APPLYING DEEP LEARNING MODELS TO IDENTIFY THE SATISFACTION LEVEL OF LEARNERS
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”.
Keywords
deep learning methods, emotion detection, interest level, online teaching
Article Details
References
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