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.