Individual teaching has been considered as the most successful educational form since ancient times. This form still continues its existence nowadays within intelligent systems intended to provide adapted tutoring for each student. Although, recent research has shown that emotions can affect student's learning, adaptation skills of tutoring systems are still imperfect due to weak emotional intelligence. To enhance ongoing research related to the improvement of the tutoring adaptation based on both student's knowledge and emotional state, the paper presents an analysis of emotion recognition methods used in recent developments. Study reveals that sensor-lite approach can serve as a solution to problems related to emotion identification accuracy. To provide ground-truth data for emotional state, we have explored and implemented a self-assessment method.