A Study on the Construction of a Predictive Model for Physical Education Teachers’ Professional Development Trajectories Supported by ARIMA Algorithm Driven by Physical Education Reforms

Abstract

The professional development of physical education teachers is the direction and basic requirement of modern education development, which is better promoted by strengthening the tracking and prediction of the trajectory of the professional development of physical education teachers. In this paper, a combined ARIMA-LSTM model is established to visualize the PE teachers’ professional development trajectory by predicting their professional development scores, using the advantages of ARIMA model in handling linear time series data, while combining the powerful ability of LSTM network in capturing the long-term dependency of data. Three physical education teachers were randomly selected as research subjects to predict their PE teacher professional development trajectories. The root mean square error (RMSE) and mean absolute percentage error (MAPE) values were used as the assessment indexes of the model, and the MAPE and RMSE of the ARIMA-LSTM model were less than those of the ARIMA model and the LSTM model for the physical education teachers in No. 1 and No. 3. And on the prediction of physical education teacher No. 2, the MAPE comparison of ARIMA-LSTM model and LSTM model increased by 1.12%, but the RMSE decreased by 73.4563, and the prediction curve of the professional development score was close to the original sequence, and the ARIMA-LSTM model still showed better prediction effect.