# A Multimodal Alerting System for Online Class Quality Assurance

arXiv: https://arxiv.org/abs/1909.11765 · HTML: https://mlsanity.com/paper/1909.11765/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Sep 2019.

## Built on by (most cited first, 2 of 2)

- [Multi-Task Learning based Online Dialogic Instruction Detection with Pre-trained Language Models](https://mlsanity.com/paper/2107.07119/) (2021)
- [An Educational System for Personalized Teacher Recommendation in K-12 Online Classrooms](https://mlsanity.com/paper/2107.07124/) (2021)

## Abstract (arXiv)

Online 1 on 1 class is created for more personalized learning experience. It demands a large number of teaching resources, which are scarce in China. To alleviate this problem, we build a platform (marketplace), i.e., Dahai to allow college students from top Chinese universities to register as part-time instructors for the online 1 on 1 classes. To warn the unqualified instructors and ensure the overall education quality, we build a monitoring and alerting system by utilizing multimodal information from the online environment. Our system mainly consists of two key components: banned word detector and class quality predictor. The system performance is demonstrated both offline and online. By conducting experimental evaluation of real-world online courses, we are able to achieve 74.3% alerting accuracy in our production environment.