Reading Speed and Comprehension Assessment Using Eye Tracking: Insights From a Participant Study

This study presents a new online tool that uses realtime eye tracking to assess reading comprehension and speed. The program, which was created with Flask, MongoDB, and OpenCV, tracks users' eye movements while they read sections, offering information about reading habits that is not possible to obtain with conventional assessment tools. In addition to a regular reading speed measure, the application computes an adjusted reading speed metric that takes eye movements into consideration. A set of tests intended to gauge the user's comprehension of the text are used to gauge comprehension. 55 volunteers from various parts of India participated in the system's testing, yielding a wealth of information about reading habits. The findings suggested that the adjusted reading speed is a more reliable indicator of reading competence because frequent and irregular eye movements were frequently linked to lower comprehension scores. Furthermore, the program was able to spot minute variations in reading habits among various demographic groups. These results show how eyetracking technology can be combined with reading assessment instruments to produce a more accurate and individualized reading competence test. Future studies could expand the application's functionality and apply it to school settings for individualized learning experiences and reading treatments.