Abstract. In this paper we present an Adaptive Educational Hypermedia prototype, named INSPIRE. The approach employed in INSPIRE emphasizes the fact that learners perceive and process information in very different ways, and integrates ideas from theories of instructional design and learning styles. Our aim is to make a shift towards a more “learning-focused ” paradigm of instruction by providing a sequence of authentic and meaningful tasks that matches learners ’ preferred way of studying. INSPIRE, throughout its interaction with the learner, dynamically generates learner-tailored lessons that gradually lead to the accomplishment of learner’s learning goals. It supports several levels of adaptation: from full system-control to full learner-control, and offers learners the option to decide on the level of adaptation of the system by intervening in different stages of the lesson generation process and formulating the lesson contents and presentation. Both the adaptive and adaptable behavior of INSPIRE are guided by the learner model which provides information about the learner, such as knowledge level on the domain concepts and learning style. The learner model is exploited in multiple ways: curriculum sequencing, adaptive navigation support, adaptive presentation, and supports system’s adaptable behavior. An empirical study has been performed to evaluate the adaptation framework and assess learners ’ attitudes towards the proposed instructional design.

We have developed a new stochastic image rendering method for the compression, description and segmentation of images. This paintbrush-like image transformation is based on a random searching to insert brush-strokes into a generated image at decreasing scale of brush-sizes, without predefined models or interaction. We introduced a sequential multiscale image decomposition method, based on simulated rectangular-shaped paintbrush strokes. The resulting images look like good-quality paintings with well-defined contours, at an acceptable distortion compared to the original image. The image can be described with the parameters of the consecutive paintbrush strokes, resulting in a parameter-series that can be used for compression. The painting process can be applied for image representation, segmentation and contour detection. Our original method is based on stochastic exhaustive searching which takes a long time of convergence. In this paper we propose a modified algorithm of speed up of about 2x where the faster convergence is supported by a dynamic Metropolis Hastings rule. 1

Adaptive Learning Environments (ALE) in Higher Education aim to provide academics with flexible learning tools that fulfil the needs of a heterogeneous learning community. ALE can be used to enhance traditional teaching as well as web-based instruction and can promote the implementation of alternative, open modes of learning and instruction. The utilisation of ALE in the educational process requires academics to adopt new didactical approaches, exploit innovative tools and subsequently possess the necessary competences at the technology and education level. The Education and Language Technology Group 1 at the Department of Informatics and Telecommunications, University of Athens, has developed a number of learning environments/tools with adaptive capabilities aiming to contribute and strengthen a variety of instructional and learning processes. In this paper we elaborate on eCompetence skills for using ALE in higher education and specifically for using the learning environments/tools we have developed, which focus on Adaptive Educational Hypermedia Systems,

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Abstract: Decision Support Systems are proliferating rapidly in many areas of human endeavour including clinical medicine and psychology. While these are typically based on rulebased systems, decision trees, or Artificial Neural Networks, this paper argues that Bayes’ Theorem can be applied fruitfully to support expert decisions both in dynamically changing situations requiring the system progressively to adapt, and when this is not the case. One example of each of these two types is given. One provides diagnostic support for human decision makers; the other, an e-health mental intervention system provides decision rules enabling it to respond and provide the most appropriate training modules to input from clients with changing needs. The contributions of psychological research underlying both systems is summarized.

Managers in a global business environment work with people who have different values, behavioral norms, and ways of perceiving reality. Team members bring their different national and professional backgrounds to the table, and suppliers and clients come from different corporate cultures. Consequently, intercultural competencies have become important for a wider range and larger number of people in business than ever before. In order to prepare students to become effective in the multiple cultural contexts they will face, business educators must clarify what constitutes intercultural competencies and how to develop them within the context of a business school classroom. In this paper we present the idea of learning to “negotiate reality ” as a core intercultural competence and we describe an approach we designed and used for developing this competence at an international business school in Europe. Zusammenfassung

Abstract — This paper discusses the design of adaptive e-learning system based on student’s learning styles. The system adaptivity is based on two learning style models, which are VAK and Felder. The VAK learning styles include visual, auditory, and kinesthetic, while the Felder learning styles include global and sequential. This system will combine these learning styles to alter its course presentation to each student. The system extends the advantages of conventional e-learning which are classroom and platform independence.