Social tagging evaluation methodologies in technology - enhanced learning
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Εκπαιδευτική τεχνολογία ; Διαδίκτυο (Internet) στην εκπαίδευση ; Open Learning ; Εκπαίδευση -- Πληροφορική ; IEEE 802.16 (Standard) ; Παγκόσμιος Ιστός (WWW) -- Τεχνολογικές καινοτομίεςAbstract
The key objective of this Τhesis is the implementation of a proposed Social Tagging Evaluation Methodology in an existing Open Educational Resources (OER) Repository, the OpenScienceResources Repository. In the context of Technology Enhanced Learning, Digital Educational Resources in the form of learning objects, are used to support a wide range of educational activities. In general, Digital Educational Resources are organized according to formal descriptions from centrally designed and agreed classification systems using metadata, such as IEEE Learning Object Metadata (IEEE LOM) (IEEE LTSC, 2002). However, IEEE LOM imposes a strict classification of the content (Bateman et al., 2007; Vuorikari, 2007). Social tagging has emerged in contrast and alongside the formal classification of content of Digital Educational Resources. Social tagging is supported by a number of web applications that encourage groups of individuals to openly share their private descriptions (or tags) of digital resources with other users, either by using a collection of tags created by the individual for his/her personal use (referred to as folksonomy) or by using a collective vocabulary (referred to as collabulary) (Anderson, 2007). Increasingly, recent investigations focus on the potential benefits of digital educational resources characterization by user-based tagging rather than author-based formal description based on centrally agreed classification systems, for example metadata such as IEEE LOM (Bi et al., 2009). To this end, a number of studies have been reported in field of Technology Enhanced Learning (TeL) mainly aiming to evaluate the potential benefits of social tagging in improving the search effectiveness of digital educational resources (Trant, 2009a; Vuorikari & Ayre, 2009). However, there are limited studies to investigate how users’ tagging behaviour can influence (a) the enhancement of metadata descriptions of digital educational resources and (b) the resulted folksonomy compared to formal vocabularies used for characterizing the digital educational resources. The proposed Social Tagging Evaluation Methodology which is applied by means of this Thesis to the OSR Repository aims to investigate the aforementioned quarries and examine whether different users’ tagging motivations could enhance the metadata descriptions of digital educational resources.