Abstract
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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
