Thinking over b‐learning strategy: the MIPO model approach

This article describes the main research results in a new methodology, in which the stages and strategies of the technology integration process are identified and described. A set of principles and recommendations are therefore presented. The MIPO model described in this paper is a result of the effort made regarding the understanding of the main success features of good practices, in the web environment, integrated in the information systems/information technology context. The initial model has been created, based on experiences and literature review. After that, it was tested in the information and technology system units at higher school and also adapted as a result of four cycles of an actionresearch work combined with a case study research. The information, concepts and procedures presented here give support to teachers and instructors, instructional designers and planning teams – anyone who wants to develop effective b‐learning instructions.

Six thinking hats for electricity markets simulation: adapting meeting tools to agent decision

In almost all industrialized countries, the energy sector has suffered a severe restructuring that originated a greater complexity in market players’ interactions. The complexity that these changes brought made way for the creation of decision support tools that facilitate the study and understanding of these markets. MASCEM – “Multiagent Simulator for Competitive Electricity Markets” arose in this context providing a framework for evaluating new rules, new behaviour, and new participants in deregulated electricity markets. MASCEM uses game theory, machine learning techniques, scenario analysis and optimisation techniques to model market agents and to provide them with decision-support. ALBidS is a multiagent system created to provide decision support to market negotiating players. Fully integrated with MASCEM it considers several different methodologies based on very distinct approaches. The Six Thinking Hats is a powerful technique used to look at decisions from different perspectives. This tool’s goal is to force the thinker to move outside his habitual thinking style. It was developed to be used mainly at meetings in order to “run better meetings, make faster decisions”. This dissertation presents a study about the applicability of the Six Thinking Hats technique in Decision Support Systems, particularly with the multiagent paradigm like the MASCEM simulator. As such this work’s proposal is of a new agent, a meta-learner based on STH technique that organizes several different ALBidS’ strategies and combines the distinct answers into a single one that, expectedly, out-performs any of them.

A dimensão crítica na interpretação musical

Dissertação para obtenção do grau de Mestre em Música - Interpretação Artística

Six thinking hats: A novel metalearner for intelligent decision support in electricity markets

The energy sector has suffered a significant restructuring that has increased the complexity in electricity market players' interactions. The complexity that these changes brought requires the creation of decision support tools to facilitate the study and understanding of these markets. The Multiagent Simulator of Competitive Electricity Markets (MASCEM) arose in this context, providing a simulation framework for deregulated electricity markets. The Adaptive Learning strategic Bidding System (ALBidS) is a multiagent system created to provide decision support to market negotiating players. Fully integrated with MASCEM, ALBidS considers several different strategic methodologies based on highly distinct approaches. Six Thinking Hats (STH) is a powerful technique used to look at decisions from different perspectives, forcing the thinker to move outside its usual way of thinking. This paper aims to complement the ALBidS strategies by combining them and taking advantage of their different perspectives through the use of the STH group decision technique. The combination of ALBidS' strategies is performed through the application of a genetic algorithm, resulting in an evolutionary learning approach.

O jogo como estratégia de aprendizagem rítmica: A ludicidade na exploração das fichas de exercícios rítmicos

Elaborado com vista à reflexão fundamentada acerca do percurso, das práticas educativas e das políticas de ensino, o presente trabalho pretende reunir um conjunto de saberes inerentes à atividade docente. Relacionando teorias e práticas no âmbito do ensino da música, a apresentação de uma filosofia de trabalho, congregando como eixo estruturante a prática musical supervisionada realizada no âmbito do ensino vocacional, apresenta-se como pano de fundo à análise dos vários conteúdos referentes à literatura específica inerente à prática pedagógica. Partindo da caracterização da escola do ensino vocacional de música, nos ensinos Básico e Secundário, a presente reflexão emerge no seguimento do pensamento articulado das várias áreas do saber através da apreciação, fundamentação e discussão das perspetivas de ensino vigentes ao longo do processo de estágio. Deste modo, será exposta toda a perspetiva de ensino por nós desenvolvida, partindo de uma linha temporal, tendo por princípio a descrição de um plano modelo, com o objetivo de podermos demonstrar a direção do nosso pensamento. Tendo como objetivo verificar a eficácia da abordagem ao jogo, como estratégia de ensino, na aprendizagem do ritmo, na disciplina de Formação Musical, partimos de uma investigação bibliográfica sobre a relação entre a escola tradicional e a escola moderna, o jogo e a motivação, e por último, a aprendizagem do ritmo sobre a perspetiva das atividades de aprendizagem sequencial, sustentadas por Edwin Gordon. O projeto de investigação aborda uma nova conceção do jogo, aliando o mesmo às atividades de leitura rítmicas.