“Learning through Radio, Learning for Life!”: Notas sobre o desenvolvimento de uma rádio participativa online

(Excerto) Olhando para o percurso do RadioActive, há uma ideia que parece ser transversal a todo o projeto. Referimo-nos a um princípio que chamaríamos de “identificação” e que foi determinante – é determinante – nos processos de investigação participativa. Falamos da identificação dos investigadores com os princípios da investigação-ação, da identificação das intervenções com as particularidades de cada contexto. Da imprescindível e progressiva identificação dos participantes com o projeto. Na verdade, sem esta multifacetada identificação é impossível pensar em resultados sustentáveis e persistentes. Investigadores e demais participantes têm de sentir que o projeto é “seu”, que os objetivos são “seus”, embora o façam necessariamente a velocidades diferentes. A aprendizagem, neste âmbito, expande-se sempre de dentro para fora, emerge dos interesses do sujeito e não de uma estrutura pré-concebida e imposta pelos que chegam (Ravenscroft et al., 2011), neste caso, os investigadores. Uma das diferenças das pesquisas participativas em relação às tradicionais é, precisamente, a atuação coletiva e não solitária do investigador. Os pesquisadores fazem parte de um processo participatório em que estão envolvidos numa estrutura (Cammarota & Fine, 2008: 5). Paulo Freire é o autor primordial em todos os projetos e países onde a RA101 foi aplicada. As suas concepções em torno da investigação-ação participativa tentam apontar sempre para uma ação e também para uma reflexão sobre os processos.

Using students’ learning style to create effective learning groups in MCSCL environments

Students have different ways for learning and processing information. Some students prefer learning through seeing while others prefer learning through listening; some students prefer doing activities while other prefer reflecting.Some students reason logically, while others reason intuitively, etc. Identifying the learning style of each student, and providing learning content based on these styles represents a good method to enhance the learning quality. However, there are no efforts onhow to detect the students’ learning styles in mobile computer supported collaborative learning (MCSCL) environments. We present in this paper new ways for automatically detecting the learning styles of students in MCSCL environments based on the learning style model of Felder-Silverman. The identified learning styles of students could be then stored and used at anytime toassign each one of them to his/her appropriate learning group.

Transformando o espaço educativo numa comunidade de aprendizagem

Relatório de estágio de mestrado em Educação Pré-Escolar e Ensino do 1º Ciclo do Ensino Básico

A documentação pedagógica no trabalho de projeto: relato de uma experiência em contexto de jardim-de-infância

Relatório de estágio de mestrado em Educação Pré-Escolar e Ensino do 1º Ciclo do Ensino Básico

Desenvolvimento de um laboratório pedagógico de vias de comunicação na Universidade do Minho

Dissertação de mestrado integrado em Engenharia Civil

A cooperar é que se aprende?: a aprendizagem cooperativa e educação intercultural: um contributo na construção da autonomia do aluno

Relatório de estágio de mestrado em Ensino de Inglês e Espanhol no 3º Ciclo do Ensino Básico e Ensino Secundário

Las palabras son semillas…: aquisição e ampliação de vocabulário com recurso ao audiovisual

Relatório de estágio de mestrado em Ensino do Português no 3º Ciclo do Ensino Básico e Ensino Secundário e de Espanhol nos Ensinos Básico e Secundário

The tutor's role in student learning

Higher education in Portugal, in the last forty years, has undergone profound changes with the enlargement of public higher education network, the appearance of new institutions, the quantity and the heterogeneity of students. The implementation of the Bologna Process in European community countries led to the redesign of higher education Portuguese courses as well as their corresponding curricula. In recent years, the use of Project-led education was one of the most significant changes in teaching and learning, particularly in engineering in higher education in Portugal. This teaching methodology encourages students and teachers to undertake new roles, new responsibilities and a new learning perspective. This study aims at understanding whether the role of the tutor is to be suitable to the needs and expectations of Project-led education students. These changes however are not only structural. At the University of Minho, new teaching and learning methodologies were adopted, which could guide the training of professionals on to the twenty-first century. The opportunity arising from the implementation of Project-led education in Engineering methodology was used in the University of Minho’s courses. This teaching method is intended to provide students with educational support programs that benefit the academic performance, allowing the opportunity to upgrade, train and develop the ability to study and learn more effectively. Through the Project-led education it is possible to provide students with techniques and procedures and develop the ability to communicate orally and in writing. Students and teachers have assumed new roles in the teaching-learning process allowing in one hand the students to explore, discover and question themselves about some knowledge and on the other hand the teachers to change to a tutor, a companion and to a student project guide. Therefore, surveys were analyzed, comprising questions about the most significant contribution of the tutor as well as if there are some initial expectations that have not been foreseen by the tutor.

Adult learning and education policies in Germany, Portugal and Sweden: An analysis of national reports to CONFINTEA VI

The chapter presents a theoretical proposal of three analytical models of Adult Learning and Education (ALE) policies. Some analytical categories and the corresponding dimensions are organised according to the ALE rationale which is typical of each social policy model. Historical, cultural and educational features are mentioned in connexion with the different policy models and its interpretative capacity to making sense of policies and practices implemented in Germany, Portugal and Sweden. !e analysis includes the states of the art and the official representations of ALE produced by the respective national authorities through national reports which were presented to CONFINTEA VI (2009).

A expressão dramática em contexto escolar: um estudo de caso com alunos do 1º ciclo do ensino básico na Região Autónoma da Madeira

Tese de Doutoramento em Estudos da Criança (área de especialização em Educação Dramática).

Discrimination of Brazilian propolis according to the seasoning using chemometrics and machine learning based on UV-Vis scanning data

Propolis is a chemically complex biomass produced by honeybees (Apis mellifera) from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plants resin, but a big challenge for the standardization of the chemical composition and biological effects of propolis remains on a better understanding of the influence of seasonality on the chemical constituents of that raw material. Since propolis quality depends, among other variables, on the local flora which is strongly influenced by (a)biotic factors over the seasons, to unravel the harvest season effect on the propolis chemical profile is an issue of recognized importance. For that, fast, cheap, and robust analytical techniques seem to be the best choice for large scale quality control processes in the most demanding markets, e.g., human health applications. For that, UV-Visible (UV-Vis) scanning spectrophotometry of hydroalcoholic extracts (HE) of seventy-three propolis samples, collected over the seasons in 2014 (summer, spring, autumn, and winter) and 2015 (summer and autumn) in Southern Brazil was adopted. Further machine learning and chemometrics techniques were applied to the UV-Vis dataset aiming to gain insights as to the seasonality effect on the claimed chemical heterogeneity of propolis samples determined by changes in the flora of the geographic region under study. Descriptive and classification models were built following a chemometric approach, i.e. principal component analysis (PCA) and hierarchical clustering analysis (HCA) supported by scripts written in the R language. The UV-Vis profiles associated with chemometric analysis allowed identifying a typical pattern in propolis samples collected in the summer. Importantly, the discrimination based on PCA could be improved by using the dataset of the fingerprint region of phenolic compounds ( = 280-400m), suggesting that besides the biological activities of those secondary metabolites, they also play a relevant role for the discrimination and classification of that complex matrix through bioinformatics tools. Finally, a series of machine learning approaches, e.g., partial least square-discriminant analysis (PLS-DA), k-Nearest Neighbors (kNN), and Decision Trees showed to be complementary to PCA and HCA, allowing to obtain relevant information as to the sample discrimination.

Um modelo para a gestão do conhecimento organizacional no contexto dos serviços partilhados com recurso à utilização do e-Learning

Tese de Doutoramento em Tecnologias e Sistemas de Informação

Off-line simulation inspires insight: a neurodynamics approach to efficient robot task learning

There is currently an increasing demand for robots able to acquire the sequential organization of tasks from social learning interactions with ordinary people. Interactive learning-by-demonstration and communication is a promising research topic in current robotics research. However, the efficient acquisition of generalized task representations that allow the robot to adapt to different users and contexts is a major challenge. In this paper, we present a dynamic neural field (DNF) model that is inspired by the hypothesis that the nervous system uses the off-line re-activation of initial memory traces to incrementally incorporate new information into structured knowledge. To achieve this, the model combines fast activation-based learning to robustly represent sequential information from single task demonstrations with slower, weight-based learning during internal simulations to establish longer-term associations between neural populations representing individual subtasks. The efficiency of the learning process is tested in an assembly paradigm in which the humanoid robot ARoS learns to construct a toy vehicle from its parts. User demonstrations with different serial orders together with the correction of initial prediction errors allow the robot to acquire generalized task knowledge about possible serial orders and the longer term dependencies between subgoals in very few social learning interactions. This success is shown in a joint action scenario in which ARoS uses the newly acquired assembly plan to construct the toy together with a human partner.

Metabolic profiling and classification of propolis samples from Southern Brazil: an NMR-based platform coupled with machine learning

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.

A network approach to brain aging through multimodal neuroimaging

Tese de Doutoramento em Ciências da Saúde.