%0 Conference Proceedings %T Supporting Technology-enhanced Learning through Semi-automatic Detection and Management of Skill and Competence Structures %+ Cognitive Science Section %+ Institute for Information Systems and New Media %A Nussbaumer, Alexander %A Gütl, Christian %A Albert, Dietrich %Z The work presented in this paper is partially supported by European Community under the Information Society Technologies (IST) program of the 6th FP for RTD - project iClass contract IST-507922. The authors are solely responsible for the content of this paper. It does not represent the opinion of the European Community, and the European Community is not responsible for any use that might be made of data appearing therein. %< avec comité de lecture %( Proceedings of the International Conference of "Interactive computer aided learning" ICL2007 : EPortofolio and Quality in e-Learning %B Conference ICL2007, September 26 -28, 2007 %C Villach, Austria %Y Michael E. Auer %I Kassel University Press %P 9 pages %8 2007 %D 2007 %K technology enhanced learning (TEL) %K competencies %K skill management %Z Computer Science [cs]/Technology for Human LearningConference papers %X A paradigm shift from a knowledge to a competence society is going on, which also becomes increasingly important for educational and vocational training purposes. Skills and competences are employed to describe learning content, students' capabilities, learning processes, and the like. Creating descriptions of skills and competences and assigning them manually is usually an exhausting task. Thus technology-enhanced support is needed. This paper presents a solution approach which enables both the semi-automatic detection of skills and competences comprised in learning content, as well as their assignments to learning content, students, and learning processes, and the exploitation of these relational structures. The methodology is based on a skill model which incorporates both a conceptual and an action component. %G English %2 https://telearn.hal.science/hal-00197243/document %2 https://telearn.hal.science/hal-00197243/file/82_Final_Paper.pdf %L hal-00197243 %U https://telearn.hal.science/hal-00197243 %~ TELEARN %~ TICE %~ TEL