Impression Investigation of a Robot's Learning by Observing the Learner

Recently, research and development regarding education support robots has been conducted. In this study, we focus on a partner-type robot, such as a collaborative learner. According to a previous study, human learners lose likeability toward robots as learning advances, and thus, cannot perform collaborative learning with them. To address this problem, we must maintain the learner's likeability toward the robot. It is important to make the learner realize that they learn more with a robot. Therefore, this study develops a partner-type robot that learns by observing the learner. The proposed robot solves problems along with the learner in an alternating manner. When the learner solves the problem correctly, the robot learns the answer. Moreover, when the robot answers a question, it asks the learner whether the solution is correct. Thus, the robot emphasizes to the learner that it does observational learning. In addition, the robot makes the learner strongly realize that they learn with it. Thus, the robot can promote the learner's likeability toward itself. This study investigates the impression evaluation that a robot that learns by observing a learner gives to the learner. In impression evaluation, we evaluate likeability and perceived intelligence of the robot. The experimental result shows that our robot can improve the learner's likeability with itself via collaborative learning.