On the role of politeness in online human–human tutoring

Researchers have demonstrated that dialoguebased intelligent tutoring systems (ITS) can be effective in assisting students in learning. However, little research has attempted to explore the necessity of equipping dialogue-based ITS with one of the most important capabilities of human tutors, that is, maintaining polite interactions with students, which is essential to provide students with a pleasant learning experience. In this study, we examined the role of politeness by analysing a large-scale real-world dataset consisting of over 14K online human–human tutorial dialogues. Specifically, we employed linguistic theories of politeness to characterise the politeness levels of tutor–student-generated utterances, investigated the correlation between the politeness levels of tutors' utterances and students' problem-solving performance and quantified the power of politeness in predicting students' problem-solving performance by applying Gradient Tree Boosting. The study results showed that: (i) in the effective tutorial sessions (ie, sessions in which students successfully solved problems), tutors tended to be very polite at the start of a tutorial session and become more direct to guide students as the session progressed; (ii) students with better performance in solving problems tended to be more polite at the beginning and the end of a tutorial session than their counterparts who failed to solve problems; (iii) the correlation between tutors' polite expressions and students' performance was not