Leveraging Big Data Analytics for Cultural Teaching Competence in international Chinese Linguistic Learning using Weighted Random Forest Model

The teaching of Chinese language and culture has gained significant importance on the global stage due to China's growing influence in various domains. International teachers play a crucial role promoting cross-cultural understanding facilitating effective communication between non-Chinese speakers. This paper aims explore concept cultural competence for international teachers, with focus national context application framework supported by big data analytics. model uses Integrated Machine Learning Teaching Framework (iMLTF). constructs evaluation Language based National Context. iMLTF Multivariant examination integrated Weighted Random Forest model. simulation analysis expressed that proposed achieves higher classification accuracy value 98% compared conventional state-of-art techniques.