Personalized Chinese Course Recommendation Model of Online Vocational Education Learning Platform based on Collaborative Filtering Algorithm

The current Chinese education system is mainly based on traditional teaching methods. Facts have proved that this method cannot meet the needs of students and their learning methods. In order to improve China's education system, it is necessary to find a new teaching method. One of the most effective methods is to use technology. Technology can help teachers and students interact more effectively, thus improving students' learning outcomes. This study aims to develop a personalized Chinese course recommendation model for online vocational education learning platform. In order to achieve this goal, the author uses collaborative filtering algorithm to analyze students' past experience and preferences to provide personalized Chinese courses. The study was conducted using data sets collected from actual case studies. This dataset contains information about students who have registered for online careers. First, we will use the KDD process to develop a problem statement and data collection plan. Secondly, we will use a priori method to analyze the data and build a database for further analysis. Third, we will apply different algorithms and use different methods to solve this problem.