Exploring affiliation network models as a collaborative filtering mechanism in e-learning

作者: Daniel Rodríguez , Miguel Ángel Sicilia , Salvador Sánchez-Alonso , Leonardo Lezcano , Elena García-Barriocanal

DOI: 10.1080/10494820903148610

关键词: Social network analysisFilter (signal processing)Affiliation networkCohesion (computer science)E-learning (theory)Collaborative filteringWorld Wide WebComputer scienceHuman–computer interactionMechanism (biology)Structure (mathematical logic)

摘要: The online interaction of learners and tutors in activities with concrete objectives provides a valuable source data that can be analyzed for different purposes. One these purposes is the use information extracted from to aid decision making about either configuration further learning or filtering resources. This article explores an affiliation network model such kind Concretely, techniques as blockmodeling – a technique used derive meaningful patterns relationships network – and analysis m-slices – a helpful study cohesion relationships – are explored tools decide on topics and/or learner groups. In particular, results case show (i) filter participants rearranging groups; (ii) rearrange interest; (iii) dynamically change structure cour...

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