AI-Based Evaluation to Assist Students Studying through Online Systems
Nidhi Shukla, K. S. Perianayagam, Anand Sinha · 2021
We shall present artificial intelligence (AI) techniques to evaluate the effectiveness of online learning methods. The techniques presented here are independent of the different online learning models like online classroom, video/audio tutorials, eBooks, etc. where there is no teacher to assist. The commonly accepted system to test a student is through question and answer method. This relies upon a sample-based questions from a subject and collect the answers from students. Mostly this activity is performed at the end of the course. An evaluation by this method is limited to the correctness of the answers and basis on which we infer the student’s knowledge on the subject. In this paper we propose that the student should be assessed the on a continuous basis. This type of assessment is different from testing a student to qualify as ‘Pass’ or ‘Fail’ and assess the student on a graded scale. We will focus on AI techniques to assist to grade the performance of the student in an online learning environment and provide a feedback to improve the learning process. A simple implementation based on Markov Decision Process is present to understand this approach.