User profiles

• US 20080133437A1
• Filed: 06/07/2007
• Published: 06/05/2008
• Est. Priority Date: 11/30/2006
• Status: Active Grant

• Current Assignee: ITI Scotland Limited (Scottish Government)
• Original Assignee: ITI Scotland Limited (Scottish Government)
• Inventors: Foster, Andrew, Shaw, Craig, Bacchus, Phil, Astheimer, Peter, Setty, David
• Granted Patent: US 7,937,348 B2
• Time in Patent Office: Days
• US Class Current: 706/15
• CPC Class Codes: G09B 7/04 characterised by modifying the teaching programme in response to a wrong answer, e.g. repeating the question, supplying a further explanation
• CPC Class Codes: H04L 67/306 User profiles

Abstract

A system is disclosed for correlating user profiles to software applications. The system may be adapted as part of a software system that interrogates a user profile and reading a learning objective as a first input, interrogates a software application and reading a learning objective as a second input, calculates a relevance of the first input learning objective to the second input learning objective, and adapts the software application in accordance with the determined relevance and/or updating the user profile in accordance with the determined relevance. A method is disclosed that correlates user profiles to software applications by reading a first learning objective from a user profile, reading a second learning objective from a software application, determining a relevance of the first to the second learning objective, and adapting the software application in accordance with the determined relevance and/or updating the user profile in accordance with the determined relevance.

Claims

1. An instruction set in machine readable code for a computer comprising:

a system for interrogating a user profile and reading a learning objective as a first input;

a system for interrogating a software application and reading a learning objective as a second input;

a calculation component for determining a relevance of the first input learning objective to the second input learning objective; and

a system for adapting the software application in accordance with the determined relevance and/or updating the user profile in accordance with the determined relevance.

2. The instruction set of claim 1, wherein said system for adapting the software application comprises instructions for applying a weighting factor to at least one of existing experience data in the user profile related to the learning objective of the software application and performance data related to the subsequent use of the software application.

3. The instruction set of claim 1, wherein the calculation component comprises a semantic profiling component adapted to determine a quantitative similarity of meaning between the first input learning objective and the second input learning objective for use as the relevance.

4. The instruction set of claim 3, wherein the semantic profiling component comprises a predefined relevance look up table (LUT) for the comparison of one learning objective with the other to obtain the quantitative similarity.

5. The instruction set of claim 3, wherein the semantic profiling component comprises a thesaurus comprising clusters of similar terms.

6. The instruction set of claim 5, wherein the thesaurus is further provided with an indication of the degree of similarity of each cluster or individual term.

7. The instruction set of claim 3, wherein the semantic profiling component comprises a search engine for querying a predefined resource or an on-line search engine and then learning the closeness of the two input terms from the results.

8. The instruction set of claim 1, wherein the learning objectives can be viewed by a facilitator and modified manually.

9. The instruction set of claim 1, comprising a profile update component for receiving user performance data and an updated learning objective from a software application, and then translating said performance data and said updated learning objective back into a user profile.

10. The instruction set of claim 9, wherein said translation step uses a weighting factor which is the inverse of the weighting factor used for adapting the software application.

11. The instruction set of claim 1, wherein the user profile is a team profile.

12. The instruction set of claim 1, wherein the user profile is part of a composite team profile.

13. The instruction set of claim 1, wherein the weighting factor takes into account a level-of-activity factor calculated on the basis of at least one of:

the number of attempts that have been made to perform certain actions in a given software application, the elapsed time and the degree of success or failure.

14. The instruction set of claim 1, further comprising a data gathering component to gather statistical data.

15. The instruction set of claim 14, wherein the statistical data comprises at least one of:

high scores low scores, average scores, median scores, standard deviation of scores, most popular combination of first and second learning objective, least popular combination of first and second learning objective.

16. The instruction set of claim 14 or claim 15, the statistical data is computed for groups of users with similar attributes.

17. The instruction set of claim 16, wherein the groups of users with similar attributes correspond to high or low achieving groups.

18. The instruction set of claim 1, wherein said software application comprises one or more measured objectives formed from a related group of software application measurements;

and is adapted for the assessment of a learning objective, said learning objective being formed from;

the selection of one or more measured objectives;

defined outcome conditions for the measured objectives; and

selected outcome activities that each invoke a command in the learning application.

19. The instruction set of claim 1, executed on a server computer that controls the operation of the software application.

20. The instruction set of claim 1, executed on a client or user computer.

21. The instruction set of claim 1, stored as part of the user profile.

22. The instruction set of claim 1, wherein the software application is at least one of:

a game, a learning application, a games based learning application or a training simulation.

45. A software system comprising a software application for the assessment of a learning objective and an instruction set according to claim 1.

23. A method of correlating user profiles to software applications comprising the steps of:

reading a first learning objective from a user profile;

reading a second learning objective from a software application;

determining a relevance of the first learning objective to the second learning objective; and

adapting the software application in accordance with the determined relevance and/or updating the user profile in accordance with the determined relevance.

24. The method of claim 23, wherein said step of adapting the software application comprises applying a weighting factor to at least one of existing experience data in the user profile related to the learning objective of the software application and performance data related to the subsequent use of the software application.

25. The method of claim 23, wherein the step of determining a relevance of the first learning objective to the second learning objective comprises determining a quantitative similarity of meaning therebetween.

26. The method of claim 25, wherein the step of determining a quantitative similarity of meaning between the first and second learning objectives comprises performing a look-up operation to interrogate a predefined relevance look up table (LUT).

27. The method of claim 25, wherein the step of determining a quantitative similarity of meaning between the first and second learning objectives comprises interrogating a thesaurus comprising clusters of similar terms.

28. The method of claim 27, wherein the thesaurus is further provided with an indication of the degree of similarity of each cluster or individual term.

29. The method of claim 25, wherein the step of determining a quantitative similarity of meaning between the first and second learning objectives comprises an interrogating search engine to query a predefined resource or an on-line search engine and then learning the closeness of the two input terms from the results.

30. The method of claim 23, wherein the learning objectives can be viewed by a facilitator and modified manually.

31. The method of claim 23, further comprising the step of receiving user performance data and an updated learning objective from a software application, and then translating said performance data and said updated learning objective back into a user profile.

32. The method of claim 31, wherein the step of translating said performance data back into a user profile comprises the use of a weighting factor which is the inverse of the weighting factor used for adapting the software application.

33. The method of claim 23, wherein the user profile is a team profile.

34. The method of claim 23, wherein the user profile is part of a composite team profile.

35. The method of claim 23, wherein the weighting factor takes into account a level-of-activity factor calculated on the basis of at least one of:

the number of attempts that have been made to perform certain actions in a given software application, the elapsed time and the degree of success or failure.

36. The method of claim 23, further comprising the step of gathering statistical data.

37. The method of claim 36, wherein the statistical data comprises at least one of:

high scores, low scores, average scores, median scores, standard deviation of scores, most popular combination of first and second learning objective, least popular combination of first and second learning objective.

38. The method of claim 36, wherein the statistical data is computed for groups of users with similar attributes.

39. The method of claim 38, wherein the groups of users with similar attributes correspond to high or low achieving groups.

40. The method of claim 23, wherein said software application comprises one or more measured objectives formed from a related group of software application measurements;

and is adapted for the assessment of a learning objective, said learning objective being formed from;

the selection of one or more measured objectives;

defined outcome conditions for the measured objectives; and

selected outcome activities that each invoke a command in the learning application.

41. The method of claim 23, executed by a server computer that controls the operation of the software application.

42. The method of claim 23, executed by a client or user computer.

43. The method of claim 23, executed by the user profile.

44. The method of claim 23, wherein the software application is at least one of:

a game, a learning application, games based learning application, or training simulation.

46. A computer program product comprising a computer useable medium having program logic stored thereon, the program logic comprising machine readable code executable by a computer, the machine readable code comprising instructions for performing the steps according to claim 23.