Abstract
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.
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CITATION STYLE
Chen, J., Li, H., Wang, W., Ding, W., Huang, G. Y., & Liu, Z. (2019). A multimodal alerting system for online class quality assurance. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11626 LNAI, pp. 381–385). Springer Verlag. https://doi.org/10.1007/978-3-030-23207-8_70
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