<p>E-learning has revolutionized education all over the world, defining a different and promising aspect of education, reinforcing the perception that it builds inclusive knowledge societies. Higher Education Institutes (HEI) adopted this innovative education model in order to provide to their students the option of distance education. Since the most important component of e-learning is e-content, its development is a popular research topic in the educational community. Due to the fact that e-content reusability can be increased by using an approach based on Learning Objects (LOs), many methodologies of e-content design introduce guidelines for creating LOs. LOs can make the process of e-learning effective and can offer high quality e-Learning experience to students. The Hellenic Open University (HOU) is introducing LOs in the educational process, using teaching subject domain ontologies to describe them. Ontologies provide a simple way of identifying the knowledge domains covered by LOs, while facilitating its reusability. The preliminary step to create these domain ontologies is the design of the Concept Map (CM), that is a diagram for representing knowledge in a structured form. Concept Maps foster meaningful learning and serve both as a knowledge base for building domain ontologies and as a frame for composing more detailed LOs. Concept Map Mining (CMM), a process for automatic or semi-automatic creation of Concept Maps from documents, is used to facilitate the construction and sharing of Concept Maps. In this paper, we propose a methodological framework and a semi-automatic method for Concept Map creation from unstructured text, which can even handle the morphologically rich Greek language skillfully. The proposed approach combines language processing tools and the knowledge of domain experts. In addition, a case study based on a HOU teaching domain is presented, illustrating the process of Concept Map Mining and showing encouraging results.</p>

Educational content plays a significant role in the process of delivering knowledge, that’s why it needs to be designed carefully, following designated principles. Learning Objects (LOs) constitute a novel approach in the educational content’s organization, bearing features that if effectively used could lead to enhanced e-learning services. What is missing from literature, though, is a common agreement about the LO’s attributes and structure. For this reason, we initially try to specify the main characteristics of a LO and determine its functionality, especially in the context of distance education. Having realized its fundamental role in the instructional design process, we make explicit its correlation with educational objectives and other aspects of learning. Finally, in an attempt to capture all LO’s characteristics and make them utilizable by e-learning applications, we propose a metadata schema, reflecting all features of a LO, as described in this work.

The importance of e-learning and e-commerce applications has significantly increased in the past few years. Seeking better design and implementation principles is a research goal with, potentially, a significant impact. One of the commonalities of both applications is user-centricity. Understanding user behavior is critical especially in user-centered applications such as e-commerce and e-learning. In this work we discuss some of the fundamental similarities and differences in e-commerce and formal e-learning adaptation and discuss lessons that could be learned. We argue that current user pattern mining techniques should take into account behavioral and educational theories for distance learning in order to be efficient.