In this work we describe a proposal for managing educational resources produced by three high level educational institutions. Our approach takes into account not only the meta informations inside educational resources but also the meta informations extracted from linked open data in the web associated to massive open online courses (MOOCs). We visualize educational resources as a semantic corporate memory where semantic technologies and Linked Open Data approaches can improve the information integration. Textmining takes an important part in our approach for generating links between concepts and detecting some important associations.
This paper presents an analysis of different models used to assess the quality of formative actions, considering classroom learning and distance education courses. Taking as starting point one of the analyzed models, the paper sets out the necessity of developing a new model that could measure the quality of a blended formation process, by selecting the applicable indicators and proposing some new. The model is composed of seven different categories, which include a sum of thirty five indicators. They will be used to represent courses quality level in Kiviat's diagrams. This model is currently being put into practice in a real university environment.
Recommendation systems have been growing in number for the last fifteen years. To evolve and adapt to the demands of the actual society, many paradigms emerged giving birth to even more paradigms and hybrid approaches. Mobile devices have also been under an incredible growth rate in every business area, and there are already lots of mobile based systems to assist tourists. This explosive growth gave birth to different mobile applications, each having their own advantages and disadvantages. Since recommendation and mobile systems might as well be integrated, this work intends to present the current state of the art in tourism mobile and recommendation systems, as well as to state their advantages and disadvantages.
