805 resultados para LEARNING OBJECTS REPOSITORIES - MODELS


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It is widely accepted that solving programming exercises is fundamental to learn how to program. Nevertheless, solving exercises is only effective if students receive an assessment on their work. An exercise solved wrong will consolidate a false belief, and without feedback many students will not be able to overcome their difficulties. However, creating, managing and accessing a large number of exercises, covering all the points in the curricula of a programming course, in classes with large number of students, can be a daunting task without the appropriated tools working in unison. This involves a diversity of tools, from the environments where programs are coded, to automatic program evaluators providing feedback on the attempts of students, passing through the authoring, management and sequencing of programming exercises as learning objects. We believe that the integration of these tools will have a great impact in acquiring programming skills. Our research objective is to manage and coordinate a network of eLearning systems where students can solve computer programming exercises. Networks of this kind include systems such as learning management systems (LMS), evaluation engines (EE), learning objects repositories (LOR) and exercise resolution environments (ERE). Our strategy to achieve the interoperability among these tools is based on a shared definition of programming exercise as a Learning Object (LO).

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The LMS plays an indisputable role in the majority of the eLearning environments. This eLearning system type is often used for presenting, solving and grading simple exercises. However, exercises from complex domains, such as computer programming, require heterogeneous systems such as evaluation engines, learning objects repositories and exercise resolution environments. The coordination of networks of such disparate systems is rather complex. This work presents a standard approach for the coordination of a network of eLearning systems supporting the resolution of exercises. The proposed approach use a pivot component embedded in the LMS with two roles: provide an exercise resolution environment and coordinate the communication between the LMS and other systems exposing their functions as web services. The integration of the pivot component with the LMS relies on the Learning Tools Interoperability. The validation of this approach is made through the integration of the component with LMSs from two vendors.

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The computational power is increasing day by day. Despite that, there are some tasks that are still difficult or even impossible for a computer to perform. For example, while identifying a facial expression is easy for a human, for a computer it is an area in development. To tackle this and similar issues, crowdsourcing has grown as a way to use human computation in a large scale. Crowdsourcing is a novel approach to collect labels in a fast and cheap manner, by sourcing the labels from the crowds. However, these labels lack reliability since annotators are not guaranteed to have any expertise in the field. This fact has led to a new research area where we must create or adapt annotation models to handle these weaklylabeled data. Current techniques explore the annotators’ expertise and the task difficulty as variables that influences labels’ correction. Other specific aspects are also considered by noisy-labels analysis techniques. The main contribution of this thesis is the process to collect reliable crowdsourcing labels for a facial expressions dataset. This process consists in two steps: first, we design our crowdsourcing tasks to collect annotators labels; next, we infer the true label from the collected labels by applying state-of-art crowdsourcing algorithms. At the same time, a facial expression dataset is created, containing 40.000 images and respective labels. At the end, we publish the resulting dataset.

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For many types of learners one can compute the statistically 'optimal' way to select data. We review how these techniques have been used with feedforward neural networks. We then show how the same principles may be used to select data for two alternative, statistically-based learning architectures: mixtures of Gaussians and locally weighted regression. While the techniques for neural networks are expensive and approximate, the techniques for mixtures of Gaussians and locally weighted regression are both efficient and accurate.

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Completed, available and free to use Learning Objects listed by subject area

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The Centre for Inter-Professional e-Learning (CIPeL) at Coventry University provides a number of useful reusable learning objects.

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These are the Reusable Learning Objects (RLOs) that Intute have evaluated and added to their nursing and midwifery section. If you search for 'rlo' you'll get a list of over 60 RLOs, they are mostly related to A&P but some of them are about research skills and referencing...

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An introduction/overview to the whole issue of learning objects, interoperability and IMS specifications in Learning Technology

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Monogr??fico con el t??tulo: 'Estado actual de los sistemas e-learning'. Resumen basado en el de la publicaci??n

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El artículo está incluido en un número monográfico especial con los trabajos del I Simposio Pluridisciplinar sobre Diseño, Evaluación y Descripción de Contenidos Educativos Reutilizables (Guadalajara, Octubre 2004).Resumen basado en el de la publicación

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El artículo está incluido en un número monográfico especial con los trabajos del I Simposio Pluridisciplinar sobre Diseño, Evaluación y Descripción de Contenidos Educativos Reutilizables (Guadalajara, Octubre 2004).Resumen basado en el de la publicación

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El artículo está incluido en un número monográfico especial con los trabajos del I Simposio Pluridisciplinar sobre Diseño, Evaluación y Descripción de Contenidos Educativos Reutilizables (Guadalajara, Octubre 2004).Resumen basado en el de la publicación

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Pair Programming is a technique from the software development method eXtreme Programming (XP) whereby two programmers work closely together to develop a piece of software. A similar approach has been used to develop a set of Assessment Learning Objects (ALO). Three members of academic staff have developed a set of ALOs for a total of three different modules (two with overlapping content). In each case a pair programming approach was taken to the development of the ALO. In addition to demonstrating the efficiency of this approach in terms of staff time spent developing the ALOs, a statistical analysis of the outcomes for students who made use of the ALOs is used to demonstrate the effectiveness of the ALOs produced via this method.