EFFECTS AND RELATIONSHIPS OF RECEIVING INFORMATION AMOUNT ON EYE-MOVEMENT FEATURES

Kerviona, Keren (2021) EFFECTS AND RELATIONSHIPS OF RECEIVING INFORMATION AMOUNT ON EYE-MOVEMENT FEATURES. S1 thesis, UNIVERSITAS ATMA JAYA YOGYAKARTA.

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Abstract

The vast development of technology in this era encourages researchers to study about the interrelationship of the amount of information with human cognitive functions. This study was aimed to test the hypothesis of whether the amount of information can affect human cognitive function analyzed from the responses of human eye-movement features, as well as the relationships between information amount and eye-movement features. Six students from a Yuan Ze University were involved in playing a game that stimulated a different amount of information. The participants’ eye-movements were recorded using a screenbased eye-tracker (GP3 HD GazepointTM Canada) while playing ZType game. There were nineteen generated traditional features from the experiment. These traditional features were then being processed as complexity features. The analysis of variance (ANOVA) was done to know which features that were affected by the amount of information. The results showed that there were four traditional features comprising left and right pupil diameter, amount of blink, and saccade magnitude that were significantly affected by the amount of information. Moreover, the amount of information also affected the thirteen complexity features from fixation (duration and coordinates), pupil (diameter and coordinates), and saccade (magnitude and direction) elements. The linear regression analysis was done to know which features are the critical features, which later can be used to build the AI model. The results showed that there were three traditional features comprising left and right pupil diameter, and amount of blink that have negative and positive correlation respectively, with the information amount. This study indicates that the amount of information is influencing the eyes’ response that is related to the human cognitive function. Moreover, the complexity analysis can help researchers to generate more eye-movement features from the traditional features.

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