الفهرس 
Chapter 1 overviewOnly 14 pages are availabe for public view
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Abstract
The virtual learning environment (VLE) is an e-learning center that allows the uploading of lessons and educational resources. The need for virtual learning environments has emerged in light of the increasing number of students, and in light of the Corona pandemic, which forced the educational process to adopt e-learning. There are challenges facing virtual learning environments, including: 1- It does not take into account the individual differences between the students 2- Focusing on the theoretical side and shortening the live experiences 3- Lack of guidance for students within the learning environment 4 Many students withdraw or fail at a noticeable rate. To overcome these challenges, monitor students’ behavior in a virtual learning environment and suggest to students the learning materials that are appropriate for each student. This intelligent agent can also predict the probability of students failing or dropping out of the materials using the modified Random forest method. A specially designed virtual learning environment is built The educational materials were collected for several courses in the form of video, audio and text lectures in line with the students’ learning styles. The Internet of Things experience was developed, and built to monitor students’ behavior. This intelligent agent can suggest to students the educational materials that suit each student, This intelligent agent can also predict the probability of students failing or dropping out of a course using the modified Random forest method. The modified Random forest method, which gives 100% accuracy, was compared to machine learning methods on a famous standard data, which is the Open University Learning Analytics Dataset (OULAD). This intelligent agent can suggest to students the educational materials that suit each student, and this can also The intelligent agent can predict the probability of students failing or dropping out of the course with 100% accuracy using the modified Random forest method. The conclusions obtained from the application and study of the proposed method and what can be added in the future to obtain better performance of student. The Internet of Things (IoT) experiment has been developed. A smart agent has been built to monitor the behavior of students. This smart agent can suggest to students the educational materials that suit each student. This smart agent can predict the rate of students failing or withdrawing of the course with 100% accuracy using the fine-tuned Random Forest method.