A construção de um currículo de project-based learning: o currículo ideal e o currículo formal

O objetivo deste trabalho é apresentar os resultados da análise das concepções de dois protagonistas de uma reforma curricular que está sendo implementada numa escola de engenharia. A principal característica do novo currículo é o uso de projetos e oficinas como atividades complementares a serem realizadas pelos estudantes. As atividades complementares acontecerão em paralelo ao trabalho realizado nas disciplinas sem que haja uma relação de interdisciplinaridade. O novo currículo está sendo implantado desde fevereiro de 2015. Segundo Pacheco (2005) há dois momentos, dentre outros, no processo de mudança curricular, o currículo “ideal”, determinado por dimensões epistemológica, política, econômica, ideológica, técnica, estética, e histórica e, que recebe influência direta daquele que idealiza e cria o novo currículo e, o currículo “formal” que se traduz na prática implementada na escola. São essas duas etapas estudadas nesta pesquisa. Para isso serão considerados como fontes de dados dois protagonistas, um mais ligado à concepção do currículo e outro da sua implementação, a partir dos quais se busca compreender as motivações, crenças e percepções que, por sua vez, determinam a reforma curricular. Entrevistas semiestruturadas foram utilizadas como técnica de pesquisa, com o propósito de se entender a gênese da proposta e as mudanças entre essas duas etapas. Os dados revelam que mudanças aconteceram desde a idealização até a formalização do currículo, motivadas por demandas do processo de implementação, revela ainda diferenças na visão de currículo e a motivação para romper com padrões na formação de engenheiros no Brasil.

Tecnologias da informação e comunicação na formação continuada de professores: estudode caso em escolas do Brasil e Portugal com recursos e aplicação do Google+

Tese de Doutoramento em Ciências da Educação (área de especialização em Tecnologia Educativa)

Cost-effective and lightweight mobile units for MixAR: A comparative trial among different setups

Cultural heritage has arousing the interest of the general public (e.g. tourists), resulting in the increasing number of visitations to archaeological sites. However, many buildings and monuments are severely damaged or completely destroyed, which doesn’t allow to get a full experience of “travelling in time”. Over the years, several Augmented Reality (AR) approaches were proposed to overcome these issues by providing three-dimensional visualization of reconstructed ancient structures in situ. However, most of these systems were made available through heavy and expensive technological bundles. Alternatively, MixAR intends to be a lightweight and cost-effective Mixed Reality system which aims to provide the visualization of virtual ancient buildings reconstructions in situ, properly superimposed and aligned with real-world ruins. This paper proposes and compares different AR mobile units setups to be used in the MixAR system, with low-cost and lightweight requirements in mind, providing different levels of immersion. It was propounded four different mobile units, based on: a laptop computer, a single-board computer (SBC), a tablet and a smartphone, which underwent a set of tests to evaluate their performances. The results show that mobile units based on laptop computer and SBC reached a good overall performance while mobile units based on tablet and smartphone did not meet such a satisfactory result even though they are acceptable for the intended use.

MixAR mobile prototype: visualizing virtually reconstructed ancient structures in situ

Archeology and related areas have a special interest on cultural heritage sites since they provide valuable information about past civilizations. However, the ancient buildings present in these sites are commonly found in an advanced state of degradation which difficult the professional/expert analysis. Virtual reconstructions of such buildings aim to provide a digital insight of how these historical places could have been in ancient times. Moreover, the visualization of such models has been explored by some Augmented Reality (AR) systems capable of providing support to experts. Their compelling and appealing environments have also been applied to promote the social and cultural participation of general public. The existing AR solutions regarding this thematic rarely explore the potential of realism, due to the following lacks: the exploration of mixed environments is usually only supported for indoors or outdoors, not both in the same system; the adaptation of the illumination conditions to the reconstructed structures is rarely addressed causing a decrease of credibility. MixAR [1] is a system concerned with those challenges, aiming to provide the visualization of virtual buildings augmented upon real ruins, allowing soft transitions among its interiors and exteriors and using relighting techniques for a faithful interior illumination, while the user freely moves in a given cultural heritage site, carrying a mobile unit. Regarding the focus of this paper, we intend to report the current state of MixAR mobile unit prototype, which allows visualizing virtual buildings – properly aligned with real-world structures – based on user's location, during outdoor navigation. In order to evaluate the prototype performance, a set of tests were made using virtual models with different complexities.

Identifying finger postures when interacting with the touch screen of mobile devices

This study presents the results of preliminary test on the interaction between fingertip and touch screen. The objective of this study is to identify the fingertip posture when interacting with touch screen devices. Ten participants, 7 males and 3 females, participated in this study. The participants were asked to touch targets on the mobile devices screen by tapping them sequentially and connecting them. The participants performed the tasks in a sitting posture. A tablet with 10 inches screen and a mobile phone with 4 inches screen were used in the study. The results showed that all participants dominantly used their thumb to interact with the mobile phone in single and two hands postures. The common thumb posture adopted by the participants is the combination of the 60° pitch and 0° roll angles. While for interaction with tablet in various postures observed in the study, the participants commonly used their index fingers in the combination of 60° pitch and 0° roll angles. This study also observed the participant with long finger nails touched targets on the mobile devices screen by using her index or middle fingers very low pitch.

Improving quality of medical service with mobile health software

An increasing number of m-Health applications are being developed benefiting health service delivery. In this paper, a new methodology based on the principle of calm computing applied to diagnostic and therapeutic procedure reporting is proposed. A mobile application was designed for the physicians of one of the Portuguese major hospitals, which takes advantage of a multi-agent interoperability platform, the Agency for the Integration, Diffusion and Archive (AIDA). This application allows the visualization of inpatients and outpatients medical reports in a quicker and safer manner, in addition to offer a remote access to information. This project shows the advantages in the use of mobile software in a medical environment but the first step is always to build or use an interoperability platform, flexible, adaptable and pervasive. The platform offers a comprehensive set of services that restricts the development of mobile software almost exclusively to the mobile user interface design. The technology was tested and assessed in a real context by intensivists.

Gamification e game-based learning: uma abordagem lúdica à aprendizagem

Relatório de estágio de mestrado em Ensino de Informática

Cross-language influences on new second language vocabulary acquisition: the effect of learning method

Dissertação de mestrado integrado em Psicologia

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).

Literacy practices in adult learning biographies: possibilities and constraints

[Extrat] The answer to the social and economic challenges that it is assumed literacy (or its lack) puts to developed countries deeply concerns public policies of governments namely those of the OECD area. In the last decades, these concerns gave origin to several and diverse monitoring devices, initiatives and programmes for reading (mainly) development, putting a strong stress on education. UNESCO (2006, p. 6), for instance, assumes that the literacy challenge can only be met raising the quality of primary and secondary education and intensifying programmes explicitly oriented towards youth and adult literacy. (...)

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.

Learning Robotics for youngsters - the RoboParty experience

Series: "Advances in intelligent systems and computing , ISSN 2194-5357, vol. 417"

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

Learning joint representations for order and timing of perceptual-motor sequences: a dynamic neural field approach

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.

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.