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Erschienen in: Artificial Intelligence Review 4/2015

01.12.2015

Learning content design and learner adaptation for adaptive e-learning environment: a survey

verfasst von: K. R. Premlatha, T. V. Geetha

Erschienen in: Artificial Intelligence Review | Ausgabe 4/2015

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Abstract

This paper presents a survey about learning content designs and various adaptation levels, in order to adapt the learners’ necessities in e-learning environment. Normally, learners have different learning styles, cognitive traits, learning goals and varying progress of their learning over period of time, which affects the learner’s performance while providing the same bundle of course to all learners. Hence, there is a need to create adaptive e-learning environment to offer appropriate learning content to all individuals. In general, the adaptation can be done based on learners’ characteristics. Here, we explore the adaptation that can be done, not only based on learner context parameters but also on the learning content (learning object) and the configuration of e-learning environment. In this paper, we provide a detail review about the various levels of adaptation, learning object design and process for learning content design, learner context parameters, and models/components of e-learning; moreover, we analyze and portray the associations among the components, necessary to achieve the well-defined adaptation in e-learning environment.

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Metadaten
Titel
Learning content design and learner adaptation for adaptive e-learning environment: a survey
verfasst von
K. R. Premlatha
T. V. Geetha
Publikationsdatum
01.12.2015
Verlag
Springer Netherlands
Erschienen in
Artificial Intelligence Review / Ausgabe 4/2015
Print ISSN: 0269-2821
Elektronische ISSN: 1573-7462
DOI
https://doi.org/10.1007/s10462-015-9432-z

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