Computer game-based and traditional learning method: a comparison regarding students’ knowledge retention

Abstract Background Educational computer games are examples of computer-assisted learning objects, representing an educational strategy of growing interest. Given the changes in the digital world over the last decades, students of the current generation expect technology to be used in advancing their learning requiring a need to change traditional passive learning methodologies to an active multisensory experimental learning methodology. The objective of this study was to compare a computer game-based learning method with a traditional learning method, regarding learning gains and knowledge retention, as means of teaching head and neck Anatomy and Physiology to Speech-Language and Hearing pathology undergraduate students. Methods Students were randomized to participate to one of the learning methods and the data analyst was blinded to which method of learning the students had received. Students’ prior knowledge (i.e. before undergoing the learning method), short-term knowledge retention and long-term knowledge retention (i.e. six months after undergoing the learning method) were assessed with a multiple choice questionnaire. Students’ performance was compared considering the three moments of assessment for both for the mean total score and for separated mean scores for Anatomy questions and for Physiology questions. Results Students that received the game-based method performed better in the pos-test assessment only when considering the Anatomy questions section. Students that received the traditional lecture performed better in both post-test and long-term post-test when considering the Anatomy and Physiology questions. Conclusions The game-based learning method is comparable to the traditional learning method in general and in short-term gains, while the traditional lecture still seems to be more effective to improve students’ short and long-term knowledge retention.

Rich media content adaptation in e-learning systems

The wide use of e-technologies represents a great opportunity for underserved segments of the population, especially with the aim of reintegrating excluded individuals back into society through education. This is particularly true for people with different types of disabilities who may have difficulties while attending traditional on-site learning programs that are typically based on printed learning resources. The creation and provision of accessible e-learning contents may therefore become a key factor in enabling people with different access needs to enjoy quality learning experiences and services. Another e-learning challenge is represented by m-learning (which stands for mobile learning), which is emerging as a consequence of mobile terminals diffusion and provides the opportunity to browse didactical materials everywhere, outside places that are traditionally devoted to education. Both such situations share the need to access materials in limited conditions and collide with the growing use of rich media in didactical contents, which are designed to be enjoyed without any restriction. Nowadays, Web-based teaching makes great use of multimedia technologies, ranging from Flash animations to prerecorded video-lectures. Rich media in e-learning can offer significant potential in enhancing the learning environment, through helping to increase access to education, enhance the learning experience and support multiple learning styles. Moreover, they can often be used to improve the structure of Web-based courses. These highly variegated and structured contents may significantly improve the quality and the effectiveness of educational activities for learners. For example, rich media contents allow us to describe complex concepts and process flows. Audio and video elements may be utilized to add a “human touch” to distance-learning courses. Finally, real lectures may be recorded and distributed to integrate or enrich on line materials. A confirmation of the advantages of these approaches can be seen in the exponential growth of video-lecture availability on the net, due to the ease of recording and delivering activities which take place in a traditional classroom. Furthermore, the wide use of assistive technologies for learners with disabilities injects new life into e-learning systems. E-learning allows distance and flexible educational activities, thus helping disabled learners to access resources which would otherwise present significant barriers for them. For instance, students with visual impairments have difficulties in reading traditional visual materials, deaf learners have trouble in following traditional (spoken) lectures, people with motion disabilities have problems in attending on-site programs. As already mentioned, the use of wireless technologies and pervasive computing may really enhance the educational learner experience by offering mobile e-learning services that can be accessed by handheld devices. This new paradigm of educational content distribution maximizes the benefits for learners since it enables users to overcome constraints imposed by the surrounding environment. While certainly helpful for users without disabilities, we believe that the use of newmobile technologies may also become a fundamental tool for impaired learners, since it frees them from sitting in front of a PC. In this way, educational activities can be enjoyed by all the users, without hindrance, thus increasing the social inclusion of non-typical learners. While the provision of fully accessible and portable video-lectures may be extremely useful for students, it is widely recognized that structuring and managing rich media contents for mobile learning services are complex and expensive tasks. Indeed, major difficulties originate from the basic need to provide a textual equivalent for each media resource composing a rich media Learning Object (LO). Moreover, tests need to be carried out to establish whether a given LO is fully accessible to all kinds of learners. Unfortunately, both these tasks are truly time-consuming processes, depending on the type of contents the teacher is writing and on the authoring tool he/she is using. Due to these difficulties, online LOs are often distributed as partially accessible or totally inaccessible content. Bearing this in mind, this thesis aims to discuss the key issues of a system we have developed to deliver accessible, customized or nomadic learning experiences to learners with different access needs and skills. To reduce the risk of excluding users with particular access capabilities, our system exploits Learning Objects (LOs) which are dynamically adapted and transcoded based on the specific needs of non-typical users and on the barriers that they can encounter in the environment. The basic idea is to dynamically adapt contents, by selecting them from a set of media resources packaged in SCORM-compliant LOs and stored in a self-adapting format. The system schedules and orchestrates a set of transcoding processes based on specific learner needs, so as to produce a customized LO that can be fully enjoyed by any (impaired or mobile) student.

Distributed Repositories for Educational Content

As education providers increasingly integrate digital learning media into their education processes, the need for the systematic management of learning materials and learning arrangements becomes clearer. Digital repositories, often called Learning Object Repositories (LOR), promise to provide an answer to this challenge. This article is composed of two parts. In this part, we derive technological and pedagogical requirements for LORs from a concretization of information quality criteria for e-learning technology. We review the evolution of learning object repositories and discuss their core features in the context of pedagogical requirements, information quality demands, and e-learning technology standards. We conclude with an outlook in Part 2, which presents concrete technical solutions, in particular networked repository architectures.

Distributed Repositories for Educational Content

In Part 1 of this article we discussed the need for information quality and the systematic management of learning materials and learning arrangements. Digital repositories, often called Learning Object Repositories (LOR), were introduced as a promising answer to this challenge. We also derived technological and pedagogical requirements for LORs from a concretization of information quality criteria for e-learning technology. This second part presents technical solutions that particularly address the demands of open education movements, which aspire to a global reuse and sharing culture. From this viewpoint, we develop core requirements for scalable network architectures for educational content management. We then present edu-sharing, an advanced example of a network of homogeneous repositories for learning resources, and discuss related technology. We conclude with an outlook in terms of emerging developments towards open and networked system architectures in e-learning.

The Comprehensive Assessment of Leadership for Learning: A Next Generation Formative Evaluation and Feedback System

Recent developments in federal policy have prompted the creation of state evaluation frameworks for principals and teachers that hold educators accountable for effective practices and student outcomes. These changes have created a demand for formative evaluation instruments that reflect current accountability pressures and can be used by schools to focus school improvement and leadership development efforts. The Comprehensive Assessment of Leadership for Learning (CALL) is a next generation, 360-degree on-line assessment and feedback system that reflect best practices in feedback design. Some unique characteristics of CALL include a focus on: leadership distributed throughout the school rather than as carried out by an individual leader; assessment of leadership tasks rather than perceptions of leadership practice; a focus on larger complex systems of middle and high school; and transparency of assessment design. This paper describes research contributing to the design and validation of the CALL survey instrument.

Distributed Fault Diagnosis Using Bayesian Reasoning in MAGNETO

Many of the emerging telecom services make use of Outer Edge Networks, in particular Home Area Networks. The configuration and maintenance of such services may not be under full control of the telecom operator which still needs to guarantee the service quality experienced by the consumer. Diagnosing service faults in these scenarios becomes especially difficult since there may be not full visibility between different domains. This paper describes the fault diagnosis solution developed in the MAGNETO project, based on the application of Bayesian Inference to deal with the uncertainty. It also takes advantage of a distributed framework to deploy diagnosis components in the different domains and network elements involved, spanning both the telecom operator and the Outer Edge networks. In addition, MAGNETO features self-learning capabilities to automatically improve diagnosis knowledge over time and a partition mechanism that allows breaking down the overall diagnosis knowledge into smaller subsets. The MAGNETO solution has been prototyped and adapted to a particular outer edge scenario, and has been further validated on a real testbed. Evaluation of the results shows the potential of our approach to deal with fault management of outer edge networks.

New Methodology for Integrating Teams into Multidisciplinary Project Based Learning

This paper describes the collaboration among students and professors in four different subjects, to develop multidisciplinary projects. The objective is to simulate the conditions in a company environment. A new methodology based on student interaction and content development in a Wiki environment has been developed. The collaborative server created an ‘out of the classroom’ discussion forum for students of different subjects, and allowed them to compile a ‘project work’ portfolio. Students and professors participated with enthusiasm, due to the correct well-distributed work and the easiness of use of the selected platform in which only an internet connected computer is needed to create and to discuss the multidisciplinary projects. Quality of developed projects has been dramatically improved due to integration of results provided from the different teams.

Response threshold models, stochastic learning automata and ant colony optimization-based decentralized self-coordination algorithms for heterogeneous multi-tasks distribution in multi-robot systems

In recent decades, there has been an increasing interest in systems comprised of several autonomous mobile robots, and as a result, there has been a substantial amount of development in the eld of Articial Intelligence, especially in Robotics. There are several studies in the literature by some researchers from the scientic community that focus on the creation of intelligent machines and devices capable to imitate the functions and movements of living beings. Multi-Robot Systems (MRS) can often deal with tasks that are dicult, if not impossible, to be accomplished by a single robot. In the context of MRS, one of the main challenges is the need to control, coordinate and synchronize the operation of multiple robots to perform a specic task. This requires the development of new strategies and methods which allow us to obtain the desired system behavior in a formal and concise way. This PhD thesis aims to study the coordination of multi-robot systems, in particular, addresses the problem of the distribution of heterogeneous multi-tasks. The main interest in these systems is to understand how from simple rules inspired by the division of labor in social insects, a group of robots can perform tasks in an organized and coordinated way. We are mainly interested on truly distributed or decentralized solutions in which the robots themselves, autonomously and in an individual manner, select a particular task so that all tasks are optimally distributed. In general, to perform the multi-tasks distribution among a team of robots, they have to synchronize their actions and exchange information. Under this approach we can speak of multi-tasks selection instead of multi-tasks assignment, which means, that the agents or robots select the tasks instead of being assigned a task by a central controller. The key element in these algorithms is the estimation ix of the stimuli and the adaptive update of the thresholds. This means that each robot performs this estimate locally depending on the load or the number of pending tasks to be performed. In addition, it is very interesting the evaluation of the results in function in each approach, comparing the results obtained by the introducing noise in the number of pending loads, with the purpose of simulate the robot's error in estimating the real number of pending tasks. The main contribution of this thesis can be found in the approach based on self-organization and division of labor in social insects. An experimental scenario for the coordination problem among multiple robots, the robustness of the approaches and the generation of dynamic tasks have been presented and discussed. The particular issues studied are: Threshold models: It presents the experiments conducted to test the response threshold model with the objective to analyze the system performance index, for the problem of the distribution of heterogeneous multitasks in multi-robot systems; also has been introduced additive noise in the number of pending loads and has been generated dynamic tasks over time. Learning automata methods: It describes the experiments to test the learning automata-based probabilistic algorithms. The approach was tested to evaluate the system performance index with additive noise and with dynamic tasks generation for the same problem of the distribution of heterogeneous multi-tasks in multi-robot systems. Ant colony optimization: The goal of the experiments presented is to test the ant colony optimization-based deterministic algorithms, to achieve the distribution of heterogeneous multi-tasks in multi-robot systems. In the experiments performed, the system performance index is evaluated by introducing additive noise and dynamic tasks generation over time.

Diffusion Gradient Temporal Difference for Cooperative Reinforcement Learning with Linear Function Approximation

We introduce a diffusion-based algorithm in which multiple agents cooperate to predict a common and global statevalue function by sharing local estimates and local gradient information among neighbors. Our algorithm is a fully distributed implementation of the gradient temporal difference with linear function approximation, to make it applicable to multiagent settings. Simulations illustrate the benefit of cooperation in learning, as made possible by the proposed algorithm.

Decentralized multi-tasks distribution in heterogeneous robot teams by means of ant colony optimization and learning automata

This paper focuses on the general problem of coordinating multiple robots. More specifically, it addresses the self-election of heterogeneous specialized tasks by autonomous robots. In this paper we focus on a specifically distributed or decentralized approach as we are particularly interested on decentralized solution where the robots themselves autonomously and in an individual manner, are responsible of selecting a particular task so that all the existing tasks are optimally distributed and executed. In this regard, we have established an experimental scenario to solve the corresponding multi-tasks distribution problem and we propose a solution using two different approaches by applying Ant Colony Optimization-based deterministic algorithms as well as Learning Automata-based probabilistic algorithms. We have evaluated the robustness of the algorithm, perturbing the number of pending loads to simulate the robot’s error in estimating the real number of pending tasks and also the dynamic generation of loads through time. The paper ends with a critical discussion of experimental results.

Response threshold models and stochastic learning automata for self-coordination of heterogeneous multi-task distribution in multi-robot systems.

This paper focuses on the general problem of coordinating multiple robots. More specifically, it addresses the self-selection of heterogeneous specialized tasks by autonomous robots. In this paper we focus on a specifically distributed or decentralized approach as we are particularly interested in a decentralized solution where the robots themselves autonomously and in an individual manner, are responsible for selecting a particular task so that all the existing tasks are optimally distributed and executed. In this regard, we have established an experimental scenario to solve the corresponding multi-task distribution problem and we propose a solution using two different approaches by applying Response Threshold Models as well as Learning Automata-based probabilistic algorithms. We have evaluated the robustness of the algorithms, perturbing the number of pending loads to simulate the robot’s error in estimating the real number of pending tasks and also the dynamic generation of loads through time. The paper ends with a critical discussion of experimental results.

PUE attack detection in CWSN using collaboration and learning behavior

Cognitive Wireless Sensor Network (CWSN) is a new paradigm which integrates cognitive features in traditional Wireless Sensor Networks (WSNs) to mitigate important problems such as spectrum occupancy. Security in Cognitive Wireless Sensor Networks is an important problem because these kinds of networks manage critical applications and data. Moreover, the specific constraints of WSN make the problem even more critical. However, effective solutions have not been implemented yet. Among the specific attacks derived from new cognitive features, the one most studied is the Primary User Emulation (PUE) attack. This paper discusses a new approach, based on anomaly behavior detection and collaboration, to detect the PUE attack in CWSN scenarios. A nonparametric CUSUM algorithm, suitable for low resource networks like CWSN, has been used in this work. The algorithm has been tested using a cognitive simulator that brings important results in this area. For example, the result shows that the number of collaborative nodes is the most important parameter in order to improve the PUE attack detection rates. If the 20% of the nodes collaborates, the PUE detection reaches the 98% with less than 1% of false positives.

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.

Cooperative Multi-robot Patrolling: A study of distributed approaches based on mathematical models of game theory to protect infrastructures

El principio de Teoría de Juegos permite desarrollar modelos estocásticos de patrullaje multi-robot para proteger infraestructuras criticas. La protección de infraestructuras criticas representa un gran reto para los países al rededor del mundo, principalmente después de los ataques terroristas llevados a cabo la década pasada. En este documento el termino infraestructura hace referencia a aeropuertos, plantas nucleares u otros instalaciones. El problema de patrullaje se define como la actividad de patrullar un entorno determinado para monitorear cualquier actividad o sensar algunas variables ambientales. En esta actividad, un grupo de robots debe visitar un conjunto de puntos de interés definidos en un entorno en intervalos de tiempo irregulares con propósitos de seguridad. Los modelos de partullaje multi-robot son utilizados para resolver este problema. Hasta el momento existen trabajos que resuelven este problema utilizando diversos principios matemáticos. Los modelos de patrullaje multi-robot desarrollados en esos trabajos representan un gran avance en este campo de investigación. Sin embargo, los modelos con los mejores resultados no son viables para aplicaciones de seguridad debido a su naturaleza centralizada y determinista. Esta tesis presenta cinco modelos de patrullaje multi-robot distribuidos e impredecibles basados en modelos matemáticos de aprendizaje de Teoría de Juegos. El objetivo del desarrollo de estos modelos está en resolver los inconvenientes presentes en trabajos preliminares. Con esta finalidad, el problema de patrullaje multi-robot se formuló utilizando conceptos de Teoría de Grafos, en la cual se definieron varios juegos en cada vértice de un grafo. Los modelos de patrullaje multi-robot desarrollados en este trabajo de investigación se han validado y comparado con los mejores modelos disponibles en la literatura. Para llevar a cabo tanto la validación como la comparación se ha utilizado un simulador de patrullaje y un grupo de robots reales. Los resultados experimentales muestran que los modelos de patrullaje desarrollados en este trabajo de investigación trabajan mejor que modelos de trabajos previos en el 80% de 150 casos de estudio. Además de esto, estos modelos cuentan con varias características importantes tales como distribución, robustez, escalabilidad y dinamismo. Los avances logrados con este trabajo de investigación dan evidencia del potencial de Teoría de Juegos para desarrollar modelos de patrullaje útiles para proteger infraestructuras. ABSTRACT Game theory principle allows to developing stochastic multi-robot patrolling models to protect critical infrastructures. Critical infrastructures protection is a great concern for countries around the world, mainly due to terrorist attacks in the last decade. In this document, the term infrastructures includes airports, nuclear power plants, and many other facilities. The patrolling problem is defined as the activity of traversing a given environment to monitoring any activity or sensing some environmental variables If this activity were performed by a fleet of robots, they would have to visit some places of interest of an environment at irregular intervals of time for security purposes. This problem is solved using multi-robot patrolling models. To date, literature works have been solved this problem applying various mathematical principles.The multi-robot patrolling models developed in those works represent great advances in this field. However, the models that obtain the best results are unfeasible for security applications due to their centralized and predictable nature. This thesis presents five distributed and unpredictable multi-robot patrolling models based on mathematical learning models derived from Game Theory. These multi-robot patrolling models aim at overcoming the disadvantages of previous work. To this end, the multi-robot patrolling problem was formulated using concepts of Graph Theory to represent the environment. Several normal-form games were defined at each vertex of a graph in this formulation. The multi-robot patrolling models developed in this research work have been validated and compared with best ranked multi-robot patrolling models in the literature. Both validation and comparison were preformed by using both a patrolling simulator and real robots. Experimental results show that the multirobot patrolling models developed in this research work improve previous ones in as many as 80% of 150 cases of study. Moreover, these multi-robot patrolling models rely on several features to highlight in security applications such as distribution, robustness, scalability, and dynamism. The achievements obtained in this research work validate the potential of Game Theory to develop patrolling models to protect infrastructures.

Plataformas experimentales para la formación en el área de la electrónica en entornos de e-learning

El campo de estudio relacionado con los laboratorios remotos en el ámbito educativo de las ciencias y la ingeniería está sufriendo una notable expansión ante la necesidad de adaptar los procesos de aprendizaje en dichas áreas a las características y posibilidades de la formación online. Muchos de los recursos educativos basados en esta tecnología, existentes en la actualidad, presentan ciertas limitaciones que impiden alcanzar las competencias que se deben adquirir en los laboratorios de ingeniería. Estas limitaciones están relacionadas con diferentes aspectos de carácter técnico y formativo. A nivel técnico las limitaciones principales se centran en el grado de versatilidad que son capaces de proporcionar comparado con el que se dispone en un laboratorio tradicional y en el modo de interacción del usuario, que provoca que el estudiante no distinga claramente si está realizando acciones sobre sistemas reales o simulaciones. A nivel formativo las limitaciones detectadas son relevantes para poder alcanzar un aprendizaje significativo. En concreto están relacionadas principalmente con un escaso sentimiento de inmersión, una reducida sensación de realismo respecto a las operaciones que se realizan o la limitada posibilidad de realizar actividades de forma colaborativa. La aparición de nuevas tecnologías basadas en entornos inmersivos, unida a los avances producidos relacionados con el aumento de la capacidad gráfica de los ordenadores y del ancho de banda de acceso a Internet, han hecho factible que las limitaciones comentadas anteriormente puedan ser superadas gracias al desarrollo de nuevos recursos de aprendizaje surgidos de la fusión de laboratorios remotos y mundos virtuales 3D. Esta tesis doctoral aborda un trabajo de investigación centrado en proponer un modelo de plataformas experimentales, basado en la fusión de las dos tecnologías mencionadas, que permita generar recursos educativos online que faciliten la adquisición de competencias prácticas similares a las que se consiguen en un laboratorio tradicional vinculado a la enseñanza de la electrónica. El campo de aplicación en el que se ha focalizado el trabajo realizado se ha centrado en el área de la electrónica aunque los resultados de la investigación realizada se podrían adaptar fácilmente a otras disciplinas de la ingeniería. Fruto del trabajo realizado en esta tesis es el desarrollo de la plataforma eLab3D, basada en el modelo de plataformas experimentales propuesto, y la realización de dos estudios empíricos llevados a cabo con estudiantes de grado en ingeniería, muy demandados por la comunidad investigadora. Por un lado, la plataforma eLab3D, que permite llevar a cabo de forma remota actividades prácticas relacionadas con el diseño, montaje y prueba de circuitos electrónicos analógicos, aporta como novedad un dispositivo hardware basado en un sistema de conmutación distribuido. Dicho sistema proporciona un nivel de versatilidad muy elevado, a nivel de configuración de circuitos y selección de puntos de medida, que hace posible la realización de acciones similares a las que se llevan a cabo en los laboratorios presenciales. Por otra parte, los estudios empíricos realizados, que comparaban la eficacia educativa de una metodología de aprendizaje online, basada en el uso de la plataforma eLab3D, con la conseguida siguiendo una metodología clásica en los laboratorios tradicionales, mostraron que no se detectaron diferencias significativas en el grado de adquisición de los resultados de aprendizaje entre los estudiantes que utilizaron la plataforma eLab3D y los que asistieron a los laboratorios presenciales. Por último, hay que destacar dos aspectos relevantes relacionados directamente con esta tesis. En primer lugar, los resultados obtenidos en las experiencias educativas llevadas a cabo junto a valoraciones obtenidas por el profesorado que ha colaborado en las mismas han sido decisivos para que la plataforma eLab3D se haya integrado como recurso complementario de aprendizaje en titulaciones de grado de ingeniería de la Universidad Politécnica de Madrid. En segundo lugar, el modelo de plataformas experimentales que se ha propuesto en esta tesis, analizado por investigadores vinculados a proyectos en el ámbito de la fusión nuclear, ha sido tomado como referencia para generar nuevas herramientas de formación en dicho campo. ABSTRACT The field of study of remote laboratories in sciences and engineering educational disciplines is undergoing a remarkable expansion given the need to adapt the learning processes in the aforementioned areas to the characteristics and possibilities of online education. Several of the current educational resources based on this technology have certain limitations that prevent from reaching the required competencies in engineering laboratories. These limitations are related to different aspects of technical and educational nature. At the technical level, they are centered on the degree of versatility they are able to provide compared to a traditional laboratory and in the way the user interacts with them, which causes the student to not clearly distinguish if actions are being performed over real systems or over simulations. At the educational level, the detected limitations are relevant in order to reach a meaningful learning. In particular, they are mainly related to a scarce immersion feeling, a reduced realism sense regarding the operations performed or the limited possibility to carry out activities in a collaborative way. The appearance of new technologies based on immersive environments, together with the advances in graphical computer capabilities and Internet bandwidth access, have made the previous limitations feasible to be overcome thanks to the development of new learning resources that arise from merging remote laboratories and 3D virtual worlds. This PhD thesis tackles a research work focused on the proposal of an experimental platform model, based on the fusion of both mentioned technologies, which allows for generating online educational resources that facilitate the acquisition of practical competencies similar to those obtained in a traditional electronics laboratory. The application field, in which this work is focused, is electronics, although the research results could be easily adapted to other engineering disciplines. A result of this work is the development of eLab3D platform, based on the experimental platform model proposed, and the realization of two empirical studies with undergraduate students, highly demanded by research community. On one side, eLab3D platform, which allows to accomplish remote practical activities related to the design, assembling and test of analog electronic circuits, provides, as an original contribution, a hardware device based on a distributed switching system. This system offers a high level of versatility, both at the circuit configuration level and at the selection of measurement points, which allows for doing similar actions to those conducted in hands-on laboratories. On the other side, the empirical studies carried out, which compare the educational efficiency of an online learning methodology based on the use of eLab3D platform with that obtained following a classical methodology in traditional laboratories, shows that no significant differences in the acquired degree of learning outcomes among the students that used eLab3D platform and those that attended hands-on laboratories were detected. Finally, it is important to highlight two relevant aspects directly related with this thesis work. First of all, the results obtained in the educational experiences conducted, along with the assessment from the faculty that has collaborated in them, have been decisive to integrate eLab3D platform as a supplementary learning resource in engineering degrees at Universidad Politecnica de Madrid. Secondly, the experimental platform model originally proposed in this thesis, which has been analysed by nuclear fusion researchers, has been taken as a reference to generate new educational tools in that field.