As a decision support tool, a hybrid modelling can offer the ability to better understand the dynamics of a particular ecosystem, as well as to explore possible futures based on different online learning scenarios. From this perspective, the present paper proposes/discusses a hybrid approach that may serve as a means to synthesize/represent knowledge obtained from the data, in order to explore ...

In recent years there has been a flurry of works on learning probabilistic belief networks. Current state of the art methods have been shown to be successful for two learning scenarios: learning both network structure and parameters from complete data, and learning parameters for a fixed network from incomplete data—that is, in the presence of missing values or hidden variables. However, no met...

Pervasive learning will become increasingly important in technology-enhanced learning (TEL). In this context, development efforts focus on features such as context-awareness, adaptation, services retrieval and orchestration mechanisms. This paper proposes a process to assist the development of such systems, from conception through to execution. This paper focuses mainly on pervasive TEL systems...

There has been considerable political pressure, and much hope invested in, the use of Communication and Information Technologies to provide wider access to education, while improving quality and reducing costs. Unfortunately, many of the responses to the challenge of these aspirations have consisted of simple Web technology-driven products which have failed to progress effective learning. We ou...

In this paper, the recognition of temporal scenarios is expressed by the mean of a proximity between a scenario which represents a possible system’s behavior and a session which describes the observed behaviour. This recognition is qualified with a proximity index which allows to classify on-line or out-line the scenarios candidates for an evolution’s explanation. This approach, when used in a ...

As we enter into the big data age and an avalanche of images have become readily available, recognition systems face the need to move from close, lab settings where the number of classes and training data are fixed, to dynamic scenarios where the number of categories to be recognized grows continuously over time, as well as new data providing useful information to update the system. Recent atte...

Our ideas move essentially from two main thoughtfulness: from one side there are the lacks characterising the existing software platforms for supporting traditional and distance learning processes and, from the other side there is the continuous achievement of GRID technologies as a solution for truly implementation of e-science infrastructure. The main drawbacks of current distance learning so...

1. Introduction Both practitioners and researchers have increasingly emphasized the importance of competence development, training and education in contemporary organizations. Changing organizational demands have made work dependent on distribution and mobility, this has altered the possibilities for workers daily dialogue with colleagues. The context for this research is organizations of distr...

The term “Cloud Computing” does not primarily specify new types of core technologies but rather addresses features to do with integration, inter-operability and accessibility. Although not new, virtualization and automation are core features that characterize Cloud Computing. In this paper, we intend to explore the possibility of integrating cloud services with educational scenarios without re-...

 This paper illustrates the use of PALO, a general-purpose Educative Modeling Language (EML), to embed constructivist features in distance learning scenarios. Educative Modeling Languages allow describing learning content using an XML-based representation independent from the final delivery format, thus providing a higher level of abstraction in the authoring process. We have defined a subset ...