Main Article Content
E-learning model has been developed rapidly because of development in technology, mobile platform such as smart phone and pad etc. But due to low rate of completion of e-learning platform it is necessary to analyze behavior characteristics of online learners which enhance the quality of learning. This can be achieved by recommending suitable e-contents available in learning servers that are based on learning style, learning pattern, time, environment, psychology and mood of learners. All these factors are uncertain. In such case fuzzy logic and neural network approach of soft computing is desirable to use and helps to take decision for prediction of e-learning. The aim of this paper is to study development and work in e-learning, adaptive learning and web-based learning globally. Also study for to develop reliable and efficient solution for e-learners and e-content provider. This paper represent studies of learning style prediction, learning style model, learning system and analysis of related work in e-learning and web environments. This is review of previous research in e-learning prediction.
How to Cite
, S. A. J. D. S. B. J. “Fuzzy Logic A Soft Computing Approach For E-Learning: A Qualitative Review”. International Journal on Recent and Innovation Trends in Computing and Communication, vol. 6, no. 8, Aug. 2018, pp. 20-23, doi:10.17762/ijritcc.v6i8.5170.