In recent years, with the deepening of application of big data in the industry, the education field has ushered in new opportunities and challenges.Big data thinking and ideas can provide an objective basis and new research perspectives for theoretical research, such as optimization of educational policies, innovation of education and teaching models, and changes in educational measurement and evaluation methods, and can better promote changes in the education field.The development of big data on education has become a strategic choice to promote and deepen reforms and innovations in the education field in China.
With respect to the education big data service, by adopting the unique model of ToB+ToC and combining the commercial consumer personalized analysis model / capacity that it is adept at with educational business features, HCR provides personalized analysis and effective teaching / upgrade strategy services targeted at K12 schools / students through the productization services of partners.
Teaching situation analysis, forward-looking early warning decision-making, promotion of guiding strategies, and forecast of crossing-the-line rate and distribution of middle schools and high schools
Improving the rate of enrollment, improving the inter-school ranking, management of academic performance, teaching and research
Diagnosing the situation mastered, improving the excellent and support of the poor purposefully, improving the marks rapidly during the sprint period, and customizing personalized improvement services for the candidates
The daily examination data and teaching quality research data of the jurisdiction are collected before being integrated into third-party data sources and precipitating in the big data pool for the academic district for the purpose of forecast of crossing-the-line rate and distribution of middle schools and high schools. Besides, the critical students of each school are identified, and guiding promotion strategies are recommended.
Through performance management and collection, light cross-school joint examination collection (real-time comparison), and resource labeling management (school-based question bank construction), the school's critical students are identified and an overall promotion strategy is developed. Besides, recommendations are provided for teaching and formation of individualized, small class groups, in addition to ability assessment conducted for inter-school students and gaining of insight into the teachers' teaching ability / defect portrait.
Through analysis and summarization of the answering data (daily exams, cross-school joint exams, assignments and online classrooms) and various research data, the poor are identified for purposes of formulation of promotion strategies, recommendation of self-adaptive reinforcement tests, and offer of comprehensive learning ability recommendations.
Through the education big data, schools are helped to carry out in-depth analysis of the critical students and develop personalized promotion strategies.
The program draws on business logic as well as the characteristics of education business. Through quantitative analysis of the data, comprehensive knowledge of students' subject knowledge and capabilities, hobbies, personality, psychology, social circles as well as data on their behaviors in the family, class and school is acquired. Based on the quantitative data, the big data modeling and analysis technology is used to carry out in-depth analysis and give suggestions and strategies for improvement.View more
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