Aprender a gostar de poesia: contributos para uma didática do texto poético em contexto de Educação Pré-Escolar e Ensino do 1º Ciclo

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

Ensino, aprendizagem e avaliação no Ensino Superior: Perspetivas e práticas

Tese de Doutoramento em Ciências da Educação - Especialidade de Desenvolvimento Curricular

Encontros e desencontros da educação de adultos numa associação de teatro amador

Dissertação de mestrado em Ciências da Educação (área de especialização em Educação de Adultos)

À descoberta do mundo pelo jogo dos sentidos

Relatório de estágio de mestrado em Educação Pré-Escolar

Using data mining for prediction of hospital length of stay: an application of the CRISP-DM Methodology

Hospitals are nowadays collecting vast amounts of data related with patient records. All this data hold valuable knowledge that can be used to improve hospital decision making. Data mining techniques aim precisely at the extraction of useful knowledge from raw data. This work describes an implementation of a medical data mining project approach based on the CRISP-DM methodology. Recent real-world data, from 2000 to 2013, were collected from a Portuguese hospital and related with inpatient hospitalization. The goal was to predict generic hospital Length Of Stay based on indicators that are commonly available at the hospitalization process (e.g., gender, age, episode type, medical specialty). At the data preparation stage, the data were cleaned and variables were selected and transformed, leading to 14 inputs. Next, at the modeling stage, a regression approach was adopted, where six learning methods were compared: Average Prediction, Multiple Regression, Decision Tree, Artificial Neural Network ensemble, Support Vector Machine and Random Forest. The best learning model was obtained by the Random Forest method, which presents a high quality coefficient of determination value (0.81). This model was then opened by using a sensitivity analysis procedure that revealed three influential input attributes: the hospital episode type, the physical service where the patient is hospitalized and the associated medical specialty. Such extracted knowledge confirmed that the obtained predictive model is credible and with potential value for supporting decisions of hospital managers.

O ensino experimental das ciências: mudança concetual a partir das conceções alternativas dos alunos do 1.º Ciclo do Ensino Básico

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

Sustainability education in PBL education: the case study of IEM-UMINHO

Sustainability-related skills are becoming more and more relevant for a proficient and professional engineering practice. Industrial engineers in particular, given their broad field of intervention and being at the heart of industrial activity, hold a great deal of potential and responsibility in providing and delivering best industrial practices, that support enhanced industrial systems and products. Therefore making a real contribution in generating wealth and income for all the companies’ stakeholders, including local communities, as well as adding up to more sustainable ecosystems. Previous work by the authors focused on studying the inclusion of this subject on the education of industrial engineers, especially through active-learning methodologies, as well as presenting results on the use of one such approach. The study conducted tried to identify the impacts on sustainability learning using a given specific activity, i.e. a workshop on industrial ecology, held in the 2014/2015 academic year on the Integrated MSc degree on Industrial Engineering and Management at the University of Minho, Portugal. The study uses content analysis of student teams’ reports for two consecutive academic years. The former did not include one such workshop, while the latter did. The Fink taxonomy was used in the discussion of results and reflection. The study outcomes aimed at supporting decision making on worthiness of investment on similar education instruments for sustainability competency development. Some results of the study highlight that: (1) the workshop seem to globally have a positive contribution on the sustainability learning; (2) a number of dimensions of the Life cycle design strategy wheel was developed, but the approach was not broadly used, (3) There was a mismatch on the workshop schedule; (4) students enjoy the workshop; (5) a clearer endorsement on relevance of this aspect is required. Suggestions for future work are also issued.

Motivação para o desporto escolar: estudo em alunos do ensino secundário, de uma escola do concelho de Guimarães

Relatório de estágio de mestrado em Ensino de Educação Física nos Ensinos Básico e Secundário

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

Dissertação de mestrado integrado em Engenharia Civil

Promover a educação sensorial: dar "Sentidos" à transição entre a educação pré-escolar e o 1.º Ciclo do Ensino Básico

Relatório de estágio de mestrado em Educação Pré-escolar e Ensino no 1.º Ciclo do Ensino Básico

Saber cooperar para saber aprender: contributos da aprendizagem cooperativa na promoção de competências sociais e no sucesso educativo através do desenvolvimento de um projeto curricular integrado

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

Hand gesture recognition for human computer interaction : a comparative study of different image features

Hand gesture recognition for human computer interaction, being a natural way of human computer interaction, is an area of active research in computer vision and machine learning. This is an area with many different possible applications, giving users a simpler and more natural way to communicate with robots/systems interfaces, without the need for extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them to convey information or for device control. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. In this study we try to identify hand features that, isolated, respond better in various situations in human-computer interaction. The extracted features are used to train a set of classifiers with the help of RapidMiner in order to find the best learner. A dataset with our own gesture vocabulary consisted of 10 gestures, recorded from 20 users was created for later processing. Experimental results show that the radial signature and the centroid distance are the features that when used separately obtain better results, with an accuracy of 91% and 90,1% respectively obtained with a Neural Network classifier. These to methods have also the advantage of being simple in terms of computational complexity, which make them good candidates for real-time hand gesture recognition.

Hand gesture recognition system based in computer vision and machine learning

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

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

Assistive locomotion strategies for active lower limb devices

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Eletrónica Médica)