# The Teacher-Student Chatroom Corpus

arXiv: https://arxiv.org/abs/2011.07109 · HTML: https://mlsanity.com/paper/2011.07109/

## Key facts

- Cited by 17 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Nov 2020.

## Built on by (most cited first, 17 of 17)

- [MathDial: A Dialogue Tutoring Dataset with Rich Pedagogical Properties Grounded in Math Reasoning Problems](https://mlsanity.com/paper/2305.14536/) (2023)
- [The AI Teacher Test: Measuring the Pedagogical Ability of Blender and GPT-3 in Educational Dialogues](https://mlsanity.com/paper/2205.07540/) (2022)
- [Grounding Gaps in Language Model Generations](https://mlsanity.com/paper/2311.09144/) (2023)
- [Opportunities and Challenges in Neural Dialog Tutoring](https://mlsanity.com/paper/2301.09919/) (2023)
- [The BEA 2023 Shared Task on Generating AI Teacher Responses in Educational Dialogues](https://mlsanity.com/paper/2306.06941/) (2023)
- [Strategize Before Teaching: A Conversational Tutoring System with Pedagogy Self-Distillation](https://mlsanity.com/paper/2302.13496/) (2023)
- [The StudyChat Dataset: Analyzing Student Dialogues With ChatGPT in an Artificial Intelligence Course](https://mlsanity.com/paper/2503.07928/) (2025)
- [TeachLM: Post-Training LLMs for Education Using Authentic Learning Data](https://mlsanity.com/paper/2510.05087/) (2025)
- [Assessing the efficacy of large language models in generating accurate teacher responses](https://mlsanity.com/paper/2307.04274/) (2023)
- [Pedagogy-driven Evaluation of Generative AI-powered Intelligent Tutoring Systems](https://mlsanity.com/paper/2510.22581/) (2025)
- [How About Kind of Generating Hedges using End-to-End Neural Models?](https://mlsanity.com/paper/2306.14696/) (2023)
- [ErAConD : Error Annotated Conversational Dialog Dataset for Grammatical Error Correction](https://mlsanity.com/paper/2112.08466/) (2021)
- [The ADAIO System at the BEA-2023 Shared Task on Generating AI Teacher Responses in Educational Dialogues](https://mlsanity.com/paper/2306.05360/) (2023)
- [Modeling the Quality of Dialogical Explanations](https://mlsanity.com/paper/2403.00662/) (2024)
- [Project MOSLA: Recording Every Moment of Second Language Acquisition](https://mlsanity.com/paper/2403.17314/) (2024)
- [EduDial: Constructing a Large-scale Multi-turn Teacher-Student Dialogue Corpus](https://mlsanity.com/paper/2510.12899/) (2025)
- [GeoDial: A Multimodal Conversational Tutoring Dataset for Geometry Problem-Solving with Visual Tutor Turns](https://mlsanity.com/paper/2606.12419/) (2026)

## Abstract (arXiv)

The Teacher-Student Chatroom Corpus (TSCC) is a collection of written conversations captured during one-to-one lessons between teachers and learners of English. The lessons took place in an online chatroom and therefore involve more interactive, immediate and informal language than might be found in asynchronous exchanges such as email correspondence. The fact that the lessons were one-to-one means that the teacher was able to focus exclusively on the linguistic abilities and errors of the student, and to offer personalised exercises, scaffolding and correction. The TSCC contains more than one hundred lessons between two teachers and eight students, amounting to 13.5K conversational turns and 133K words: it is freely available for research use. We describe the corpus design, data collection procedure and annotations added to the text. We perform some preliminary descriptive analyses of the data and consider possible uses of the TSCC.