Estimation of objective understanding measure based on student’s nonverbal behavior recognition in a person-to-person teaching situation

Ryo Miyoshi; Koichi Taguchi; Manabu Hashimoto

doi:10.1117/12.2521616

22 March 2019 Estimation of objective understanding measure based on student’s nonverbal behavior recognition in a person-to-person teaching situation

Ryo Miyoshi, Koichi Taguchi, Manabu Hashimoto

Author Affiliations +

Proceedings Volume 11049, International Workshop on Advanced Image Technology (IWAIT) 2019; 110493A (2019) https://doi.org/10.1117/12.2521616
Event: 2019 Joint International Workshop on Advanced Image Technology (IWAIT) and International Forum on Medical Imaging in Asia (IFMIA), 2019, Singapore, Singapore

Abstract

In this paper, we propose using image recognition techniques to estimate the “understanding measure” in person-toperson teaching situations. The phrase “understanding measure” refers to how strongly a teacher feels a student understands a topic. First, we extract a student’s nonverbal behavior (head movement, gazes, and blinking) as the features for the estimation process. Next, we calculate the subspace from the aforementioned feature by using principal component analysis (PCA) and linear discriminant analysis (LDA). Finally, we classify unknown data as either “understood” or “did not understand” by using a kNN classifier in subspace. Our experiments confirmed that the Fmeasure of the classification “understood” by our method was 0.75 and “did not understand” was 0.60, indicating that our method improved F-measures 0.38 and 0.11, respectively, compared with previous methods.

Citation Download Citation

Ryo Miyoshi, Koichi Taguchi, and Manabu Hashimoto "Estimation of objective understanding measure based on student’s nonverbal behavior recognition in a person-to-person teaching situation", Proc. SPIE 11049, International Workshop on Advanced Image Technology (IWAIT) 2019, 110493A (22 March 2019); https://doi.org/10.1117/12.2521616

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