APPLYING DEEP LEARNING MODELS TO IDENTIFY THE SATISFACTION LEVEL OF LEARNERS

Hồng Thúy Vũ Lê , Viết Hưng Nguyễn , Huy Hoàng Trịnh

Main Article Content

Abstract

Based on the students’ expressions, teachers will know whether the lesson activities are attractive or boring, appropriately adjust their teaching. In online teaching, teachers and learners interact through computer screens. Therefore, assessing learners' satisfaction is mainly based on facial emotions. Today, thanks to deep learning, the facial recognition of emotions has had positive results and holds an important position in computer vision and artificial intelligence. The study proposes a deep learning model that detects facial emotions to help identify learners’ interest levels. The training is based on the separately collected data set “HSTVK-EMO”.

 

Article Details

References

Chang, K. Y., Chen, C. S., & Hung, Y. P. (2013, October). Intensity rank estimation of facial expressions based on a single image. In 2013 IEEE International Conference on Systems, Man, and Cybernetics (pp. 3157-3162). IEEE.
Dandıl, E., & Özdemir, R. (2019). Real-time Facial Emotion Classification Using Deep Learning. Data Science and Applications, 2(1).
Ekman, P. (1971). Universals and cultural differences in facial expressions of emotion. In Nebraska symposium on motivation. University of Nebraska Press.
Majeed, M. A., & Srayyih, M. N. (2018). Using neural network for recognition handwritten indian numbers. Misan Journal of Academic Studies, 17(33-2).
Park, B. J., Jang, E. H., Kim, S. H., Huh, C., & Sohn, J. H. (2012, April). Seven emotion recognition by means of particle swarm optimization on physiological signals: Seven emotion recognition. In Proceedings of 2012 9th IEEE International Conference on Networking, Sensing and Control (pp. 277-282). IEEE.
Sfetcu, N. (2020), Models of Emotion, A partial translation of: Sfetcu, Nicolae, "Emoțiile și inteligența emoțională în organizații". MultiMedia Publishing (ISBN 978-606-033-328-9).
Tran, S. H., & Le, H. T., & Nguyen, T. T. (2018). Phan lop anh dua tren to hop da dac trung [Image Classification Based On Multiple Feature Combination]. Ho Chi Minh City University Of Education Journal Of Science, 15(12), 67-81.
Rinn, W. E. (1984). The neuropsychology of facial expression: a review of the neurological and psychological mechanisms for producing facial expressions. Psychological bulletin, 95(1), 52.