A prediction system using AI techniques to predict Students’ learning difficulties using LMS for sustainable development at KFU

Abstract With the emergence of the covid 19 pandemic, E-learning usage was the only way to solve the problem of study interruption in educational institutions and universities. Therefore, this field reserved significant attention in current times. In this paper, we used ten Machine Learning (ML) algorithms: Decision Tree(DT), Random Forest(RF), Logistic Regression(LR), SGD Classifier, Multinomial NB, K- Nearest Neighbors Classifier(KNN), Ridge Classifier, Nearest Centroid, Complement NB and Bernoulli NB) to build a prediction system based on artificial intelligence techniques to predict the difficulties students face in using the e-learning management system, to support related decision-making. Which, in turn, contributes supporting the sustainable development of technology at the university. From the results obtained, we detect the important factors that affect the use of E-learning to solve students' learning difficulties using LMS by building a prediction system based on AI techniques.