Primary supervisor

Guanliang Chen

Politeness plays an important part in facilitating people's daily communication. There have been quite some studies developed to demonstrate that polite communication is beneficial for instructors to build solidarity and rapport with students, which, in turn, facilitate students to learn and gain better performance. However, it remains largely unexplored to what extent instructors and teachers provide polite feedback to students in educational discussion forums.

Student cohort

Double Semester

Aim/outline

This project aims to apply Natural Language Processing techniques to characterize the politeness levels displayed by instructors and teachers in their replies to students' posts on Moodle at Monash University. In addition, this project will apply Deep Learning to develop methods to converted a non-polite reply to a polite one and further investigate the quality and utility of such converted replies in teaching and learning practices.

URLs/references

  • Danescu-Niculescu-Mizil, C., Sudhof, M., Jurafsky, D., Leskovec, J., & Potts, C. (2013). A computational approach to politeness with application to social factors. arXiv preprint arXiv:1306.6078.
  • Jionghao Lin, David Lang, Haoran Xie, Dragan Gašević, and Guanliang Chen. Investigating the Role of Politeness in Human-Human Online Tutoring. The International Conference on Artificial Intelligence in Education (AIED), 2020.

Required knowledge

  • Strong programming skills (e.g., Python)
  • Basic knowledge in Data Science, Natural Language Processing, and Machine Learning
  • The following can be a plus: (i) good at academic writing; and (ii) strong motivation in pursing a quality academic publication.