Kostenorientiertes Controlling von E-Learning-Plattformen mit dem TCO-Konzept

Zur administrativen Unterstützung von Lehr- und Lernprozessen werden E-Learning-Plattformen eingesetzt, die auf der Grundlage des Internet Funktionen zur Distribution von Lehr- und Lernmaterialien und zur Kommunikation zwischen Lehrenden und Lernenden anbieten. Zahlreiche wissenschaftliche Beiträge und Marktstudien beschäftigen sich mit der multikriteriellen Evaluation dieser Softwareprodukte zur informatorischen Fundierung strategischer Investitionsentscheidungen. Demgegenüber werden Instrumente zum kostenorientierten Controlling von E-Learning-Plattformen allenfalls marginal thematisiert. Dieser Beitrag greift daher das Konzept der Total Cost of Ownership (TCO) auf, das einen methodischen Ansatzpunkt zur Schaffung von Kostentransparenz von E-Learning-Plattformen bildet. Aufbauend auf den konzeptionellen Grundlagen werden Problembereiche und Anwendungspotenziale für das kostenorientierte Controlling von LMS identifiziert. Zur softwaregestützten Konstruktion und Analyse von TCO-Modellen wird das Open Source-Werkzeug TCO-Tool eingeführt und seine Anwendung anhand eines synthetischen Fallbeispiels erörtert. Abschließend erfolgt die Identifikation weiterführender Entwicklungsperspektiven des TCO-Konzepts im Kontext des E-Learning. Die dargestellte Thematik ist nicht nur von theoretischem Interesse, sondern adressiert auch den steigenden Bedarf von Akteuren aus der Bildungspraxis nach Instrumenten zur informatorischen Fundierung von Investitions- und Desinvestitionsentscheidungen im Umfeld des E-Learning.

Standards and specifications to manage accessibility issues in e-learning

Despite the acknowledged need of providing a personalized and adaptive learning process for all, current learning management systems do not properly cover personalization and accessibility issues and they are still struggling to support the reusability requirements coming from the pervasive usage of standards. There is a lack of frameworks for providing layered-based infrastructure covering the interoperability required to manage the whole range of standards, applications and services needed to meet accessibility and adaptations needs of lifelong learning services.

Contribución al diseño y modelado de plataformas de gestión e impartición de titulaciones conjuntas en ambientes de e-learning

Las Tecnologías de la Información y de las Comunicaciones, ofrecen una buena oportunidad para el desarrollo de comunidades virtuales de aprendizaje, especialmente en el caso de las titulaciones conjuntas entre organizaciones. Estas comunidades permiten a las organizaciones aprovechar mejor las oportunidades de aprendizaje que brindan las tecnologías de Internet, aportando mejores contenidos y experiencias de aprendizaje (Recursos de aprendizaje) tanto para los profesores como para los alumnos. Sin embargo, actualmente no existe una tecnología clara con la que poder federar plataformas de gestión e impartición de titulaciones virtuales (LMS), con la que dar un adecuado soporte a las titulaciones conjuntas. En este trabajo, se presenta una metodología y una arquitectura de federación de plataformas LMS para poder gestionar titulaciones conjuntas en ambiente de e-learning. Actualmente, existe escaso conocimiento acerca de los problemas que están imposibilitando la utilización de estos escenarios. Por ello, este trabajo se presenta como una solución para los miembros de la comunidad (directores, docentes, investigadores y estudiantes), ofreciendo un marco conceptual, que ayuda a entender estos escenarios e identifica los requisitos de diseño que son útiles para generar servicios de aprendizaje accesibles a los miembros de la comunidad (Grid de recursos de aprendizaje) y para integrar los LMS en una nube de titulaciones conjuntas en ambientes de e-learning. Así mismo, en el presente documento se presentan varias experiencias, en las que se han implementado comunidades virtuales de aprendizaje en la ciudad de Cartagena de Indias (Colombia), que han servido para inspirar y validar la solución propuesta en este trabajo. ABSTRACT Information and communication technologies offer a great opportunity for the development of virtual learning communities, like as joint degrees between Organizations. Virtual Learning Communities allow organizations to be more cooperative during training activities via the Internet, with the provision of their learning expertise (learning resource). Internet enables multiple organizations to share their learning expertise with others. In these cooperative knowledge spaces, each organization contributes with their partners providing learning resources that they offer to students and teachers. However, currently there is no clear technology with which to federate Learning Management Systems (LMS) to give adequate support to joint degrees. In this work, we present a description of the problems that would face the generation of the Joint degrees in e-learning environments. Currently little is known about the problems that prevent the formation of virtual learning communities generated from the experience contributed by multiple organizations, so, this work is important for community members (Directors, Teachers, Researchers and practitioners) because it offers a conceptual framework that helps understand these scenarios and can provide useful design requirements when generating learning services for the community (Grid of Learning Resources) and to integrate the LMS in a cloud of joint degrees in e-learning environments. We also propose various experiences in which virtual learning communities have been integrated in Cartagena de Indias (Colombia) which have served to inspire and validate the solution proposed in this paper.

An online e-Learning authoring tool to create interactive multi-device learning objects using e-Infrastructure resources

Education can take advantage of e-Infrastructures to provide teachers with new opportunities to increase students' motivation and engagement while they learn. Nevertheless, teachers need to find, integrate and customize the resources provided by e-Infrastructures in an easy way. This paper presents ViSH Editor, an innovative web-based e-Learning authoring tool that aims to allow teachers to create new learning objects using e-Infrastructure resources. These new learning objects are called Virtual Excursions and are created as reusable, granular and interoperable learning objects. This way they can be reused to build new ones and they can be integrated in websites or Learning Management Systems. Details about the design, development and the tool itself are explained in this paper as well as the concept, structure and metadata of the new learning objects. Lastly, some real examples of how to enrich learning using Virtual Excursions are exposed.

Sistema de e-learning en el entorno AFRICA BUILD Portal

Diversos estudios consideran que las claves para el desarrollo técnico, social y económico de los países en desarrollo, y en especial en África, son la educación, la investigación y la innovación. No obstante, en el ámbito sanitario en particular, la formación e investigación en África sigue siendo escasa por diversos motivos. Por un lado, los investigadores africanos encuentran dificultades añadidas para obtener financiación frente a investigadores en países de desarrollo. Y, por otro lado, los investigadores no disponen de las herramientas y tecnologías adecuadas para acceder a información relevante para su trabajo. En este contexto, el proyecto AFRICA BUILD tiene como principal objetivo mejorar y fomentar la investigación y educación sanitaria en África a través de las nuevas tecnologías. Uno de los resultados principales de este proyecto es el AFRICA BUILD Portal (ABP), que pretende ser un punto de encuentro para los investigadores africanos, donde podrán encontrar un amplio abanico de herramientas que les permita no sólo mejorar su educación, sino compartir conocimientos con otros investigadores. Este portal, que está actualmente en desarrollo, pretende fomentar la comunicación entre instituciones africanas y les proveerá herramientas biomédicas avanzadas. En este Trabajo de Fin de Grado se han marcado como principal objetivo la mejora del sistema de e-learning que existía en el ABP. El nuevo sistema será: (i) más potente, óptimo y rico en funcionalidades, (ii) tendrá una importante base social permitiendo a los usuarios aportar información y compartir conocimiento, y (iii) será distribuido y escalable, capaz de integrar distintos gestores de contenidos didácticos como fuentes de información. Los resultados obtenidos son positivos y el nuevo sistema de aprendizaje ha mejorado la usabilidad, funcionalidad y apariencia del anterior. Para concluir, la herramienta posee aún un gran margen de mejora, pero gracias al trabajo realizado el sistema de e-learning es ahora más social, distribuido, escalable e innovador. ---ABSTRACT---Several studies find that the keys to the technical, social and economic development of developing countries, especially in Africa, are education, research and innovation. However, in the health sector in particular, training and research in Africa remains low for various reasons. On the one hand, African researchers experience additional difficulties for funding against researchers in developing countries. And on the other hand, researchers do not have the right tools and technologies to access information relevant to their work. In this context, the AFRICA BUILD project's main objective is to improve and enhance research and health education in Africa through new technologies. One of the main results of this project is the AFRICA BUILD Portal (ABP), which aims to be a meeting point for African researchers, where they can find a wide range of tools that allows them to not only improve their education but to share knowledge with other researchers. This portal, which is currently under development, aims to promote communication between African institutions and will provide advanced biomedical tools. The main objective of this Final Year Project is the improvement of the former elearning system that already existed in the ABP. The new system will be: (i) more powerful, richer in features, (ii) will have an important social base allowing users to contribute information and knowledge sharing; and (iii) will be distributed and scalable, capable of integrating different learning management systems as sources of information. The final results obtained are fairly positive and the new e-learning system has improved its usability, functionality and appearance of the former. To conclude, the tool still has much room for improvement, but thanks to the new features of the improved elearning system has become more social, distributed, scalable and innovative.

DAEDALUS at PAN 2014: Guessing tweet author's gender and age

This paper describes our participation at PAN 2014 author profiling task. Our idea was to define, develop and evaluate a simple machine learning classifier able to guess the gender and the age of a given user based on his/her texts, which could become part of the solution portfolio of the company. We were interested in finding not the best possible classifier that achieves the highest accuracy, but to find the optimum balance between performance and throughput using the most simple strategy and less dependent of external systems. Results show that our software using Naive Bayes Multinomial with a term vector model representation of the text is ranked quite well among the rest of participants in terms of accuracy.

Diseño y desarrollo de un sistema basado en Learning Analytics para evaluar la competencia de trabajo en equipo.Design and development of a Learning Analytics System to evaluate group work competence

La adquisición de la competencia grupal es algo básico en la docencia universitaria. Esta tarea va a suponer evaluar diferentes factores en un número elevado de alumnos, lo que puede supone gran complejidad y un esfuerzo elevado. De cara a evitar este esfuerzo se puede pensar en emplear los registros de la interacción de los usuarios almacenados en las plataformas de aprendizaje. Para ello el presente trabajo se basa en el desarrollo de un sistema de Learning Analytics que es utilizado como herramienta para analizar las evidencias individuales de los distintos miembros de un equipo de trabajo. El trabajo desarrolla un modelo teórico apoyado en la herramienta, que permite relacionar las evidencias observadas de forma empírica para cada alumno, con indicadores obtenidos tanto de la acción individual como cooperativo de los miembros de un equipo realizadas a través de los foros de trabajo. Abstract — The development of the group work competence is something basic in university teaching. It should be evaluated, but this means to analyze different issues about the participation of a high number of students which is very complex and implies a lot of effort. In order to facilitate this evaluation it is possible to analyze the logs of students’ interaction in Learning Management Systems. The present work describes the development of a Learning Analytics system that analyzes the interaction of each of the members of working group. This tool is supported by a theoretical model, which allows establishing links between the empirical evidences of each student and the indicators of their action in working forums.

Can diversity amongst learners improve online object tracking?

We present a novel analysis of the state of the art in object tracking with respect to diversity found in its main component, an ensemble classifier that is updated in an online manner. We employ established measures for diversity and performance from the rich literature on ensemble classification and online learning, and present a detailed evaluation of diversity and performance on benchmark sequences in order to gain an insight into how the tracking performance can be improved. © Springer-Verlag 2013.

Models, Techniques and Applications of e-Learning Personalization

In recent years Web has become mainstream medium for communication and information dissemination. This paper presents approaches and methods for adaptive learning implementation, which are used in some contemporary web-interfaced Learning Management Systems (LMSs). The problem is not how to create electronic learning materials, but how to locate and utilize the available information in personalized way. Different attitudes to personalization are briefly described in section 1. The real personalization requires a user profile containing information about preferences, aims, and educational history to be stored and used by the system. These issues are considered in section 2. A method for development and design of adaptive learning content in terms of learning strategy system support is represented in section 3. Section 4 includes a set of innovative personalization services that are suggested by several very important research projects (SeLeNe project, ELENA project, etc.) dated from the last few years. This section also describes a model for role- and competency-based learning customization that uses Web Services approach. The last part presents how personalization techniques are implemented in Learning Grid-driven applications.

Learning user and product distributed representations using a sequence model for sentiment analysis

In product reviews, it is observed that the distribution of polarity ratings over reviews written by different users or evaluated based on different products are often skewed in the real world. As such, incorporating user and product information would be helpful for the task of sentiment classification of reviews. However, existing approaches ignored the temporal nature of reviews posted by the same user or evaluated on the same product. We argue that the temporal relations of reviews might be potentially useful for learning user and product embedding and thus propose employing a sequence model to embed these temporal relations into user and product representations so as to improve the performance of document-level sentiment analysis. Specifically, we first learn a distributed representation of each review by a one-dimensional convolutional neural network. Then, taking these representations as pretrained vectors, we use a recurrent neural network with gated recurrent units to learn distributed representations of users and products. Finally, we feed the user, product and review representations into a machine learning classifier for sentiment classification. Our approach has been evaluated on three large-scale review datasets from the IMDB and Yelp. Experimental results show that: (1) sequence modeling for the purposes of distributed user and product representation learning can improve the performance of document-level sentiment classification; (2) the proposed approach achieves state-of-The-Art results on these benchmark datasets.

Utilizando comitês de classificadores para predição de rendimento escolar

Educational Data Mining is an application domain in artificial intelligence area that has been extensively explored nowadays. Technological advances and in particular, the increasing use of virtual learning environments have allowed the generation of considerable amounts of data to be investigated. Among the activities to be treated in this context exists the prediction of school performance of the students, which can be accomplished through the use of machine learning techniques. Such techniques may be used for student’s classification in predefined labels. One of the strategies to apply these techniques consists in their combination to design multi-classifier systems, which efficiency can be proven by results achieved in other studies conducted in several areas, such as medicine, commerce and biometrics. The data used in the experiments were obtained from the interactions between students in one of the most used virtual learning environments called Moodle. In this context, this paper presents the results of several experiments that include the use of specific multi-classifier systems systems, called ensembles, aiming to reach better results in school performance prediction that is, searching for highest accuracy percentage in the student’s classification. Therefore, this paper presents a significant exploration of educational data and it shows analyzes of relevant results about these experiments.

Digital anthropology and educational eGames: learning through behavioural patterns in digital, game-based contexts

The selected publications are focused on the relations between users, eGames and the educational context, and how they interact together, so that both learning and user performance are improved through feedback provision. A key part of this analysis is the identification of behavioural, anthropological patterns, so that users can be clustered based on their actions, and the steps taken in the system (e.g. social network, online community, or virtual campus). In doing so, we can analyse large data sets of information made by a broad user sample,which will provide more accurate statistical reports and readings. Furthermore, this research is focused on how users can be clustered based on individual and group behaviour, so that a personalized support through feedback is provided, and the personal learning process is improved as well as the group interaction. We take inputs from every person and from the group they belong to, cluster the contributions, find behavioural patterns and provide personalized feedback to the individual and the group, based on personal and group findings. And we do all this in the context of educational games integrated in learning communities and learning management systems. To carry out this research we design a set of research questions along the 10-year published work presented in this thesis. We ask if the users can be clustered together based on the inputs provided by them and their groups; if and how these data are useful to improve the learner performance and the group interaction; if and how feedback becomes a useful tool for such pedagogical goal; if and how eGames become a powerful context to deploy the pedagogical methodology and the various research methods and activities that make use of that feedback to encourage learning and interaction; if and how a game design and a learning design must be defined and implemented to achieve these objectives, and to facilitate the productive authoring and integration of eGames in pedagogical contexts and frameworks. We conclude that educational games are a resourceful tool to provide a user experience towards a better personalized learning performance and an enhance group interaction along the way. To do so, eGames, while integrated in an educational context, must follow a specific set of user and technical requirements, so that the playful context supports the pedagogical model underneath. We also conclude that, while playing, users can be clustered based on their personal behaviour and interaction with others, thanks to the pattern identification. Based on this information, a set of recommendations are provided Digital Anthropology and educational eGames 6 /216 to the user and the group in the form of personalized feedback, timely managed for an optimum impact on learning performance and group interaction level. In this research, Digital Anthropology is introduced as a concept at a late stage to provide a backbone across various academic fields including: Social Science, Cognitive Science, Behavioural Science, Educational games and, of course, Technology-enhance learning. Although just recently described as an evolution of traditional anthropology, this approach to digital behaviour and social structure facilitates the understanding amongst fields and a comprehensive view towards a combined approach. This research takes forward the already existing work and published research onusers and eGames for learning, and turns the focus onto the next step — the clustering of users based on their behaviour and offering proper, personalized feedback to the user based on that clustering, rather than just on isolated inputs from every user. Indeed, this pattern recognition in the described context of eGames in educational contexts, and towards the presented aim of personalized counselling to the user and the group through feedback, is something that has not been accomplished before.

Motor Unit Spike Trains Recontruction from sEMG Signals for Gesture Classification on a Low-Power Processing Platform

Hand gesture recognition based on surface electromyography (sEMG) signals is a promising approach for the development of intuitive human-machine interfaces (HMIs) in domains such as robotics and prosthetics. The sEMG signal arises from the muscles' electrical activity, and can thus be used to recognize hand gestures. The decoding from sEMG signals to actual control signals is non-trivial; typically, control systems map sEMG patterns into a set of gestures using machine learning, failing to incorporate any physiological insight. This master thesis aims at developing a bio-inspired hand gesture recognition system based on neuromuscular spike extraction rather than on simple pattern recognition. The system relies on a decomposition algorithm based on independent component analysis (ICA) that decomposes the sEMG signal into its constituent motor unit spike trains, which are then forwarded to a machine learning classifier. Since ICA does not guarantee a consistent motor unit ordering across different sessions, 3 approaches are proposed: 2 ordering criteria based on firing rate and negative entropy, and a re-calibration approach that allows the decomposition model to retain information about previous sessions. Using a multilayer perceptron (MLP), the latter approach results in an accuracy up to 99.4% in a 1-subject, 1-degree of freedom scenario. Afterwards, the decomposition and classification pipeline for inference is parallelized and profiled on the PULP platform, achieving a latency < 50 ms and an energy consumption < 1 mJ. Both the classification models tested (a support vector machine and a lightweight MLP) yielded an accuracy > 92% in a 1-subject, 5-classes (4 gestures and rest) scenario. These results prove that the proposed system is suitable for real-time execution on embedded platforms and also capable of matching the accuracy of state-of-the-art approaches, while also giving some physiological insight on the neuromuscular spikes underlying the sEMG.

Teaching with Moodle in higher education

Nowadays, with the use of technology and the Internet, education is undergoing significant changes, contemplating new ways of teaching and learning. One of the widely methods of teaching used to promote knowledge, consists in the use of virtual environments available in various formats, taking as example the teaching-learning platforms, which are available online. The Internet access and use of Laptops have created the technological conditions for teachers and students can benefit from the diversity of online information, communication, collaboration and sharing with others. The integration of Internet services in the teaching practices can provide thematic, social and digital enrichment for the agents involved. In this paper we will talk about the advantages of LMS (Learning Management Systems) such as Moodle, to support the presential lectures in higher education. We also will analyse its implications for student support and online interaction, leading educational agents to a mixing of different learning environments, where they can combine face-to-face instruction with computer-mediated instruction, blended-learning, and increases the options for better quality and quantity of human interaction in a learning environment. We also will present some tools traditionally used in online assessment and that are part of the functionalities of Moodle. These tools can provide interesting alternatives to promote a more significant learning and contribute to the development of flexible and customized models of an evaluation which we want to be more efficient.