The Sleepiness of International Students in Online Chinese Classroom: An Experimental Study Based on Hybrid Technology of Facial Feature Point Distribution Model

Abstract

The study presented in this article is a ground-breaking investigation into the quick advancement of intelligent online language instruction based on wireless communication networks, learner physiological and psychological alterations;to predict and prompt learners’ sleepiness, a hybrid technology of facial feature point distribution model is applied to the process of online learning of Chinese for international students. This technology aids teachers in timely monitoring and discovering learners’ levels of sleepiness in the process of online learning and adjusting it, ensuring effective teacher-student interaction and the accomplishment of learning objectives in the classroom. The following specific designs are carried out in order to increase the contribution of teaching and training samples to the classification effect: (1) To train the neural network classifier and ensure more stable and accurate recognition results, the system employs the particle swarm optimization approach with adaptive parameter adjustment; (2) A simulated annealing technique is suggested to address the premature convergence flaw of the conventional particle swarm optimization algorithm, and an adjustable inertia weight factor is created to enhance the optimization capability of particle swarm optimization; (3) A PSO-SVM based facial expression recognition system based on multi-scale wavelet transform theory and support vector regression machine is created in order to further enhance the network’s generalization capability. The simulation findings demonstrate some improvement in the convergence of the two widely used face recognition techniques. Additionally, this study provides a principal component analysis approach based on DCT coefficient singular decomposition and a texture feature selection method based on LDA model in an effort to apply wavelet analysis theory to face recognition. Highlights A system for predicting and prompting learners’ sleepiness in online foreign language classroom teaching is constructed In the case of being unable to actively integrate into online classroom teaching, learners are prone to lack of concentration, sleepiness, even anxiety, irritability and facial muscle twitching Eye fatigue identified at a distance of 0.3–1.5 m from ordinary cameras is relatively easy to identify The appearance of a large proportion of tired students in the online classroom suggests that teachers should adjust the teaching design scheme The reasons leading to the burnout of online learners are very complex, and it still needs interdisciplinary in-depth research