Conceptual Design of a Learning State Monitoring System Based on Lightweight Neural Network

With the popularity of online learning, effectively monitoring and enhancing students' learning state has become a key issue in the field of education. Emotion, as one of the important indicators of students' learning state, has received more and more attention. This study explores the effectiveness of MobileNetV2, a lightweight neural network, on emotion recognition, proposes a conceptual design of a learning state monitoring system based on lightweight neural network, and demonstrates in detail the architecture and functional design of the system, aiming to provide effective learning state monitoring and feedback support for students and teachers by monitoring and analysing students' emotions.