877 resultados para Specific Learning Disabilities


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Todas as crianças, independentemente das suas necessidades, deveriam ter acesso a uma educação de qualidade e a serem incluídas nas suas famílias e comunidades. Esta afirmação inclui as crianças mais vulneráveis, em particular as crianças com dificuldades intelectuais e multideficiência. Os resultados da investigação sobre a educação de crianças com dificuldades intelectuais e multideficiência ainda não produziram até ao momento informação suficiente que possa ser usada para desenvolver indicadores de qualidade para a avaliação das práticas e dos serviços. A investigação nesta área é limitada por constrangimentos éticos, dificuldades na determinação de amostras e desafios metodológicos, sendo reduzido o número de estudos capaz de produzir a informação necessária. Este artigo tem como objetivo discutir fatores que contribuam para a qualidade do envolvimento de crianças com dificuldades intelectuais e multideficiência em atividades educativas, com base na experiência das autoras e na informação disponível que tem sido publicada sobre este assunto. Com base nesta discussão é sugerido um conjunto de indicadores que poderão ajudar os profissionais a dirigir as suas observações para a qualidade da oferta educativa e para aspetos significativos dos desempenhos das crianças quando envolvidas em atividades curriculares.

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Concepts like E-learning and M-learning are changing the traditional learning place. No longer restricted to well-defined physical places, education on Automation and other Engineering areas is entering the so-called ubiquitous learning place, where even the more practical knowledge (acquired at lab classes) is now moving into, due to emergent concepts such as Remote Experimentation or Mobile Experimentation. While Remote Experimentation is traditionally regarded as the remote access to real-world experiments through a simple web browser running on a PC connected to the Internet, Mobile Experimentation may be seen as the access to those same (or others) experiments, through mobile devices, used in M-learning contexts. These two distinct client types (PCs versus mobile devices) pose specific requirements for the remote lab infrastructure, namely the ability to tune the experiment interface according to the characteristics (e.g. display size) of the accessing device. This paper addresses those requirements, namely by proposing a new architecture for the remote lab infrastructure able to accommodate both Remote and Mobile Experimentation scenarios.

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Dissertação apresentada à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em 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 (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. This paper presents a methodology to provide decision support to electricity market negotiating players. This model allows integrating different strategic approaches for electricity market negotiations, and choosing the most appropriate one at each time, for each different negotiation context. This methodology is integrated in ALBidS (Adaptive Learning strategic Bidding System) – a multiagent system that provides decision support to MASCEM's negotiating agents so that they can properly achieve their goals. ALBidS uses artificial intelligence methodologies and data analysis algorithms to provide effective adaptive learning capabilities to such negotiating entities. The main contribution is provided by a methodology that combines several distinct strategies to build actions proposals, so that the best can be chosen at each time, depending on the context and simulation circumstances. The choosing process includes reinforcement learning algorithms, a mechanism for negotiating contexts analysis, a mechanism for the management of the efficiency/effectiveness balance of the system, and a mechanism for competitor players' profiles definition.

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Measuring the quality of a b-learning environment is critical to determine the success of a b-learning course. Several initiatives have been recently conducted on benchmarking and quality in e-learning. Despite these efforts in defining and examining quality issues concerning online courses, a defining instrument to evaluate quality is one of the key challenges for blended learning, since it incorporates both traditional and online instruction methods. For this paper, six frameworks for quality assessment of technological enhanced learning were examined and compared regarding similarities and differences. These frameworks aim at the same global objective: the quality of e-learning environment/products. They present different perspectives but also many common issues. Some of them are more specific and related to the course and other are more global and related to institutional aspects. In this work we collected and arrange all the quality criteria identified in order to get a more complete framework and determine if it fits our b-learning environment. We also included elements related to our own b-learning research and experience, acquired during more than 10 years of experience. As a result we have create a new quality reference with a set of dimensions and criteria that should be taken into account when you are analyzing, designing, developing, implementing and evaluating a b-learning environment. Besides these perspectives on what to do when you are developing a b-learning environment we have also included pedagogical issues in order to give directions on how to do it to reach the success of the learning. The information, concepts and procedures here presented give support to teachers and instructors, which intend to validate the quality of their blended learning courses.

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Em acordo com o Dec. Lei nº 3/2008 de 7 de janeiro e para alunos com necessidades educativas especiais a medida currículo específico individual é considerada a mais restritiva de todas as medidas educativas. A área disciplinar da matemática, pela sua aplicabilidade no quotidiano, assume primordial importância no Programa Educativo Individual (PEI) destes alunos. Assim, o presente estudo visa analisar a área curricular de matemática dos PEI de alunos a frequentar o 2º e 3º ciclo de ensino básico ao abrigo da medida educativa currículo específico individual (CEI); visa igualmente constatar que seleção de conteúdos programáticos são percecionados como prioritários para a equipa que elabora o PEI. Em suma, o estudo visa compreender alguns aspetos que, de forma direta ou indireta, interagem com a elaboração do currículo. Tem, ainda, um caráter exploratório e está apoiado numa metodologia de natureza qualitativa e quantitativa (numa dimensão descritiva) que procede à análise documental de excertos (área curricular de matemática) dos Programas Educativos Individuais (PEI). Para o efeito foram analisados 50 PEI que identificaram regularidades relativas aos diferentes conteúdos e à extensão de cada conteúdo. Os resultados evidenciam uma escolha maioritária de conteúdos matemáticos associados ao programa do 1º ano do 1º ciclo do ensino básico e, simultaneamente, de descritores associados aos números e operações. Os resultados permitem extrapolar acerca da interação entre níveis de programação e de funcionalidade dos alunos em CEI e requerem mais estudos que sustentem aquelas evidências e clarifiquem variáveis que interagem na elaboração do currículo.

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Dissertação para obtenção do Grau de Mestre em Engenharia Informática

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The computational power is increasing day by day. Despite that, there are some tasks that are still difficult or even impossible for a computer to perform. For example, while identifying a facial expression is easy for a human, for a computer it is an area in development. To tackle this and similar issues, crowdsourcing has grown as a way to use human computation in a large scale. Crowdsourcing is a novel approach to collect labels in a fast and cheap manner, by sourcing the labels from the crowds. However, these labels lack reliability since annotators are not guaranteed to have any expertise in the field. This fact has led to a new research area where we must create or adapt annotation models to handle these weaklylabeled data. Current techniques explore the annotators’ expertise and the task difficulty as variables that influences labels’ correction. Other specific aspects are also considered by noisy-labels analysis techniques. The main contribution of this thesis is the process to collect reliable crowdsourcing labels for a facial expressions dataset. This process consists in two steps: first, we design our crowdsourcing tasks to collect annotators labels; next, we infer the true label from the collected labels by applying state-of-art crowdsourcing algorithms. At the same time, a facial expression dataset is created, containing 40.000 images and respective labels. At the end, we publish the resulting dataset.

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Special issue of Anthropology in Action originated from the Working Images Conference, a joint meeting of TAN and VAN EASA networks

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Dissertação de mestrado em Educação Especial (área de especialização em Dificuldades de Aprendizagem Específicas)

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"Lecture notes in computational vision and biomechanics series, ISSN 2212-9391, vol. 19"

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Many of our everyday tasks require the control of the serial order and the timing of component actions. Using the dynamic neural field (DNF) framework, we address the learning of representations that support the performance of precisely time action sequences. In continuation of previous modeling work and robotics implementations, we ask specifically the question how feedback about executed actions might be used by the learning system to fine tune a joint memory representation of the ordinal and the temporal structure which has been initially acquired by observation. The perceptual memory is represented by a self-stabilized, multi-bump activity pattern of neurons encoding instances of a sensory event (e.g., color, position or pitch) which guides sequence learning. The strength of the population representation of each event is a function of elapsed time since sequence onset. We propose and test in simulations a simple learning rule that detects a mismatch between the expected and realized timing of events and adapts the activation strengths in order to compensate for the movement time needed to achieve the desired effect. The simulation results show that the effector-specific memory representation can be robustly recalled. We discuss the impact of the fast, activation-based learning that the DNF framework provides for robotics applications.

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The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.

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Tese de Doutoramento em Engenharia de Eletrónica e de Computadores

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Las didácticas específicas de las ciencias naturales revelan diferentes problemáticas en su enseñanza y aprendizaje en los diferentes niveles del sistema educativo. En particular, en las clases de ciencias la interacción discursiva docente alumnos adquiere relevancia, ya que el proceso de comunicación del conocimiento es uno de los pilares didácticos, junto a la trasposición del mismo. Especificamente, en este proyecto nos abocamos a aquellas intervenciones de docentes y alumnos que se relacionan con la construcción del conocimiento biológico y químico. El proyecto se enmarca en una actual linea de trabajo que indaga sobre las dificultades en los abordajes del conocimiento científico en las aulas, las características del discurso entre docentes y alumnos, las habilidades y dificultades en la comprensión de los enunciados de problemas y las características de los textos que se utilizan en las clases. Se focaliza este estudio en casos que intentan dar respuesta a tres temáticas, agrupadas en un conjunto de situaciones de investigación relacionadas con la interacción discursiva docente-alumno, retomando el rol del docente al hablar, guiar o diseñar las situaciones de referencia para el aprendizaje de los alumnos. Los casos son: 1- En cuanto a las concepciones sobre diversidad biológica en estudiantes de escuela secundaria y en textos académicos, atendemos a cómo la escuela presenta los contenidos ecológicos como un conjunto de dogmas y conceptos estáticos. Además suelen simplificarse conceptualmente y presentarse poco actualizados. Es por ello que se planea estudiar las concepciones y actitudes de los alumnos de secundaria sobre la biodiversidad, cómo estas dificultan su comprensión y los textos usados en relación a la promoción de la transposición didáctica. 2- En relación a cómo se elabora el patrón temático del tema célula en clases de Biología, se analizarán las diferentes estrategias de significados y de desarrollo temático, que se emplean en la comunicación aulica. Se intentará establecer si hay cambios en el desarrollo temático a medida que se avanza en la escolaridad. Esto es porque se puede apreciar que muchos de los problemas de aprendizaje del alumnado se deben a un desconocimiento tanto del patrón temático como del patrón estructural de la ciencia, siendo preciso evocar los patrones temáticos que se quieren utilizar, para construir un conocimiento compartido. 3-Finalmente, en los enunciados de problemas de Química, se analizarán las dificultades de comprensión lectora de alumnos de Ingeniería. Los docentes frecuentemente atribuyen los problemas a deficiencias en la instrucción recibida, sin considerarse los conocimientos previos del alumno, los obstáculos conceptuales originados en el tema, las deficiencias en la habilidad lectora, el tipo textual predominante en la consigna, el formato en el que se escribió la consigna y los factores personales, etc., siendo que la comprensión del enunciado de una consigna de trabajo condiciona fuertemente la posibilidad de su resolución. Los tres casos utilizarán metodologías cualitaritas que incluyan análisis de contenido en discursos orales y escritos. Los datos se registrarán desde observación no participante, registro etnográfico y con grabaciones de audio. Se espera contribuir al conocimiento, realizando aportes a la formación docente en tanto las estrategias discursivas que se emplean en el aula, en forma oral y en la escrita, conocer concepciones que dificultan o favoren la construcción del conocimiento científico, entre otras. Los productos de estos estudios estarán integrados por nuevos desarrollos para la formación docente, publicaciones científicas de impacto nacional e internacional, presentaciones a congresos, materiales didácticos y divulgativos, dictado de seminarios y/o cursos, redacción de informes a las escuelas intervinientes.. The specific Natural Sciences didactics show different problems in teaching and learning along the school system. In particular, the discourse used to communicate knowledge in Science lessons becomes important. With this project we will focus on the teachers and students actions regarding the construction of biological and chemical knowledge. This project attempts to answer these issues and brings together a range of research situations related to teacher-student interaction, through discourse, taking up the role of the teacher to speak, to plan and to guide student learning. We will study the ideas and attitudes of high school students about biodiversity that make difficult its understanding and the textbooks used in relation to promotion of the didactic transposition. In addition, regarding how the thematic pattern in biology classes is costructed, it will be analyzed the different meaning and thematic development strategies that are used in communication. We will attempt to establish whether there are any changes in the thematic development throughout high school education. Finally, we will analyze the reading comprehension problems in engineering students. Teachers frequently attribute these issues to deficiencies in prior education, without considering the students background, the conceptual obstacles arising in the field, the format in which the prompt is written, personal factors, etc., keeping in mind that the outcome of an activity is strictly dependant con the prompt understanding. We expect to make contributions to the teacher education in both the discourse strategies used in the classroom, orally and in writing, to learn about the conceptions that hinder or favor the knowledge construction, among others. The products of this study will be national and international impact scientific publications, conference presentations, popular science publications, seminars courses and reports to the schools involeved.