Design a Robot as a Double with Micro-expression to Participate in a Virtual Situational Learning Environment and its Effect on Students' Learning Performance

One way to encourage students to keep on practicing and studying learning materials is to let them be aware of how they will perform if they are placed in the situational evaluation. Thus, there should be a mechanism to act as a double that can be trained and revised by students so they can watch, monitor, and learn their own performances. Besides, emotional intelligence has gained a lot of attention due to its potential in maintaining situational interactions. Such a skill can detect the micro-expression to grasp the true feelings and hence students can take the appropriate responses. Therefore, this study proposes a learning approach, where students can collaboratively design the robot as their double with micro-expression to participate in situational evaluation tests. To evaluate the effectiveness of the proposed approach, a quasi-experiment was conducted with 90 undergraduate students who enrolled in a Hospitality Japanese course in Taiwan. Three classes were assigned randomly with different learning approaches. The experiment results indicated that the groups with a robot as a double showed significant positive effects in terms of learning motivation and anxiety. Furthermore, a group of students using a double robot with micro-expression exhibited better learning achievement, but their anxiety was also increased. Finally, the limitations of the study and some suggestions for improvement of this proposed approach are provided.