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Leveraging social semantic components in executable environments for learning

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Abstract

Learning can benefit from the modern Web structure through the convergence of top-down encyclopedic institutional knowledge and bottom-up user-generated annotations. A promising approach to such convergence consists in leveraging the social functionalities in 3.0 executable environments through the recommendation of tags with the mediation of lexical and semantic resources.

This paper addresses such issues through the design and evaluation of a tag recommendation system in a Web 3.0 Web portal, ‘150 Digit’. Designed for schools, 150 Digit encourages students and teachers to interact with a set of four exhibitions on the historical and social aspects of the Italian unification process in a virtual environment. The website displays the exhibits and their related documents promoting the users' active participation through tagging, voting and commenting on the exhibits. Tags become a way for students to create and explore new relations among the site contents, orthogonal to the institutional viewpoint. In this paper, we illustrate the recommendation strategy incorporated in 150 Digit, which relies on a semantic middleware to mediate between the input expressed by the users through tags and the top-down institutional classification provided by the curators of the exhibitions. Following this, we describe the evaluation process conducted in a real experimental setting and discuss the evaluation results and their implications for learning environments.

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