An Adaptive Learning System Based on Learner’s Knowledge Level

personalizing learning contents to learners become an important field in recent years. This paper proposes an adaptive e-learning system based on students learning style and knowledge level. The system also measures the learner’s knowledge level using the C4.5 decision tree algorithm on their quiz results. The findings show the students who used the system has increased their knowledge level after performing knowledge tests prior to course personalization and after finishing the course. students who are considered in the beginner level has reduced from 58.3% to 25.3%, whereas the intermediate level has increased greatly from 28.1% to 41.6%. finally, the advanced level has increased from 13.3% to 33.3%.