Peer tutoring, in which one student teaches material to another student, has been shown to increase learning. In particular, there can be significant learning gains for the person taking on the role of the teacher if they can engage in reflective knowledge building as they tutor. Unfortunately, it is difficult to find other students who can play this role and it is likely that students would tend not to believe it if adults played the role.
We propose that a suitable social robot could believably play the role of ignorant learner, while in reality it would already understand the concept being taught and so could subtly guide the student teacher with its behaviors and modes of interaction (often referred to as “back leading”).
Just as important as helping students cognitively is to help them emotionally: providing encouragement and helping students maintain focus, build confidence, persevere, overcome frustration, etc. To do so, the robot needs to infer the student’s affective (emotional) state and provide suitable feedback to either reinforce positive affect or counter negative affect. By detecting these emotional states in students and providing affective feedback and encouragement, personalized to the individual student, we believe that a robot learner would help strengthen the students’ confidence in teaching the subject and general interest in learning.