Analysis of Affective Factors and Optimization Strategies of Emotion in Online Teaching Based on Improved SVM Model

Abstract

Online teaching has the advantages of not being limited by location and space but it also has some shortcomings. The lack of face-to-face real-time interaction between teachers and students will affect some students’ learning mood. The improved support vector machine (SVM) model is a simple model based on linear algebra, which can convert text data into structured data that can be processed by a computer and then calculate the similarity between two documents into the similarity between two vectors. The facial expression features of learners in the situation collected and extracted by the students of this project group are analyzed and modeled, and the time consumption, occupied space, and classification effect of the feature vectors produced by the improved model are integrated. The original feature dimension can be optimized from 100 dimensions to 60 dimensions, which not only saves the time of training feature vectors but also reduces the size of the final feature vectors. Besides, on the basis of 60-dimensional preliminary features extracted by SVM model, four classification models can also achieve the best results. Therefore, in the optimization part of feature extraction, the dimension of initial features extracted by SVM model is set to 60 dimensions. We can gradually use the improved SVM model to analyze the emotional influencing factors and optimization strategies in online teaching, so as to keep abreast of students’ lectures and let more students participate in online teaching as much as possible.

Classroom Video Image Emotion Analysis Method for Online Teaching Quality Evaluation

“…Online teaching has the advantage of not being limited by location and space, but it also has some disadvantages. Wu and Huwan [20] analyzed and modeled the facial expression features of learners in the situations collected and extracted by the students of the project group, and integrated the time consumption, space occupation and classification effect of feature vectors generated by the improved model. The literature [21] aims to verify the application effect of online automatic evaluation system in English translation teaching, and understand students' satisfaction with different feedback methods.…”

Retracted: Analysis of Affective Factors and Optimization Strategies of Emotion in Online Teaching Based on Improved SVM Model

“…Tis article has been retracted by Hindawi, as publisher, following an investigation undertaken by the publisher [1]. Tis investigation has uncovered evidence of systematic manipulation of the publication and peer-review process.…”