Blended College English Teaching Model and Evaluation based on MOOC

Main Article Content

Jingbo Hao
Wulian Wei


MOOC teaching has been developing rapidly in the context of COVID-19, and its teaching quality has become the focus of social attention. Therefore, this study analyzes the blended college English teaching model based on MOOC by constructing a teaching evaluation model. The co-occurrence rate index is used to improve the K-modes algorithm, and then the important index in the teaching mode is extracted. The neural network is used to construct the prediction model of student learning effect, which reflects the advantages and disadvantages of the teaching mode. Through experimental analysis, the accuracy of the improved K-modes algorithm in the model reaches 0.985. The recall rate reached 0.982; The average error of the prediction model is less than 1 in the error analysis. Therefore, the model accurately reflects the problems existing in the teaching model, and has a high prediction accuracy, indicating that the teaching evaluation model has a good evaluation effect.

Article Details

Special Issue - Scalable Computing in Online and Blended Learning Environments: Challenges and Solutions