AI education advocates the concept of: thousands of people. That is, you have used a combination of artificial intelligence, to receive education, then all your learning records, answer records are collected, through the artificial intelligence algorithm for analysis, through you to do the answer rate of the paper, the correct rate, statistical analysis of the data, know, you are currently the best at which topics, that is, it means that you learn better knowledge, the next time the AI will focus on the topics and knowledge that you are not good at, that is, you often do the wrong items of knowledge. Next time, AI will focus on the topics and knowledge that you are not good at, that is, the knowledge related to the topics that you often do wrong. The machine can remember the data of each person, according to analyze the data of each person, find the shortcomings of the learner, focus on his shortcomings. Thus, you can quickly target to improve the ability of the learner.

So, AI can do everyone's learning progress is not uniform, learning ability to learn fast, AI can automatically match the corresponding knowledge, you learn slow, then AI will be relatively speaking to your knowledge slower. This can improve the efficiency of education, people with strong learning ability, do not need to accommodate people with slow learning.

Feasibility

The feasibility of this AI-advocated teaching concept is very strong, and it's relatively easy to realize. In fact, just like the algorithmic recommendations of today's headlines, what do you like, what will be recommended to you? Because you often read a certain type of news, the headline will focus on pushing this type of news to you more. So, the same reason, change into learning is the same, if you answer a certain type of question is relatively bad, it will be considered that you learn in this area is relatively poor, the next time to push the learning knowledge, will focus on pushing the type of knowledge to you