50 resultados para Active learning methods


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El artículo plantea un análisis empírico sobre las posibilidades de aplicación de las nuevas tecnologías de la información al proceso de reclutamiento de personal. Las competencias sociales y cognitivas que requieren las nuevas formas de organización de la producción plantean nuevos métodos de aprendizaje y la actualización del desarrollo de capacidades y comportamientos. Se trata de renovar y completar las competencias profesionales en un proceso permanente, que implica la adopción de una política de reclutamiento orientada por la consideración del conocimiento como elemento diferenciador de competitividad empresarial y de creación de riqueza.

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Several methods and approaches for measuring parameters to determine fecal sources of pollution in water have been developed in recent years. No single microbial or chemical parameter has proved sufficient to determine the source of fecal pollution. Combinations of parameters involving at least one discriminating indicator and one universal fecal indicator offer the most promising solutions for qualitative and quantitative analyses. The universal (nondiscriminating) fecal indicator provides quantitative information regarding the fecal load. The discriminating indicator contributes to the identification of a specific source. The relative values of the parameters derived from both kinds of indicators could provide information regarding the contribution to the total fecal load from each origin. It is also essential that both parameters characteristically persist in the environment for similar periods. Numerical analysis, such as inductive learning methods, could be used to select the most suitable and the lowest number of parameters to develop predictive models. These combinations of parameters provide information on factors affecting the models, such as dilution, specific types of animal source, persistence of microbial tracers, and complex mixtures from different sources. The combined use of the enumeration of somatic coliphages and the enumeration of Bacteroides-phages using different host specific strains (one from humans and another from pigs), both selected using the suggested approach, provides a feasible model for quantitative and qualitative analyses of fecal source identification.

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This paper analyzes an innovative experience of formative assessment aimed at improving the teaching of Statistics, which could be easily extrapolated to other studies. We detail the implementation of the double correction, consisting of correcting students' work twice. With the first correction, carried out by classmates according to a rubric developed by the academic, possible errors or deficiencies are discovered, and students are provided with a feedback that allows them to correct and improve their work before being graded by the teacher; whereas in the second correction of the work, once upgraded, the professor evaluates and grades the work. As a result, there is a significant improvement in the quality of students" works, and an active learning from their own mistakes. Both contents and competencies are reinforced by the experience.

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En el presente documento proponemos un ejercicio tutorial y una práctica docente que permita al estudiante a asimilar y entender mejor el concepto de exceso de gravamen o pérdida irrecuperable de eficiencia asociada a la imposición. Para ello planteamos, en primer lugar, un modelo de elección individual entre ocio y trabajo/consumo. Centrándonos en el individuo representativo, estudiamos su elección de horas de trabajo en ausencia de impuestos. A continuación, introducimos un impuesto proporcional sobre la renta del trabajo y, alternativamente, un impuesto de suma fija capaz de generar una recaudación igual. Verificamos que el impuesto proporcional siempre deja al individuo con un nivel de bienestar inferior respecto al escenario del impuesto de suma fija, es decir, que el impuesto proporcional genera una pérdida irrecuperable de eficiencia. Aunque la resolución manual del problema es factible, proponemos utilizar la herramienta Solver de Excel. Esto nos permite jugar de manera más ágil con los valores de los diferentes parámetros y verificar que hay pérdida de eficiencia independientemente de que el individuo decida trabajar más o menos horas en respuesta a la introducción del impuesto sobre la renta del trabajo

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Són molts els estudis que avui en dia incideixen en la necessitat d’oferir un suport metodològic i psicològic als aprenents que treballen de manera autònoma. L’objectiu d’aquest suport és ajudar-los a desenvolupar les destreses que necessiten per dirigir el seu aprenentatge així com una actitud positiva i una major conscienciació envers aquest aprenentatge. En definitiva, aquests dos tipus de preparació es consideren essencials per ajudar els aprenents a esdevenir més autònoms i més eficients en el seu propi aprenentatge. Malgrat això, si bé és freqüent trobar estudis que exemplifiquen aplicacions del suport metodològic dins els seus programes, principalment en la formació d’estratègies o ajudant els aprenents a desenvolupar un pla de treball, aquest no és el cas quan es tracta de la seva preparació psicològica. Amb rares excepcions, trobem estudis que documentin com s’incideix en les actituds i en les creences dels aprenents, també coneguts com a coneixement metacognitiu (CM), en programes que fomenten l’autonomia en l’aprenentatge. Els objectius d’aquest treball son dos: a) oferir una revisió d’estudis que han utilitzat diferents mitjans per incidir en el CM dels aprenents i b) descriure les febleses i avantatges dels procediments i instruments que utilitzen, tal com han estat valorats en estudis de recerca, ja que ens permetrà establir criteris objectius sobre com i quan utilitzar-los en programes que fomentin l’aprenentatge autodirigit.

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Autonomous underwater vehicles (AUV) represent a challenging control problem with complex, noisy, dynamics. Nowadays, not only the continuous scientific advances in underwater robotics but the increasing number of subsea missions and its complexity ask for an automatization of submarine processes. This paper proposes a high-level control system for solving the action selection problem of an autonomous robot. The system is characterized by the use of reinforcement learning direct policy search methods (RLDPS) for learning the internal state/action mapping of some behaviors. We demonstrate its feasibility with simulated experiments using the model of our underwater robot URIS in a target following task

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The creation of the European Higher Education Area has meant a number of significant changes to the educational structures of the university community. In particular, the new system of European credits has generated the need for innovation in the design of curricula and teaching methods. In this paper, we propose debating as a classroom tool that can help fulfill these objectives by promoting an active student role in learning. To demonstrate the potential of this tool, a classroom experiment was conducted in a bachelor’s degree course in Industrial Economics -Regulation and Competition-, involving a case study in competition policy and incorporating the techniques of a conventional debate -presentation of standpoints, turns, right to reply and summing up-. The experiment yielded gains in student attainment and positive assessments of the subject. In conclusion, the incorporation of debating activities helps students to acquire the skills, be they general or specific, required to graduate successfully in Economics.

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El projecte ha estat realitzat en la Unitat de Farmàcia Clínica i Farmacoteràpia de la Facultat de Farmàcia de la Universitat de Barcelona i ha estat a desenvolupar en dos anys. La finalitat del projecte ha estat oferir a l'alumne un material docent en suport digital, adaptat a una metodologia més creativa i de treball en grup, orientat a la millora de la seva formació, autonomia i rendiment acadèmic, en els aspectes relacionats amb la Farmàcia Clínica i Farmacoteràpia i l'Atenció Farmacèutica, i que consistirà en una primera aproximació a les directrius europees. Aquest material docent en suport digital són WebQuest (WQ) estructurades per temes i via Internet, la qual cosa possibilita un sistema dinàmic de fàcil retroalimentació i en constant actualització. Mitjançant la utilització d'aquest material docent es treballen aspectes com l'ús de metodologies docents centrades en l'alumne, autoaprenentatge a distància, aprenentatge seqüencial, treball en grup, participació activa i responsabilitat de l'alumne en el procés d'ensenyament aprenentatge i l'aproximació del mateix a la realitat professional entre altres, i tot això encaminat a promoure l'adaptació dels plans docents a l'Espai Europeu d'Educació Superior (EEES). En aquest sentit podem indicar que s'han elaborat cinc WQs, els títols del qual són Sistemes Personalitzats de Dosificació, Compliment terapèutic: el gran repte actual: informació al pacient, Compliment terapèutic: el gran repte actual: informació al professional sanitari, Dispensació activa en Diabetis mellitus tipus 2 i Dispensació activa en Hipertensión arterial. Cadascuna de les WQs elaborades consta dels apartats Introducció, Tasca, Procés, Recursos, Avaluació, Conclusió, Guia Didàctica i Crèdits. Les WQs estan allotjades en la pàgina web de la Unitat de Farmàcia Clínica i Farmacoteràpia, i a elles s'accedeix a través de l'adreça web http://www.ub.és/farcli/wp0.htm

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This paper proposes a high-level reinforcement learning (RL) control system for solving the action selection problem of an autonomous robot. Although the dominant approach, when using RL, has been to apply value function based algorithms, the system here detailed is characterized by the use of direct policy search methods. Rather than approximating a value function, these methodologies approximate a policy using an independent function approximator with its own parameters, trying to maximize the future expected reward. The policy based algorithm presented in this paper is used for learning the internal state/action mapping of a behavior. In this preliminary work, we demonstrate its feasibility with simulated experiments using the underwater robot GARBI in a target reaching task

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A study of how the machine learning technique, known as gentleboost, could improve different digital watermarking methods such as LSB, DWT, DCT2 and Histogram shifting.

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One of the most relevant difficulties faced by first-year undergraduate students is to settle into the educational environment of universities. This paper presents a case study that proposes a computer-assisted collaborative experience designed to help students in their transition from high school to university. This is done by facilitating their first contact with the campus and its services, the university community, methodologies and activities. The experience combines individual and collaborative activities, conducted in and out of the classroom, structured following the Jigsaw Collaborative Learning Flow Pattern. A specific environment including portable technologies with network and computer applications has been developed to support and facilitate the orchestration of a flow of learning activities into a single integrated learning setting. The result is a Computer-Supported Collaborative Blended Learning scenario, which has been evaluated with first-year university students of the degrees of Software and Audiovisual Engineering within the subject Introduction to Information and Communications Technologies. The findings reveal that the scenario improves significantly students’ interest in their studies and their understanding about the campus and services provided. The environment is also an innovative approach to successfully support the heterogeneous activities conducted by both teachers and students during the scenario. This paper introduces the goals and context of the case study, describes how the technology was employed to conduct the learning scenario, the evaluation methods and the main results of the experience.

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Purpose: To evaluate the suitability of an improved version of an automatic segmentation method based on geodesic active regions (GAR) for segmenting cerebral vasculature with aneurysms from 3D X-ray reconstruc-tion angiography (3DRA) and time of °ight magnetic resonance angiography (TOF-MRA) images available in the clinical routine.Methods: Three aspects of the GAR method have been improved: execution time, robustness to variability in imaging protocols and robustness to variability in image spatial resolutions. The improved GAR was retrospectively evaluated on images from patients containing intracranial aneurysms in the area of the Circle of Willis and imaged with two modalities: 3DRA and TOF-MRA. Images were obtained from two clinical centers, each using di®erent imaging equipment. Evaluation included qualitative and quantitative analyses ofthe segmentation results on 20 images from 10 patients. The gold standard was built from 660 cross-sections (33 per image) of vessels and aneurysms, manually measured by interventional neuroradiologists. GAR has also been compared to an interactive segmentation method: iso-intensity surface extraction (ISE). In addition, since patients had been imaged with the two modalities, we performed an inter-modality agreement analysis with respect to both the manual measurements and each of the two segmentation methods. Results: Both GAR and ISE di®ered from the gold standard within acceptable limits compared to the imaging resolution. GAR (ISE, respectively) had an average accuracy of 0.20 (0.24) mm for 3DRA and 0.27 (0.30) mm for TOF-MRA, and had a repeatability of 0.05 (0.20) mm. Compared to ISE, GAR had a lower qualitative error in the vessel region and a lower quantitative error in the aneurysm region. The repeatabilityof GAR was superior to manual measurements and ISE. The inter-modality agreement was similar between GAR and the manual measurements. Conclusions: The improved GAR method outperformed ISE qualitatively as well as quantitatively and is suitable for segmenting 3DRA and TOF-MRA images from clinical routine.

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Two important challenges that teachers are currently facing are the sharing and the collaborative authoring of their learning design solutions, such as didactical units and learning materials. On the one hand, there are tools that can be used for the creation of design solutions and only some of them facilitate the co-edition. However, they do not incorporate mechanisms that support the sharing of the designs between teachers. On the other hand, there are tools that serve as repositories of educational resources but they do not enable the authoring of the designs. In this paper we present LdShake, a web tool whose novelty is focused on the combined support for the social sharing and co-edition of learning design solutions within communities of teachers. Teachers can create and share learning designs with other teachers using different access rights so that they can read, comment or co-edit the designs. Therefore, each design solution is associated to a group of teachers able to work on its definition, and another group that can only see the design. The tool is generic in that it allows the creation of designs based on any pedagogical approach. However, it can be particularized in instances providing pre-formatted designs structured according to a specific didactic method (such as Problem-Based Learning, PBL). A particularized LdShake instance has been used in the context of Human Biology studies where teams of teachers are required to work together in the design of PBL solutions. A controlled user study, that compares the use of a generic LdShake and a Moodle system, configured to enable the creation and sharing of designs, has been also carried out. The combined results of the real and controlled studies show that the social structure, and the commenting, co-edition and publishing features of LdShake provide a useful, effective and usable approach for facilitating teachers' teamwork.

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Minimax lower bounds for concept learning state, for example, thatfor each sample size $n$ and learning rule $g_n$, there exists a distributionof the observation $X$ and a concept $C$ to be learnt such that the expectederror of $g_n$ is at least a constant times $V/n$, where $V$ is the VC dimensionof the concept class. However, these bounds do not tell anything about therate of decrease of the error for a {\sl fixed} distribution--concept pair.\\In this paper we investigate minimax lower bounds in such a--stronger--sense.We show that for several natural $k$--parameter concept classes, includingthe class of linear halfspaces, the class of balls, the class of polyhedrawith a certain number of faces, and a class of neural networks, for any{\sl sequence} of learning rules $\{g_n\}$, there exists a fixed distributionof $X$ and a fixed concept $C$ such that the expected error is larger thana constant times $k/n$ for {\sl infinitely many n}. We also obtain suchstrong minimax lower bounds for the tail distribution of the probabilityof error, which extend the corresponding minimax lower bounds.

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In this work I study the stability of the dynamics generated by adaptivelearning processes in intertemporal economies with lagged variables. Iprove that determinacy of the steady state is a necessary condition for the convergence of the learning dynamics and I show that the reciprocal is not true characterizing the economies where convergence holds. In the case of existence of cycles I show that there is not, in general, a relationship between determinacy and convergence of the learning process to the cycle. I also analyze the expectational stability of these equilibria.