An online evaluation model for classroom teaching quality in universities based on facial expression features
In response to the low recognition rate and strong subjectivity of the online evaluation model for classroom teaching quality in universities,a facial expression based online evaluation model for classroom teaching quality in universities is proposed.Extract facial expression features from university classroom classrooms,use image layers,S1 layers,C1 layers,S2 layers,and C2 layers for feature matching and selection.Use Bayesian classification models to optimize the smoothing parameters of feature images,determine a prior probability of usage,judge students'status,and evaluate classroom quality.The experimental results show that the evaluation rate of the proposed evaluation model is better than that of traditional evaluation models.Within 10 to 30 minutes,students have the highest listening rate.Therefore,key and difficult problems can be explained within 10 to 30 minutes to improve teaching quality.
facial expression featuresBayesian classificationteaching qualityquality online evaluationevaluation model
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