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Artificial Intelligence Review

Erschienen in:

01.10.2015

Adaptive systems: a content analysis on technical side for e-learning environments

verfasst von: Ahmad A. Kardan, Mahdi Aziz, Maryam Shahpasand

Erschienen in: Artificial Intelligence Review | Ausgabe 3/2015

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Abstract

Adaptive systems refer to autonomous interactive systems that adjust their behavior and functionality to environmental changes. In e-learning context, adaptive e-learning systems (AESs) adapt their services to users interests, knowledge and goals. In order to investigate the trend of researches in the field of adaptation in e-learning systems, a comprehensive survey of research papers in this context is presented. In this regard, 190 research papers, published between 2000 and 2012, from 45 journals are reviewed and analyzed. The basic contributions of the paper are manifold. First, it provides classifications of research papers from two different points of view: the adaptive technologies utilized in research papers in order to provide adaptation services for AESs and the application fields of research papers in AESs as research goals. Second, it presents statistical analyses on adaptive technologies and application fields. The analyses are carried out based on publication year of papers, the publication year versus adaptive technologies, the publication year versus application fields and adaptive technologies versus application fields. Third, the open problems, current state and prospective direction of researches in AESs are discussed. Finally, the paper suggests what adaptive technology might be the best choice for ongoing researches in each application field.

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Titel: Adaptive systems: a content analysis on technical side for e-learning environments
verfasst von: Ahmad A. Kardan
Mahdi Aziz
Maryam Shahpasand
Publikationsdatum: 01.10.2015
Verlag: Springer Netherlands
Erschienen in: Artificial Intelligence Review / Ausgabe 3/2015
Print ISSN: 0269-2821
Elektronische ISSN: 1573-7462
DOI: https://doi.org/10.1007/s10462-015-9430-1

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