The role of Lifelong Learning in the creation of a knowledge-based society for Europe: european policies

Link do editor: http://www.igi-global.com/chapter/role-lifelong-learning-creation-european/13314

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.

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.

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.

Problem-Based Learning e suas implica����es: breve revis��o te��rica

A ESTSP-IPP implementou em 2008-2009 um novo modelo pedag��gico, o PBL, em tr��s licenciaturas. Este modelo tem sido considerado capaz de promover a aquisi����o de conhecimentos mas tamb��m o desenvolvimento de compet��ncias 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 atrav��s de pesquisa individual e trabalho de grupo; e visa ainda desenvolver processos cognitivos e metacognitivos como levantar hip��teses, comparar, analisar, interpretar e avaliar. Neste artigo, caracterizamos brevemente o modelo e respectivas implica����es, justificando o interesse em investigar as repercuss��es da sua implementa����o.

Information and communication technologies in education ��� a web-based intelligent tutoring system on teaching and learning electrical project

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.

A web-based intelligent tutoring system on teaching and learning electrical project

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.

How to integrate stories and ICT in content-based units of work for English learning

The aim of this article is to show how it is possible to integrate stories and ICT in Content Language Integrated Learning (CLIL) for English as a foreign language (EFL) learning in bilingual schools. Two Units of Work are presented. One, for the second year of Primary, is based on a Science topic, ���Materials���. The story used is ���The three little pigs��� and the computer program ���JClic���. The other one is based on a Science and Arts topic for the sixth year of Primary, the story used is ���Charlotte���s Web��� and the computer program ���Atenex���.

Reverse problem-based learning - a case study with a Braille machine

Engineering Education includes not only teaching theoretical fundamental concepts but also its verification during practical lessons in laboratories. The usual strategies to carry out this action are frequently based on Problem Based Learning, starting from a given state and proceeding forward to a target state. The possibility or the effectiveness of this procedure depends on previous states and if the present state was caused or resulted from earlier ones. This often happens in engineering education when the achieved results do not match the desired ones, e.g. when programming code is being developed or when the cause of the wrong behavior of an electronic circuit is being identified. It is thus important to also prepare students to proceed in the reverse way, i.e. given a start state generate the explanation or even the principles that underlie it. Later on, this sort of skills will be important. For instance, to a doctor making a patient?s story or to an engineer discovering the source of a malfunction. This learning methodology presents pedagogical advantages besides the enhanced preparation of students to their future work. The work presented on his document describes an automation project developed by a group of students in an engineering polytechnic school laboratory. The main objective was to improve the performance of a Braille machine. However, in a scenario of Reverse Problem-Based learning, students had first to discover and characterize the entire machine's function before being allowed (and being able) to propose a solution for the existing problem.

A mobile robot platform for open learning based on serious games and remote laboratories

Within the pedagogical community, Serious Games have arisen as a viable alternative to traditional course-based learning materials. Until now, they have been based strictly on software solutions. Meanwhile, research into Remote Laboratories has shown that they are a viable, low-cost solution for experimentation in an engineering context, providing uninterrupted access, low-maintenance requirements, and a heightened sense of reality when compared to simulations. This paper will propose a solution where both approaches are combined to deliver a Remote Laboratory-based Serious Game for use in engineering and school education. The platform for this system is the WebLab-Deusto Framework, already well-tested within the remote laboratory context, and based on open standards. The laboratory allows users to control a mobile robot in a labyrinth environment and take part in an interactive game where they must locate and correctly answer several questions, the subject of which can be adapted to educators' needs. It also integrates the Google Blockly graphical programming language, allowing students to learn basic programming and logic principles without needing to understand complex syntax.

Hand gesture recognition system based in computer vision and machine learning : applications on human-machine interaction

Sendo uma forma natural de intera����o homem-m��quina, o reconhecimento de gestos implica uma forte componente de investiga����o em ��reas como a vis��o por computador e a aprendizagem computacional. O reconhecimento gestual �� uma ��rea com aplica����es muito diversas, fornecendo aos utilizadores uma forma mais natural e mais simples de comunicar com sistemas baseados em computador, sem a necessidade de utiliza����o de dispositivos extras. Assim, o objectivo principal da investiga����o na ��rea de reconhecimento de gestos aplicada �� interac����o homemm��quina �� o da cria����o de sistemas, que possam identificar gestos espec��ficos e us��los para transmitir informa����es ou para controlar dispositivos. Para isso as interfaces baseados em vis��o para o reconhecimento de gestos, necessitam de detectar a m��o de forma r��pida e robusta e de serem capazes de efetuar o reconhecimento de gestos em tempo real. Hoje em dia, os sistemas de reconhecimento de gestos baseados em vis��o s��o capazes de trabalhar com solu����es espec��ficas, constru��dos para resolver um determinado problema e configurados para trabalhar de uma forma particular. Este projeto de investiga����o estudou e implementou solu����es, suficientemente gen��ricas, com o recurso a algoritmos de aprendizagem computacional, permitindo a sua aplica����o num conjunto alargado de sistemas de interface homem-m��quina, para reconhecimento de gestos em tempo real. A solu����o proposta, Gesture Learning Module Architecture (GeLMA), permite de forma simples definir um conjunto de comandos que pode ser baseado em gestos est��ticos e din��micos e que pode ser facilmente integrado e configurado para ser utilizado numa s��rie de aplica����es. �� um sistema de baixo custo e f��cil de treinar e usar, e uma vez que �� constru��do unicamente com bibliotecas de c��digo. As experi��ncias realizadas permitiram mostrar que o sistema atingiu uma precis��o de 99,2% em termos de reconhecimento de gestos est��ticos e uma precis��o m��dia de 93,7% em termos de reconhecimento de gestos din��micos. Para validar a solu����o proposta, foram implementados dois sistemas completos. O primeiro �� um sistema em tempo real capaz de ajudar um ��rbitro a arbitrar um jogo de futebol rob��tico. A solu����o proposta combina um sistema de reconhecimento de gestos baseada em vis��o com a defini����o de uma linguagem formal, o CommLang Referee, �� qual demos a designa����o de Referee Command Language Interface System (ReCLIS). O sistema identifica os comandos baseados num conjunto de gestos est��ticos e din��micos executados pelo ��rbitro, sendo este posteriormente enviado para um interface de computador que transmite a respectiva informa����o para os rob��s. O segundo �� um sistema em tempo real capaz de interpretar um subconjunto da Linguagem Gestual Portuguesa. As experi��ncias demonstraram que o sistema foi capaz de reconhecer as vogais em tempo real de forma fi��vel. Embora a solu����o implementada apenas tenha sido treinada para reconhecer as cinco vogais, o sistema �� facilmente extens��vel para reconhecer o resto do alfabeto. As experi��ncias tamb��m permitiram mostrar que a base dos sistemas de intera����o baseados em vis��o pode ser a mesma para todas as aplica����es e, deste modo facilitar a sua implementa����o. A solu����o proposta tem ainda a vantagem de ser suficientemente gen��rica e uma base s��lida para o desenvolvimento de sistemas baseados em reconhecimento gestual que podem ser facilmente integrados com qualquer aplica����o de interface homem-m��quina. A linguagem formal de defini����o da interface pode ser redefinida e o sistema pode ser facilmente configurado e treinado com um conjunto de gestos diferentes de forma a serem integrados na solu����o final.

Multi-Agent Based Smart Grid Management and Simulation: Situation Awareness and Learning in a Test Bed with Simulated and Real Installations and Players

The rising usage of distributed energy resources has been creating several problems in power systems operation. Virtual Power Players arise as a solution for the management of such resources. Additionally, approaching the main network as a series of subsystems gives birth to the concepts of smart grid and micro grid. Simulation, particularly based on multi-agent technology is suitable to model all these new and evolving concepts. MASGriP (Multi-Agent Smart Grid simulation Platform) is a system that was developed to allow deep studies of the mentioned concepts. This paper focuses on a laboratorial test bed which represents a house managed by a MASGriP player. This player is able to control a real installation, responding to requests sent by the system operators and reacting to observed events depending on the context.

Reinforcement Learning Based on the Bayesian Theorem for Electricity Markets Decision Support

This paper presents the applicability of a reinforcement learning algorithm based on the application of the Bayesian theorem of probability. The proposed reinforcement learning algorithm is an advantageous and indispensable tool for ALBidS (Adaptive Learning strategic Bidding System), a multi-agent system that has the purpose of providing decision support to electricity market negotiating players. ALBidS uses a set of different strategies for providing decision support to market players. These strategies are used accordingly to their probability of success for each different context. The approach proposed in this paper uses a Bayesian network for deciding the most probably successful action at each time, depending on past events. The performance of the proposed methodology is tested using electricity market simulations in MASCEM (Multi-Agent Simulator of Competitive Electricity Markets). MASCEM provides the means for simulating a real electricity market environment, based on real data from real electricity market operators.