Learning object analytics for collections, repositories & federations

Abstract

A large number of curated digital collections containing learning resources of a various kind has emerged in the last year. These include referatories containing descriptions for resources in the Web (as MERLOT), aggregated collections (as Organic.Edunet), concrete initiatives as Khan Academy, repositories hosting and versioning modular content (as Connexions) and meta-aggregators (as Globe and Learning Registry). Also, OpenCourseware and other OER initiatives have contributed to making this ecosystem of resources richer. Very interesting insights can be extracted when studying the usage and social data that are produced within the learning collections, repositories and federations. At the same time, concerns for the quality and sustainability of these collections have been raised, which has lead to research on quality measurement and metrics. The Workshop attempts to bring studies and demonstrations for any kind of analysis done on learning resource collections, from an interdisciplinary perspective. We consider digital collections not as merely IT deployments but as social systems with contributors, owners, evaluators and users forming patterns of interactions on top of portals or through search systems embedded in other learning technology components. This is in coherence of considering these social systems under a Web Science approach (http://webscience.org/).