Two Recommending Strategies to Enhance Online Presence in Personal Learning Environments

Abstract : Aiming to facilitate and support online learning practices, TEL researchers and practitioners have been increasingly focused on the design and use of Web-based Personal Learning Environments (PLE). A PLE is a set of services selected and cus-tomized by students. Among these services, resource (either digital or human) rec-ommendation is a crucial one. Accordingly, this chapter describes a novel approach to supporting PLEs through recommendation services. The proposed approach makes extensive use of ontologies to formally represent learning context that, among other components, includes students' presence in the online world, i.e., their online pres-ence. This approach has been implemented in and evaluated with the OP4L (Online Presence for Learning) prototype. In this chapter, we expose recommendation strate-gies devised for OP4L. One is already implemented in OP4L, it is based on the well-known Analytical Hierarchical Process (AHP) method. The other one which has been tested on data coming from the prototype is based on the active user's navigation stream and used a Kalman filter approach.
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Samuel Nowakowski, Ivana Ognjanović, Monique Grandbastien, Jelena Jovanovic, Ramo Šendelj. Two Recommending Strategies to Enhance Online Presence in Personal Learning Environments. Springer Science+Business Media New York 2014. Recommender Systems for Technology Enhanced Learning: Research Trends and Applications, 2014, Recommender Systems for Technology Enhanced Learning: Research Trends and Applications, ⟨10.1007/978-1-4939-0530-0_11⟩. ⟨hal-01102265⟩

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