The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Creating High Quality Learning Object Metadata Based on Web 2.0 Concepts
|
|
Author(s): Daniel Dahl (European Research Center for Information Systems (ERCIS) Westfälische Wilhelms-Universität Münster, Germany)and Gottfried Vossen (European Research Center for Information Systems (ERCIS) Westfälische Wilhelms-Universität Münster, Germany)
Copyright: 2010
Pages: 15
Source title:
ICTs for Modern Educational and Instructional Advancement: New Approaches to Teaching
Source Author(s)/Editor(s): Lawrence A. Tomei (Robert Morris University, USA)
DOI: 10.4018/978-1-60566-936-6.ch004
Purchase
|
Abstract
When introducing the metadata standard LOM, objectives such as the ability to find or to reuse learning objects were followed. These objectives are actually achieved in LOM to a limited degree only, despite the designation as de-facto standard for description of electronic learning content. Based on the complexity of the standard, a high theoretical potential faces rejection in practice. One reason for this is that the process of metadata generation—for example, who creates which metadata attributes—is not defined in detail yet. This paper illustrates an approach which guarantees a high quantity as well as a high quality of learning object metadata records, bringing together known ways of metadata creation and the new paradigm of users describing content as implemented in recent Web 2.0 applications. In the context of a concrete e-learning platform, we exemplarily illustrate who creates which metadata records of LOM in which way at what time. Finally, we show why this approach of creating metadata matters as we measure our metadata quality and compare it with other’s findings.
Related Content
|
Sylvia Robertson.
© 2023.
28 pages.
|
|
Dimitrios Stamovlasis, Charalampos Tsanidis.
© 2023.
23 pages.
|
|
Ikram Chelliq, Lamya Anoir, Mohamed Erradi, Mohamed Khaldi.
© 2023.
26 pages.
|
|
Vasiliki Ioakeimidou.
© 2023.
27 pages.
|
|
Eleni Bonti.
© 2023.
25 pages.
|
|
Lamya Anoir, Ikram Chelliq, Mohamed Erradi, Mohamed Khaldi.
© 2023.
29 pages.
|
|
Shibu Puthalath, M. R. Mallaiah, Viswesh Sekhar.
© 2023.
17 pages.
|
|
|