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A Multimodal Framework for Automated Teaching Quality Assessment of One-to-many Online Instruction Videos

Publication ,  Conference
Pan, Y; Wu, J; Ju, R; Zhou, Z; Gu, J; Zeng, S; Yuan, L; Li, M
Published in: Proceedings - International Conference on Pattern Recognition
January 1, 2022

In the post-pandemic era, online courses have been adopted universally. Manually assessing online course teaching quality requires significant time and professional pedagogy experience. To address this problem, we design an evaluation protocol and propose a multimodal machine learning framework1 for automated teaching quality assessment of one-to-many online instruction videos. Our framework evaluates online teaching quality from five aspects, namely Clarity, Classroom interaction, Technical management of online teaching, Empathy, and Time management. Our method includes mid-level behavior feature extraction, high-level interpretable feature extraction, and supervised learning prediction. Our automated multimodal teaching quality assessment system achieves comparable performance to human annotators on our one-to-many online instruction videos. For binary classification, the best average accuracy of five aspects is 0.898. For regression, the best average means square error is 0.527 on a 0-10 scale.

Duke Scholars

Published In

Proceedings - International Conference on Pattern Recognition

DOI

ISSN

1051-4651

Publication Date

January 1, 2022

Volume

2022-August

Start / End Page

1777 / 1783
 

Citation

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MLA
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Pan, Y., Wu, J., Ju, R., Zhou, Z., Gu, J., Zeng, S., … Li, M. (2022). A Multimodal Framework for Automated Teaching Quality Assessment of One-to-many Online Instruction Videos. In Proceedings - International Conference on Pattern Recognition (Vol. 2022-August, pp. 1777–1783). https://doi.org/10.1109/ICPR56361.2022.9956185
Pan, Y., J. Wu, R. Ju, Z. Zhou, J. Gu, S. Zeng, L. Yuan, and M. Li. “A Multimodal Framework for Automated Teaching Quality Assessment of One-to-many Online Instruction Videos.” In Proceedings - International Conference on Pattern Recognition, 2022-August:1777–83, 2022. https://doi.org/10.1109/ICPR56361.2022.9956185.
Pan Y, Wu J, Ju R, Zhou Z, Gu J, Zeng S, et al. A Multimodal Framework for Automated Teaching Quality Assessment of One-to-many Online Instruction Videos. In: Proceedings - International Conference on Pattern Recognition. 2022. p. 1777–83.
Pan, Y., et al. “A Multimodal Framework for Automated Teaching Quality Assessment of One-to-many Online Instruction Videos.” Proceedings - International Conference on Pattern Recognition, vol. 2022-August, 2022, pp. 1777–83. Scopus, doi:10.1109/ICPR56361.2022.9956185.
Pan Y, Wu J, Ju R, Zhou Z, Gu J, Zeng S, Yuan L, Li M. A Multimodal Framework for Automated Teaching Quality Assessment of One-to-many Online Instruction Videos. Proceedings - International Conference on Pattern Recognition. 2022. p. 1777–1783.

Published In

Proceedings - International Conference on Pattern Recognition

DOI

ISSN

1051-4651

Publication Date

January 1, 2022

Volume

2022-August

Start / End Page

1777 / 1783