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.

Autonomous classification models in ubiquitous environments

Stream-mining approach is defined as a set of cutting-edge techniques designed to process streams of data in real time, in order to extract knowledge. In the particular case of classification, stream-mining has to adapt its behaviour to the volatile underlying data distributions, what has been called concept drift. Moreover, it is important to note that concept drift may lead to situations where predictive models become invalid and have therefore to be updated to represent the actual concepts that data poses. In this context, there is a specific type of concept drift, known as recurrent concept drift, where the concepts represented by data have already appeared in the past. In those cases the learning process could be saved or at least minimized by applying a previously trained model. This could be extremely useful in ubiquitous environments that are characterized by the existence of resource constrained devices. To deal with the aforementioned scenario, meta-models can be used in the process of enhancing the drift detection mechanisms used by data stream algorithms, by representing and predicting when the change will occur. There are some real-world situations where a concept reappears, as in the case of intrusion detection systems (IDS), where the same incidents or an adaptation of them usually reappear over time. In these environments the early prediction of drift by means of a better knowledge of past models can help to anticipate to the change, thus improving efficiency of the model regarding the training instances needed. By means of using meta-models as a recurrent drift detection mechanism, the ability to share concepts representations among different data mining processes is open. That kind of exchanges could improve the accuracy of the resultant local model as such model may benefit from patterns similar to the local concept that were observed in other scenarios, but not yet locally. This would also improve the efficiency of training instances used during the classification process, as long as the exchange of models would aid in the application of already trained recurrent models, that have been previously seen by any of the collaborative devices. Which it is to say that the scope of recurrence detection and representation is broaden. In fact the detection, representation and exchange of concept drift patterns would be extremely useful for the law enforcement activities fighting against cyber crime. Being the information exchange one of the main pillars of cooperation, national units would benefit from the experience and knowledge gained by third parties. Moreover, in the specific scope of critical infrastructures protection it is crucial to count with information exchange mechanisms, both from a strategical and technical scope. The exchange of concept drift detection schemes in cyber security environments would aid in the process of preventing, detecting and effectively responding to threads in cyber space. Furthermore, as a complement of meta-models, a mechanism to assess the similarity between classification models is also needed when dealing with recurrent concepts. In this context, when reusing a previously trained model a rough comparison between concepts is usually made, applying boolean logic. The introduction of fuzzy logic comparisons between models could lead to a better efficient reuse of previously seen concepts, by applying not just equal models, but also similar ones. This work faces the aforementioned open issues by means of: the MMPRec system, that integrates a meta-model mechanism and a fuzzy similarity function; a collaborative environment to share meta-models between different devices; a recurrent drift generator that allows to test the usefulness of recurrent drift systems, as it is the case of MMPRec. Moreover, this thesis presents an experimental validation of the proposed contributions using synthetic and real datasets.

Proposal of a trust and reputation model to provide recommendation in open quality oriented environments

El auge y penetración de las nuevas tecnologías junto con la llamada Web Social están cambiando la forma en la que accedemos a la medicina. Cada vez más pacientes y profesionales de la medicina están creando y consumiendo recursos digitales de contenido clínico a través de Internet, surgiendo el problema de cómo asegurar la fiabilidad de estos recursos. Además, un nuevo concepto está apareciendo, el de pervasive healthcare o sanidad ubicua, motivado por pacientes que demandan un acceso a los servicios sanitarios en todo momento y en todo lugar. Este nuevo escenario lleva aparejado un problema de confianza en los proveedores de servicios sanitarios. Las plataformas de eLearning se están erigiendo como paradigma de esta nueva Medicina 2.0 ya que proveen un servicio abierto a la vez que controlado/supervisado a recursos digitales, y facilitan las interacciones y consultas entre usuarios, suponiendo una buena aproximación para esta sanidad ubicua. En estos entornos los problemas de fiabilidad y confianza pueden ser solventados mediante la implementación de mecanismos de recomendación de recursos y personas de manera confiable. Tradicionalmente las plataformas de eLearning ya cuentan con mecanismos de recomendación, si bien están más enfocados a la recomendación de recursos. Para la recomendación de usuarios es necesario acudir a mecanismos más elaborados como son los sistemas de confianza y reputación (trust and reputation) En ambos casos, tanto la recomendación de recursos como el cálculo de la reputación de los usuarios se realiza teniendo en cuenta criterios principalmente subjetivos como son las opiniones de los usuarios. En esta tesis doctoral proponemos un nuevo modelo de confianza y reputación que combina evaluaciones automáticas de los recursos digitales en una plataforma de eLearning, con las opiniones vertidas por los usuarios como resultado de las interacciones con otros usuarios o después de consumir un recurso. El enfoque seguido presenta la novedad de la combinación de una parte objetiva con otra subjetiva, persiguiendo mitigar el efecto de posibles castigos subjetivos por parte de usuarios malintencionados, a la vez que enriquecer las evaluaciones objetivas con información adicional acerca de la capacidad pedagógica del recurso o de la persona. El resultado son recomendaciones siempre adaptadas a los requisitos de los usuarios, y de la máxima calidad tanto técnica como educativa. Esta nueva aproximación requiere una nueva herramienta para su validación in-silico, al no existir ninguna aplicación que permita la simulación de plataformas de eLearning con mecanismos de recomendación de recursos y personas, donde además los recursos sean evaluados objetivamente. Este trabajo de investigación propone pues una nueva herramienta, basada en el paradigma de programación orientada a agentes inteligentes para el modelado de comportamientos complejos de usuarios en plataformas de eLearning. Además, la herramienta permite también la simulación del funcionamiento de este tipo de entornos dedicados al intercambio de conocimiento. La evaluación del trabajo propuesto en este documento de tesis se ha realizado de manera iterativa a lo largo de diferentes escenarios en los que se ha situado al sistema frente a una amplia gama de comportamientos de usuarios. Se ha comparado el rendimiento del modelo de confianza y reputación propuesto frente a dos modos de recomendación tradicionales: a) utilizando sólo las opiniones subjetivas de los usuarios para el cálculo de la reputación y por extensión la recomendación; y b) teniendo en cuenta sólo la calidad objetiva del recurso sin hacer ningún cálculo de reputación. Los resultados obtenidos nos permiten afirmar que el modelo desarrollado mejora la recomendación ofrecida por las aproximaciones tradicionales, mostrando una mayor flexibilidad y capacidad de adaptación a diferentes situaciones. Además, el modelo propuesto es capaz de asegurar la recomendación de nuevos usuarios entrando al sistema frente a la nula recomendación para estos usuarios presentada por el modo de recomendación predominante en otras plataformas que basan la recomendación sólo en las opiniones de otros usuarios. Por último, el paradigma de agentes inteligentes ha probado su valía a la hora de modelar plataformas virtuales complejas orientadas al intercambio de conocimiento, especialmente a la hora de modelar y simular el comportamiento de los usuarios de estos entornos. La herramienta de simulación desarrollada ha permitido la evaluación del modelo de confianza y reputación propuesto en esta tesis en una amplia gama de situaciones diferentes. ABSTRACT Internet is changing everything, and this revolution is especially present in traditionally offline spaces such as medicine. In recent years health consumers and health service providers are actively creating and consuming Web contents stimulated by the emergence of the Social Web. Reliability stands out as the main concern when accessing the overwhelming amount of information available online. Along with this new way of accessing the medicine, new concepts like ubiquitous or pervasive healthcare are appearing. Trustworthiness assessment is gaining relevance: open health provisioning systems require mechanisms that help evaluating individuals’ reputation in pursuit of introducing safety to these open and dynamic environments. Technical Enhanced Learning (TEL) -commonly known as eLearning- platforms arise as a paradigm of this Medicine 2.0. They provide an open while controlled/supervised access to resources generated and shared by users, enhancing what it is being called informal learning. TEL systems also facilitate direct interactions amongst users for consultation, resulting in a good approach to ubiquitous healthcare. The aforementioned reliability and trustworthiness problems can be faced by the implementation of mechanisms for the trusted recommendation of both resources and healthcare services providers. Traditionally, eLearning platforms already integrate recommendation mechanisms, although this recommendations are basically focused on providing an ordered classifications of resources. For users’ recommendation, the implementation of trust and reputation systems appears as the best solution. Nevertheless, both approaches base the recommendation on the information from the subjective opinions of other users of the platform regarding the resources or the users. In this PhD work a novel approach is presented for the recommendation of both resources and users within open environments focused on knowledge exchange, as it is the case of TEL systems for ubiquitous healthcare. The proposed solution adds the objective evaluation of the resources to the traditional subjective personal opinions to estimate the reputation of the resources and of the users of the system. This combined measure, along with the reliability of that calculation, is used to provide trusted recommendations. The integration of opinions and evaluations, subjective and objective, allows the model to defend itself against misbehaviours. Furthermore, it also allows ‘colouring’ cold evaluation values by providing additional quality information such as the educational capacities of a digital resource in an eLearning system. As a result, the recommendations are always adapted to user requirements, and of the maximum technical and educational quality. To our knowledge, the combination of objective assessments and subjective opinions to provide recommendation has not been considered before in the literature. Therefore, for the evaluation of the trust and reputation model defined in this PhD thesis, a new simulation tool will be developed following the agent-oriented programming paradigm. The multi-agent approach allows an easy modelling of independent and proactive behaviours for the simulation of users of the system, conforming a faithful resemblance of real users of TEL platforms. For the evaluation of the proposed work, an iterative approach have been followed, testing the performance of the trust and reputation model while providing recommendation in a varied range of scenarios. A comparison with two traditional recommendation mechanisms was performed: a) using only users’ past opinions about a resource and/or other users; and b) not using any reputation assessment and providing the recommendation considering directly the objective quality of the resources. The results show that the developed model improves traditional approaches at providing recommendations in Technology Enhanced Learning (TEL) platforms, presenting a higher adaptability to different situations, whereas traditional approaches only have good results under favourable conditions. Furthermore the promotion period mechanism implemented successfully helps new users in the system to be recommended for direct interactions as well as the resources created by them. On the contrary OnlyOpinions fails completely and new users are never recommended, while traditional approaches only work partially. Finally, the agent-oriented programming (AOP) paradigm has proven its validity at modelling users’ behaviours in TEL platforms. Intelligent software agents’ characteristics matched the main requirements of the simulation tool. The proactivity, sociability and adaptability of the developed agents allowed reproducing real users’ actions and attitudes through the diverse situations defined in the evaluation framework. The result were independent users, accessing to different resources and communicating amongst them to fulfil their needs, basing these interactions on the recommendations provided by the reputation engine.

Self-Learning Embedded System for Object Identification in Intelligent Infrastructure Sensors

The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this paper, a self-learning embedded system for object identification based on adaptive-cooperative dynamic approaches is presented for intelligent sensor’s infrastructures. The proposed system is able to detect and identify moving objects using a dynamic decision tree. Consequently, it combines machine learning algorithms and cooperative strategies in order to make the system more adaptive to changing environments. Therefore, the proposed system may be very useful for many applications like shadow tolls since several types of vehicles may be distinguished, parking optimization systems, improved traffic conditions systems, etc.

Knowledge spirals, situational leadership and informal learning applied on b-learning methodology

The methodology “b-learning” is a new teaching scenario and it requires the creation, adaptation and application of new learning tools searching the assimilation of new collaborative competences. In this context, it is well known the knowledge spirals, the situational leadership and the informal learning. The knowledge spirals is a basic concept of the knowledge procedure and they are based on that the knowledge increases when a cycle of 4 phases is repeated successively.1) The knowledge is created (for instance, to have an idea); 2) The knowledge is decoded into a format to be easily transmitted; 3) The knowledge is modified to be easily comprehensive and it is used; 4) New knowledge is created. This new knowledge improves the previous one (step 1). Each cycle shows a step of a spiral staircase: by going up the staircase, more knowledge is created. On the other hand, the situational leadership is based on that each person has a maturity degree to develop a specific task and this maturity increases with the experience. Therefore, the teacher (leader) has to adapt the teaching style to the student (subordinate) requirements and in this way, the professional and personal development of the student will increase quickly by improving the results and satisfaction. This educational strategy, finally combined with the informal learning, and in particular the zone of proximal development, and using a learning content management system own in our University, gets a successful and well-evaluated learning activity in Master subjects focused on the collaborative activity of preparation and oral exhibition of short and specific topics affine to these subjects. Therefore, the teacher has a relevant and consultant role of the selected topic and his function is to guide and supervise the work, incorporating many times the previous works done in other courses, as a research tutor or more experienced student. Then, in this work, we show the academic results, grade of interactivity developed in these collaborative tasks, statistics and the satisfaction grade shown by our post-graduate students.

An Architecture by means of Anthropology. Beyond learning the tools of social science

Los arquitectos y urbanistas tienen una larga tradición en el aprendizaje de las herramientas de las ciencias sociales, especialmente las que les permiten analizar y describir mejor los entornos y las personas para las que trabajan. Esto ha llevado a los arquitectos a desarrollar mejores herramientas de observación y descripción del ámbito social y no sólo el material. Sin embargo, la mayoría de las veces este acercamiento interdisciplinar ha identificado las ciencias sociales, especialmente la antropología, con la etnografía. Este artículo parte de la crítica a esta identificación hecha por el antropólogo Tim Ingold y se centra en lo que él propone como el método central de la antropología, la observación participante. Para después revisar varias propuestas actuales de científicos sociales que tratan de desarrollar una disciplina no representacional y orientada al futuro, un objetivo más cercano al de la arquitectura. El artículo intenta imaginar cómo esta práctica transdisciplinar podría desarrollarse.

De eruditione comparanda : in humanioribus, vita, studio politico, cognitione auctorum ecclesisticorum, historicorum, politicorum ac militarium, item peregrinatione tractatus /

Mode of access: Internet.

Teaching College Writing in a High School Setting: The Impact of Concurrent Enrollment on Teacher Learning and Practice

Thesis (Ph.D.)--University of Washington, 2016-06

Simulating Nursing: Rhetoric, Materiality, and Disciplinary Learning

Thesis (Ph.D.)--University of Washington, 2016-06

Problem-based learning: a case study in providing e-health education using the Internet

The current trend among many universities is to increase the number of courses available online. However, there are fundamental problems in transferring traditional education courses to virtual formats. Delivering current curricula in an online format does not assist in overcoming the negative effects on student motivation which are inherent in providing information passively. Using problem-based learning (PBL) online is a method by which computers can become a tool to encourage active learning among students. The delivery of curricula via goal-based scenarios allows students to learn at different rates and can successfully shift online learning from memorization to discovery. This paper reports on a Web-based e-health course that has been delivered via PBL for the past 12 months. Thirty distance-learning students undertook postgraduate courses in e-health delivered via the Internet (asynchronous communication). Data collected via online student surveys indicated that the PBL format was both flexible and interesting. PBL has the potential to increase the quality of the educational experience of students in online environments.

Modeling and exploiting behavior patterns in dynamic environments

This paper presents a new approach to improving the effectiveness of autonomous systems that deal with dynamic environments. The basis of the approach is to find repeating patterns of behavior in the dynamic elements of the system, and then to use predictions of the repeating elements to better plan goal directed behavior. It is a layered approach involving classifying, modeling, predicting and exploiting. Classifying involves using observations to place the moving elements into previously defined classes. Modeling involves recording features of the behavior on a coarse grained grid. Exploitation is achieved by integrating predictions from the model into the behavior selection module to improve the utility of the robot's actions. This is in contrast to typical approaches that use the model to select between different strategies or plays. Three methods of adaptation to the dynamic features of the environment are explored. The effectiveness of each method is determined using statistical tests over a number of repeated experiments. The work is presented in the context of predicting opponent behavior in the highly dynamic and multi-agent robot soccer domain (RoboCup)

Virtual training environments to improve train driver's crisis decision making

This paper reports on a current research project in which virtual reality simulators are being investigated as a means of simulating hazardous Rail work conditions in order to allow train drivers to practice decision-making under stress. When working under high stress conditions train drivers need to move beyond procedural responses into a response activated through their own problem-solving and decision-making skills. This study focuses on the use of stress inoculation training which aims to build driver’s confidence in the use of new decision-making skills by being repeatedly required to respond to hazardous driving conditions. In particular, the study makes use of a train cab driving simulator to reproduce potentially stress inducing real-world scenarios. Initial pilot research has been undertaken in which drivers have experienced the training simulation and subsequently completed surveys on the level of immersion experienced. Concurrently drivers have also participated in a velocity perception experiment designed to objectively measure the fidelity of the virtual training environment. Baseline data, against which decision-making skills post training will be measured, is being gathered via cognitive task analysis designed to identify primary decision requirements for specific rail events. While considerable efforts have been invested in improving Virtual Reality technology, little is known about how to best use this technology for training personnel to respond to workplace conditions in the Rail Industry. To enable the best use of simulators for training in the Rail context the project aims to identify those factors within virtual reality that support required learning outcomes and use this information to design training simulations that reliably and safely train staff in required workplace accident response skills.

Precision-recall operating characteristic (P-ROC) curves in imprecise environments

Traditionally, machine learning algorithms have been evaluated in applications where assumptions can be reliably made about class priors and/or misclassification costs. In this paper, we consider the case of imprecise environments, where little may be known about these factors and they may well vary significantly when the system is applied. Specifically, the use of precision-recall analysis is investigated and compared to the more well known performance measures such as error-rate and the receiver operating characteristic (ROC). We argue that while ROC analysis is invariant to variations in class priors, this invariance in fact hides an important factor of the evaluation in imprecise environments. Therefore, we develop a generalised precision-recall analysis methodology in which variation due to prior class probabilities is incorporated into a multi-way analysis of variance (ANOVA). The increased sensitivity and reliability of this approach is demonstrated in a remote sensing application.

Building learning communities to support beginning teachers use of technology

This paper reports on the early stages of a three year study that is investigating the impact of a technology-enriched teacher education program on beginning teachers' integration of computers, graphics calculators, and the internet into secondary school mathematics classrooms. Whereas much of the existing research on the role of technology in mathematics learning has been concerned with effects on curriculum content or student learning, less attention has been given to the relationship between technology use and issues of pedagogy, in particular the impact on teachers' professional learning in the context of specific classroom and school environments. Our research applies sociocultural theories of learning to consider how beginning teachers are initiated into a collaborative professional community featuring both web-based and face to face interaction, and how participation in such a community shapes their pedagogical beliefs and practices. The aim of this paper is to analyse processes through which the emerging community was established and sustained during the first year of the study. We examine features of this community in terms of identity formation, shifts in values and beliefs, and interaction patterns revealed in bulletin board discussion between students and lecturers.

A IMPORTÂNCIA DAS TICS E DA EDUCAÇÃO COMO PROCESSO COMUNICACIONAL DIALÓGICO NO ENSINO SUPERIOR: Um Estudo da Universidade Estadual de Mato Grosso do Sul

Esta tese teve por objetivo saber como o corpo docente da Universidade Estadual de Mato Grosso do Sul (UEMS) percebe, entende e reage ante a incorporação e utilização das Tecnologias de Informação e Comunicação (TICs) nos cursos de graduação dessa Instituição, considerando os novos processos comunicacionais dialógicos que elas podem proporcionar na sociedade atual. Metodologicamente, a tese é composta por pesquisa bibliográfica, buscando fundamentar as áreas da Educação e Comunicação, assim como a Educomunicação; pesquisa documental para contextualização do lócus da pesquisa e de uma pesquisa exploratória a partir da aplicação de um questionário online a 165 docentes da UEMS, que responderam voluntariamente. Verificou-se que os professores utilizam as TICs cotidianamente nas atividades pessoais e, em menor escala, nos ambientes profissionais. Os desafios estão em se formar melhor esse docente e oferecer capacitação continuada para que utilizem de forma mais eficaz as TICs nas salas de aula. Destaca-se ainda que os avanços em tecnologia e os novos ecossistemas comunicacionais construíram novas e outras realidades, tornando a aprendizagem um fator não linear, exigindo-se revisão nos projetos pedagógicos na educação superior para que estes viabilizem diálogos propositivos entre a comunicação e a educação. A infraestrutura institucional para as TICs é outro entrave apontado, tanto na aquisição como na manutenção desses aparatos tecnológicos pela Universidade. Ao final, propõe-se realizar estudos e pesquisas que possam discutir alterações nos regimes contratuais de trabalho dos docentes, uma vez que, para atuar com as TICs de maneira apropriada, exige-se mais tempo e dedicação do docente.