Interest is thought to be one of the major and a basic emotion according to psychologists. The effect of interest was emphasized recently for its role in improving and predicting many life aspects e.g. learning and education, economy, psychological well-being and social relations. However, majority of the recent studies are theoretical and only few of them addressed interest but without specifying its types physiologically. The purpose of this research is to present an approach to detect patterns of situational interest while resembling classroom environment using EEG signals. Personal Interest (PI) test, Situational Interest (SI) test and knowledge tests are used to evaluate subjectively student's interest. Fast Fourier Transform (FFT) was applied for EEG data after preprocessing and cleaning. Absolute power values and power ratio of EEG waves were used to verify similar patterns of subjects who reported high SI. The results from the objective analysis was used to interpret the subjective analysis and was found that the power ratio of alpha/beta and alpha/high beta might be an index for situational interest regardless of the status of personal interest. © 2017 IEEE.