SYSTEM AND METHOD FOR DATA ANOMALY DETECTION PROCESS IN ASSESSMENTS

• US 20140114148A1
• Filed: 12/27/2013
• Published: 04/24/2014
• Est. Priority Date: 11/04/2011
• Status: Active Grant

• Current Assignee: Questionmark Computing Limited (Learnosity Ltd.)
• Original Assignee: Questionmark Computing Limited (Learnosity Ltd.)
• Inventors: Shepherd, Eric, Kleeman, John
• Granted Patent: US 9,439,593 B2
• Time in Patent Office: Days
• US Class Current: 600/301
• CPC Class Codes: A61B 3/113 for determining or recording eye movement
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/024 Detecting, measuring or recording pulse rate or heart rate A61B5/0205, A61B5/021 take precedence
• CPC Class Codes: A61B 5/026 Measuring blood flow A61B3/1233, A61B3/1241 take precedence
• CPC Class Codes: A61B 5/0533 Measuring galvanic skin response
• CPC Class Codes: A61B 5/08 Detecting, measuring or recording devices for evaluating the respiratory organs A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/11 Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb for measuring pulse A61B5/02 ;A61B5/1038 takes precedence; motion detection to correct for motion artifacts in physiological signals A61B5/721
• CPC Class Codes: A61B 5/163 by tracking eye movement, gaze, or pupil change
• CPC Class Codes: A61B 5/164 Lie detection
• CPC Class Codes: A61B 5/168 Evaluating attention deficit, hyperactivity
• CPC Class Codes: A61B 5/369 Electroencephalography [EEG] devices for psychotechnics A61B5/16
• CPC Class Codes: A61B 5/4266 sweat secretion
• CPC Class Codes: A61B 5/7278 Artificial waveform generation or derivation, e.g. synthesising signals from measured signals A61B5/327 takes precedence
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

A method, computer program product, and computer system for identifying at least one attribute of a user. An attention level of the user is determined with the identified at least one attribute. The attention level of the user is analyzed. An action of the user is classified as an attention deficiency event using the analyzed attention level of the user.

Claims

1. A computer-implemented method comprising:

identifying at least one attribute of a user;

determining an attention level of the user with the identified at least one attribute;

analyzing the attention level of the user; and

classifying an action of the user as an attention deficiency event using the analyzed attention level of the user.

2. The computer-implemented method of claim 1 wherein analyzing the attention level of the user includes comparing the attention level of the user with a second attention level, wherein the second attention level is from at least one of the user and a second user.

3. The computer-implemented method of claim 1 wherein analyzing the attention level of the user includes comparing the attention level of the user with a difficulty level of the action of the user.

4. The computer-implemented method of claim 3 wherein analyzing the attention level of the user further includes comparing an amount of time spent by the user to perform the action with the difficulty level of the action.

5. The computer-implemented method of claim 1 wherein analyzing the attention level of the user includes:

identifying the action of the user as requiring the attention level of the user to reach a threshold attention level; and

determining that the attention level of the user is less than the threshold attention level for the action of the user.

6. The computer-implemented method of claim 1 wherein the action of the user includes answering one or more questions.

7. The computer-implemented method of claim 1 further comprising providing an alert of the attention deficiency event to at least one of the user and a second user.

8. The computer-implemented method of claim 1 wherein the at least one attribute includes gaze detection.

9. The computer-implemented method of claim 1 wherein the at least one attribute includes bodily movement detection.

10. The computer-implemented method of claim 1 wherein the at least one attribute includes eye blink detection.

11. The computer-implemented method of claim 1 wherein the at least one attribute includes blood flow velocity.

12. The computer-implemented method of claim 1 wherein the at least one attribute includes heartbeat rate detection.

13. The computer-implemented method of claim 1 wherein the at least one attribute includes breathing detection.

14. The computer-implemented method of claim 1 wherein the at least one attribute includes brain electrical activity detection.

15. The computer-implemented method of claim 1 wherein the at least one attribute includes body posture detection.

16. The computer-implemented method of claim 1 wherein the at least one attribute includes sweat detection.

17. The computer-implemented method of claim 1 wherein the attention level of the user is determined with a combination of at least two attributes of the user.

18. The computer-implemented method of claim 1 wherein the attention deficiency event includes a lack of learning by the user during a learning process.

19. The computer-implemented method of claim 1 wherein the attention deficiency event includes cheating by the user during an assessment.

20. A computer program product residing on a computer readable medium having a plurality of instructions stored thereon which, when executed by a processor, cause the processor to perform operations comprising:

identifying at least one attribute of a user;

determining an attention level of the user with the identified at least one attribute;

analyzing the attention level of the user; and

classifying an action of the user as an attention deficiency event using the analyzed attention level of the user.

21. A computing system including a processor and memory configured to perform operations comprising:

identifying at least one attribute of a user;

determining an attention level of the user with the identified at least one attribute;

analyzing the attention level of the user; and

classifying an action of the user as an attention deficiency event using the analyzed attention level of the user.