916 resultados para learning tasks
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The dominant discourse in education and training policies, at the turn of the millennium, was on lifelong learning (LLL) in the context of a knowledge-based society. As Green points (2002, pp. 611-612) several factors contribute to this global trend: The demographic change: In most advanced countries, the average age of the population is increasing, as people live longer; The effects of globalisation: Including both economic restructuring and cultural change which have impacts on the world of education; Global economic restructuring: Which causes, for example, a more intense demand for a higher order of skills; the intensified economic competition, forcing a wave of restructuring and creating enormous pressure to train and retrain the workforce In parallel, the “significance of the international division of labour cannot be underestimated for higher education”, as pointed out by Jarvis (1999, p. 250). This author goes on to argue that globalisation has exacerbated differentiation in the labour market, with the First World converting faster to a knowledge economy and a service society, while a great deal of the actual manufacturing is done elsewhere.
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O objetivo desta investigação é compreender como é que alunos do 3.º ano de escolaridade desenvolvem o conceito de área com ênfase em conhecimentos sobre figuras e propriedades geométricas. Para melhor objetivar o estudo, formulei três questões que orientaram a investigação. Pretendo (1) compreender como é que os alunos mobilizam conhecimentos sobre as propriedades das figuras geométricas no estudo da área de uma figura plana? A que estratégias recorrem? Que dificuldades sentem? (2) que compreensão é que os alunos têm sobre o processo de medição? e (3) que ideias e/ou experiências são relevantes no desenvolvimento do conceito de área? Este é um estudo que se insere no paradigma interpretativo e que segue uma abordagem qualitativa, pelo que não visa generalização de resultados, mas uma descrição compreensiva dos processos vivenciados, tendo em conta os contextos pessoais e sociais. Optei por realizar dois Estudos de Caso. Os dados foram recolhidos através de fontes diversificadas, donde se destacam a observação participante e a análise de registos audiovisuais e escritos dos alunos. A análise dos dados teve por referência categorias criadas com base em contributos da literatura de referência. As conclusões desta investigação centram-se numa análise acerca das estratégias a que os alunos em estudo tendencialmente mais recorrem, visando também algumas das suas dificuldades mais relevantes e sobre as quais importa refletir. Destaca-se que ambos os alunos foram capazes de recorrer a raciocínios baseados e não baseados na medida, embora seja evidente uma tendência para raciocínios baseados na medida. É igualmente importante referir que os dois alunos revelaram um bom conhecimento acerca do processo de medição, mesmo quando ele implicava a definição de uma unidade de medida adequada e/ou mudança de unidade. É dado, também, destaque às experiências matemáticas que devem ser proporcionadas aos alunos no sentido do desenvolvimento de um conhecimento amplo e flexível do conceito de área. - Abstract The purpose of this investigation is to understand the development of 3rd year students’ concept of area based on their knowledge of geometrical properties and figures. As means to orientate the present study, the following investigation questions were formulated: 1) how do students use their knowledge about geometrical properties in order to understand geometrical shape’s areas? Which strategies do they use? What do they struggle with? (2) What is their understanding about measurement? And (3) what are the most relevant mathematical reasonings and classroom tasks in the development of the concept of area? This is a study that follows a qualitative approach: it does not intend to be a generalization, but a fully comprehensive description of the witnessed learning processes, bearing in mind the social and personal contexts. As such, two study-cases were developed. The data were collected through various sources, such as direct observation and analysis of audiovisual records or written worksheets. The scrutiny of the generated data was undertaken following criteria based on the literature of reference. The conclusions of this investigation are centered on the most used strategies as well as the students’ difficulties upon which it is important to discuss. It was noticed that the two students were able to use both measurement and non measurement thinking – although, preferably, they tend to use the first one. On the other hand, it is equally demonstrated that the two students have shown good acquaintance about measurement, even if obliged to the establishment of a suitable unit of measurement and/or change of units. At last, it is also referred which mathematical classroom tasks are important to develop a sustained and comprehensive concept of area.
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This paper presents a Multi-Agent Market simulator designed for developing new agent market strategies based on a complete understanding of buyer and seller behaviors, preference models and pricing algorithms, considering user risk preferences and game theory for scenario analysis. This tool studies negotiations based on different market mechanisms and, time and behavior dependent strategies. The results of the negotiations between agents are analyzed by data mining algorithms in order to extract rules that give agents feedback to improve their strategies. The system also includes agents that are capable of improving their performance with their own experience, by adapting to the market conditions, and capable of considering other agent reactions.
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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 simulator 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 is integrated with ALBidS, a system that provides several dynamic strategies for agents’ behavior. This paper presents a method that aims at enhancing ALBidS competence in endowing market players with adequate strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses a reinforcement learning algorithm to learn from experience how to choose the best from a set of possible actions. These actions are defined accordingly to the most probable points of bidding success. With the purpose of accelerating the convergence process, a simulated annealing based algorithm is included.
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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.
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Dissertação apresentada à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Audiovisual e Multimédia.
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Projeto de Intervenção apresentado à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Ciências da Educação - Especialidade Educação Especial
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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 simulator 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 provides several dynamic strategies for agents’ behavior. This paper presents a method that aims to provide market players with strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses a reinforcement learning algorithm to learn from experience how to choose the best from a set of possible bids. These bids are defined accordingly to the cost function that each producer presents.
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With the current increase of energy resources prices and environmental concerns intelligent load management systems are gaining more and more importance. This paper concerns a SCADA House Intelligent Management (SHIM) system that includes an optimization module using deterministic and genetic algorithm approaches. SHIM undertakes contextual load management based on the characterization of each situation. SHIM considers available generation resources, load demand, supplier/market electricity price, and consumers’ constraints and preferences. The paper focus on the recently developed learning module which is based on artificial neural networks (ANN). The learning module allows the adjustment of users’ profiles along SHIM lifetime. A case study considering a system with fourteen discrete and four variable loads managed by a SHIM system during five consecutive similar weekends is presented.
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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.
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A ESTSP-IPP implementou em 2008-2009 um novo modelo pedagógico, o PBL, em três licenciaturas. Este modelo tem sido considerado capaz de promover a aquisição de conhecimentos mas também o desenvolvimento de competências transversais valorizadas no mercado de trabalho; orienta-se em torno de problemas significativos da realidade profissional, trabalhados segundo a metodologia dos sete passos, destacando-se a aprendizagem através de pesquisa individual e trabalho de grupo; e visa ainda desenvolver processos cognitivos e metacognitivos como levantar hipóteses, comparar, analisar, interpretar e avaliar. Neste artigo, caracterizamos brevemente o modelo e respectivas implicações, justificando o interesse em investigar as repercussões da sua implementação.
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The activity of Control Center operators is important to guarantee the effective performance of Power Systems. Operators’ actions are crucial to deal with incidents, especially severe faults like blackouts. In this paper, we present an Intelligent Tutoring approach for training Portuguese Control Center operators in tasks like incident analysis and diagnosis, and service restoration of Power Systems. Intelligent Tutoring System (ITS) approach is used in the training of the operators, having into account context awareness and the unobtrusive integration in the working environment. Several Artificial Intelligence techniques were criteriously used and combined together to obtain an effective Intelligent Tutoring environment, namely Multiagent Systems, Neural Networks, Constraint-based Modeling, Intelligent Planning, Knowledge Representation, Expert Systems, User Modeling, and Intelligent User Interfaces.
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Paper presented at the Conference “The Reflective Conservatoire – 2nd International Conference: Building Connections”. Guildhall School of Music and Drama and Barbican Conference Centre, London. 28 February – 3 March 2009
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Electrical activity is extremely broad and distinct, requiring by one hand, a deep knowledge on rules, regulations, materials, equipments, technical solutions and technologies and assistance in several areas, as electrical equipment, telecommunications, security and efficiency and rational use of energy, on the other hand, also requires other skills, depending on the specific projects to be implemented, being this knowledge a characteristic that belongs to the professionals with relevant experience, in terms of complexity and specific projects that were made.
Resumo:
The Information and Communication Technology (ICT) provide new strategies for disseminating information and new communication models in order to change attitudes and human behaviour concerning to education. Nowadays the internet is crucial as a means of communication and information sharing. To education or tutorship will be required to use ICT, supported on the internet, to establish the communication of teacher-student and student-student, disseminating the content of the subjects, and as a way of teaching and learning process. This paper presents an intelligent tutor that aims to be a tool to support teaching and learning in the field of the electrical engineering project.