introduction

Virtual Reality technologies are evolving at a fast pace. It is important to establish if these novel solutions met the goals they were developed for (i. e., to evaluate if they are effective). These technological-based products, whether based on a conventional PC setup or an immersive virtual reality setup, predominantly rely on the stimulation of the sight. With this, the eye movement analysis appears as an important metric to evaluate technological environments. Thorough eye movement analysis can establish how persons collect information and what influences their actions and decisions and determine certain preferences or behaviors.

The capture of eye movements can be achieved using eye-trackers, which can be categorized into three different categories:

The major outcome of the eye-tracking devices is overlaying what the user is watching and his eye movements. To achieve this overlay with precision, first a calibration step at the beginning of the usage of the eye-tracker. In addition to this outcome, a set of visual maps and metrics need to be set up. Visual maps consist of a heat map of visual attention, focus map, and metrics of the number of saccades, the number of fixations, and their durations

The usage of eye-tracking techniques to study human behavior was already addressed on PsychTech by two studies, namely the study entitled “Physical exercise, female preference in corporal dimensions in men: A comparative study on eye-tracking” (^{Medon, et al., 2020}) and the study entitled “The Position Of The Target In The Influence Of Eye Movement On Navigational And Informative Research Tasks” (^{Vasconcelos-Raposo et al., 2017}). Nevertheless, there are still many research gaps open that can be pursued in two perspectives: how the features of a virtual reality environment affect the user; and how different factors can be used to condition behaviors within virtual environments. As so, works that make use of eye-tracking analysis are encouraged to be submitted to PyschTech