Que learning objects (LOs) utilizam as instituições de ensino superior ?

O uso das tecnologias com base na Web, no processo ensino/aprendizagem, têm obtido excelentes resultados, onde a Internet é a plataforma base de comunicação e interacção entre estudantes e professores. Assiste-se, também, a uma partilha/reutilização constante de conteúdos educativos/Learning Objects, em diferentes formatos e diferentes tipos de plataformas, incrementada pela Web 2.0. Este artigo apresenta um estudo sobre o desenvolvimento, disponibilização e utilização de Learning Objects em instituições de Ensino Superior. Conclui-se que as instituições de Ensino Superior inquiridas não desenvolvem, não reutilizam nem promovem a reutilização de LOs, que utilizam as especificações SCORM e IMS, e apresentam-se observações sobre as vantagens e desvantagens da sua utilização.

Experiencing flow while teaching and learning in individual tuition settings

Conferência anual da ISME

The Role of lifelong learning in creation of a european knowledge-based society

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.

O currículo funcional no desenvolvimento da autonomia e da comunicação oral e escrita

Os alunos com necessidades educativas especiais, mais concretamente os alunos que apresentam deficiência mental, com limitações acentuadas no comportamento adaptativo, necessitam um ensino mais individualizado, com uma vertente mais funcional. Os currículos funcionais, planeados de acordo com os contextos de vida atuais e futuros em que cada aluno se insere e se irá inserir, permitem desenvolver competências com significado e úteis para a formação pessoal, social e laboral, possibilitando uma vida adulta com mais qualidade e com mais autonomia. Este estudo incide no desenvolvimento de atividades funcionais para a promoção da autonomia e da comunicação oral e escrita em duas crianças, com 11 anos de idade, com défice cognitivo. Delinearam-se três objetivos para o estudo: i) caraterizar o nível de desenvolvimento e aprendizagem de duas alunas com défice cognitivo, nomeadamente no que respeita à autonomia e ao desenvolvimento da linguagem; ii) desenvolver conteúdos, estratégias e atividades funcionais que facilitem o progressivo aumento da participação das alunas em contextos reais de atividades de vida diária; iii) contribuir para o desenvolvimento de competências de autonomia e comunicação oral e escrita de duas alunas com défice cognitivo. Organizou-se um projeto de intervenção, desenvolvido na lógica da investigação ação. De modo a se elaborar o plano de intervenção, avaliaram-se as competências das alunas ao nível da comunicação oral e escrita, autonomia e funcionalidade, recorrendo à análise documental, a entrevistas às encarregadas de educação e à docente de Educação Especial, à observação direta e à elaboração de diários de aula. O plano de intervenção foi planeado no quadro dos currículos funcionais e centrou-se em atividades de vida diária, selecionadas a partir da análise das necessidades atuais e futuras das alunas. Após a implementação da intervenção, concluiu-se que a aplicação de atividades de um currículo funcional melhorou as competências de autonomia e de comunicação oral e escrita das alunas.- Abstract: Students with special educational needs, more specifically students who have mental disabilities, with significant behavior limits to adapt, need a more individual and functional education. The functional curriculum, planned according to the current and future life contexts in which every student is and will be, allow the development of meaningful skills, useful to their personal education, social life and labour, enabling them with an adulthood life with more quality and more autonomy. This study focuses on the development of functional activities for the promotion of autonomy and of oral and written communication in two children with 11 years old with mental disability. Three goals were outlined for the study: i) to characterize the level of development and learning of two students with cognitive dysfunction, regarding particularly the autonomy and the language development, ii) to develop contents, strategies and functional activities that increase the participation of the students in real daily life activities, iii) to contribute to the development of autonomy and oral and written communication of two students with mental disability. We organized an intervention project, developed in the logic of action research. In order to develop the intervention plan, we evaluated the level of oral and written communication, autonomy and functionality, through document analysis, interviews to the guardians and to the Special Educational teacher, as well as through direct observation and preparation of diaries of lessons. The intervention plan was outlined within the framework of functional curriculum and focused on activities of daily living, selected trough the analysis of current and future needs of the students. After the implementation of the intervention plan, we observed that the application of the activities of a functional curriculum improved the skills of autonomy and oral and written communication of the students

A novel framework for modeling value for the customer, an essay on negotiation

This paper proposes a novel framework for modelling the Value for the Customer, the so-called the Conceptual Model for Decomposing Value for the Customer (CMDVC). This conceptual model is first validated through an exploratory case study where the authors validate both the proposed constructs of the model and their relations. In a second step the authors propose a mathematical formulation for the CMDVC as well as a computational method. This has enabled the final quantitative discussion of how the CMDVC can be applied and used in the enterprise environment, and the final validation by the people in the enterprise. Along this research, we were able to confirm that the results of this novel quantitative approach to model the Value for the Customer is consistent with the company's empirical experience. The paper further discusses the merits and limitations of this approach, proposing that the model is likely to bring value to support not only the contract preparation at an Ex-Ante Negotiation Phase, as demonstrated, but also along the actual negotiation process, as finally confirmed by an enterprise testimonial.

Learning business strategies for competitive electronic marketplaces

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.

Intelligent decision making in electricity markets: simulated annealing Q-Learning

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.

Methods for automatic and assisted image annotation

Personal memories composed of digital pictures are very popular at the moment. To retrieve these media items annotation is required. During the last years, several approaches have been proposed in order to overcome the image annotation problem. This paper presents our proposals to address this problem. Automatic and semi-automatic learning methods for semantic concepts are presented. The automatic method is based on semantic concepts estimated using visual content, context metadata and audio information. The semi-automatic method is based on results provided by a computer game. The paper describes our proposals and presents their evaluations.

Meta-heuristics self-configuration for scheduling

Scheduling resolution requires the intervention of highly skilled human problemsolvers. This is a very hard and challenging domain because current systems are becoming more and more complex, distributed, interconnected and subject to rapidly changing. A natural Autonomic Computing evolution in relation to Current Computing is to provide systems with Self-Managing ability with a minimum human interference. This paper addresses the resolution of complex scheduling problems using cooperative negotiation. A Multi-Agent Autonomic and Meta-heuristics based framework with self-configuring capabilities is proposed.

A regulatory framework for short-term stochastic maintenance outage scheduling in smart grids

The current regulatory framework for maintenance outage scheduling in distribution systems needs revision to face the challenges of future smart grids. In the smart grid context, generation units and the system operator perform new roles with different objectives, and an efficient coordination between them becomes necessary. In this paper, the distribution system operator (DSO) of a microgrid receives the proposals for shortterm (ST) planned outages from the generation and transmission side, and has to decide the final outage plans, which is mandatory for the members to follow. The framework is based on a coordination procedure between the DSO and other market players. This paper undertakes the challenge of optimization problem in a smart grid where the operator faces with uncertainty. The results show the effectiveness and applicability of the proposed regulatory framework in the modified IEEE 34- bus test system.

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.

A utilização da plataforma Educast@fccn, como ferramenta de gravação de aulas no ambiente de e-learning português

Dissertação apresentada à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Audiovisual e Multimédia.

Cost dependent strategy for electricity markets bidding based on adaptive reinforcement learning

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.

Contextual intelligent load management with ANN adaptive learning module

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.