MONITORING LEARNING PERFORMANCE USING NEUROFEEDBACK

• US 20180075772A1
• Filed: 09/09/2016
• Published: 03/15/2018
• Est. Priority Date: 09/09/2016
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Carr, Kevin Gerard, Das, Payel
• Granted Patent: US 10,839,712 B2
• Time in Patent Office: Days
• CPC Class Codes: A61B 5/0075 by spectroscopy, i.e. measuring spectra, e.g. Raman spectroscopy, infrared absorption spectroscopy A61B5/0071 takes precedence
• CPC Class Codes: A61B 5/02028 Determining haemodynamic parameters not otherwise provided for, e.g. cardiac contractility or left ventricular ejection fraction
• CPC Class Codes: A61B 5/14551 for measuring blood gases
• CPC Class Codes: A61B 5/168 Evaluating attention deficit, hyperactivity
• CPC Class Codes: A61B 5/375 using biofeedback
• CPC Class Codes: A61B 5/4064 Evaluating the brain A61B5/031, A61B5/369, A61B5/14553 take precedence
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: G09B 19/00 Teaching not covered by other main groups of this subclass teaching or practice apparatus for gun-aiming or gun-laying F41G3/26
• CPC Class Codes: G09B 19/06 Foreign languages with audible presentation of material to be studied G09B5/04
• CPC Class Codes: G09B 5/08 providing for individual presentation of information to a plurality of student stations
• CPC Class Codes: G09B 7/02 of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by a student

Abstract

Techniques that facilitate monitoring learning performance using neurofeedback are described. In one embodiment, a system is provided that comprises a memory that stores computer-executable components and a processor that executes computer-executable components stored in the memory. In one implementation, the computer-executable components comprise a feedback component that receives first feedback information regarding mental function of a user in association with participation in a learning experience, wherein the first feedback information is captured via a NIRS spectroscopy sensor worn by the user. The computer-executable components further comprise an assessment component that determines learning performance information for the user based on the first feedback information, wherein the learning performance information reflects the user'"'"'s learning of content presented to the user in the learning experience, and a notification component that generates a notification based on the learning performance information indicating the user'"'"'s learning of the content is below a defined learning performance level.

Claims

1. A system, comprising:

a memory that stores computer executable components;

a processor that executes the computer executable components stored in the memory, wherein the computer executable components comprise;

a feedback component that receives first feedback information regarding mental function of a user in association with participation in a learning experience, wherein the first feedback information is captured via a near-infrared spectroscopy sensor worn by the user;

an assessment component that determines learning performance information for the user based on the first feedback information, wherein the learning performance information reflects user learning of content presented to the user in the learning experience; and

a notification component that generates a notification based on the learning performance information indicating the user learning of the content is below a defined learning performance level.

2. The system of claim 1, wherein the user is a first user, and wherein based on generation of the notification, the notification component further sends the notification to a first external device associated with the first user or a second external device associated with a second user responsible for facilitating learning of the content by the first user.

3. The system of claim 1, wherein the user is a first user, and wherein the notification component further sends the notification to a second device associated with a second user based on reception of a request, by the system from the second device, for the notification, wherein the second user is responsible for facilitating learning of the content by the user.

4. The system of claim 1, wherein the learning performance information comprises learning performance levels of the user with respect to defined cognitive function areas associated with the mental function of the user.

5. The system of claim 4, wherein the defined cognitive function areas are selected from a group consisting of working memory, mental effort, and attention.

6. The system of claim 4, wherein the assessment component further determines if one or more of the learning performance levels for one or more cognitive function areas of the defined cognitive function areas are below a threshold value, and wherein the notification component generates the notification based on a determination that the one or more of the learning performance levels are below the threshold value, thereby facilitating improved processing time for determining if the user is having difficulty learning the content and for notifying a second user regarding the user'"'"'s difficulty.

7. The system of claim 1, wherein the first feedback information comprises haemodynamic information selected from a group consisting of working memory performance levels, stress levels and attention levels of the user.

8. The system of claim 1, wherein the first feedback information comprises metabolic information representative of a mental function area selected from a group consisting of working memory performance levels, stress levels, and attention levels of the user.

9. The system of claim 1, wherein the feedback component further receives second feedback information regarding the mental function of the user in association with the participation in the learning experience, wherein the second feedback information is captured via an electroencephalogram sensor worn by the user, and wherein the assessment component further determines the learning performance information for the user based on the first feedback information and the second feedback information, wherein the learning performance information comprises learning performance levels of the user with respect to defined cognitive function areas associated with the mental function of the user.

10. The system of claim 9, wherein the defined cognitive function areas are selected from a group consisting of:

attention, familiarity, mental effort, working memory, linguistic acquisition, social learning, and mediation.

11. The system of claim 1, wherein the user is a first user, and the computer-executable components further comprise:

a review component that stores the learning performance information and facilitates review of the learning performance information by the first user or a second user responsible for facilitating learning of the content by the first user.

12. A computer implemented method, comprising:

receiving, by a device operatively coupled to a processor, first feedback information regarding mental activity of a user in a learning environment, wherein the first feedback information is captured via a near-infrared spectroscopy sensor worn by the user; and

determining, by the device, learning performance information for the user based on the first feedback information, wherein the learning performance information comprises learning performance levels of the user with respect to defined cognitive function areas associated with the mental activity of the user; and

generating, by the device, a notification based on the learning performance information indicating user learning performance is below a defined learning performance level.

13. The computer implemented method of claim 12, wherein the user is a first user, wherein the method further comprises:

sending, by the device based on the generating the notification, the notification to a first external device associated with the first user or a second external device associated with a second user responsible for facilitating learning of the content by the first user.

14. The computer implemented method of claim 12, wherein the defined cognitive function areas are selected from a group consisting of working memory, mental effort, and attention.

15. The computer implemented method of claim 12, further comprising:

determining, by the device, if one or more of the learning performance levels for one or more cognitive function areas of the defined cognitive function areas are below a threshold value, wherein the generating the notification comprises generating the notification based on a determination that the one or more of the learning performance levels are below the threshold value, and wherein the notification identifies the user, the one or more cognitive function areas, and the learning performance levels for the one or more cognitive function areas.

16. The computer implemented method of claim 12, wherein the first feedback information comprises haemodynamic information selected from a group consisting of working memory performance levels, stress levels and attention levels of the user.

17. The computer implemented method of claim 12, further comprising:

receiving, by the device, second feedback information regarding the mental activity of the user in the learning environment, wherein the second feedback information is captured via an electroencephalogram sensor worn by the user, and wherein the determining the learning performance information comprises determining the learning performance information for the user based on the first feedback information and the second feedback information.

18. The computer implemented method of claim 12, wherein the defined cognitive function areas are selected from a group consisting of:

attention, familiarity, mental effort, working memory, linguistic acquisition, social learning, and mediation.

19. A computer program product for monitoring learning performance based on neurofeedback, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processing component to cause the processing component to:

receive neurofeedback information regarding mental function of a user in a learning context, wherein the neurofeedback information is captured via a near-infrared spectroscopy sensor worn by the user;

determine learning performance information for the user based on the neurofeedback information, wherein the learning performance information reflects the user learning of content presented to the user in the learning context;

generate a notification based on the learning performance information indicating the user learning of the content is below a defined learning performance level; and

send the notification to a device associated with an entity responsible for teaching the content to the user to facilitate improving the user'"'"'s learning of the content.

20. The computer program product of claim 19, wherein the learning performance information comprises learning performance levels of the user with respect to defined cognitive function areas associated with the mental function of the user, wherein the defined cognitive function areas comprise one or more of:

attention, familiarity, mental effort, working memory, linguistic acquisition, social learning, and mediation.