Visual analytics

Example photograph with SIFT keypoints (shown by circles)Suzanne Little has developed our Ed-Media 2011 paper, which she presented in Lisbon in June last year, into a full-scale journal article. The article focuses on visual similarity search, which uses features of images in order to find material that is visually related, thus supporting navigation of educational materials in a variety of ways, including identifying the source of an image, finding items that offer different ways of understanding a concept, or finding other content in which a given image or video frame is used

Little, Suzanne; Ferguson, Rebecca and Rüger, Stefan (2012). Finding and reusing learning materials with multimedia similarity search and social networks. Technology, Pedagogy and Education, 21(2), pp. 255–271.

Abstract

The authors describe how content-based multimedia search technologies can be used to help learners find new materials and learning pathways by identifying semantic relationships between educational resources in a social learning network. This helps users – both learners and educators – to explore and find material to support their learning aims. Exciting new technologies are emerging for designing and deploying multi-modal, interactive educational tools such as video, 3D models, games, remote sensors or collaborative community-created resources (e.g. wikis). With the increasing availability of open educational resources in online, semantically marked-up and socially connected spaces, users are building their own learning pathways by exploring and remixing content. In this article the authors look at how the integration of multimedia search into the SocialLearn platform for shared learning spaces can contribute to this vision.

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