期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2021
卷号：99
期号：2
页码：343
出版社：Journal of Theoretical and Applied
摘要：Every learner follows a special Learning Style (LS), which enables him to learn and understand efficiently; it is necessary to discover every learner's behavior and LS to offer him his specialized materials. The success of the E-learning systems comes from the ability to select and recommend the suitable subject contents to the learner. This paper suggested a new adapted technique for the Fuzzy C Mean (FCM) Algorithm named Adaptive Fuzzy C Mean (AFCM). Moreover, this paper proposed a new adapted E-learning model to predict the Learning Style through the process of learning, depending on the suggested AFCM. The suggested model can store the access data of the learner's navigation, finds out the behavior pattern that personalizes every learner, and then offers individualization due to the LS. The analysis of AFCM performance can be performed by the calculation of the two test accuracy; the performance of using the AFCM algorithm in the second test is much better with an overall performance of 88.7%. The AFCM introduced a preprocessing step before the FCM Algorithm to reduce the time and reduced the number of iterations taken by FCM. The proposed model assists the learners for an English course in the Faculty of Computer Science, October 6University, to maximize the E-learning advantage with high performance, in COVID 19 circumference.
关键词：Learning Style; Fuzzy C Mean Algorithm; Questionnaire; Adaptive E-Learning; Log File
