Practical RST Tutor
|
For a course I took called, 'Personalized Online Learning', I worked on a team to design an online tutoring system called 'Practical RST Tutor'. Rhetorical Structure Theory, also known as RST, is a method of annotation that focuses on identifying relations between sentences. Annotation is commonly used to identify patterns and elements in computer generated text, which can then be converted into a format to feed Machine Learning algorithms. Many annotators are unfamiliar with RST and learning the method can be quite dry and laborious. It typically involves mulling over academic papers and websites, which is a generally un-engaging process. Identifying a need to enhance the RST learning process, we decided to build an engaging online adaptive tutor to help annotators learn this method more efficiently. This tutor relies on CTAT, Cognitive Tutor Authoring Tools, a software designed to help create tutors and track student progress.
Related Publication: Shiyan Jiang, Kexin Yang, Chandrakumari Suvarna, Pooja Casula, Mingtong Zhang, and Carolyn Rosé. 2019. Applying Rhetorical Structure Theory to Student Essays for Providing Automated Writing Feedback. In Proceedings of the Workshop on Discourse Relation Parsing and Treebanking 2019, pages 163–168, Minneapolis, MN. Association for Computational Linguistics. |
Project Year:
2018 Project Team: Kexin Yang Mingtong Zhang Pooja Casula Project Advisors: Vincent Aleven Jonathan Sewall |