A Review: Artificial Intelligent Approach for Enhancing Adaptability in an Adaptive E-Learning Environment
M.P.L. Perera

M.P.L.Perera*, Department of Software Engineering, Faculty of Computing and Technology, University of Kelaniya, Dalugama, Sri Lanka. 
Manuscript received on March 02, 2021. | Revised Manuscript received on March 30, 2021. | Manuscript published on April 30, 2021. | PP: 1-9 | Volume-10 Issue-4, April 2021. | Retrieval Number: 100.1/ijeat.D22970410421 | DOI: 10.35940/ijeat.D2297.0410421
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Abstract: Adaptive e-learning the aim is to fill the gap between the pupil and the educator by discussing the needs and skills of individual learners. Artificial intelligence strategies that have the potential to simulate human decision-making processes are important around adaptive e-Learning. This paper explores the Artificial techniques; Fuzzy Logic, Neural Networks, Bayesian Networks and Genetic Algorithms, highlighting their contributions to the notion of the adaptability in the sense of Adaptive E-learning. The implementation of Artificial Neural Networks to resolve problems in the current Adaptive e-learning frameworks have been established. 
Keywords: Adaptive e-Learning, Artificial Intelligence techniques, Bayesian networks, fuzzy logic, Genetic Algorithms, Neural Networks.
Scope of the Article: Artificial Intelligent