Knowledgeable Feedback via a Cast of Virtual Characters with Different Competences

DynaLearn (http://www.DynaLearn.eu) develops a cognitive artefact that engages learners in an active learning by modelling process to develop conceptual system knowledge. Learners create external representations using diagrams. The diagrams capture conceptual knowledge using the Garp3 Qualitative Reasoning (QR) formalism [2]. The expressions can be simulated, confronting learners with the logical consequences thereof. To further aid learners, DynaLearn employs a sequence of knowledge representations (Learning Spaces, LS), with increasing complexity in terms of the modelling ingredients a learner can use [1]. An online repository contains QR models created by experts/teachers and learners. The server runs semantic services [4] to generate feedback at the request of learners via the workbench. The feedback is communicated to the learner via a set of virtual characters, each having its own competence [3]. A specific feedback thus incorporates three aspects: content, character appearance, and a didactic setting (e.g. Quiz mode). In the interactive event we will demonstrate the latest achievements of the DynaLearn project. First, the 6 learning spaces for learners to work with. Second, the generation of feedback relevant to the individual needs of a learner using Semantic Web technology. Third, the verbalization of the feedback via different animated virtual characters, notably: Basic help, Critic, Recommender, Quizmaster & Teachable agen

The Learning of the subject Biology in a Master in Biomedical Physics

BIOLOGY is a dynamic and fascinating science. The study of this subject is an amazing trip for all the students that have a first contact with this subject. Here, we present the development of the study and learning experience of this subject belonging to an area of knowledge that is different to the training curriculum of students who have studied Physics during their degree period. We have taken a real example, the “Elements of Biology” subject, which is taught as part of the Official Biomedical Physics Master, at the Physics Faculty, of the Complutense University of Madrid, since the course 2006/07. Its main objective is to give to the student an understanding how the Physics can have numerous applications in the Biomedical Sciences area, giving the basic training to develop a professional, academic or research career. The results obtained when we use new virtual tools combined with the classical learning show that there is a clear increase in the number of persons that take and pass the final exam. On the other hand, this new learning strategy is well received by the students and this is translated to a higher participation and a decrease of the giving the subject up

Implementación de ingeniería virtual con Joomla!

El Proyecto Final de Carrera(PFC)Implementación de Ingeniería Virtual con Joomla! tiene como objetivo la creación de una plataforma web. Para desarrollar un proyecto de ingeniería multidisciplinar, basado en el trabajo en red, grupos de trabajo y el trabajo flexible. El trabajo en red es desempeñar el trabajo por medio de las Tecnología de la Información y la comunicación (TIC). Los grupos de trabajo están compuestos por personas multidisciplinares, multirraciales, de diferentes religiones, situados en husos horarios distintos y multiculturales donde la colaboración, flexibilidad y la compartición de recursos están a la orden del día. La flexible es la capacidad de adaptación de los propios trabajadores a la demanda de la productividad, los responsables depositan sobre ellos su confianza, recibiendo el trabajo terminado en forma y fecha. Estos trabajadores no necesitan una supervisión constante ni un sitio fijo donde realizar su trabajo. Todo lo que necesitan esta en la red, la información que necesitan como las herramientas. Convirtiéndose este tipo de trabajador en teletrabajadores. Estos trabajadores utilizan de forma intensiva sus conocimientos, no se puede permitir quedarse obsoletos en su conocimientos, sería su gran desgracia. Por está razón, necesitan estar formándose continuamente, aprendiendo y conociendo las nuevas tecnologías que aparecen. Con el objetivo de conseguir nuevas líneas de negocio, con el fin de lograr nuevos ingresos. Los trabajadores que hacen un uso intensivo en la tecnología de la información y comunicación, se caracterizan por la continua innovación y cambio tecnológico. Estos trabajadores necesitan una red profesional, social amplia con enlaces fuertes y poderosos. Las redes son importantes, para estar actualizado con las innovaciones que se realizan en las empresas, optar a nuevos puesto de trabajo, curso en nuevas tecnologías… Gracias a los servicios actuales en Internet facilitan mantener vivos una gran cantidad de enlaces (contactos), en comparación con otras épocas. La plataforma propuesta en este proyecto final de carrera esta compuesta de todas las herramientas necesarias para que estos trabajadores puedan desarrollar su actividad y mantenimiento de sus redes profesionales. Abstract: The aim of this Final Project of Career, Implementation of Virtual Engineering with Joomla!, is to create a web software application where a multidisciplinary engineering project bases on the networking, working groups and the flexible working can be implemented. The networking is the job through the Information Technology and Communication (ITC) where working groups compounded of multidisciplinary and multiracial professions, different religions and located in different time zones are created. The multicultural environment, collaboration, flexibility and to share resources are the order of the day on this kind of groups. The flexibility is the ability to adaptability of workers to the productivity demand, with the trust which is placed on them by supervisor people who wait to receive the work completed in a specific form and date. These workers do not need either constant supervision or a fixed site where to do the job. Everything the workers need is on the network, as the information as the tools, that is why they become teleworkers. These workers demand a high use of their knowledge, so it can not be allowed to become obsolete. This would be a great misfortune. That is why they need to continue learning and knowing the new technologies emerging with the aim of getting new revenues. Workers do an intensive use of the information technology and communication, characterized by continuous innovation and technological change. These workers need a broad social and professional network with great power. This network is important to keep updated with innovations taking place at the companies, to apply for a new job, a new technology course etc.. Thanks to Internet services a bigger number of contacts are provided compared to earlier times. The software application of this project is compounded with enough tools with the aim of the workers can carry out their activity and maintenance of the links on their professional nets.

Mejora de la enseñanza de la Geología mediante e-learning

Resumen: en este trabajo se presentan nuevas estrategias de enseñanza y aprendizaje a través de las nuevas tecnologías en su variante virtual a distancia (e-learning) implementadas en asignaturas relacionadas con la Geología. El objetivo básico fue acercar los aspectos geológicos a los estudiantes mediante el empleo de estas tecnologías. Se ha observado una mayor motivación y adquisición de conocimientos geológicos por parte del alumnado, que se ha traducido en una mejora en las calificaciones. Abstract: This paper deals with new teaching and learning approaches through the use of new technologies, mainly virtual distance learning (e-learning) in courses related to Geology. The main objective is to bring the geological aspects of Nature to students using these technologies. These new approaches have produced an increase in student motivation and acquisition of geological knowledge, accompanied by an improvement in their grades.

Strengthening communication skills in an innovative context of engineering project management learning

This document presents an innovative, formal educational initiative that is aimed at enhancing the development of engineering students’ specific competences when studying Project Management (PM) subject. The framework of the experience combines (1) theoretical concepts, (2) the development of a real-case project carried out by multidisciplinary groups of three different universities, (3) the use of software web 2.0 tools and (4) group and individual assignments of students that play different roles (project managers and team members). Under this scenario, the study focuses on monitoring the communication competence in the ever growing PM virtual environment. Factors such as corporal language, technical means, stage, and PM specific vocabulary among others have been considered in order to assess the students’ performance on this issue. As a main contribution, the paper introduces an ad-hoc rubric that, based on previous investigations, has been adapted and tested for the first time to this new and specific context. Additionally, the research conducted has provided some interesting findings that suggest further actions to improve and better define future rubrics, oriented to communication or even other competences. As specific PM subject concerns, it has been detected that students playing the role of Project Managers strengthen their competences more than those ones that play the role of Team Members. It has also been detected that students have more difficulty assimilating concepts related to risk and quality management. However those concepts related with scope, time or cost areas of knowledge have been better assimilated by the students.

Learning curves of basic laparoscopic psychomotor skills in SINERGIA VR simulator

Purpose: Surgical simulators are currently essential within any laparoscopic training program because they provide a low-stakes, reproducible and reliable environment to acquire basic skills. The purpose of this study is to determine the training learning curve based on different metrics corresponding to five tasks included in SINERGIA laparoscopic virtual reality simulator. Methods: Thirty medical students without surgical experience participated in the study. Five tasks of SINERGIA were included: Coordination, Navigation, Navigation and touch, Accurate grasping and Coordinated pulling. Each participant was trained in SINERGIA. This training consisted of eight sessions (R1–R8) of the five mentioned tasks and was carried out in two consecutive days with four sessions per day. A statistical analysis was made, and the results of R1, R4 and R8 were pair-wise compared with Wilcoxon signed-rank test. Significance is considered at P value <0.005. Results: In total, 84.38% of the metrics provided by SINERGIA and included in this study show significant differences when comparing R1 and R8. Metrics are mostly improved in the first session of training (75.00% when R1 and R4 are compared vs. 37.50% when R4 and R8 are compared). In tasks Coordination and Navigation and touch, all metrics are improved. On the other hand, Navigation just improves 60% of the analyzed metrics. Most learning curves show an improvement with better results in the fulfillment of the different tasks. Conclusions: Learning curves of metrics that assess the basic psychomotor laparoscopic skills acquired in SINERGIA virtual reality simulator show a faster learning rate during the first part of the training. Nevertheless, eight repetitions of the tasks are not enough to acquire all psychomotor skills that can be trained in SINERGIA. Therefore, and based on these results together with previous works, SINERGIA could be used as training tool with a properly designed training program.

Virtual Excursions: a new way to explore science in class

The educational platform Virtual Science Hub (ViSH) has been developed as part of the GLOBAL excursion European project. ViSH (http://vishub.org/) is a portal where teachers and scientist interact to create virtual excursions to science infrastructures. The main motivation behind the project was to connect teachers - and in consequence their students - to scientific institutions and their wide amount of infrastructures and resources they are working with. Thus the idea of a hub was born that would allow the two worlds of scientists and teachers to connect and to innovate science teaching. The core of the ViSH?s concept design is based on virtual excursions, which allow for a number of pedagogical models to be applied. According to our internal definition a virtual excursion is a tour through some digital context by teachers and pupils on a given topic that is attractive and has an educational purpose. Inquiry-based learning, project-based and problem-based learning are the most prominent approaches that a virtual excursion may serve. The domain specific resources and scientific infrastructures currently available on the ViSH are focusing on life sciences, nano-technology, biotechnology, grid and volunteer computing. The virtual excursion approach allows an easy combination of these resources into interdisciplinary teaching scenarios. In addition, social networking features support the users in collaborating and communicating in relation to these excursions and thus create a community of interest for innovative science teaching. The design and development phases were performed following a participatory design approach. An important aspect in this process was to create design partnerships amongst all actors involved, researchers, developers, infrastructure providers, teachers, social scientists, and pedagogical experts early in the project. A joint sense of ownership was created and important changes during the conceptual phase were implemented in the ViSH due to early user feedback. Technology-wise the ViSH is based on the latest web technologies in order to make it cross-platform compatible so that it works on several operative systems such as Windows, Mac or Linux and multi-device accessible, such as desktop, tablet and mobile devices. The platform has been developed in HTML5, the latest standard for web development, assuring that it can run on any modern browser. In addition to social networking features a core element on the ViSH is the virtual excursions editor. It is a web tool that allows teachers and scientists to create rich mash-ups of learning resources provided by the e-Infrastructures (i.e. remote laboratories and live webcams). These rich mash-ups can be presented in either slides or flashcards format. Taking advantage of the web architecture supported, additional powerful components have been integrated like a recommendation engine to provide personalized suggestions about educational content or interesting users and a videoconference tool to enhance real-time collaboration like MashMeTV (http://www.mashme.tv/).

Monitoring the communication competence in an innovative context of project management learning

This document presents an innovative, formal educational initiative that is aimed at enhancing the development of engineering students' specific competences. The subject of project management is the common theoretical and practical framework that articulates an experience that is carried out by multidisciplinary groups. Full utilization of Web 2.0 platforms and Project Based Learning constitutes the applied methodology. More specifically, this study focuses on monitoring communication competence when working in virtual environments, providing an ad-hoc rubric as a final result.

Unidad didáctica sobre el uso del programa Virtual.Lab para simulaciones acústicas. Parte I

El presente Proyecto de Fin de Carrera supone el propósito conjunto de los alumnos Álvaro Morillas y Fernando Sáez, y del profesor Vladimir Ulin, de desarrollar una unidad didáctica sobre el programa de simulación para ingeniería Virtual.Lab. La versión sobre la que se ha trabajado para realizar este texto es la 11, publicada en agosto de 2012. Virtual.Lab, del fabricante belga LMS International, es una plataforma software de ingeniería asistida por ordenador, que agrupa en una misma aplicación varias herramientas complementarias en el diseño de un producto, desde su definición geométrica a los análisis de durabilidad, ruido u optimización. No obstante, de entre todas las posibles simulaciones que nos permite el programa, en este proyecto sólo se tratan las que están relacionadas con la acústica. Cabe resaltar que gran parte de los conceptos manejados en Virtual.Lab son compatibles con el programa CATIA V5, ya que ambos programas vienen instalados y funcionan conjuntamente. Por eso, el lector de este proyecto podrá transportar sus conocimientos al que es uno de los programas estándar en las industrias aeronáutica, naval y automovilística, entre otras. Antes de este proyecto, otros alumnos de la escuela también realizaron proyectos de fin de carrera en el campo de la simulación computarizada en acústica. Una característica común a estos trabajos es que era necesario hacer uso de distintos programas para cada una de las etapas de simulación (como por ejemplo, ANSYS para el modelado y estudio de la vibración y SYSNOISE para las simulaciones acústicas, además de otros programas auxiliares para las traducciones de formato). Con Virtual.Lab desaparece esta necesidad y el tiempo empleado se reduce. Debido a que las soluciones por ordenador están ganando cada vez más importancia en la industria actual, los responsables de este proyecto consideran la necesidad de formación de profesionales en esta rama. Para responder a la demanda empresarial de trabajadores cualificados, se espera que en los próximos años los planes de estudio contengan más cursos en esta materia. Por tanto la intención de los autores es que este material sea de utilidad para el aprendizaje y docencia de estas asignaturas en cursos sucesivos. Por todo esto, se justifica la relevancia de este PFC como manual para introducir a los alumnos interesados en iniciarse en un sistema actual, de uso extendido en otras universidades tecnológicas europeas, y con buenas perspectivas de futuro. En este proyecto se incluyen varios ejemplos ejecutables desde el programa, así como vídeos explicativos que ayudan a mostrar gráficamente los procesos de simulación. Estos archivos se pueden encontrar en el CD adjunto. Abstract This final thesis is a joint project made by the students Álvaro Morillas and Fernando Sáez, and the professor Vladimir Ulin. The nature of the joint regards the writing of a didactic unit on Virtual.Lab, the simulation software. The software version used in this text is the number 11, released in August 2012. Virtual.Lab, from the Belgian developer LMS International, is a computer-aided engineering software which is used for several related tasks in this field: product design, durability simulation, optimization, etc. However, this project is focused on the acoustical capabilities. It is worthy to highlight that most procedures explained in this text can be used in the software CATIA V5 as well. Both tools come installed together and may be used at the same time. Therefore, the reader of this project will be able to use the acquired knowledge in one of the most relevant softwares for the aerospace, marine and automotive engineering. Previously to the development of this project, this School has conducted projects on this field. These projects regarded the use of ANSYS for modeling and meshing stages as well as the use of SYSNOISE for the final acoustic analysis. Since both systems use different file formats, a third-party translation software was required. This thesis fulfill this pending necessity with Virtual.Lab; the translation software procedure is not necessary anymore and simulations can be done in a more flexible, fast way. Since companies have an increasing usage of numerical methods in the development of their products and services, the authors think that it is important to develop the appropriate method to instruct new professionals in the field. Thus, the aim of this project is to help teachers and students in their process of learning the use of this leading software in acoustical simulations. For all the reasons mentioned above, we consider that this project is relevant for the School and the educational community. Aiming to achieve this objective the author offers example files and video demonstrations with guidance in the CD that accompanies this material. This facilitates the comprehension of the practical tasks and guides the prospect users of the software.

Contributions to Bayesian network learning with applications to neuroscience

Neuronal morphology is a key feature in the study of brain circuits, as it is highly related to information processing and functional identification. Neuronal morphology affects the process of integration of inputs from other neurons and determines the neurons which receive the output of the neurons. Different parts of the neurons can operate semi-independently according to the spatial location of the synaptic connections. As a result, there is considerable interest in the analysis of the microanatomy of nervous cells since it constitutes an excellent tool for better understanding cortical function. However, the morphologies, molecular features and electrophysiological properties of neuronal cells are extremely variable. Except for some special cases, this variability makes it hard to find a set of features that unambiguously define a neuronal type. In addition, there are distinct types of neurons in particular regions of the brain. This morphological variability makes the analysis and modeling of neuronal morphology a challenge. Uncertainty is a key feature in many complex real-world problems. Probability theory provides a framework for modeling and reasoning with uncertainty. Probabilistic graphical models combine statistical theory and graph theory to provide a tool for managing domains with uncertainty. In particular, we focus on Bayesian networks, the most commonly used probabilistic graphical model. In this dissertation, we design new methods for learning Bayesian networks and apply them to the problem of modeling and analyzing morphological data from neurons. The morphology of a neuron can be quantified using a number of measurements, e.g., the length of the dendrites and the axon, the number of bifurcations, the direction of the dendrites and the axon, etc. These measurements can be modeled as discrete or continuous data. The continuous data can be linear (e.g., the length or the width of a dendrite) or directional (e.g., the direction of the axon). These data may follow complex probability distributions and may not fit any known parametric distribution. Modeling this kind of problems using hybrid Bayesian networks with discrete, linear and directional variables poses a number of challenges regarding learning from data, inference, etc. In this dissertation, we propose a method for modeling and simulating basal dendritic trees from pyramidal neurons using Bayesian networks to capture the interactions between the variables in the problem domain. A complete set of variables is measured from the dendrites, and a learning algorithm is applied to find the structure and estimate the parameters of the probability distributions included in the Bayesian networks. Then, a simulation algorithm is used to build the virtual dendrites by sampling values from the Bayesian networks, and a thorough evaluation is performed to show the model’s ability to generate realistic dendrites. In this first approach, the variables are discretized so that discrete Bayesian networks can be learned and simulated. Then, we address the problem of learning hybrid Bayesian networks with different kinds of variables. Mixtures of polynomials have been proposed as a way of representing probability densities in hybrid Bayesian networks. We present a method for learning mixtures of polynomials approximations of one-dimensional, multidimensional and conditional probability densities from data. The method is based on basis spline interpolation, where a density is approximated as a linear combination of basis splines. The proposed algorithms are evaluated using artificial datasets. We also use the proposed methods as a non-parametric density estimation technique in Bayesian network classifiers. Next, we address the problem of including directional data in Bayesian networks. These data have some special properties that rule out the use of classical statistics. Therefore, different distributions and statistics, such as the univariate von Mises and the multivariate von Mises–Fisher distributions, should be used to deal with this kind of information. In particular, we extend the naive Bayes classifier to the case where the conditional probability distributions of the predictive variables given the class follow either of these distributions. We consider the simple scenario, where only directional predictive variables are used, and the hybrid case, where discrete, Gaussian and directional distributions are mixed. The classifier decision functions and their decision surfaces are studied at length. Artificial examples are used to illustrate the behavior of the classifiers. The proposed classifiers are empirically evaluated over real datasets. We also study the problem of interneuron classification. An extensive group of experts is asked to classify a set of neurons according to their most prominent anatomical features. A web application is developed to retrieve the experts’ classifications. We compute agreement measures to analyze the consensus between the experts when classifying the neurons. Using Bayesian networks and clustering algorithms on the resulting data, we investigate the suitability of the anatomical terms and neuron types commonly used in the literature. Additionally, we apply supervised learning approaches to automatically classify interneurons using the values of their morphological measurements. Then, a methodology for building a model which captures the opinions of all the experts is presented. First, one Bayesian network is learned for each expert, and we propose an algorithm for clustering Bayesian networks corresponding to experts with similar behaviors. Then, a Bayesian network which represents the opinions of each group of experts is induced. Finally, a consensus Bayesian multinet which models the opinions of the whole group of experts is built. A thorough analysis of the consensus model identifies different behaviors between the experts when classifying the interneurons in the experiment. A set of characterizing morphological traits for the neuronal types can be defined by performing inference in the Bayesian multinet. These findings are used to validate the model and to gain some insights into neuron morphology. Finally, we study a classification problem where the true class label of the training instances is not known. Instead, a set of class labels is available for each instance. This is inspired by the neuron classification problem, where a group of experts is asked to individually provide a class label for each instance. We propose a novel approach for learning Bayesian networks using count vectors which represent the number of experts who selected each class label for each instance. These Bayesian networks are evaluated using artificial datasets from supervised learning problems. Resumen La morfología neuronal es una característica clave en el estudio de los circuitos cerebrales, ya que está altamente relacionada con el procesado de información y con los roles funcionales. La morfología neuronal afecta al proceso de integración de las señales de entrada y determina las neuronas que reciben las salidas de otras neuronas. Las diferentes partes de la neurona pueden operar de forma semi-independiente de acuerdo a la localización espacial de las conexiones sinápticas. Por tanto, existe un interés considerable en el análisis de la microanatomía de las células nerviosas, ya que constituye una excelente herramienta para comprender mejor el funcionamiento de la corteza cerebral. Sin embargo, las propiedades morfológicas, moleculares y electrofisiológicas de las células neuronales son extremadamente variables. Excepto en algunos casos especiales, esta variabilidad morfológica dificulta la definición de un conjunto de características que distingan claramente un tipo neuronal. Además, existen diferentes tipos de neuronas en regiones particulares del cerebro. La variabilidad neuronal hace que el análisis y el modelado de la morfología neuronal sean un importante reto científico. La incertidumbre es una propiedad clave en muchos problemas reales. La teoría de la probabilidad proporciona un marco para modelar y razonar bajo incertidumbre. Los modelos gráficos probabilísticos combinan la teoría estadística y la teoría de grafos con el objetivo de proporcionar una herramienta con la que trabajar bajo incertidumbre. En particular, nos centraremos en las redes bayesianas, el modelo más utilizado dentro de los modelos gráficos probabilísticos. En esta tesis hemos diseñado nuevos métodos para aprender redes bayesianas, inspirados por y aplicados al problema del modelado y análisis de datos morfológicos de neuronas. La morfología de una neurona puede ser cuantificada usando una serie de medidas, por ejemplo, la longitud de las dendritas y el axón, el número de bifurcaciones, la dirección de las dendritas y el axón, etc. Estas medidas pueden ser modeladas como datos continuos o discretos. A su vez, los datos continuos pueden ser lineales (por ejemplo, la longitud o la anchura de una dendrita) o direccionales (por ejemplo, la dirección del axón). Estos datos pueden llegar a seguir distribuciones de probabilidad muy complejas y pueden no ajustarse a ninguna distribución paramétrica conocida. El modelado de este tipo de problemas con redes bayesianas híbridas incluyendo variables discretas, lineales y direccionales presenta una serie de retos en relación al aprendizaje a partir de datos, la inferencia, etc. En esta tesis se propone un método para modelar y simular árboles dendríticos basales de neuronas piramidales usando redes bayesianas para capturar las interacciones entre las variables del problema. Para ello, se mide un amplio conjunto de variables de las dendritas y se aplica un algoritmo de aprendizaje con el que se aprende la estructura y se estiman los parámetros de las distribuciones de probabilidad que constituyen las redes bayesianas. Después, se usa un algoritmo de simulación para construir dendritas virtuales mediante el muestreo de valores de las redes bayesianas. Finalmente, se lleva a cabo una profunda evaluaci ón para verificar la capacidad del modelo a la hora de generar dendritas realistas. En esta primera aproximación, las variables fueron discretizadas para poder aprender y muestrear las redes bayesianas. A continuación, se aborda el problema del aprendizaje de redes bayesianas con diferentes tipos de variables. Las mixturas de polinomios constituyen un método para representar densidades de probabilidad en redes bayesianas híbridas. Presentamos un método para aprender aproximaciones de densidades unidimensionales, multidimensionales y condicionales a partir de datos utilizando mixturas de polinomios. El método se basa en interpolación con splines, que aproxima una densidad como una combinación lineal de splines. Los algoritmos propuestos se evalúan utilizando bases de datos artificiales. Además, las mixturas de polinomios son utilizadas como un método no paramétrico de estimación de densidades para clasificadores basados en redes bayesianas. Después, se estudia el problema de incluir información direccional en redes bayesianas. Este tipo de datos presenta una serie de características especiales que impiden el uso de las técnicas estadísticas clásicas. Por ello, para manejar este tipo de información se deben usar estadísticos y distribuciones de probabilidad específicos, como la distribución univariante von Mises y la distribución multivariante von Mises–Fisher. En concreto, en esta tesis extendemos el clasificador naive Bayes al caso en el que las distribuciones de probabilidad condicionada de las variables predictoras dada la clase siguen alguna de estas distribuciones. Se estudia el caso base, en el que sólo se utilizan variables direccionales, y el caso híbrido, en el que variables discretas, lineales y direccionales aparecen mezcladas. También se estudian los clasificadores desde un punto de vista teórico, derivando sus funciones de decisión y las superficies de decisión asociadas. El comportamiento de los clasificadores se ilustra utilizando bases de datos artificiales. Además, los clasificadores son evaluados empíricamente utilizando bases de datos reales. También se estudia el problema de la clasificación de interneuronas. Desarrollamos una aplicación web que permite a un grupo de expertos clasificar un conjunto de neuronas de acuerdo a sus características morfológicas más destacadas. Se utilizan medidas de concordancia para analizar el consenso entre los expertos a la hora de clasificar las neuronas. Se investiga la idoneidad de los términos anatómicos y de los tipos neuronales utilizados frecuentemente en la literatura a través del análisis de redes bayesianas y la aplicación de algoritmos de clustering. Además, se aplican técnicas de aprendizaje supervisado con el objetivo de clasificar de forma automática las interneuronas a partir de sus valores morfológicos. A continuación, se presenta una metodología para construir un modelo que captura las opiniones de todos los expertos. Primero, se genera una red bayesiana para cada experto y se propone un algoritmo para agrupar las redes bayesianas que se corresponden con expertos con comportamientos similares. Después, se induce una red bayesiana que modela la opinión de cada grupo de expertos. Por último, se construye una multired bayesiana que modela las opiniones del conjunto completo de expertos. El análisis del modelo consensuado permite identificar diferentes comportamientos entre los expertos a la hora de clasificar las neuronas. Además, permite extraer un conjunto de características morfológicas relevantes para cada uno de los tipos neuronales mediante inferencia con la multired bayesiana. Estos descubrimientos se utilizan para validar el modelo y constituyen información relevante acerca de la morfología neuronal. Por último, se estudia un problema de clasificación en el que la etiqueta de clase de los datos de entrenamiento es incierta. En cambio, disponemos de un conjunto de etiquetas para cada instancia. Este problema está inspirado en el problema de la clasificación de neuronas, en el que un grupo de expertos proporciona una etiqueta de clase para cada instancia de manera individual. Se propone un método para aprender redes bayesianas utilizando vectores de cuentas, que representan el número de expertos que seleccionan cada etiqueta de clase para cada instancia. Estas redes bayesianas se evalúan utilizando bases de datos artificiales de problemas de aprendizaje supervisado.

Incorporating proactivity to context-aware recommender systems for e-learning

Recommender systems in e-learning have proved to be powerful tools to find suitable educational material during the learning experience. But traditional user request-response patterns are still being used to generate these recommendations. By including contextual information derived from the use of ubiquitous learning environments, the possibility of incorporating proactivity to the recommendation process has arisen. In this paper we describe methods to push proactive recommendations to e-learning systems users when the situation is appropriate without being needed their explicit request. As a result, interesting learning objects can be recommended attending to the user?s needs in every situation. The impact of this proactive recommendations generated have been evaluated among teachers and scientists in a real e-learning social network called Virtual Science Hub related to the GLOBAL excursion European project. Outcomes indicate that the methods proposed are valid to generate such kind of recommendations in e-learning scenarios. The results also show that the users' perceived appropriateness of having proactive recommendations is high.

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.

An ICT based Project Management Learning Framework

The objective of this paper is to present a framework that can facilitate the university level learning process in the Project Management of different students who are enrolled in different universities in different locations and attending their own Project Management courses, but running a virtual experience in executing and managing projects. The framework includes both information systems and methodological procedures that are integrated in the information system, making it possible to assess learning performance.

Development and implementation of a virtual laboratory for training process improvement in the mechanics of continuous media

The project arises from the need to develop improved teaching methodologies in field of the mechanics of continuous media. The objective is to offer the student a learning process to acquire the necessary theoretical knowledge, cognitive skills and the responsibility and autonomy to professional development in this area. Traditionally the teaching of the concepts of these subjects was performed through lectures and laboratory practice. During these lessons the students attitude was usually passive, and therefore their effectiveness was poor. The proposed methodology has already been successfully employed in universities like University Bochum, Germany, University the South Australia and aims to improve the effectiveness of knowledge acquisition through use by the student of a virtual laboratory. This laboratory allows to adapt the curricula and learning techniques to the European Higher Education and improve current learning processes in the University School of Public Works Engineers -EUITOP- of the Technical University of Madrid -UPM-, due there are not laboratories in this specialization. The virtual space is created using a software platform built on OpenSim, manages 3D virtual worlds, and, language LSL -Linden Scripting Language-, which imprints specific powers to objects. The student or user can access this virtual world through their avatar -your character in the virtual world- and can perform practices within the space created for the purpose, at any time, just with computer with internet access and viewfinder. The virtual laboratory has three partitions. The virtual meeting rooms, where the avatar can interact with peers, solve problems and exchange existing documentation in the virtual library. The interactive game room, where the avatar is has to resolve a number of issues in time. And the video room where students can watch instructional videos and receive group lessons. Each audiovisual interactive element is accompanied by explanations framing it within the area of knowledge and enables students to begin to acquire a vocabulary and practice of the profession for which they are being formed. Plane elasticity concepts are introduced from the tension and compression testing of test pieces of steel and concrete. The behavior of reticulated and articulated structures is reinforced by some interactive games and concepts of tension, compression, local and global buckling will by tests to break articulated structures. Pure bending concepts, simple and composite torsion will be studied by observing a flexible specimen. Earthquake resistant design of buildings will be checked by a laboratory test video.

Ayuda virtual al aprendizaje de Geología en la E.T.S.I Minas y Energía de Madrid

El aprendizaje de la Geología requiere de una habilidad que se consigue principalmente con la práctica en la Naturaleza, siendo más efectiva cuando los conocimientos se intentan trasmitir a otra persona. En este trabajo se muestran los resultados obtenidos tras introducir cambios en asignaturas relacionadas con la Geología empleando nuevas tecnologías, que han supuesto la mejora del aprendizaje combinando el trabajo práctico personal del estudiante con la realización de vídeos en el medio físico en los que explican los aspectos geológicos visibles a diferentes escalas. Asimismo, se han elaborado fichas de “rutas geológicas”, acompañadas por estos vídeos en las que se señalan los aspectos geológicos más importantes. Los vídeos se han subido a las plataformas “moodle”, “facebook” y canal “youtube” donde las personas interesadas pueden consultarlos. Las guías se encuentran en la plataforma “moodle”. Los estudiantes manifestaron su satisfacción por esta actividad ya que, además de adquirir conocimientos geológicos, adquirieron la seguridad de expresarse en público con un lenguaje técnico. Ello supuso una mejora en las calificaciones y un incremento de la motivación. Por otro lado, los estudiantes que lo deseen pueden realizar itinerarios de interés geológico sin necesidad de ir acompañados de un docente, profundizando en los temas que más les interesen Abstract: Learning Geology requires a skill that is primarily achieved with practice in nature, being more effective when one tries to transmit knowledge to others. Here, we show the results of an educational innovation program in courses related to Geology using new technologies (ITC) in order to increase the acquisition of geological knowledge. This program is designed mainly on the basis of individual work with video recordings in the field in which students explain geological concepts at various scales. These videos have been uploaded to the “moodle”, “facebook” and “youtube” channel, where people can view them. We also elaborated "Geological routes," which are accompanied by these videos indicating the most important geological aspects that can be observed, that were uploaded to “moodle” platform. The realization of these videos has been warmly welcomed by students, and they show increased motivation, accompanied by an improvement in grades. They also gained confidence in public speaking using technical language. Also, students can make itineraries of geological interest without having to be accompanied by a professor, deeping into the most interesting topics.