Abstract
Traditional English teaching model neglects student emotions, making many tired of learning. Machine learning supports end-to-end recognition of learning emotions, such that the recognition system can adaptively adjust the learning difficulty in English classroom. With the help of machine learning, this paper presents a method to extract the facial expression features of students in business English class, and establishes a student emotion recognition model, which consists of such modules as emotion mechanism, signal acquisition, analysis and recognition, emotion understanding, emotion expression, and wearable equipment. The results show that the proposed emotion recognition model monitors the real-time emotional states of each student during English learning; upon detecting frustration or boredom, machine learning will timely switch to the contents that interest the student or easier to learn, keeping the student active in learning. The research provides an end-to-end student emotion recognition system to assist with classroom teaching, and enhance the positive emotions of students in English learning.
Highlights
Emotions are the psychological states and emotional responses of a person to things based on the person’s subjective experience in a certain environment
Based on machine learning and business English class, this paper proposed a student facial expression feature extraction method and constructed a student emotion recognition model to obtain the emotional states of learners of business English class
The emotion recognition system monitors the emotional states of students during English learning in real time
Summary
Emotions are the psychological states and emotional responses of a person to things based on the person’s subjective experience in a certain environment. In terms of the defining of machine learning environment, during the learning of business English, students can learn and practice in a purposeful, planned, and organized way, develop their knowledge and ability in English recognition, understanding and communication, and use emotions to express their business English learning during this process [15, 16]. Based on machine learning and business English class, this paper proposed a student facial expression feature extraction method and constructed a student emotion recognition model to obtain the emotional states of learners of business English class
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