Monitoring learning activities in PLE using semantic modelling of learner behaviour.

Autor/inn/en	Softic, Selver; Taraghi, Behnam; Ebner, Martin; Vocht, Laurens de; Mannens, Erik; Walle, Rik van de
Titel	Monitoring learning activities in PLE using semantic modelling of learner behaviour.
Quelle	Aus: Holzinger, Andreas (Hrsg.); Ziefle, Martina (Hrsg.); Hitz, Martin (Hrsg.); Debevc, Matjaz (Hrsg.): Human factors in computing and informatics. First international conference. Proceedings. Berlin u.a.: Springer (2013) S. 74-90 PDF als Volltext (1); PDF als Volltext (2) Link als defekt meldenVerfügbarkeit
Sprache	englisch
Dokumenttyp	online; gedruckt; Sammelwerksbeitrag
ISBN	3-642-39061-7; 978-3-642-39061-6; 978-3-642-39062-3
DOI	10.1007/978-3-642-39062-3_5
Schlagwörter	Medienpädagogik; Lernumgebung; Lernverhalten; Semantik; Ontologie; Reflexion (Phil); Medieninformatik; E-Learning; Analyse; World Wide Web; Graz
Abstract	[The authors] report on the reflection of learning activities and revealing hidden information based on tracked user behaviour in [their] widget based PLE (Personal Learning Environment) at Graz University of Technology. [The] reference data set includes information of more then 4000 active learners for a period of around two years. [The authors] have modelled activity and usage traces using domain specific ontologies like Activity Ontology and Learning Context Ontology from the IntelLEO EU project. Generally [they] distinguish three different metrics: user centric, learning object (widget) centric and activity centric. [The authors] have used Semantic Web query languages like SPARQL and representation formats like RDF to implement a human and machine readable web service along with a learning analytics dashboard for metrics visualization. The results offer a quick overview of learning habits, preferred set-ups of learning objects (widgets) and overall reflection of usages and activity dynamics in the PLE platform over time. The architecture delivers insights for intervening and recommending as closure of a learning analytics cycle to optimize confidence in the PLE. (Orig.).
Erfasst von	Externer Selbsteintrag
Update	2014/4