Analysis of user testing records consumes a lot of the study moderators time. If we want to find a problem in user interface, it is necessary to watch the whole recording of the testing and focus on all its outputs. Forms belong to the most problematic features of the user interface. Therefore, we focused on the problems, which typically can be found in forms and we have also implemented our own forms for the experimental purposes. As the participant is asked to fill form on his own without any help, we expect that the stress, cognitive overload and/or negative emotions might occur when the participant runs into problems in form. All of the mentioned should cause the pupil dilatation, which we measure using eye tracking technology. Primary, we focus on the pupil dilatation, but we have explored another alternative techniques, such as measuring skin conductance by GSR sensor. Our aim is to develop a tool, which determines timestamps of problems occurred in a process of filling a form on the basis of pupil dilatation and save moderators time, which he would otherwise spend on finding these occurrences. To identify problems in forms, we have had to explore and examine the usage of several methods of filtrating the raw data from eye tracker. Afterwards, the filtrated data were simpler to analyze and construe. Our research shows, that the pupil size fluctuated more, when participants were filling the form, which contains implemented problems. On the other hand, the pupil dilatation was not so noticeable in the process of filling the problem-free form. We also identified several cases of considerable pupil dilatation during the occurrence and looking for a solution to a problem in a form.