tutoring Digital Futures Demonstrator project: Semi-automated math coaching –using NLP to extend mattecoach
Title: tutoring Digital Futures Demonstrator project: Semi-automated math coaching –using NLP to extend mattecoach
DNr: Berzelius-2023-170
Project Type: LiU Berzelius
Principal Investigator: Kathy Tian <kathyt@kth.se>
Affiliation: Kungliga Tekniska högskolan
Duration: 2023-06-19 – 2024-01-01
Classification: 10202
Homepage: https://www.digitalfutures.kth.se/research/demonstrator-projects/semi-automated-math-tutoring/


This project aims to develop and study a demonstrator of semi-automated online math tutoring by combining a human approach and automated tutoring. The automation will be based on Natural Language Processing analysis of previous tutor-student interactions. To evaluate the semi-automated tutoring concept, we will conduct a randomized controlled trial by randomly assigning students into a treatment group where tutoring is semi-automated and to a control group with only human online tutoring. We will also conduct a thematic comparative analysis of student-automated tutor interaction compared to student-human tutor. The findings will contribute to research on semi-automated tutoring, a scientific area that has received limited attention. The semi-automated approach could have a great societal impact because tutors can help more students. The project will serve as an example of beneficially using semi-automation without losing the human touch of tutoring. It has been known for decades that one-to-one tutoring is a very effective teaching method, although the key challenge is to scale it up. Maths Coach Online (mattecoach.se) has been offering one-to-one tutoring by teacher students to K-12 students using chat and interactive whiteboard since 2009 and has conducted more than 70,000 tutoring conversations. Currently, we are transforming Maths Coach Online into a national service, which makes the issue of scaling to a larger volume of students important. Therefore, we are interested in exploring how to support high-quality math learning for as many students as possible by incorporating semi-automated intelligent tutoring.