Machine Learning-Based Student Emotion Recognition for Business English Class

Authors

  • Yuxin Cui Beijing Forestry University
  • Sheng Wang Beijing Forestry University
  • Ran Zhao Beijing Institute of Economics and Management

DOI:

https://doi.org/10.3991/ijet.v16i12.23313

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.

Author Biographies

Yuxin Cui, Beijing Forestry University

Yuxin Cui is studying in Beijing Forestry University with a Bachelor’s degree in Business English. Her main research interest is Business English

Sheng Wang, Beijing Forestry University

Sheng Wang received his bachelor’s degree in computer science and technology from Beijing Forestry University, in 2019. He is currently pursuing the master's degree in Computer science and technology, with a focus on few-shot learning. His research interests include machine learning, software develop, program design, remote sensing

Ran Zhao, Beijing Institute of Economics and Management

Ran Zhao graduated from Beijing Forestry University with a Master's degree in English translation. She is currently a full-time teacher of English at Beijing Institute of Economics and Management. Her main research interest is English teaching

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Published

2021-06-18

How to Cite

Cui, Y., Wang, S., & Zhao, R. (2021). Machine Learning-Based Student Emotion Recognition for Business English Class. International Journal of Emerging Technologies in Learning (iJET), 16(12), pp. 94–107. https://doi.org/10.3991/ijet.v16i12.23313

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Papers