Advancing Chinese proficiency evaluation in universities with big data analytics

With the rapid development of information technology, the application of big data analysis in the field of education has gradually become a research hotspot. The purpose of this study is to explore the application of big data analysis in the evaluation of college Chinese learning effectiveness. By collecting, processing and analyzing students' learning data, we can deeply explore the characteristics of the subject, provide personalized teaching support, and realize the comprehensive evaluation of students' overall subject level. The research adopts the methods of students' basic information, big data collection, outlier processing, missing data processing, statistical analysis, machine learning algorithm and other stages, and combines data visualization technology to conduct in-depth research on students' academic performance. The research results show that big data analysis can provide a comprehensive and accurate evaluation method for Chinese education. Through the analysis of students' learning progress, it is found that the overall trend of students is gradually rising, and some fluctuations are also found, which provides guidance clues for personalized teaching. In terms of knowledge mastery, the research results show the contribution of different knowledge points to students' overall discipline mastery, which provides clues for identifying weak links in the discipline. The findings of this study provide a scientific, objective and comprehensive evaluation method for Chinese education and a more effective teaching support tool for educators.