CleverThings: Comercializing the opportunity of an improved e-learning process

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Analysis of the progress of lifelong learning strategies of Portuguese Economics and Management Schools

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Machine learning Gaussian short rate

Dissertação para obtenção do Grau de Doutor em Estatística e Gestão do Risco

Estudo para a implementação de um sitema de e/b-learning no Centro de Formação da RTP

Trabalho de Projeto apresentado para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Gestão de Sistemas de e-­‐Learning

O treino da expressão oral, estratégias em E-learning

Trabalho de Projeto apresentado para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Gestão de Sistemas de E‐learning

Haptic robot-environment interaction for self-supervised learning in ground mobility

Dissertação para obtenção do Grau de Mestre em Engenharia Eletrotécnica e de Computadores

Integração de um Modelo de Aprendizagem em Blended-Learning no Curso de Informática Educativa, do Instituto Superior de Ciências da Educação da Huíla

Trabalho de Projecto apresentado para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Gestão de Sistema de E-learning

Personal Learning Environments – Um Ecossistema de Aprendizagem em e-Learning

Esta investigação tem como tema de estudo os ambientes pessoais de aprendizagem que se podem desenvolver em e-learning. Estes ambientes com características singulares, face ao atual estado de desenvolvimento tecnológico e social, têm sido designados na doutrina científica pela expressão anglo-saxónica Personal Learning Environments, da qual derivam os acrónimos PLE ou PLEs. Este estudo tem, como objetivo, compreender o papel dos PLEs na aprendizagem dos alunos da parte letiva do Mestrado em Gestão de Sistemas de e-Learning, da Faculdade de Ciências Sociais e Humanas da Universidade Nova de Lisboa, nos biénios que decorreram de 2010-2011 a 2012-2013. Estes alunos, ao longo da sua aprendizagem, utilizaram várias ferramentas e/ou serviços associados com as TIC e Web 2.0. Esta utilização permitiu aos alunos criarem um ecossistema de aprendizagem próprio. A metodologia de investigação utilizada teve em consideração sobretudo aspetos qualitativos. A estratégia utilizada para a recolha de informações foi o inquérito por questionário. As informações recolhidas foram sujeitas a tratamento estatístico descritivo, e posterior triangulação dos resultados de algumas das variáveis.Dos resultados obtidos, é possível concluir que os alunos do Mestrado criaram os seus próprios PLEs e que estes facilitaram as suas aprendizagens. Que a sua utilização conferiu vantagens aos alunos. Que os PLEs foram fundamentais para poderem desenvolver atividades colaborativas, e que criaram um ecossistema próprio, uma rede de troca de conhecimentos.

English Language Learning Inside and Outside the Classroom in Portugal

This study investigates the way of learning the English language in Portugal. First-year students of the faculty of Social Sciences and Humanities of New University of Lisbon were selected as participants in the case study. As data collection tools a questionnaire and focus-groups were used. 115 students completed the designed questionnaire and after that 12 students were selected for the more detailed focus-group discussions. Results of the research show that most part of the students´ English knowledge is received from outside the classroom by means of movies, songs, computer games, the Internet, communication with friends and other sources. Also, the results show that motivation is very important in language learning process and motivated students acquire the language faster and easier.

Learning Activities with Semantic. Hypermedia in Higher Education

The increasing use of information and communication technologies (ICT) in diverse professional and personal contexts calls for new knowledge, and a set of abilities, competences and attitudes, for an active and participative citizenship. In this context it is acknowledged that universities have an important role innovating in the educational use of digital media to promote an inclusive digital literacy. The educational potential of digital technologies and resources has been recognized by both researchers and practitioners. Multiple pedagogical models and research approaches have already contributed to put in evidence the importance of adapting instructional and learning practices and processes to concrete contexts and educational goals. Still, academic and scientific communities believe further investments in ICT research is needed in higher education. This study focuses on educational models that may contribute to support digital technology uses, where these can have cognitive and educational relevance when compared to analogical technologies. A teaching and learning model, centered in the active role of the students in the exploration, production, presentation and discussion of interactive multimedia materials, was developed and applied using the internet and exploring emergent semantic hypermedia formats. The research approach focused on the definition of design principles for developing class activities that were applied in three different iterations in undergraduate courses from two institutions, namely the University of Texas at Austin, USA and the University of Lisbon, Portugal. The analysis of this study made possible to evaluate the potential and efficacy of the model proposed and the authoring tool chosen in the support of metacognitive skills and attitudes related to information structuring and management, storytelling and communication, using computers and the internet.

Human activity recognition with accelerometry: novel time and frequency features

Human Activity Recognition systems require objective and reliable methods that can be used in the daily routine and must offer consistent results according with the performed activities. These systems are under development and offer objective and personalized support for several applications such as the healthcare area. This thesis aims to create a framework for human activities recognition based on accelerometry signals. Some new features and techniques inspired in the audio recognition methodology are introduced in this work, namely Log Scale Power Bandwidth and the Markov Models application. The Forward Feature Selection was adopted as the feature selection algorithm in order to improve the clustering performances and limit the computational demands. This method selects the most suitable set of features for activities recognition in accelerometry from a 423th dimensional feature vector. Several Machine Learning algorithms were applied to the used accelerometry databases – FCHA and PAMAP databases - and these showed promising results in activities recognition. The developed algorithm set constitutes a mighty contribution for the development of reliable evaluation methods of movement disorders for diagnosis and treatment applications.

Diffusional kurtosis imaging using a fast heuristic constrained linear least squares algorithm: a plugin for OsiriX

Diffusion Kurtosis Imaging (DKI) is a fairly new magnetic resonance imag-ing (MRI) technique that tackles the non-gaussian motion of water in biological tissues by taking into account the restrictions imposed by tissue microstructure, which are not considered in Diffusion Tensor Imaging (DTI), where the water diffusion is considered purely gaussian. As a result DKI provides more accurate information on biological structures and is able to detect important abnormalities which are not visible in standard DTI analysis. This work regards the development of a tool for DKI computation to be implemented as an OsiriX plugin. Thus, as OsiriX runs under Mac OS X, the pro-gram is written in Objective-C and also makes use of Apple’s Cocoa framework. The whole program is developed in the Xcode integrated development environ-ment (IDE). The plugin implements a fast heuristic constrained linear least squares al-gorithm (CLLS-H) for estimating the diffusion and kurtosis tensors, and offers the user the possibility to choose which maps are to be generated for not only standard DTI quantities such as Mean Diffusion (MD), Radial Diffusion (RD), Axial Diffusion (AD) and Fractional Anisotropy (FA), but also DKI metrics, Mean Kurtosis (MK), Radial Kurtosis (RK) and Axial Kurtosis (AK).The plugin was subjected to both a qualitative and a semi-quantitative analysis which yielded convincing results. A more accurate validation pro-cess is still being developed, after which, and with some few minor adjust-ments the plugin shall become a valid option for DKI computation

Learning facial-expression models with crowdsourcing

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.

About using serious games to teach (Portuguese) sign language

Sign language is the form of communication used by Deaf people, which, in most cases have been learned since childhood. The problem arises when a non-Deaf tries to contact with a Deaf. For example, when non-Deaf parents try to communicate with their Deaf child. In most cases, this situation tends to happen when the parents did not have time to properly learn sign language. This dissertation proposes the teaching of sign language through the usage of serious games. Currently, similar solutions to this proposal do exist, however, those solutions are scarce and limited. For this reason, the proposed solution is composed of a natural user interface that is intended to create a new concept on this field. The validation of this work, consisted on the implementation of a serious game prototype, which can be used as a source for learning (Portuguese) sign language. On this validation, it was first implemented a module responsible for recognizing sign language. This first stage, allowed the increase of interaction and the construction of an algorithm capable of accurately recognizing sign language. On a second stage of the validation, the proposal was studied so that the pros and cons can be determined and considered on future works.