Research on the construction of xiang yang online education platform based on big data

Although the emergence of online education institutions makes the allocation of educational resources more reasonable to a certain extent, and also promotes the reform and development of education, these exist some problems such as solidified and not targeted course content, private absorption of the institutional students by teachers and exorbitant course fees. By considering the above issues, our organization takes the junior and senior high school students as service customers to supply online tutoring after class, and has constructed a series of innovative schemes: by collecting and cleaning a large number of data from the online learning platform of institutions, the characteristics of online learning behavior of students are extracted and meanwhile data mining and big data analysis technologies are used to study the learning process in order to carry out personalized teaching for each student. The partner system and feedback mechanism are adopted to encourage teachers to innovate teaching and actively absorb students for institutions. The system of part-time teaching for college students is applied to reduce the cost and the burden of their parents. From the results of institutional revenue forecast (including risk), the sales forecast is more optimistic, and the innovation strategy is better.