Determining Gaze Behavior Patterns in On-Screen Testing

This study proposes a software system for determining gaze patterns in on-screen testing. The system applies machine learning techniques to eye-movement data obtained from an eye-tracking device to categorize students according to their gaze behavior pattern while solving an on-screen test. These patterns are determined by converting eye movement coordinates into a sequence of regions of interest. The proposed software system extracts features...