Applying Machine Learning and AI on Self Automated Personalized Online Learning

Abstract

Machine Learning (ML) and Artificial Intelligence (AI) allowed researchers to view and analyze student's behaviors as never before. By monitoring them online, teachers can beforehand help students who need assistance. Many research papers revealed that there is a positive correlation between those students who exhibit good classroom behavior and academic achievement. RSU-AI-Monitoring System is an effective tool for behavioral improvement. RSU-AI-Monitoring System tracks many attributes on user activities' logs such as attendances, quiz marks, login and logout timestamps, IP addresses, names, etc. This research traces and directs students online to proper their behaviors. The experiment traced and tracked on two courses, which are THAI106 and ENG101. These subjects are the general education courses offering online. Student can access these subjects on an e-learning platform via mobile devices. Sample data were collected from 1,890 students in one semester. This paper discusses the data mining, ML and AI techniques to construct a new method enabling personalized learning. The experiment revealed a good progress on the overall student marks on their final examinations. 65 of 345 students were received the grade of B+ after participated in the tutoring program by AI Bot. 240 students who failed on the midterm examinations or received the low quiz scores, were able to pass their final examinations. The experiments revealed that 69.5% of the students had passed their final examinations and 18% obtained the B+ grades.