Applying knowledge engineering methods to didactic knowledge: first steps towards an ultimate goal

Generally, learning systems suffer from a lack of an explicit and adaptable didactic design. Since E-Learning systems are digital by their very nature, their introduction rises the issue of modeling the didactic design in a way that implies the chance to apply Knowledge Engineering Techniques (like Machine Learning and Data Mining). A modeling approach called storyboarding, is outlined here. Storyboarding is setting the stage to apply Knowledge Engineering Technologies to verify and validate the didactics behind a learning process. Moreover, didactics can be refined according to revealed weaknesses and proven excellence and successful didactic patterns can be inductively inferred by analyzing the particular knowledge processing and its alleged contribution to learning success

Information technology for learning: a European students' perspectiv

This study was mainly focused on European university students, in particular on their thinking about IT for learning. Participators came from different European countries and took part in a summer school this year. A total of 21 international students participated in this summer school program. They came from different European countries. The data collection includes a questionnaire survey and interview data. The data were analyzed and common opinions have been extracted. Finally, the authors of the present paper provide six conclusions and refer to university education in European countries to implement an IT integrated instruction. Researchers hope to promote the instructional quality by a well-performed way of IT integration into instruction in high education

Personalized curriculum composition by learner profile driven data mining

The paper is focused on modeling, processing, evaluating and refining processes with humans involved like (not only, but also e-) learning. A formerly developed concept called storyboarding has been applied at Tokyo Denki University (TDU) to model the various ways to study at this university. Along with this storyboard, we developed a Data Mining Technology to estimate success chances of curricula. Here, we introduce a learner profiling concept that represents the students’ individual properties, talents and preferences personalized data mining

Personalized curriculum composition by learner profile driven data mining

The paper is focused on modeling, processing, evaluating and refining processes with humans involved like (not only, but also e-) learning. A formerly developed concept called storyboarding has been applied at Tokyo Denki University (TDU) to model the various ways to study at this university. Along with this storyboard, we developed a Data Mining Technology to estimate success chances of curricula. Here, we introduce a learner profiling concept that represents the students’ individual properties, talents and preferences personalized data mining