Real-Time Facial Emotion Analysis for Adaptive Teaching Strategies Using Deep Learning:

V. Suganthi Vels Institute of Science, Technology, and Advanced Studies, India M. Yogeshwari Vels Institute of Science, Technology, and Advanced Studies, India https://orcid.org/0009-0001-2627-4814 Real-Time Facial Emotion Analysis for Adaptive Teaching Strategies Using Deep Learning

Facial emotion extraction is a process of identifying and extracting emotional information from human facial expressions. Due to its potential applications in a variety of fields, including psychology, marketing, and human-computer interaction, this technology has been gaining popularity recently. Technology for detecting facial expressions can be applied to smart classrooms to improve students' learning. By analyzing the emotions of students, teachers can gain insights into how engaged and attentive students are during the lesson and adjust their teaching style accordingly. This can help to improve the learning outcomes of students and create a more dynamic and engaging classroom environment. Facial emotion detection technology can be integrated into existing classroom tools, such as video conferencing software or smart boards. Students' facial expressions can be analyzed in real-time to identify emotions such as happiness, sadness, confusion, or boredom. This data can then be used to provide feedback to teachers about the effectiveness of their lesson and the engagement level of students. All papers found during the search will also sentence to review the current situation and pinpoint any potential gaps.
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