Prediction of English teachers’ professional development based on data mining and time series model

English is a basic required course in colleges and universities. Different from other majors, students majoring in English usually have to pass CET-4, IELTS, and TOEFL. Therefore, both English majors and teachers have necessary feature vectors. Using data mining technology to predict the professional development direction of English major students from the perspective of big data is the goal of this paper. Based on a convolutional neural network and sequential model algorithm, the career development prediction model is established, and its accuracy is evaluated. It proves that the prediction effect of the model has the value of continuing in-depth research, and then the prediction model is further optimized. Finally, based on the design and development of the optimization model of English major students’ career development prediction software, the prediction model is analyzed and studied based on the real data of the school.