Validation of the REyeker (Remote Eye Tracker) using on-site eye tracker and EEG data

Background: Eye tracking data provides crucial information about program com-prehension. Due to the current pandemic, it is more difficult to collect the data in the conventional way using an on-site eye tracker. Therefore, Mucke et al. [1] developed an remote eye tracker that allows eye tracking studies to be conducted safely. In this process, participants receive a blurred image of the program code. With a click, they can make their areas of interest visible. This study is intended to test the validity of REyeker.

Objective: The long-term goal is to present alternative ways to collect eye tracking data that are similarly accurate to the on-site eye trackers. In addition, a safe framework for conducting these studies will be established, which also allows a larger group of participants to be tested in a shorter period of time.

Method: In the study, participants receive simple code snippets e.g, to sort an array or compare strings. At the same time, by using the EEG, the mental workload can be measured to get a better overall picture of code understanding. Furthermore, it allows to compare whether a higher DepDegree is associated with more cognitive effort. A second group of participants will conduct the experiment with REyeker, so the code snippets will be blurred. With those results, we can comparethe areas of interest of both eye tracking tools to see whether the two sets of data have reached a similar conclusion.

Expected Results: We hope to find similar eye movements in both groups. We suspect a smaller area of interest with the Tobii eye tracker, since the field of view of the REyker eye tracker is set slightly larger than it is in natural reading. This results from the fact that when setting a smaller field of view, subjects would have to click more often and more information would have to be stored in working memory. This would make the experiment more difficult. [1]

 

References

J. Mucke, M. Schwarzkopf, and J. Siegmund, “Reyeker: Remote eye tracker,” 2021.
N. Peitek, S. Apel, C. Parnin, A. Brechmann, and J. Siegmund, “Program Com-prehension and Code Complexity Metrics: An fMRI Study,” in Proceedings of theIEEE/ACM 43rd International Conference on Software Engineering. IEEE, 2021.