A Study on Predicting International Students’ Academic Chinese Writing Ability Based on BPNN Algorithm

Abstract

We evaluated the Chinese academic writing ability of international students. To evaluate it accurately and objectively, we adopted a data mining method. The research process included establishing indicators for assessing the Chinese writing ability of international students, modeling, and validating the model. The prediction model was constructed based on the Back Propagation (BP) neural network to predict the academic Chinese writing ability of international students. Five evaluation indicators were selected as inputs for the model, and the model output the predicted ability. Multiple tests demonstrated the stability and reliability of the model. It can be used for analyzing the academic Chinese writing ability of international students and providing data support for the development and advancement of international Chinese language education. The research results are innovative in that they establish a prediction model for assessing the Chinese writing ability of international students.