The Open UniversitySkip to content

A semantic framework for cloud learning environments

Mikroyannidis, Alexander (2012). A semantic framework for cloud learning environments. In: Chao, Lee ed. Cloud Computing for Teaching and Learning: Strategies for Design and Implementation. Hershey, PA: IGI Global, pp. 17–31.

Full text available as:
PDF (Version of Record) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (969Kb)
DOI (Digital Object Identifier) Link:
Google Scholar: Look up in Google Scholar


Cloud Learning Environments (CLEs) are gradually gaining ground over traditional Learning Management Systems (LMS) by facilitating the lone or collaborative study of user-chosen blends of content and courses from heterogeneous sources, including Open Educational Resources (OER). In this chapter, we describe the use of ontologies for modelling various aspects of the learning process within such an environment. In particular, we consider a semantic knowledge base as the core of the learning environment, facilitating learners in finding educational services on the cloud. We describe how different stakeholder clusters are involved in the creation and maintenance of this knowledge base, through collaborative ontology management techniques. Finally, we define the mechanisms for the evolution of this knowledge base and the constant updating of the associated cloud learning services.

Item Type: Book Chapter
Copyright Holders: 2012 IGI Global
ISBN: 1-4666-0957-5, 978-1-4666-0957-0
Academic Unit/Department: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Interdisciplinary Research Centre: Centre for Research in Computing (CRC)
Item ID: 33220
Depositing User: Kay Dave
Date Deposited: 19 Mar 2012 10:26
Last Modified: 05 Oct 2016 01:48
Share this page:


Scopus Citations

Download history for this item

These details should be considered as only a guide to the number of downloads performed manually. Algorithmic methods have been applied in an attempt to remove automated downloads from the displayed statistics but no guarantee can be made as to the accuracy of the figures.

▼ Automated document suggestions from open access sources

Actions (login may be required)

Policies | Disclaimer

© The Open University   + 44 (0)870 333 4340