Abstract:

Carl Ransom Rogers (1983) attributed learning to the result of the interaction of learners' behavior, cognition and emotion, and emphasized the influence of emotion on learners' learning motivation and interest. However, in the traditional classroom teaching, teachers are unable to perceive the emotional state of multiple students effectively, and students do not often pay attention to their own emotions in the learning process. So it is difficult to adjust the students' state of learning in a timely manner, and the learning effect is difficult to guarantee. Therefore, it is very important for learners to have a good emotional state in classroom teaching.

For students, It is difficult to accurately judge their own emotion while they are in a confused mood. Nowadays, brain waves have attracted more and more attention. By analysing the emotional information hidden in electroencephalogram data (Zhang & Wang, 2008), this technology can realize accurate emotional perception. In addition, because of the ability of visualizing abstract content (Cai, Wang, Yang, & Liu), and supporting learners' interaction, Augmented Reality (AR) has a powerful potential in visualizing complex emotional perception results.

Therefore, in this study, we attempt to use Muse headband to collect brainwave data. Through the emotional representation of α, β, δ and θ, we developed an AR application to display the main emotion in front of students in the scene of virtual and real fusion. During the in-field learning activity, students can pay attention to the virtual character on the screen, and try to change their emotional state. The aim of this research focuses on the problems of inability to timely perceive multiple students' emotional states for teachers and difficulties in emotional regulation for students in traditional teaching. We sent pre-test and post-test questionnaires to college students, and recruited 18 subjects to participate in empirical experiments and interviews. From the questionnaires and emotional data, it is found that accurate emotion recognition and visualization have a high demand among students. In addition, this application based on AR and brain waves abtains a high accuracy and a good visual effect, and has a positive impact on helping learners understand their emotional states and adjust their emotions.

Keywords:

Augmented Reality, Brain Waves, Learner's Emotion Recognition, Emotional Visualization.