Leveraging Emotion Recognition for Personalized Teaching Strategies
Keywords:
Emotion Recognition, Deep Learning, Adaptive Teaching, Real-Time Feedback, Facial Expression Analysis, Learning OutcomesAbstract
Emotions play a critical role in student learning, significantly
affecting academic performance. For instance, negative emotions
such as anxiety and frustration can impede cognitive processes,
while positive emotions like happiness enhance motivation and
cognitive engagement. This research proposes an emotion
recognition system utilizing deep learning and facial expression
analysis to enable adaptive teaching strategies. By detecting
emotions such as frustration, confusion, and engagement,
educators can adjust lesson delivery in realtime to better suit
student needs. The performance of the system is evaluated against
traditional manual observation methods, with its effectiveness in
improving real-time teaching adjustments discussed.
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