AI Virtual Assistant for Online Laboratory Experiments Based on Multi-threshold Technique and Genetic Algorithm for Analyzing the Student's Mouse Interaction Activities

There is a great interest in online learning systems, especially due to COVID-19 pandemic. However, there are a lot of limitations and challenges of online laboratory learning systems. This paper presents an efficient technique that provides an intelligent virtual tutor for online laboratory environment, as in engineering and science sectors. Based on the analysis of the student's mouse activities, the AI virtual Assistant or virtual tutor will automatically estimate the difficulties that the student stuck during conducting the steps of lab's experiment. Hence, the virtual tutor can assist the student, accordingly. The technique is based on multi-threshold that are used to discriminate different levels of difficulties. The values of these thresholds are estimated and optimized via the genetic algorithm. The experimental results show that discrimination between different student behaviors can be achieved accurately and efficiently.