IP Library Granted Patent US 9,763,613
Granted Patent B2
US 9,763,613 · App. 15/190,393 · Granted Sep 19, 2017

System and method for data anomaly detection process in assessments

Inventors: Eric Shepherd (Miami Beach, FL); John Kleeman (London, GB)
Assignee: Questionmark Computing Limited
A61B5/168A61B3/113A61B5/0022A61B5/0205A61B5/0476A61B5/11A61B5/164A61B5/4266A61B5/7278A61B5/024A61B5/026A61B5/0533A61B5/08
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Quick Facts
Patent No.
US 9,763,613
App. No.
15/190,393
Granted
Sep 19, 2017
Kind
B2
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 (54)

1. A computer-implemented method comprising:

identifying, by at least one computing device of one or more computing devices, at least one attribute of a user;

determining, by at least one computing device of the one or more computing devices, an attention level of the user with the identified at least one attribute during a learning process using learning material other than an assessment;

analyzing, by at least one computing device of the one or more computing devices, the attention level of the user; and

classifying, by at least one computing device of the one or more computing devices, an action of the user as an attention deficiency event using the analyzed attention level of the user, wherein the attention deficiency event includes an indication of possible lack of learning by the user during the learning process using the learning material.

2. The computer-implemented method of claim 1 wherein analyzing the attention level of the user includes at least one of:

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;

comparing the attention level of the user with a difficulty level of the action of the user; and

comparing an amount of time spent by the user to perform the action with the difficulty level of the action.

3. The computer-implemented method of claim 1 wherein the learning process includes compliance training.

4. The computer-implemented method of claim 3 further comprising documenting whether the compliance training has taken place based upon, at least in part, the attention level of the user.

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 learning process includes viewing the learning material via on screen learning.

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 at least one of a gaze detection, a bodily movement detection, an eye blink detection, a blood flow velocity, a heartbeat rate detection, a breathing detection, a brain electrical activity detection, a body posture detection, and a sweat detection.

9. The computer-implemented method of claim 8 wherein the attention level of the user is determined with a combination of at least two attributes of the user.

10. A computer program product residing on a non-transitory 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 during a learning process using learning material other than an assessment;

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, wherein the attention deficiency event includes an indication of possible lack of learning by the user during the learning process using the learning material.

11. The computer program product of claim 10 wherein analyzing the attention level of the user includes at least one of:

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;

comparing the attention level of the user with a difficulty level of the action of the user; and

comparing an amount of time spent by the user to perform the action with the difficulty level of the action.

12. The computer program product of claim 10 wherein the learning process includes compliance training.

13. The computer program product of claim 12 wherein the operations further comprise documenting whether the compliance training has taken place based upon, at least in part, the attention level of the user.

14. The computer program product of claim 10 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.

15. The computer program product of claim 10 wherein the learning process includes viewing the learning material via on screen learning.

16. The computer program product of claim 10 wherein the operations further comprise providing an alert of the attention deficiency event to at least one of the user and a second user.

17. The computer program product of claim 10 wherein the at least one attribute includes at least one of a gaze detection, a bodily movement detection, an eye blink detection, a blood flow velocity, a heartbeat rate detection, a breathing detection, a brain electrical activity detection, a body posture detection, and a sweat detection.

18. The computer program product of claim 17 wherein the attention level of the user is determined with a combination of at least two attributes of the user.

19. 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 during a learning process using learning material other than an assessment;

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, wherein the attention deficiency event includes an indication of possible lack of learning by the user during the learning process using the learning material.

20. The computing system of claim 19 wherein analyzing the attention level of the user includes at least one of:

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;

comparing the attention level of the user with a difficulty level of the action of the user; and

comparing an amount of time spent by the user to perform the action with the difficulty level of the action.

21. The computing system of claim 19 wherein the learning process includes compliance training.

22. The computing system of claim 21 wherein the operations further comprise documenting whether the compliance training has taken place based upon, at least in part, the attention level of the user.

23. The computing system of claim 19 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.

24. The computing system of claim 19 wherein the learning process includes viewing the learning material via on screen learning.

25. The computing system of claim 19 wherein the operations further comprise providing an alert of the attention deficiency event to at least one of the user and a second user.

26. The computing system of claim 19 wherein the at least one attribute includes at least one of a gaze detection, a bodily movement detection, an eye blink detection, a blood flow velocity, a heartbeat rate detection, a breathing detection, a brain electrical activity detection, a body posture detection, and a sweat detection.

27. The computing system of claim 26 wherein the attention level of the user is determined with a combination of at least two attributes of the user.

Assignments (3)
RELEASE OF SECURITY INTEREST Recorded Jan 16, 2025
From: HSBC INNOVATION BANK LIMITED, AS SUCCESSOR IN INTEREST TO SILICON VALLEY BANK, AS THE ADMINISTRATIVE AGENT
To: LEARNOSITY LIMITED; QUESTIONMARK COMPUTING LIMITED
Reel/Frame 069898/0223 →
SECURITY INTEREST Recorded Jun 9, 2021
From: LEARNOSITY LIMITED; QUESTIONMARK COMPUTING LIMITED
To: SILICON VALLEY BANK, AS ADMINISTRATIVE AND COLLATERAL AGENT
Reel/Frame 056488/0014 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 23, 2016
From: SHEPHERD, ERIC; KLEEMAN, JOHN
To: QUESTIONMARK COMPUTING LIMITED
Reel/Frame 038993/0928 →
Continuity (5)
Continuation 14141825 · Dec 27, 2013
Continuation In Part 13667425 · Nov 2, 2012
Provisional Application 61873443 · Sep 4, 2013
Provisional Application 61555748 · Nov 4, 2011
Related Publication 20160296152A1 · Oct 13, 2016