2020 China AI + Education Industry Development Report

Source:iResearchApril 24,20204:34 PM Overview

Development Background of China’s AI+ Education Industry

Definition of AI+ Education

Application of AI technology in educational scenarios

The definition of "AI + education" should return to the core of technology, centering around basic data, core algorithms, and service purposes. Meanwhile, it should also return to the starting point of education activities, focusing on educational goals and evaluation methods. In this report, "AI + Education" means that under the conditions of the deep integration and development of AI and education, the application of AI-based on the educational scenarios serves as a path to promote educational equity, improve education quality, and achieve personalized education. "AI + Education" is a collection of technologies, models, and practices of AI applied in the field of education. It can be divided into "computing intelligence + education", "perception intelligence + education" and "cognition intelligence + education", which means AI + education is developing from "storage and computing" to "listening, speaking, watching and understanding" and will achieve" understanding and thinking "in the end.

Contents

Online after-school education is booming, and the informationization of school education is developing steadily. Capital and market drive the upgrade of the consumption experience. Policies and technologies promote the improvement of service quality. Both the school education market and the after-school education market urgently need intelligent solutions to accelerate education modernization to promote education equity, improve education quality, and realize education individualization.
The players can be divided into 5 groups with different strengths. The penetration rates in the four kinds of scenarios are different. In the To C area, the application of AI is high in the peripheral teaching links and low in the core teaching links. and in the To B area, the commercial application in management and exam scenarios is fast, but the underlying data is not ready yet. It's not time to realize customized education for students.

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