Recently, Human-Robot Interaction (HRI) researchers have paid lots of attentions on the conversational robots that can provide didactic or pedagogy teachings, especially for the children and young adolescents with cognitive disabilities, such as autism and epilepsy. The research and developments of such robots for educational purposes are investigated intensively. Above all the difficult challenges, how to evaluate the effectiveness of a conversational robot, which mimics a teacher communicating with a student, to improve the performance of learning and studying, is the key factor to deploy such robots in our society and be widely adopted. However, we haven't seen much investigation in previous literatures so far. In order to bridge the gap, this preliminary study had explored the use of conversational robot with electroencephalogram (EEG) biosignals as evidence measurements to improve the self-learning performance during COVID-19 pandemic crisis, while the schools are forced to close, and the students are inevitably segregated in social isolations. We had collected 10 student participants' EEG data, which were calculated to find concentration levels, and then the robot had conversations with the students adaptively according to his/her concentration levels. The result showed that the conversations between robot and humans, who are constantly not concentrating on the learning tasks, could effectively increase his/her level of concentrations.