Towards a Social Trust-Aware Recommender for Teachers

Fazeli, S., Drachsler, H., Brouns, F., & Sloep, P. B. (2014). Towards a Social Trust-aware Recommender for Teachers. In N. Manouselis, H. Drachsler, K. Verbert & O. C. Santos (Eds.), Recommender Systems for Technology Enhanced Learning (pp. 177-194): Springer New York.Online communities and networked learning provide teachers with social learning opportunities, allowing them to interact and collaborate with others in order to develop their personal and professional skills. However, with the large number of learning resources produced everyday, teachers need to find out what are the most suitable ones for them. In this paper, we introduce recommender systems as a potential solution to this . The setting is the Open Discovery Space (ODS) project. Unfortunately, due to the sparsity of the educational datasets most educational recommender systems cannot make accurate recommendations. To overcome this problem, we propose to enhance a trust-based recommender algorithm with social data obtained from monitoring the activities of teachers within the ODS platform. In this article, we outline the re-quirements of the ODS recommender system based on experiences reported in related TEL recommender system studies. In addition, we provide empirical ev-idence from a survey study with stakeholders of the ODS project to support the requirements identified from a literature study. Finally, we present an agenda for further research intended to find out which recommender system should ul-timately be deployed in the ODS platform.NELLL, EU 7th framework Open Discovery Spac

Smart Fitness System: Training Programming

Sistemas de recomendação no geral estão a ser cada vez mais usados por empresas que procuram oferecer uma experiência de utilização mais individual e personalizada aos seus clientes. Obter feedback em transações de negócio online nunca foi tão fácil e acessível, o que apenas ajuda a catalisar a evolução dos sistemas de recomendação. Adicionalmente, o uso de dispositivos tecnológicos como smartphones e computadores, juntamente com a conexão à internet, estão também a crescer a um ritmo acelerado sem sinal de paragem em vista. Juntando-se a este grupo de indústrias em crescimento está a indústria fitness, que está a ficar cada vez mais popular. Com isto, mais e mais pessoas estão a começar a usar os dispositivos mencionados anteriormente em combinação com as suas atividades fitness, para aumentar o seu desempenho, monitorizar progresso, definir objetivos, entre outros. Consequentemente, o mercado para sistemas fitness (p.e. aplicações fitness) está a aumentar e já é bastante denso. No entanto, a qualidade associada com tais sistemas fica um pouco aquém tanto em termos de inovação como de funcionalidades essenciais. Como resultado disto, este projeto propôs uma solução – um sistema fitness sob a forma de uma aplicação móvel aliada a um poderoso sistema de recomendação. Este sistema é pretendido que providencie uma experiência mais individual e personalizada para qualquer tipo de utilizador fitness através da oferta de funcionalidades essenciais como registo e monitorização de informação, análise de progresso, e também através de funcionalidades inovadoras como a implementação de um sistema de recomendação capaz de sugerir tópicos relacionados com fitness (p.e. regimes de treino ou exercícios específicos) baseado em múltiplos fatores como os objetivos, características individuais e historial de cada utilizador. Além do mais, deve também oferecer um assistente pessoal virtual, onde os utilizadores podem expressar as suas questões e dúvidas, e tê-las respondidas instantaneamente por um chatbot. Durante o desenvolvimento foi decidido que um segundo sistema de recomendação seria necessário para melhorar o sistema no geral. Este, o sistema, depois de implementado, foi avaliado e pode ser concluído que o resultado foi um sucesso, tendo passado em todas as métricas definidas, exceto uma, com classificações médias nos questionários de satisfação acima de 4/5. O feedback obtido por um especialista no sistema de recomendação foi altamente vantajoso e no geral decentemente positivo, apenas com algumas questões que necessitam de melhoramento. Embora o sistema de recomendação inteligente não tenha conseguido ser testado com informação aplicável, a investigação e trabalho feito constituem uma mais valia caso mais tarde exista a possibilidade de aplicar dados reais.Recommender systems in general are increasingly becoming more exploited by companies who seek to provide a more individual and personalized user-experience to their customers. The fact that providing feedback on online business transactions is also becoming ever so easier only helps to catalyze the evolution of recommender systems. Moreover, the use of technological devices such as smartphones and computers, in conjunction with an internet connection, are also continuing to grow at a fast pace, with no slowing down in sight. Joining on this group of growing industries is the fitness sector, which is becoming increasingly popular. With this, more and more people are starting to use the aforementioned devices in combination with their fitness activities, to boost performance, monitor progress, define goals, among other things. Consequently, the market for fitness systems (i.e. fitness applications) is expanding and is already very dense. However, the associated quality with such systems falls short both in terms of innovation and even crucial features. As a result, this dissertation proposes a solution - an innovative fitness system in the form of a mobile application allied with a powerful recommender system. The system is intended to provide a more individual and personalized experience to any type of fitness user through the offering of crucial features including the log and monitor of information, progress analysis, and also through innovative features such as the implementation of a recommender system capable of making fitness-related suggestions (i.e. training regimens or specific exercises) based on multiple factors like the user’s individual goals, characteristics, and history. Additionally, it should also provide a personal virtual assistant, where users can express their questions and doubts and have them answered instantly by a chatbot. During development, it was decided that a second recommender system was required to improve the system as a whole. This, the system, after being implemented, was evaluated and it can be concluded that the result was a success, having passed in all the defined metrics, except one, with average classifications of 4/5 on the satisfaction inquiries. The feedback obtained from the expert on the recommender system was highly useful and, in general, decently positive, having only a few questions that need improvement. Even though the intelligent recommender system couldn’t be tested with applicable data, the investigation and work done constitute a great asset in case there’s the opportunity to employ real data

Mass Collaboration and Learning: Structure and Methods

The rapid emergence of social networks and collaborative communities supported by the Internet and associated innovative technologies, and the increasing demand for continuous improvement and fostering lifelong learning have led to unprecedented waves of novelty in the ways people create and share knowledge in different spheres. In this regard, mass collaboration (MC) through Internet-based solutions has opened new windows of opportunity to collaborate massively and learn collectively in ways that seemed impossible even a few decades ago. Learning ecosystems can benefit from mass collaboration where large numbers of minds collectively drive intellectual efforts to learn in the form of knowledge building and sharing. Mass collaborative learning (MCL) is a new paradigm that represents a significant shift away from the traditional teacher-centered approach towards a self-directed model in virtual communities in which contributing members take on creative roles to maximize their learning and that of their peers. Furthermore, MCL provides greater opportunities for distributed contributors to engage in virtual global learning and take the advantage of powerful social communities of experts and counterparts. Even though MCL opens up an apparently limitless field for promoting social inclusion in effective learning, not all aspects, features, and characteristics of this phenomenon are quite clear and discovered at present. In order to design, implement, and exploit such a learning approach, influencing constituents should be identified, and appropriate conditions need to be provided. However, existing literature offers limited information, guidance, and support for the creation, operation, coordination, and development of MCL initiatives. In this context, there are a number of identified critical issues, specific problems, gaps, and inconsistencies, and this thesis is correspondingly conducted to propose a Meta-Governance framework for MCL initiatives (MGF-MCL). This framework, by benefiting from various other related ideas, models, and methods, tries to give further insights into an integrated perspective of the most complex concerning issues and also some internal and external aspects of governance for the MCL initiatives. Furthermore, the MGF-MCL intends to provide some directions, guidance, and support for the implementation, operation, and development of MCL initiatives. In this thesis work, in order to (a) guide our research endeavor, (b) concretize our research design, (c) design, develop, validate, and apply the MGF-MCL, and (d) understand the practical value of our findings, we have followed the design science research process (DSRP) approach. We have evaluated the validity and applicability of the MGF-MCL through a mix of methods namely, case studies in EU projects, peer-review publications, and an MCL illustration case. A number of scenarios made within the case studies have brought together several industry and academic experts to evaluate the validity and applicability of MGF-MCL. The peer reviews of contributed publications also assessed the quality of the work and helped to establish the validity of MGF-MCL based upon the expert knowledge of other researchers. The MCL illustration case provided empirical evidence, relying on observation and experimentation. In terms of research, the findings of our work offer direction and support for the creation, operation, and implementation of MLC initiatives.A rápida emergência de redes sociais e comunidades colaborativas apoiadas pela Internet e tecnologias inovadoras associadas, e a crescente procura de melhorias contínuas e a promoção da aprendizagem ao longo da vida levaram a ondas de inovação sem precedentes na forma como as pessoas criam e partilham conhecimentos em diferentes esferas. A este respeito, a colaboração em massa (MC) através de soluções baseadas na Internet abriu novas janelas de oportunidade para colaborar massivamente e aprender colectivamente de formas que pareciam impossíveis mesmo há algumas décadas atrás. Os ecossistemas de aprendizagem podem beneficiar da colaboração em massa, onde grandes números de mentes impulsionam colectivamente os esforços intelectuais para aprender sob a forma de construção e partilha de conhecimento. A aprendizagem colaborativa em massa (MCL) é um novo paradigma que representa uma mudança significativa da abordagem tradicional centrada no professor para um modelo auto-dirigido em comunidades virtuais em que os membros contribuintes assumem papéis criativos para maximizar a sua aprendizagem e a dos seus pares. Além disso, a MCL oferece maiores oportunidades a contribuintes geograficamente distribuídos para se envolverem na aprendizagem global virtual e tirarem partido das ricas comunidades sociais de especialistas e homólogos. Embora a MCL abra um campo aparentemente ilimitado para promover a inclusão social na aprendizagem efectiva, nem todos os aspetos, facetas e características deste fenómeno são totalmente claros e conhecidos actualmente. A fim de conceber, implementar, e explorar uma tal abordagem de aprendizagem, devem ser identificados os constituintes relevantes, e devem ser criadas condições de suporte apropriadas. Contudo, a literatura existente apenas oferece de forma limitada informação, orientação e apoio para a criação, operação, coordenação e desenvolvimento de iniciativas MCL. Neste contexto, há uma série de questões críticas, problemas específicos, lacunas e inconsistências identificados, e esta tese é correspondentemente desenvolvida para propor um quadro de Meta-Governança para iniciativas MCL (MGF-MCL). Este quadro, ao beneficiar de várias outras ideias, modelos e métodos relacionados, tenta fornecer uma perspectiva integrada das questões mais complexas e também de alguns aspectos internos e externos de governação para as iniciativas MCL. Além disso, o MGF-MCL pretende fornecer alguma orientação e apoio para a implementação, operação e desenvolvimento das iniciativas MCL. Neste trabalho de tese, a fim de (a) orientar o nosso esforço de investigação, (b) concretizar o nosso projecto de investigação, (c) conceber, desenvolver, validar, e aplicar o MGF-MCL, e (d) compreender o valor prático dos resultados, seguimos a abordagem do "DESIGN SCIENCE RESEARCH PROCESS" (DSRP). Avaliámos a adequação e aplicabilidade do MGF-MCL através de uma combinação de métodos, nomeadamente, estudos de caso em projetos da UE, publicações com revisão por pares e, um caso de ilustração MCL. Vários cenários feitos no âmbito dos estudos de caso envolveram vários peritos da indústria e da academia para avaliar a validade e a aplicabilidade do MGF-MCL. As revisões por pares das publicações produzidas neste trabalho também permitiram aferir a qualidade do trabalho e ajudaram a estabelecer a validade do MGF-MCL com base no conhecimento especializado de outros investigadores. O caso da ilustração de MCL forneceu uma evidência empírica, apoiando-se na observação e experimentação. Em termos de investigação, os resultados do nosso trabalho oferecem orientação e apoio para a criação, operação e implementação de iniciativas MLC

Groupware requirements evolution patterns

Requirements evolution is a generally known problem in software development. Requirements are known to change all throughout a system's lifecycle. Nevertheless, requirements evolution is a poorly understood phenomenon. Most studies on requirements evolution focus on changes to written specifications and on software architecture and design. Usually, the focus is when the software is under development. Little is known about how requirements evolve when software is put into use.\ud Groupware is an example of an application domain in which the requirements continue to evolve after the system is deployed to the organization. Groupware is any ICT (software + hardware) application that supports the cooperative processes of individuals working as a group. Increasingly, groupware functionality is becoming more present in today's business applications and large information systems. The cooperative processes supported by a groupware application have no structure. Rather, its structure evolves in a way that cannot be specified in advance and arises spontaneously. Therefore, how a groupware system will be used in its operating enviroment cannot be anticipated in advance. There is also the added complication that groupware requirements are difficult to elicit due to the elusive nature of cooperative work. As software for supporting the cooperative processes of people working together, groupware technology has the potential to bring about profound organizational changes. Various studies of groupware implementation point to emergent organizational properties. The interaction between users and software leads to improvements in performance, new forms of communication, changes to group structure and functioning, all of which indicate that requirements have changed.\ud This study is an empirical investigation of requirements evolution for groupware systems in use by means of case studies. Its goal is to contribute to the development of a theory of requirements evolution. A conceptual framework offering an integrated view of requirements as a collection of domains was developed to guide and structure the investigation. The view takes the broad dimensions of business, software, problems, and solutions as requirements thus giving rise to four domains of requirements: business problem, business solution, software product concept, and software solution specification. Requirements evolution is initially formulated as the change in requirements over the course of time.\ud The application domain of groupware was chosen as the empirical setting in which to observe requirements evolution during system use. Four case studies of groupware implementations were conducted. Two failed implementation and two successful implementations were investigated. The conceptual framework is used to analyze the cases and is updated and improved based on an evaluation of how useful has it been in providing insights about requirements evolution. A final version of the framework is developed and this is used to analyze the last two case studies.\ud The results include the discovery of impact relations: commonly recurring mechanisms by which changed and new requirements lead to other requirements in different areas. Ultimately, requirements evolution is the resolution of a breakdown or an initiative resulting in an impact relation. The most important contribution of this research is a set of requirements evolution patterns: aggregations of impact relation sequences that explain the mechanisms underlying awkwardly familiar patterns of behavior in system implementation

Share and reuse of context metadata resulting from interactions between users and heterogeneous web-based learning environments

L'intérêt pour l'observation, l'instrumentation et l'évaluation des systèmes éducatifs en ligne est devenu de plus en plus important ces dernières années au sein de la communauté des Environnements Informatique pour l'Apprentissage Humain (EIAH). La conception et le développement d'environnements d'apprentissage en ligne adaptatifs (AdWLE - Adaptive Web-based Learning Environments) représentent une préoccupation majeure aujourd'hui, et visent divers objectifs tels que l'aide au processus de réingénierie, la compréhension du comportement des utilisateurs, ou le soutient à la création de systèmes tutoriels intelligents. Ces systèmes gèrent leur processus d'adaptation sur la base d'informations détaillées reflétant le contexte dans lequel les étudiants évoluent pendant l'apprentissage : les ressour-ces consultées, les clics de souris, les messages postés dans les logiciels de messagerie instantanée ou les forums de discussion, les réponses aux questionnaires, etc. Les travaux présentés dans ce document sont destinés à surmonter certaines lacunes des systèmes actuels en fournissant un cadre dédié à la collecte, au partage et à la réutilisation du contexte représenté selon deux niveaux d'abstraction : le contexte brut (résultant des interactions directes entre utilisateurs et applications) et le contexte inféré (calculé à partir des données du contexte brut). Ce cadre de travail qui respecte la vie privée des usagers est fondé sur un standard ouvert dédié à la gestion des systèmes, réseaux et applications. Le contexte spécifique aux outils hétérogènes constituant les EIAHs est représenté par une structure unifiée et extensible, et stocké dans un référentiel central. Pour faciliter l'accès à ce référentiel, nous avons introduit une couche intermédiaire composée d'un ensemble d'outils. Certains d'entre eux permettent aux utilisateurs et applications de définir, collecter, partager et rechercher les données de contexte qui les intéressent, tandis que d'autres sont dédiés à la conception, au calcul et à la délivrance des données de contexte inférées. Pour valider notre approche, une mise en œuvre du cadre de travail proposé intègre des données contextuelles issues de trois systèmes différents : deux plates-formes d'apprentissage Moodle (celle de l'Université Paul Sabatier de Toulouse, et une autre déployée dans le cadre du projet CONTINT financé par l'Agence Nationale de la Recherche) et une instanciation locale du moteur de recherche de la fondation Ariadne. A partir des contextes collectés, des indicateurs pertinents ont été calculés pour chacun de ces environnements. En outre, deux applications qui exploitent cet ensemble de données ont été développées : un système de recommandation personnalisé d'objets pédagogiques ainsi qu'une application de visualisation fondée sur les technologies tactiles pour faciliter la navigation au sein de ces données de contexte.An interest for the observation, instrumentation, and evaluation of online educational systems has become more and more important within the Technology Enhanced Learning community in the last few years. Conception and development of Adaptive Web-based Learning Environments (AdWLE) in order to facilitate the process of re-engineering, to help understand users' behavior, or to support the creation of Intelligent Tutoring Systems represent a major concern today. These systems handle their adaptation process on the basis of detailed information reflecting the context in which students evolve while learning: consulted resources, mouse clicks, chat messages, forum discussions, visited URLs, quizzes selections, and so on. The works presented in this document are intended to overcome some issues of the actual systems by providing a privacy-enabled framework dedicated to the collect, share and reuse of context represented at two abstraction levels: raw context (resulting from direct interactions between users and applications) and inferred context (calculated on the basis of raw context). The framework is based on an open standard dedicated to system, network and application management, where the context specific to heterogeneous tools is represented as a unified and extensible structure and stored into a central repository. To facilitate access to this context repository, we introduced a middleware layer composed of a set of tools. Some of them allow users and applications to define, collect, share and search for the context data they are interested in, while others are dedicated to the design, calculation and delivery of inferred context. To validate our approach, an implementation of the suggested framework manages context data provided by three systems: two Moodle servers (one running at the Paul Sabatier University of Toulouse, and the other one hosting the CONTINT project funded by the French National Research Agency) and a local instantiation of the Ariadne Finder. Based on the collected context, relevant indicators have been calculated for each one of these environments. Furthermore, two applications which reuse the encapsulated context have been developed on top of the framework: a personalized system for recommending learning objects to students, and a visualization application which uses multi-touch technologies to facilitate the navigation among collected context entities

Ontology-based augmented reality content-related techniques and their impact in knowledge capture and re-use within maintenance diagnosis

This PhD thesis aims to study ontology-based AR content-related methods and their impact in knowledge transfer, capture and re-use for cost-effective human knowledge integration in digital diagnostic systems. Industry 4.0 has revealed the importance of maintainers’ knowledge capture and re-use in diagnostics systems for providing satisfactory solutions in cases where those systems cannot (e.g. nofault-found). Augmented Reality (AR) utilises content-related techniques to transfer knowledge to maintainers for improving efficiency and effectiveness of diagnosis tasks. Academic literature has shown that AR can also be utilised for knowledge capture and re-use, but this has only been demonstrated in simple, step-by-step repair operations. In diagnosis research, ontology-based methods are applied to capture and re-use knowledge from unstructured and heterogenous sources like humans. Nevertheless, these methods have not made use of AR potential to contextualise knowledge and so, improve efficiency and effectiveness of knowledge capture and re-use diagnosis operations...[cont.]Manufacturin

Human-Computer Interaction

In this book the reader will find a collection of 31 papers presenting different facets of Human Computer Interaction, the result of research projects and experiments as well as new approaches to design user interfaces. The book is organized according to the following main topics in a sequential order: new interaction paradigms, multimodality, usability studies on several interaction mechanisms, human factors, universal design and development methodologies and tools