HT06, tagging paper, taxonomy, Flickr, academic article, to read
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Evolution of learning folksonomies: social tagging in e-learning repositories
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A personalized recommendation method using a tagging ontology for a social E-learning system
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The emerging Web 2.0 applications have allowed new ways of characterizing digital educational resources, which moves from the expert-based descriptions relying on formal classification systems such as the IEEE Learning Object Metadata (LOM) to a less formal user-based tagging. This alternative way of characterizing digital educational resources is commonly referred to as social tagging, whereas the collection of tags created by the different users individually is referred to as folksonomy. As a result, a number of studies have been reported in the field of Technology-enhanced Learning (TeL) which provide evidence that social tagging has the potential to enlarge metadata descriptions, as well as the formal structured vocabularies with additional terms derived by the resulted folksonomy but more in depth studies are needed regarding this enlargement process. Thus, one issue to investigate further is the possible influence of users' tagging motivation to the resulted enlarged metadata descriptions. In this paper we aim to investigate this issue by first proposing a methodology that aims to evaluate whether users' tagging motivation can influence (a) the enlargement of educational resources possible descriptions compared to the anticipated creators' descriptions and (b) the resulted folksonomy compared with formal structured vocabularies used by the creators of the educational resources and then, apply it to an existing LOR with more than 3,000 science education resources, 434 taggers and 14,707 social tags. Our experiments provided evidence that taggers with a specific type of tagging motivation can produce tags that are significantly different from formal metadata generated by the creators of the educational resources.