Application of Data Mining Based on Wireless Sensor Networks in Emotional Recognition and English Online Teaching

ABSTRACT With the rapid progress of educational informatization and computer networks, online course teaching resources play a very important role in actual classrooms. Currently, people from all walks of life are paying increasing attention to online teaching. As a new technology for online learning, online teaching will become an important model for future classroom teaching reform. In the network teaching environment, it is important to cultivate learners' innovative thinking and critical thinking ability, and emotional change is a crucial factor. However, due to the inability to conduct face‐to‐face teaching, learners' emotions are difficult to accurately recognize. Now, the above research results can be used in the evaluation of English classroom quality, and the decision tree can be used as a basis to better build the evaluation index set of the English online teaching system. The algorithm proposed in this paper has shown significant improvement in the accuracy of emotional recognition for learners in English online teaching. Experiments have shown that the method proposed in this paper is effective and can more accurately reflect the learners' emotional state. By identifying the emotions of English online teaching learners, their learning effectiveness can be evaluated, which can greatly improve the progress and quality of English teaching.