Learning system based on user biological curve and learning curve as well as method thereof

Abstract

The present invention discloses a learning system based on biological curves and learning curves of users, as well as the method thereof. The present invention uses the birth date of a user to establish a biological curve for showing a biological state cycle of the user, and generates a learning curve corresponding to a learning state cycle of the user through the learning operation time distribution accumulation of the user. On learning content configuration, content configuration control parameters corresponding to each index in the biological curve are determined at first by referring to the current time when the user carries out learning operation; then the learning state parameter of the user is determined according to the current time, and the content configuration control parameters are further adjusted through the learning state parameter; finally the configuration of learning content is realized. Therefore, the configuration of learning content in all aspects accords with the biological and learning states of the user, achieving the objective of promoting learning effect.

Description

technical field [0001] The present invention relates to a learning system and its method, in particular to a learning system and its method which can adjust the configuration of learning content according to the user's biological state and learning state. Background technique [0002] In the early days, the learning system often adopted a fixed system for the configuration of user learning content, that is, whenever the user wants to use the learning system to perform learning operations, the learning system will provide the user with predetermined learning content for learning, and the user can only passively Accept the learning content without the right to dominate. Due to the limited configuration of learning content, this kind of learning system does not meet the needs of some users who often need to plan learning content by themselves. [0003] Later, some learning systems appeared, mainly emphasizing that users can configure the learning content they need by themselve...

AI Technical Summary

Problems solved by technology

This kind of learning system, due to the limited configuration of learning content, makes it unsuitable for some users who often need to self-plan learning content

[0003] Later, some learning systems appeared, mainly emphasizing that users can configure the learning content they need by themselves. However, because users are not familiar with the configuration of learning content, users often spend a lot of money without knowing the configuration of learning content. More time to learn, but can't get the learning effect it should have

Furthermore, the configuration provided by this type of learning system often only provides users with a single-oriented configuration for the learning content, such as the configuration of local conditions on the learning theme or the choice of learning form, and cannot fully take into account various Oriented to the impact factors on the learning effect, so although it is more flexible than the early learning system, it does not seem to be of great help to really improve the learning effect

[0004] In fact, no matter in the learning of any knowledge field, the biggest key to whether the learning effect is significant or not lies in the user himself. No matter how rich and effective learning content configuration the learning system can provide, if the user himself is in a In the low-tide state of learning willingness, this state may not even be grasped by the user himself, even if there are more and better learning content configurations, it will not be able to exert the greatest effect, and of course the learning effect of the user will be greatly reduced

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