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Metadata for Social Recommendations: Storing, Sharing, and Reusing Evaluations of Learning Resources

Metadata for Social Recommendations: Storing, Sharing, and Reusing Evaluations of Learning Resources

Riina Vuorikari, Nikos Manouselis, Erik Duval
Copyright: © 2008 |Pages: 22
ISBN13: 9781599045436|ISBN10: 1599045435|ISBN13 Softcover: 9781616927356|EISBN13: 9781599045450
DOI: 10.4018/978-1-59904-543-6.ch005
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MLA

Vuorikari, Riina, et al. "Metadata for Social Recommendations: Storing, Sharing, and Reusing Evaluations of Learning Resources." Social Information Retrieval Systems: Emerging Technologies and Applications for Searching the Web Effectively, edited by Dion Goh and Schubert Foo, IGI Global, 2008, pp. 87-108. https://doi.org/10.4018/978-1-59904-543-6.ch005

APA

Vuorikari, R., Manouselis, N., & Duval, E. (2008). Metadata for Social Recommendations: Storing, Sharing, and Reusing Evaluations of Learning Resources. In D. Goh & S. Foo (Eds.), Social Information Retrieval Systems: Emerging Technologies and Applications for Searching the Web Effectively (pp. 87-108). IGI Global. https://doi.org/10.4018/978-1-59904-543-6.ch005

Chicago

Vuorikari, Riina, Nikos Manouselis, and Erik Duval. "Metadata for Social Recommendations: Storing, Sharing, and Reusing Evaluations of Learning Resources." In Social Information Retrieval Systems: Emerging Technologies and Applications for Searching the Web Effectively, edited by Dion Goh and Schubert Foo, 87-108. Hershey, PA: IGI Global, 2008. https://doi.org/10.4018/978-1-59904-543-6.ch005

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Abstract

Social information retrieval systems, such as recommender systems, can benefit greatly from sharable and reusable evaluations of online resources. For example, in distributed repositories with rich collections of learning resources, users can benefit from evaluations, ratings, reviews, annotations, etc. that previous users have provided. Furthermore, sharing these evaluations and annotations can help attain the critical mass of data required for social information retrieval systems to be effective and efficient. This kind of interoperability requires a common framework that can be used to describe in a reusable manner the evaluation approach, as well as the results of the evaluation. This chapter discusses this concept, focusing on the rationale for a reusable and interoperable framework, that can be used to facilitate the representation, management and reuse of results from the evaluation of learning resources. For this purpose, we review a variety of evaluation approaches for learning resources, and study ways in which evaluation results may be characterised, so as to draw requirements for sharable and reusable evaluation metadata. Usage scenarios illustrate how evaluation metadata can be useful in the context of recommender systems for learning resources.

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