Analysis Of Influencing Factors Of User Participation In Online Education Courses In China

Online education provides high-quality learning opportunities for learners and is conducive to the formation and promotion of a learning society in China.Obviously,online education has become a hot area for Internet companies,and the market prospects are very broad.However,with the rapid development,it has also fallen into an increasingly fierce competition.The problems of homogeneity and mass of online education products and services,as well as the low participation of registered users,have gradually emerged.In this case,online education platforms should actively explore the various factors affecting user participation,and attach importance to user accumulation and exploration.And improve the learning model,adopt different promotion models in different types of courses,continuously improve the quality of the course content,focus on how to effectively improve product user stickiness and loyalty,and accurately locate in order to attract the appropriate user population and develop sustainable Used online education products.This article starts with a literature review of previous research on user participation in online education courses.From the perspective of online education platforms,it constructs the factors that influence user participation from the traditional online education course learning resources,teachers,and platforms.Several indicators such as course introduction,course duration,and course progress were selected.In addition,this article considers that online education courses are a service-oriented product.Users have intuitive feelings about user reviews on online education websites.The number of reviews and course rating indicators.These two indicators reflect the degree of user feedback.The higher the degree of feedback,the more comprehensive the information the user understands,and the user’s participation will be affected.Then crawl the relevant data on the website of China’s mainstream online education platform,and display the data visually after preprocessing.From the descriptive analysis of the data,you can intuitively find the course category,whether the course is paid,the number of reviews and other factors.Will affect user engagement.On this basis,in order to avoid the shortcomings of the under-fitting and low model interpretation ability in the simple linear regression algorithm,an ensemble learning algorithm model was selected,and three methods were used to model the random forest,GBDT,and XGBoost.Analyze and compare,determine the key factors to increase user participation in online education,and finally,explore the differences between two types of paid free courses and courses that attract users at different course progress.According to the importance of the variables of the XGBoost model,the number of learning evaluations,course progress,whether paid courses and duration have a significant impact on user participation in online education,and whether there is a course introduction and whether art courses have an impact on user participation.Big.At the same time,the impact of class progress,course grading,and course source platform factors on user participation is regulated by whether courses are paid.Under different class progress,whether paid courses,teacher profiles,and course source platform factors affect user engagement.There are significant differences.Based on the research conclusions,the author suggests that the online education platform should combine its own advantages,optimize the platform’s technical support,provide a comfortable learning environment,actively encourage users to participate in online reviews,open course discussion forums,and set course types and pricing reasonably around the courses Additional factors such as form and teacher are developed vigorously to realize the rapid and sustainable development of the platform,so that more users can participate in online learning.