Apparatus for supporting learning based on real time brain wave and learning state and operation method for the same

1 . An operation method for a learning support apparatus, which is performed by a processor, the operation method comprising:

measuring a first brain wave signal in a resting state of a subject, and measuring a second brain wave signal in a learning state of test content;

determining a learning state measurement index of the subject based on the second brain wave signal;

determining a learning success criterion of the subject based on the second brain wave signal classified into learning success and learning failure for the test content of the subject;

measuring a third brain wave signal of the subject while learning content is provided to the subject; and

determining a learning policy for the learning content based on a result of analyzing the third brain wave signal using learning success criterion and the learning state measurement index,

wherein the process of determining the learning policy comprises:

predicting whether the subject succeeds in learning in the learning content based on the result of analyzing the third brain wave signal using the learning success criterion;

evaluating a learning state of the subject in learning in the learning content based on the result of analyzing the third brain wave signal of the subject using the learning state measurement index in response to predicting that the subject fails to succeed in learning in the learning content and a total number of predicted failures for the learning content is higher than a preset criterion; and

increasing a provision ratio of the learning content in a total learning contents in response to the learning state being higher than a second preset criterion, and determining the learning policy to store the learning content as an important list.

2 . The operation method for a learning support apparatus of claim 1 , wherein the learning content is text-based and the process of determining a learning policy comprises:

determining the learning policy to decrease a provision ratio of the learning content in total learning contents or increase a difficulty of the total learning contents when the success is predicted to be successful.

3 . The operation method for a learning support apparatus of claim 1 , wherein the process of determining a learning policy comprises:

determining the learning policy to increase a provision ratio of the learning content in total learning contents or decrease a difficulty of the total learning contents when the success is predicted to be failed and a total number of predicted failures for the learning content is less than a first preset criterion.

4 . The operation method for a learning support apparatus of claim 1 , wherein the learning state measurement index and the learning state are determined based on a concentration of the subject and an emotional state of the subject (VAD value).

5 . The operation method for a learning support apparatus of claim 1 , wherein the learning content is video-based . . . and the process of determining a learning policy comprises:

predicting a probability of success in learning in the learning content based on the result of analyzing the third brain wave signal using the learning success criterion;

evaluating a learning state of the subject in learning in the learning content based on the result of analyzing the third brain wave signal of the subject using the learning state measurement index;

evaluating a level of learning for the learning content based on the probability of success and the learning state; and

determining the learning policy to perform re-learning of the learning content based on the level of learning.

6 . The operation method for a learning support apparatus of claim 5 , further comprising:

evaluating the level of learning for each preset section of the video-based learning content and determining a section to recommend re-learning.

7 . The operation method for a learning support apparatus of claim 5 , wherein the determining of the learning policy to perform re-learning of the learning content includes

determining the learning policy to recommend re-learning of the learning content or essentially perform re-learning based on a result obtained by comparing the level of learning with third and fourth preset criterions.

8 . A learning support apparatus comprising:

a processor; and

a memory electrically connected to the processor and storing at least one code executed by the processor,

wherein when the memory is executed through the processor, the processor

measures a first brain wave signal in a resting state of a subject, and measures a second brain wave signal in a learning state of test content,

determines a learning state measurement index of the subject based on the second brain wave signal,

determines a learning success criterion of the subject based on the second brain wave signal classified into learning success and learning failure for the test content of the subject,

measures a third brain wave signal of the subject while learning content is provided to the subject, and

stores a code causing to determine a learning policy for the learning content based on a result of analyzing the third brain wave signal using learning success criterion and the learning state measurement index,

wherein the learning content is text-based and in the process of determining the learning policy, the processor is configured to:

predict whether the subject succeeds in learning in the learning content based on the result of analyzing the third brain wave signal using the learning success criterion;

evaluate a learning state of the subject in learning in the learning content based on the result of analyzing the third brain wave signal of the subject using the learning state measurement index in response to predicting that the subject fails to succeed in learning in the learning content and a total number of predicted failures for the learning content is higher than a preset criterion; and

increase a provision ratio of the learning content in a total learning contents in response to the learning state being higher than a second preset criterion, and determine the learning policy to store the learning content as an important list.