Abstract

This paper focuses on the research and application of eye movement and gaze direction analysis in online testing systems. The practical novelty of the proposed model of monitoring the direction of gaze in a computer-based knowledge control system lies in the possibility of automated remote control over a large audience of students. The practical significance lies in creating the same conditions for computer testing for all students and increasing the correspondence of knowledge level to the received test results. The implemented and tested system is relevant and necessary in higher educational institutions, particularly in Ukraine, where remote education has emerged as the safest means of acquiring knowledge. This is especially true for fields of study where practical tasks and laboratory work do not necessitate a student's physical presence at the institution. That is why the application of the latest information technologies is extremely important. The dynamic authentication based on the sequence of eye movements proposed in the model allows error-free user's eye area detection for further analysis of the test subject's behavior. The proposed authentication method excludes the need to enter passwords or CAPTCHAs, ensures the speed of determining the user's presence. Further analysis of the user's direction of vision includes responding to the information received, such as skipping a question or the need for re-authorization. Question skipping occurs when the system decides that the user has not been looking at the screen for an extended period (looking sideways, down, up for more than 30 seconds). Re-authentication becomes necessary if the user exits the test or if there is a user replacement. Real-time gaze control capability is implemented by using massive parallel processing system (NVIDIA GeForce GTX 1650 graphics card) for calculations. The analysis of the results obtained shows that the proposed approach allows gaze detection at different illumination ranges (from 0.3 lux to 10,000 lux), as well as to detect states of the user's eyes that violating test rules for further system response (skipping a question or re-authentication request).

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