O desenvolvimento de um modelo de ensino virtual num contexto de investimento incipiente em e - learning: progressos e desafios

Este artigo relata o desenvolvimento de um modelo de ensino virtual em curso na Universidade dos Açores. Depois de ter sido adotado na lecionação de disciplinas da área da Teoria e Desenvolvimento Curricular em regime de e-learning e b-learning, o modelo foi, no ano académico de 2014/15, estendido à lecionação de outras disciplinas. Além de descrever o modelo e explicar a sua evolução, o artigo destaca a sua adoção no contexto particular de uma disciplina cuja componente online foi lecionada em circunstâncias especialmente desafiadoras. Neste sentido, explica o processo de avaliação da experiência, discute os seus resultados e sugere pistas de melhoria. Essa avaliação enquadra-se num processo de investigação do design curricular – a metodologia que tem sido usada para estudar o desenvolvimento do modelo.

Relatório de estágio

I - As minhas expectativas eram elevadas pois este regresso à Escola Superior de Música de Lisboa permitia-me voltar a trabalhar com os professores que me formaram como músico e professor e com eles poder actualizar-me sobre vários temas ligados à pedagogia. Este aspecto é muito importante pois chego à conclusão que o tempo por vezes provoca-nos excesso de confiança que parece “cegar-nos” não nos deixando ver erros pedagógicos muitas vezes evitáveis. Quando ingressei neste estágio sentia-me confiante e seguro quanto às minhas capacidades como professor. O momento de viragem na minha perspectiva do estágio dá-se quando surgem as observações/gravações e respectivas análises e reflexões das aulas. Procurei trabalhar nessas aulas da forma mais natural possível pois o meu objectivo era observar o meu trabalho diário. A primeira observação das aulas permitiu-me anotar algumas coisas menos boas. Contudo, quando essa observação foi feita com o professor de didática os aspectos menos positivos ganharam uma enorme proporção: (1) falhas ao nível da instrução: demasiado longo, (2) feedback de pouca qualidade ou eficácia , (3) pouca percentagem de alunos que atingiam os objectivos., (4) ritmo de aula por vezes baixo devido a períodos longos de instrução ou devido a uma má gestão do espaço. Todos estes problemas eram mais visíveis quando as turmas eram maiores. Ao longo do estágio, e após a detecção destas falhas, fui procurando evitar estas práticas em todas as turmas onde leccionava. Senti que o ritmo de aula aumentou substancialmente não apenas à custa da energia do professor e de boas estratégias mas porque sobretudo se “falava menos e trabalhava-se mais”. Os erros dos alunos passaram a ser corrigos enquanto trabalhavam (feedback corretivo próximo do momento positivo ou negativo), o feedback positivo passou a ser mais destacado, a disposição da sala alterou-se de forma aos alunos estarem mais perto do professor, e este procurou ser menos “criativo” no momento de alterar o plano de aula devido a ideias momentâneas o que provocou mais tempo para cada estratégia e para que mais alunos fossem atingindo os objectivos. Apesar da evolução no sentido de proporcionar aos alunos aulas mais rentáveis e de ainda melhor qualidade, existe a consciência que alguns dos erros cometidos eram hábitos e como tal poderão levar algum tempo a ser corrigidos. Contudo, existe a consciência e a vontade em debelá-los da minha prática docente.

Modellus: Learning Physics with Mathematical Modelling

Tese de doutoramento em Ciências da Educação, área de Teoria Curricular e Ensino das Ciências

Blended Learning project with Applied Optics. Case study

To show with the case of Applied Optics (AO), the adequacy of blended learning to the teaching/learning process in experimental Science and technology (S&T).

Moodle e ensino-misto (b-learning)

Dissertação de mestrado em Geologia para o ensino

Scalable data acquisition for densely instrumented cyber-physical systems

Consider the problem of designing an algorithm for acquiring sensor readings. Consider specifically the problem of obtaining an approximate representation of sensor readings where (i) sensor readings originate from different sensor nodes, (ii) the number of sensor nodes is very large, (iii) all sensor nodes are deployed in a small area (dense network) and (iv) all sensor nodes communicate over a communication medium where at most one node can transmit at a time (a single broadcast domain). We present an efficient algorithm for this problem, and our novel algorithm has two desired properties: (i) it obtains an interpolation based on all sensor readings and (ii) it is scalable, that is, its time-complexity is independent of the number of sensor nodes. Achieving these two properties is possible thanks to the close interlinking of the information processing algorithm, the communication system and a model of the physical world.

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’.

The Interactive Whiteboard And Language Learning: A Case Study

In this paper, we intend to present some research carried out in a state Primary school, which is very well-equipped with ICT resources, including interactive whiteboards. The interactive whiteboard was used in the context of a Unit of Work for English learning, based on a traditional oral story, ‘Jack and the Beanstalk’. It was also used for reinforcing other topics like, ‘At the beach’, ‘In the city’, ‘Jobs’, etc. An analysis of the use of the digital board, which includes observation records as well as questionnaires for teachers and pupils, was carried out.

Democratic dialogue and collective learning in the context of self-managed teams

This paper provides a longitudinal, empirical view of the multifaceted and reciprocal processes of organizational learning in a context of self-managed teams. Organizational learning is seen as a social construction between people and actions in a work setting. The notion of learning as situated (Brown & Duguid 1989, Lave& Wenger 1991, Gherardi & al. 1998, Easterby-Smith & Araujo 1999, Abma 2003) opens up the possibility for placing the focus of research on learning in the community rather than in individual learning processes. Further, in studying processes in their social context, we cannot avoid taking power relations into consideration (Contu & Willmott 2003). The study is based on an action research with a methodology close to the ‘democratic dialogue’ presented by Gustavsen (2001). This gives a ground for research into how the learning discourse developed in the case study organization over a period of 5 years, during which time the company abandoned a middle management level of hierarchy and the teams had to figure out how to work as self-managed units. This paper discusses the (re)construction of power relations and its role in organizational learning. Power relations are discussed both in vertical and horizontal work relations. A special emphasis is placed on the dialectic between managerial aims and the space for reflection on the side of employees. I argue that learning is crucial in the search for the limits for empowerment and that these limits are negotiated both in actions and speech. This study unfolds a purpose-oriented learning process, constructing an open dialogue, and describes a favourable context for creative, knowledge building communities.

"Poster yourself": a construção colaborativa e multimédia do conhecimento no Ensino Precoce de Inglês

Mestrado em Ensino Precoce do Inglês

Automatic learning for the classification of chemical reactions and in statistical thermodynamics

This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.

Image quality and dose analysis in PA chest x-ray: comparison between AEC and manual mode acquisition using the 10 kVp rule

Purpose: To compare image quality and effective dose when the 10 kVp rule is applied with manual and AEC mode in PA chest X-ray. Methods and Materials: A total of 68 images (with and without lesions) were acquired of an anthropomorphic chest phantom in a Wolverson Arcoma X-ray unit. The images were evaluated against a reference image using image quality criteria and the 2 alternative forced choice (2 AFC) method by five radiographers. The effective dose was calculated using PCXMC software using the exposure parameters and DAP. The exposure index (lgM) was recorded. Results: Exposure time decreases considerably when applying the 10 kVp rule in manual mode (50%-28%) compared to AEC mode (36%-23%). Statistical differences for effective dose between several AEC modes were found (p=0.002). The effective dose is lower when using only the right AEC ionization chamber. Considering image quality, there are no statistical differences (p=0.348) between the different AEC modes for images with no lesions. Using a higher kVp value the lgM values will also increase. The lgM values showed significant statistical differences (p=0.000). The image quality scores did not present statistically significant differences (p=0.043) for the images with lesions when comparing manual with AEC modes. Conclusion: In general, the dose is lower in the manual mode. By using the right AEC ionising chamber the effective dose will be the lowest in comparison to other ionising chambers. The use of the 10 kVp rule did not affect the detectability of the lesions.

Experimental Study And Evaluation Of Paper-Based Inkjet Electrodes For ECG Signal Acquisition

Applications involving biosignals, such as Electrocardiography (ECG), are becoming more pervasive with the extension towards non-intrusive scenarios helping targeting ambulatory healthcare monitoring, emotion assessment, among many others. In this study we introduce a new type of silver/silver chloride (Ag/AgCl) electrodes based on a paper substrate and produced using an inkjet printing technique. This type of electrodes can increase the potential applications of biosignal acquisition technologies for everyday life use, given that there are several advantages, such as cost reduction and easier recycling, resultant from the approach explored in our work. We performed a comparison study to assess the quality of this new electrode type, in which ECG data was collected with three types of Ag/AgCl electrodes: i) gelled; ii) dry iii) paper-based inkjet printed. We also compared the performance of each electrode when acquired using a professional-grade gold standard device, and a low cost platform. Experimental results showed that data acquired using our proposed inkjet printed electrode is highly correlated with data obtained through conventional electrodes. Moreover, the electrodes are robust to high-end and low-end data acquisition devices. Copyright © 2014 SCITEPRESS - Science and Technology Publications. All rights reserved.

Lean learning academy: an innovative framework for lean manufacturing training

Worldwide competitiveness poses enormous challenges on managers, demanding a continuous quest to increase rationality in the use of resources. As a management philosophy, Lean Manufacturing focuses on the elimination of activities that do not create any type of value and therefore are considered waste. For companies to successfully implement the Lean Manufacturing philosophy it is crucial that the human resources of the organization have the necessary training, for which proper tools are required. At the same time, higher education institutions need innovative tools to increase the attractiveness of engineering curricula and develop a higher level of knowledge among students, improving their employability. This paper describes how Lean Learning Academy, an international collaboration project between five EU universities and five companies, from SME to Multinational/Global companies, developed and applied an innovative training programme for Engineers on Lean Manufacturing, a successful alternative to the traditional teaching methods in engineering courses.

Digital serious games and simulation games - comparison of two approaches to lean training

In an increasingly competitive and globalized world, companies need effective training methodologies and tools for their employees. However, selecting the most suitable ones is not an easy task. It depends on the requirements of the target group (namely time restrictions), on the specificities of the contents, etc. This is typically the case for training in Lean, the waste elimination manufacturing philosophy. This paper presents and compares two different approaches to lean training methodologies and tools: a simulation game based on a single realistic manufacturing platform, involving production and assembly operations that allows learning by playing; and a digital game that helps understand lean tools. This paper shows that both tools have advantages in terms of trainee motivation and knowledge acquisition. Furthermore, they can be used in a complementary way, reinforcing the acquired knowledge.