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2013 | OriginalPaper | Buchkapitel

Social Validation of Learning Objects in Online Communities of Practice Using Semantic and Machine Learning Techniques

verfasst von: Lamia Berkani, Lydia Nahla Driff, Ahmed Guessoum

Erschienen in: Modeling Approaches and Algorithms for Advanced Computer Applications

Verlag: Springer International Publishing

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The present paper introduces an original approach for the validation of learning objects (LOs) within an online Community of Practice (CoP). A social validation has been proposed based on two features: (1) the members’ assessments, which we have formalized semantically, and (2) an expertise-based learning approach, applying a machine learning technique. As a first step, we have chosen Neural Networks because of their efficiency in complex problem solving. An experimental study of the developed prototype has been conducted and preliminary tests and experimentations show that the results are significant.

Metadaten
Titel
Social Validation of Learning Objects in Online Communities of Practice Using Semantic and Machine Learning Techniques
verfasst von
Lamia Berkani
Lydia Nahla Driff
Ahmed Guessoum
Copyright-Jahr
2013
DOI
https://doi.org/10.1007/978-3-319-00560-7_28

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