<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The adaptive educational systems within e-learning platforms are built in response to the fact that the learning process is different for each and every learner. In order to provide adaptive e-learning services and study materials that are tailor-made for adaptive learning, this type of educational approach seeks to combine the ability to comprehend and detect a person’s specific needs in the context of learning with the expertise required to use appropriate learning pedagogy and enhance the learning process. Thus, it is critical to create accurate student profiles and models based upon analysis of their affective states, knowledge level, and their individual personality traits and skills. The acquired data can then be efficiently used and exploited to develop an adaptive learning environment. Once acquired, these learner models can be used in two ways. The first is to inform the pedagogy proposed by the experts and designers of the adaptive educational system. The second is to give the system dynamic self-learning capabilities from the behaviors exhibited by the teachers and students to create the appropriate pedagogy and automatically adjust the e-learning environments to suit the pedagogies. In this respect, artificial intelligence techniques may be useful for several reasons, including their ability to develop and imitate human reasoning and decision-making processes (learning-teaching model) and minimize the sources of uncertainty to achieve an effective learning-teaching context. These learning capabilities ensure both learner and system improvement over the lifelong learning mechanism. In this paper, we present a survey of raised and related topics to the field of artificial intelligence techniques employed for adaptive educational systems within e-learning, their advantages and disadvantages, and a discussion of the importance of using those techniques to achieve more intelligent and adaptive e-learning environments.</p></abstract>

The adaptive educational systems within e-learning platforms are built in response to the fact that the learning process is different for each and every learner. In order to provide adaptive e-learning services and study materials that are tailor-made for adaptive learning, this type of educational approach seeks to combine the ability to comprehend and detect a person’s specific needs in the context of learning with the expertise required to use appropriate learning pedagogy and enhance the learning process. Thus, it is critical to create accurate student profiles and models based upon analysis of their affective states, knowledge level, and their individual personality traits and skills. The acquired data can then be efficiently used and exploited to develop an adaptive learning environment. Once acquired, these learner models can be used in two ways. The first is to inform the pedagogy proposed by the experts and designers of the adaptive educational system. The second is to give the system dynamic self-learning capabilities from the behaviors exhibited by the teachers and students to create the appropriate pedagogy and automatically adjust the e-learning environments to suit the pedagogies. In this respect, artificial intelligence techniques may be useful for several reasons, including their ability to develop and imitate human reasoning and decision-making processes (learning-teaching model) and minimize the sources of uncertainty to achieve an effective learning-teaching context. These learning capabilities ensure both learner and system improvement over the lifelong learning mechanism. In this paper, we present a survey of raised and related topics to the field of artificial intelligence techniques employed for adaptive educational systems within e-learning, their advantages and disadvantages, and a discussion of the importance of using those techniques to achieve more intelligent and adaptive e-learning environments.

A Survey of Artificial Intelligence Techniques Employed for Adaptive Educational Systems within E-Learning Platforms

The Computational Intelligence Centre, School of Computer Science and Electronic Engineering University of Essex, Colchester,

United Kingdom of Great Britain and Northern Ireland

Faculty of Computing and Information Technology, King Abdulaziz University Jeddah,

Journal of Artificial Intelligence and Soft Computing Research

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

The adaptive educational systems within e-learning platforms are built in response to the fact that the learning process is different for each and every...

A Survey of Artificial Intelligence Techniques Employed for Adaptive Educational Systems within E-Learning Platforms

Online veröffentlicht: 17. Dez. 2016

Seitenbereich: 47 - 64

DOI: https://doi.org/10.1515/jaiscr-2017-0004

Schlüsselwörter
e-learning, adaptive educational systems, artificial intelligence

© 2016

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

A Survey of Artificial Intelligence Techniques Employed for Adaptive Educational Systems within E-Learning Platforms

Online veröffentlicht: 17. Dez. 2016

Seitenbereich: 47 - 64

DOI: https://doi.org/10.1515/jaiscr-2017-0004

Schlüsselwörtere-learning, adaptive educational systems, artificial intelligence

© 2016

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Schlüsselwörter
e-learning, adaptive educational systems, artificial intelligence