da CIF-CJ. O Perfil de Funcionalidade e Plano de Intervenção centram-se na componente Actividades e Participação sendo os Factores do Ambiente menos citados em ambos os processos. Em relação à existência de correspondência dos constructos do Perfil de Funcionalidade com o Plano de Intervenção não há uma correspondência directa em grande parte dos códigos, havendo no entanto uma correspondência na mesma área ou em áreas diferentes mas relacionáveis entre si.

Efeitos de um programa de educação para a saúde no doente portador de DPOC

Objectivo: Verificar o efeito de um programa de educação para a saúde em doentes portadores de DPOC. Metodologia: Estudo experimental (ensaio clínico) com 18 doentes portadores de DPOC seleccionados aleatoriamente através da consulta de Medicina Geral e Familiar. Depois de informar os objectivos do estudo e os aspectos éticos, os participantes realizaram uma avaliação da função pulmonar, capacidade de tolerância ao exercício, qualidade de vida, actividades de vida diária (AVD), dispneia e ansiedade e depressão. Posteriormente os indivíduos do grupo controlo receberam um manual informativo e os incluídos no grupo experimental além de receber o manual foram submetidos a 6 sessões de educação. Após 8 semanas todos os doentes foram reavaliados. O nível de significância utilizado nos testes estatísticos foi α=0.05 (intervalo de confiança de 95%). Resultados: A análise da diferença dos ganhos entre os grupos revelou-se estatisticamente significativa nas variáveis qualidade de vida (p<0,001), AVD (p<0,001) e depressão (p<0,001). Na capacidade de tolerância ao exercício ambos os grupos melhoraram significativamente mas a diferença de ganhos não foi estatisticamente significativa (p=0,289), tal como na variável ansiedade (p=0,960). Conclusão: Este estudo parece demonstrar que o programa de educação foi eficaz nas variáveis qualidade de vida, AVD e depressão.

Adaptive learning in multiagent systems: a forecasting methodology based on error analysis

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simu-lator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM pro-vides several dynamic strategies for agents’ behaviour. This paper presents a method that aims to provide market players strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses an auxiliary forecasting tool, e.g. an Artificial Neural Net-work, to predict the electricity market prices, and analyses its forecasting error patterns. Through the recognition of such patterns occurrence, the method predicts the expected error for the next forecast, and uses it to adapt the actual forecast. The goal is to approximate the forecast to the real value, reducing the forecasting error.

Genetic algorithm methodology applied to intelligent house control

In recent years the use of several new resources in power systems, such as distributed generation, demand response and more recently electric vehicles, has significantly increased. Power systems aim at lowering operational costs, requiring an adequate energy resources management. In this context, load consumption management plays an important role, being necessary to use optimization strategies to adjust the consumption to the supply profile. These optimization strategies can be integrated in demand response programs. The control of the energy consumption of an intelligent house has the objective of optimizing the load consumption. This paper presents a genetic algorithm approach to manage the consumption of a residential house making use of a SCADA system developed by the authors. Consumption management is done reducing or curtailing loads to keep the power consumption in, or below, a specified energy consumption limit. This limit is determined according to the consumer strategy and taking into account the renewable based micro generation, energy price, supplier solicitations, and consumers’ preferences. The proposed approach is compared with a mixed integer non-linear approach.

Perspetivas das educadoras de infância de uma instituição particular de solidariedade social sobre o contributo da colaboração para o seu desenvolvimento profissional

Dissertação apresentada à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Ciências da Educação, especialidade em Supervisão em Educação

Perspetivas dos professores do 1º ciclo sobre a supervisão no processo de avaliação de desempenho e os seus efeitos no desenvolvimento profissional

Dissertação apresentada à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Ciências da Educação, especialização Supervisão em Educação

Práticas de inclusão de alunos com perturbação do espectro do autismo no 1º Ciclo

Dissertação apresentada à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Ciências da Educação, especialidade Educação Especial – Problemas Cognitivos e Multideficiência

A expressão dramática/teatro no 1º ciclo do ensino básico: conceções e práticas de professores

Dissertação apresentada à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Ciências da Educação, Especialidade em Educação Artística – Teatro na Educação

A data-mining based methodology for wind forecasting

In many countries the use of renewable energy is increasing due to the introduction of new energy and environmental policies. Thus, the focus on the efficient integration of renewable energy into electric power systems is becoming extremely important. Several European countries have already achieved high penetration of wind based electricity generation and are gradually evolving towards intensive use of this generation technology. The introduction of wind based generation in power systems poses new challenges for the power system operators. This is mainly due to the variability and uncertainty in weather conditions and, consequently, in the wind based generation. In order to deal with this uncertainty and to improve the power system efficiency, adequate wind forecasting tools must be used. This paper proposes a data-mining-based methodology for very short-term wind forecasting, which is suitable to deal with large real databases. The paper includes a case study based on a real database regarding the last three years of wind speed, and results for wind speed forecasting at 5 minutes intervals.

A data-mining-based methodology for transmission expansion planning

In recent decades, all over the world, competition in the electric power sector has deeply changed the way this sector’s agents play their roles. In most countries, electric process deregulation was conducted in stages, beginning with the clients of higher voltage levels and with larger electricity consumption, and later extended to all electrical consumers. The sector liberalization and the operation of competitive electricity markets were expected to lower prices and improve quality of service, leading to greater consumer satisfaction. Transmission and distribution remain noncompetitive business areas, due to the large infrastructure investments required. However, the industry has yet to clearly establish the best business model for transmission in a competitive environment. After generation, the electricity needs to be delivered to the electrical system nodes where demand requires it, taking into consideration transmission constraints and electrical losses. If the amount of power flowing through a certain line is close to or surpasses the safety limits, then cheap but distant generation might have to be replaced by more expensive closer generation to reduce the exceeded power flows. In a congested area, the optimal price of electricity rises to the marginal cost of the local generation or to the level needed to ration demand to the amount of available electricity. Even without congestion, some power will be lost in the transmission system through heat dissipation, so prices reflect that it is more expensive to supply electricity at the far end of a heavily loaded line than close to an electric power generation. Locational marginal pricing (LMP), resulting from bidding competition, represents electrical and economical values at nodes or in areas that may provide economical indicator signals to the market agents. This article proposes a data-mining-based methodology that helps characterize zonal prices in real power transmission networks. To test our methodology, we used an LMP database from the California Independent System Operator for 2009 to identify economical zones. (CAISO is a nonprofit public benefit corporation charged with operating the majority of California’s high-voltage wholesale power grid.) To group the buses into typical classes that represent a set of buses with the approximate LMP value, we used two-step and k-means clustering algorithms. By analyzing the various LMP components, our goal was to extract knowledge to support the ISO in investment and network-expansion planning.

Strategic bidding methodology for electricity markets using adaptive learning

The very particular characteristics of electricity markets, require deep studies of the interactions between the involved players. MASCEM is a market simulator developed to allow studying electricity market negotiations. This paper presents a new proposal for the definition of MASCEM players’ strategies to negotiate in the market. The proposed methodology is implemented as a multiagent system, using reinforcement learning algorithms to provide players with the capabilities to perceive the changes in the environment, while adapting their bids formulation according to their needs, using a set of different techniques that are at their disposal. This paper also presents a methodology to define players’ models based on the historic of their past actions, interpreting how their choices are affected by past experience, and competition.

Zonal prices analysis supported by a data mining based methodology

A methodology based on data mining techniques to support the analysis of zonal prices in real transmission networks is proposed in this paper. The mentioned methodology uses clustering algorithms to group the buses in typical classes that include a set of buses with similar LMP values. Two different clustering algorithms have been used to determine the LMP clusters: the two-step and K-means algorithms. In order to evaluate the quality of the partition as well as the best performance algorithm adequacy measurements indices are used. The paper includes a case study using a Locational Marginal Prices (LMP) data base from the California ISO (CAISO) in order to identify zonal prices.

Optimal methodology for renewable energy dispatching in islanded operation

The management of energy resources for islanded operation is of crucial importance for the successful use of renewable energy sources. A Virtual Power Producer (VPP) can optimally operate the resources taking into account the maintenance, operation and load control considering all the involved cost. This paper presents the methodology approach to formulate and solve the problem of determining the optimal resource allocation applied to a real case study in Budapest Tech’s. The problem is formulated as a mixed-integer linear programming model (MILP) and solved by a deterministic optimization technique CPLEX-based implemented in General Algebraic Modeling Systems (GAMS). The problem has also been solved by Evolutionary Particle Swarm Optimization (EPSO). The obtained results are presented and compared.