Abstract
One of the most important goals of electronic assessments is to achieve the smallest measurement error with tests that are as simple and short as possible. The psychological state of an examinee is typically ignored, both in the process of designing the tests and during the exam itself. Using the developed framework, we tested 35 participants in an experiment to obtain as much data as possible about the emotional states of the students depending on the different types of question posed. In this paper, we present our current results from an examination of the potential of using EEG data towards applying artificial intelligence for improvement of electronic assessments, as well as a technical platform for this purpose.
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