A Framework for Cross-Platform Graph-based Recommendations for TEL
Key: ADFC12-1
Author: Mojisola Anjorin, Ivan Dackiewicz, Alejandro Fernandez, Christoph Rensing
Date: September 2012
Kind: In proceedings
Publisher: CEUR-WS
Book title: Proceedings of the 2nd Workshop on Recommender Systems for Technology Enhanced Learning
Keywords: TEL, Recommender Systems, Cross-Platform, Framework
Abstract: A Technology Enhanced Learning (TEL) ecosystem is a kind of Digital Ecosystem formed by independent platforms combined and used by learners to support their learning. We believe that recommendations made across these different platforms by exploiting the synergies between them will benefit learners. However, building such cross-platform recommender systems poses new and unique challenges for developers. In this paper, we present a framework to support the development of cross-platform recommender systems for TEL ecosystems and discuss challenges faced. The framework decouples the development of the recommender system from the evolution of the specific platforms by combining graph-based algorithms, a unified data model, and a service oriented architecture. As proof of concept, the framework was effectively applied to develop a cross-platform recommender system in a TEL ecosystem having Moodle as the Learning Management System, Mahara as the Social Networking Service and Ariadne as Learning Object Repository.
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