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A pedagogy-driven personalization framework to support automatic construction of adaptive learning experiences

Christodoulakis Stavros, Arapi Polyxeni, Moumoutzis Nektarios, Mylonakis Emmanouil, Theodorakis Georgios

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Περίληψη

In order to effectively exploit the wealth of content in Learning Object Repositories several issues should be addressed including the “closed corpus” problem as identified in the field of Adaptive Hypermedia as well as the “one size fits all” problem. Both are related to personalization. The creation of personalized learning experiences is considered as a necessity to cope with the overwhelming amount of available learning material. This paper presents a personalization framework that allows for the automatic creation of pedagogically-sound learning experiences taking into account the variety of the Learners and their individual needs. This framework defines a model for the representation of abstract training scenarios (Learning Designs) encoded in an instructional ontology. This ontology clearly separates pedagogy from content allowing this way the construction of real personalized learning experiences where learning objects are bound to the learning scenario at run-time taking into account information encoded in Learner Profiles.

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