DocumentCode :
259534
Title :
Learning Analytics in Linked Open Online Courses
Author :
Hover, Kai Michael ; Muhlhauser, Max
Author_Institution :
Dept. of Comput. Sci., Tech. Univ. Darmstadt, Darmstadt, Germany
fYear :
2014
fDate :
10-12 Dec. 2014
Firstpage :
369
Lastpage :
374
Abstract :
Learning offerings and learners´ activities are increasingly moving to decentralized learning environments in the cloud. The advent of MOOC platforms gives a good example for this ongoing evolution. However, most learning applications use proprietary data models. As learners nowadays not only use only one e-learning offering, the analysis of learner activities is challenging in such decentralized and heterogeneous learning environments. To address this problem, we present three different learning applications and show the potential of exploiting Semantic Web technologies.
Keywords :
computer aided instruction; educational courses; semantic Web; MOOC platforms; decentralized learning environments; e-learning offering; learner activities; learning analytics; learning applications; linked open online courses; proprietary data models; semantic Web technologies; Data models; Discussion forums; Distributed databases; Electronic learning; Interoperability; Ontologies; Semantic Web; Interoperability; Learning Analytics; Lecture Recording; Ontology; Semantic Web;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia (ISM), 2014 IEEE International Symposium on
Conference_Location :
Taichung
Print_ISBN :
978-1-4799-4312-8
Type :
conf
DOI :
10.1109/ISM.2014.51
Filename :
7033053
Link To Document :
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