Prediction of Student Grades in College English WeChat Teaching Based on Collaborative LSTM-SVR Model
In recent years,with the continuous advancement of mobile internet technology both domestically and internationally,especially the emergence and promotion of the emerging industry of WeChat mini programs,in order to optimize the auxiliary English teaching mode of WeChat mini programs and provide data support for implementing teaching interventions,a collaborative LSTM-SVR model is used to predict students'final grades through learning process evaluation results,guide teachers to adjust teaching modes and strategies based on the predicted final grades of the process assessment.The results indicate that the predicted WeChat mini program as-sisted teaching assessment results have good accuracy,which helps to reflect the effectiveness of assisted teaching and adjust teaching in a timely manner.
WeChat mini programassisted English teachingcollaborative predictionteaching effective-ness
万方数据
维普
