TY - GEN
T1 - Fuzzy-Based Head Attitude Estimation for Improved Students’ Concentration Evaluation
AU - Zhou, Zheng
AU - Hirota, Kaoru
AU - Dai, Yaping
AU - Islam, Md Shariful
AU - Mersha, Bemnet Wondimagegnehu
AU - Dai, Wei
AU - Lin, Yumin
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
PY - 2025
Y1 - 2025
N2 - In order to evaluate students’ concentration in offline education, an algorithm based on fuzzy comprehensive evaluation is proposed. The algorithm evaluates students’ concentration by measuring their head attitude angle, which consists of three modules: face key points detection, head attitude angle measurement and concentration decision, and outputs the curve of students’ overall concentration score over time. Compared with other concentration evaluation methods, the proposed algorithm achieves the evaluation of overall students’ concentration under low pixel video and is suitable for most offline classrooms with monitoring devices. The overall functional effectiveness of the algorithm was tested with a classroom video dataset of 35 students. The algorithm outputs students’ concentration scores at 30 FPS, meeting the requirement of a real-time classroom. The algorithm’s scores were compared to the artificial scores of 15 experts, resulting in an average accuracy of 88.3% and a Pearson’s correlation coefficient of 0.936 between the two, thus validating the effectiveness of the algorithm. The proposed algorithm can provide educators with a reference for educational effectiveness and help to realize the automatic assessment of educational quality in the future.
AB - In order to evaluate students’ concentration in offline education, an algorithm based on fuzzy comprehensive evaluation is proposed. The algorithm evaluates students’ concentration by measuring their head attitude angle, which consists of three modules: face key points detection, head attitude angle measurement and concentration decision, and outputs the curve of students’ overall concentration score over time. Compared with other concentration evaluation methods, the proposed algorithm achieves the evaluation of overall students’ concentration under low pixel video and is suitable for most offline classrooms with monitoring devices. The overall functional effectiveness of the algorithm was tested with a classroom video dataset of 35 students. The algorithm outputs students’ concentration scores at 30 FPS, meeting the requirement of a real-time classroom. The algorithm’s scores were compared to the artificial scores of 15 experts, resulting in an average accuracy of 88.3% and a Pearson’s correlation coefficient of 0.936 between the two, thus validating the effectiveness of the algorithm. The proposed algorithm can provide educators with a reference for educational effectiveness and help to realize the automatic assessment of educational quality in the future.
KW - Concentration evaluation
KW - Fuzzy comprehensive evaluation
KW - Head attitude estimation
KW - Offline education
UR - http://www.scopus.com/inward/record.url?scp=105003857541&partnerID=8YFLogxK
U2 - 10.1007/978-981-96-4753-8_2
DO - 10.1007/978-981-96-4753-8_2
M3 - Conference contribution
AN - SCOPUS:105003857541
SN - 9789819647521
T3 - Communications in Computer and Information Science
SP - 14
EP - 28
BT - Computational Intelligence and Industrial Applications - 11th International Symposium, ISCIIA 2024, Proceedings
A2 - Xin, Bin
A2 - Ma, Hongbin
A2 - She, Jinhua
A2 - Cao, Weihua
PB - Springer Science and Business Media Deutschland GmbH
T2 - 11th International Symposium on Computational Intelligence and Industrial Applications, ISCIIA 2024
Y2 - 1 November 2024 through 5 November 2024
ER -