Abstract
Metadata describe instructional resources and define their nature and use. Metadata are required to guarantee reusability and interchange of instructional resources into e-Learning systems. However, fulfilment of large metadata attributes is a hard and complex task for almost all LO developers. As a consequence many mistakes are made. This can cause the impoverishment of data quality in indexing, searching and recovering process. We propose a methodology to build Learning Objects from digital resources. The first phase includes automatic preprocessing of resources using techniques from information retrieval. Initial metadata obtained in this first phase are then used to search similar LO to propose missed metadata. The second phase considers assisted activities that merge computer advice with human decisions. Suggestions are based on metadata of similar Learning Object using fuzzy logic theory.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Cechinel, C., Sanchez-Alonso, S., Sicilia, M.A.: Empirical Analysis of Errors on Human-Generated Learning Objects Metadata. In: Proceedings Metadata and Semantic Research Third International Conference (MTSR 2009), Milan, Italy, pp. 60–70 (2009)
Farrell, R.G., Liburd, S.D., Thomas, J.C.: Dynamic assembly of learning objects. In: Proceedings of the 13th International World Wide Web Conference on Alternate Track Papers & Posters, New York, NY, USA, pp. 162–169 (2004)
Greenberg, J.: Metadata extraction and harvesting: A comparison of two automatic metadata generation applications. Journal of Internet Cataloging: The International Quarterly of Digital Organization, Classification and Access 6(4), 58–82 (2004)
Hamers, L., Hemeryck, Y., Herweyers, G., Janssen, M., Keters, H., Rousseau, R., Vanhoutte, A.: Similarity measures in scientometric research. The Jaccard Index Versus Salton’s Cosine Formula 25(3), 315–318 (1989)
IEEE Standard for Learning Object Metadata (2002), http://ltsc.ieee.org/wg12/
Ochoa, X., Cardinaels, K., Meire, M., Duval, E.: Frameworks for the Automatic Indexation of Learning Management Systems Content into Learning Object Repositories. In: Kommers, P., Richards, G. (eds.) Proceedings of World Conference on Educational Multimedia, Hypermedia and Telecommunications 2005, Montreal, Canada, pp. 1407–1414 (2005)
Pedersen, T., Patwardhan, S., Michelizzi, J.: WordNet: Similarity: measuring the relatedness of concepts. In: Demonstration Papers at HLT-NAACL 2004 on XX (HLT-NAACL 2004). Association for Computational Linguistics, Boston (2004)
Polsani, P.: Use and Abuse of Reusable Learning Objects. Journal of Digital Information 3(4), 1–10 (2003)
Prieto, M.E., Menendez, V., Segura, A., Vidal, C.: A Recommender System Architecture for Instructional Engineering. In: Lytras, M.D., et al. (eds.) WSKS 2008. LNCS (LNAI), vol. 5288, pp. 314–321. Springer, Heidelberg (2008)
SCORM: Sharable Course Object Reference Model (2004), http://adlnet.org/
Sicilia, M.A., Garcia, E.: On the Concepts of Usability and Reusability of Learning Objects. International Review of Open and Distance Learning 4(2) (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Menendez D., V., Zapata G., A., Vidal C., C., Segura N., A., Prieto M., M. (2010). An Approach to Metadata Generation for Learning Objects. In: Lytras, M.D., Ordonez De Pablos, P., Ziderman, A., Roulstone, A., Maurer, H., Imber, J.B. (eds) Knowledge Management, Information Systems, E-Learning, and Sustainability Research. WSKS 2010. Communications in Computer and Information Science, vol 111. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16318-0_22
Download citation
DOI: https://doi.org/10.1007/978-3-642-16318-0_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16317-3
Online ISBN: 978-3-642-16318-0
eBook Packages: Computer ScienceComputer Science (R0)