Evaluating Focused Attention Level Using Mouse Operation Data

Focused Attention Level (FAL) is important in many tasks such as driving, online learning, and many computer-related operations. Previous approaches to evaluation of FAL usually involve eye-tracking and electroencephalogram which require dedicated devices to track the movements of eyes or record the signals from the brain. In this paper, we propose a novel method of evaluation of FAL only using a user's mouse operation data which are easily available in computers equipped with a mouse device. We perform our study using the Schulte Table which is a popular task designed to improve the focused attention levels of children and students. We extract features from mouse operation data in completing a Schulte Table task and establish a machine learning model to predict the focused attention level of the subject. Experimental results show that the accuracy of our method can reach 80.9%.