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Erschienen in: Artificial Intelligence Review 3/2016

01.10.2016

A survey of personality and learning styles models applied in virtual environments with emphasis on e-learning environments

verfasst von: Somayeh Fatahi, Hadi Moradi, Leila Kashani-Vahid

Erschienen in: Artificial Intelligence Review | Ausgabe 3/2016

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Abstract

Today, one of the most important and challenging issues in artificial intelligence is modeling human behavior in virtual environments. Furthermore, studying e-learning environments is in great demand in computer science which requires understanding human behaviors. Thus, considering human behavior factors, such as personality, mood, and emotion, and modeling them in e-learning environments is a challenging issue in artificial intelligence. The purpose of this paper is to review the psychological models of personality used in computer science. In addition, the most important applications of personality models and their direct related topics in learning, i.e. learning style issues in e-learning environments, are presented. The study shows that researchers tend to use models that are simple to implement in virtual world and are as comprehensive as possible to cover all the features of human behavior. Finally, we concluded that models such as the Five Factor Model, the Myers–Briggs Type Indicator personality model, and Felder–Silverman learning styles model have the two most important features, which are simplicity and comprehensiveness. These two features have made these psychology models the most favorable in the virtual world.

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Fußnoten
1
Pleasure, Arousal, and Dominance mood model introduced by Albert Mehrabian.
 
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Metadaten
Titel
A survey of personality and learning styles models applied in virtual environments with emphasis on e-learning environments
verfasst von
Somayeh Fatahi
Hadi Moradi
Leila Kashani-Vahid
Publikationsdatum
01.10.2016
Verlag
Springer Netherlands
Erschienen in
Artificial Intelligence Review / Ausgabe 3/2016
Print ISSN: 0269-2821
Elektronische ISSN: 1573-7462
DOI
https://doi.org/10.1007/s10462-016-9469-7

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