888 resultados para Learning Society


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Dissertação apresentada à Escola Superior de Educação de Lisboa para a obtenção do grau de mestre em Ciências da Educação - Especialidade em Educação Social e Intervenção Comunitária

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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.

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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.

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The aim of this paper is presenting the modules of the Adaptive Educational Hypermedia System PCMAT, responsible for the recommendation of learning objects. PCMAT is an online collaborative learning platform with a constructivist approach, which assesses the user’s knowledge and presents contents and activities adapted to the characteristics and learning style of students of mathematics in basic schools. The recommendation module and search and retrieval module choose the most adequate learning object, based on the user's characteristics and performance, and in this way contribute to the system’s adaptability.

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The scheduling problem is considered in complexity theory as a NP-hard combinatorial optimization problem. Meta-heuristics proved to be very useful in the resolution of this class of problems. However, these techniques require parameter tuning which is a very hard task to perform. A Case-based Reasoning module is proposed in order to solve the parameter tuning problem in a Multi-Agent Scheduling System. A computational study is performed in order to evaluate the proposed CBR module performance.

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Dissertação apresentada à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Ciências da Educação Especialização em Administração Escolar

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In this paper, we foresee the use of Multi-Agent Systems for supporting dynamic and distributed scheduling in Manufacturing Systems. We also envisage the use of Autonomic properties in order to reduce the complexity of managing systems and human interference. By combining Multi-Agent Systems, Autonomic Computing, and Nature Inspired Techniques we propose an approach for the resolution of dynamic scheduling problem, with Case-based Reasoning Learning capabilities. The objective is to permit a system to be able to automatically adopt/select a Meta-heuristic and respective parameterization considering scheduling characteristics. From the comparison of the obtained results with previous results, we conclude about the benefits of its use.

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This paper is about PCMAT, an adaptive learning platform for Mathematics in Basic Education schools. Based on a constructivist approach, PCMAT aims at verifying how techniques from adaptive hypermedia systems can improve e-learning based systems. To achieve this goal, PCMAT includes a Pedagogical Model that contains a set of adaptation rules that influence the student-platform interaction. PCMAT was subject to a preliminary testing with students aged between 12 and 14 years old on the subject of direct proportionality. The results from this preliminary test are quite promising as they seem to demonstrate the validity of our proposal.

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The aim of this paper is to present an adaptation model for an Adaptive Educational Hypermedia System, PCMAT. The adaptation of the application is based on progressive self-assessment (exercises, tasks, and so on) and applies the constructivist learning theory and the learning styles theory. Our objective is the creation of a better, more adequate adaptation model that takes into account the complexities of different users.

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In the present study we focus on the interaction between the acquisition of new words and text organisation. In the acquisition of new words we emphasise the acquisition of paradigmatic relations such as hyponymy, meronymy and semantic sets. We work with a group of girls attending a private school for adolescents in serious difficulties. The subjects are from disadvantaged families. Their writing skills were very poor. When asked to describe a garden, they write a short text of a single paragraph, the lexical items were generic, there were no adjectives, and all of them use mainly existential verbs. The intervention plan assumed that subjects must to be exposed to new words, working out its meaning. In presence of referents subjects were taught new words making explicit the intended relation of the new term to a term already known. In the classroom subjects were asked to write all the words they knew drawing the relationships among them. They talk about the words specifying the relation making explicit pragmatic directions like is a kind of, is a part of or are all x. After that subjects were exposed to the task of choosing perspective. The work presented in this paper accounts for significant differences in the text of the subjects before and after the intervention. While working new words subjects were organising their lexicon and learning to present a whole entity in perspective.

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In this paper we attempt to find out which motivations influence volunteers satisfaction. So, in a first moment, we categorize satisfaction through a factor analysis and then use linear regression models to find out the relations previously mentioned. Furthermore we analyse the existence of correlations between some demographic attributes and the other variables. In this research the population under study includes volunteers that work in the health area, more precisely volunteers that work in hospital and have direct contact with patients and their families. We obtained a total of 327 questionnaires and after excluding incomplete answers we get 304 questionnaires which embody a response rate of 36%. The outcomes of our analysis reveal that we can categorize satisfaction into intrinsic and extrinsic categories and show that motivations related to belonging and protection and career recognition are the ones influencing extrinsic satisfaction; motivations associated to development and learning and altruism are the ones with higher effect in intrinsic satisfaction. There are some negative correlations between age and extrinsic satisfaction, between years of participation and extrinsic satisfaction, between education and the motivation related to belonging and protection and between age and the motivation related to career recognition. There is only one positive correlation between hours per week and intrinsic satisfaction. The results offer new insights for research about volunteers’ motivations, motive fulfillment and volunteer satisfaction. Furthermore the outcomes advocate that to ensure satisfied volunteers, their motivations must be identified in a timely and appropriate moment, meaning that should happened as early as possible.

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25th Conference of the European Cetacean Society. Long-terms datasets on marine mammals: learning from the past to manage the future, Cadiz, Spain, 21-23 March 2011.

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Mestrado (PES II), Educação Pré-Escolar e Ensino do 1.º Ciclo do Ensino Básico, 1 de Julho de 2014, Universidade dos Açores.

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In this work, we present a neural network (NN) based method designed for 3D rigid-body registration of FMRI time series, which relies on a limited number of Fourier coefficients of the images to be aligned. These coefficients, which are comprised in a small cubic neighborhood located at the first octant of a 3D Fourier space (including the DC component), are then fed into six NN during the learning stage. Each NN yields the estimates of a registration parameter. The proposed method was assessed for 3D rigid-body transformations, using DC neighborhoods of different sizes. The mean absolute registration errors are of approximately 0.030 mm in translations and 0.030 deg in rotations, for the typical motion amplitudes encountered in FMRI studies. The construction of the training set and the learning stage are fast requiring, respectively, 90 s and 1 to 12 s, depending on the number of input and hidden units of the NN. We believe that NN-based approaches to the problem of FMRI registration can be of great interest in the future. For instance, NN relying on limited K-space data (possibly in navigation echoes) can be a valid solution to the problem of prospective (in frame) FMRI registration.