Adaptive problem selection

• US 6,270,352 B1
• Filed: 04/16/1999
• Issued: 08/07/2001
• Est. Priority Date: 04/16/1999
• Status: Expired due to Fees

• Current Assignee: Youngstar Learning Technologies, Inc.
• Original Assignee: Youngstar Learning Technologies, Inc.
• Inventors: Ditto, James W.
• Primary Examiner(s): Martin-Wallace, Valencia
• Assistant Examiner(s): ADAMS, CHANDA L
• Application Number:
  US09/293,220
• Time in Patent Office: 844 Days
• Field of Search: 434/322, 434/323, 434/350, 434/362, 434/118, 434/188
• US Class Current: 434/118
• 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

A method and apparatus for selecting a category from a plurality of categories, where each category comprises a number of elements, and corresponds to a category performance determinant that represents a measurement associated with a given category, and where a category performance determinant biases the selection of a given category.

Claims

1. An apparatus for selecting a category, comprising

a. a number of computer readable media;

and

b. computer readable program code stored on said number of computer readable media, said computer readable program code comprising;

i. program code for determining a category performance determinant for each of a plurality of categories, wherein said each of a plurality of categories comprises a number of elements, and wherein;

(1) a given category performance determinant corresponds to a given one of said plurality of categories; and

(2) said given category performance determinant represents a measurement associated with said given one of said plurality of categories; and

ii. program code for making a biased random selection of a category, wherein each category performance determinant biases the selection of its corresponding category in said biased random selection.

2. Apparatus as in claim 1, wherein said number of elements in said each of said plurality of categories is one.

3. Apparatus as in claim 1, wherein each of said number of elements is a problem.

4. Apparatus as in claim 3, wherein said each of said number of elements is the same problem type.

5. Apparatus as in claim 3, wherein said category performance determinant represents a percentage of problems mastered in said given one of said plurality of categories.

6. Apparatus as in claim 5, wherein said percentage of problems mastered in said category is determined by calculating an average of:

a. a percentage of problems mastered for speed; and

b. a percentage of problems mastered for accuracy.

7. Apparatus as in claim 5, wherein said given category performance determinant biases the selection of its corresponding category in said biased random selection such that a probability of selecting said corresponding category is higher than a different category if a category performance determinant corresponding to said corresponding category is greater than a category performance determinant corresponding to said different category.

8. Apparatus as in claim 1, wherein said category performance determinant represents at least one of a plurality of measurements, said plurality of measurements comprising:

a. a number of points;

b. a number of orders; and

c. a dollar amount.

9. Apparatus as in claim 1, wherein said computer readable program code additionally comprises program code for selecting an element from a selected category, wherein said category comprises a plurality of elements.

10. Apparatus as in claim 1, further comprising a processor operably configured to execute said computer readable program code stored on said computer readable media.

11. An apparatus for selecting a category, comprising:

a. means for determining a category performance determinant for each of a plurality of categories, wherein;

i. a given category performance determinant corresponds to a given one of said plurality of categories; and

ii. said given category performance determinant is a measurement associated with said given one of a plurality of categories; and

b. means for making a biased random selection of a category, wherein said biased random selection means comprises means for each category performance determinant to bias the selection of its corresponding category in said biased random selection.

12. An apparatus for selecting a problem, comprising:

a. a number of computer readable media; and

b. computer readable program code stored on said number of computer readable media, said computer readable program code comprising;

i. program code for determining a performance number for each of a plurality of problems, wherein;

(1) a given performance number corresponds to a given one of said plurality of problems;

(2) said given performance number represents a student'"'"'s performance on said given one of said plurality of problems; and

ii. program code for making a biased random selection of a problem, wherein each performance number biases the selection of its corresponding problem in said biased random selection.

13. Apparatus as in claim 12, further comprising a processor operably configured to execute said computer readable program code stored on said computer readable media.

14. Apparatus as in claim 12, wherein said given performance number represents the number of consecutive times said student has correctly solved said given one of said plurality of problems.

15. Apparatus as in claim 14, wherein said given performance number biases the selection of its corresponding problem in said biased random selection such that a probability of selecting said corresponding problem is higher than a different problem if a first performance number representing the number of consecutive times said student has correctly solved said corresponding problem is less than a second performance number representing the number of consecutive times said student has correctly solved said different problem.

16. Apparatus as in claim 15, wherein each of said given plurality of problems is a counting problem type.

17. Apparatus as in claim 12, wherein said given performance number represents an average time it takes said student to solve said given one of said plurality of problems.

18. Apparatus as in claim 17, wherein said given performance number biases the selection of its corresponding category in said biased random selection such that a probability of selecting said corresponding problem is higher than a different problem if a first performance number representing an average time it takes said student to solve said corresponding problem is greater than a second performance number representing an average time it takes said student to solve said different problem.

19. Apparatus as in claim 18, wherein each of said plurality of problems is one of a plurality of problem types, said problem types comprising addition, subtraction, multiplication, division, and counting by multiples.

20. Apparatus as in claim 12, wherein a performance number corresponding to a given one of said plurality of problems is an average of said student'"'"'s performance on said given one of said plurality of problems, wherein said student'"'"'s performance on said given one of said plurality of problems:

a. comprises said student'"'"'s performance on one or more single presentations of said given one of said plurality of problems; and

b. is determined after each of said one or more single presentations of said given one of said plurality of problems.

21. Apparatus as in claim 12, wherein a number of said performance numbers is varied to increase a probability of selecting said number of corresponding problems, wherein said number of corresponding problems are problems not selected on a given problem selection.

22. Apparatus as in claim 12, wherein said given performance number biases the selection of its corresponding problem in said biased random selection such that a probability of selecting said corresponding problem is higher than a different problem if a performance number corresponding to said corresponding problem is less than a performance number corresponding to said different problem.

23. Apparatus as in claim 12, wherein said given performance number biases the selection of its corresponding problem in said biased random selection such that a probability of selecting said corresponding problem is higher than a different problem if a performance number corresponding to said corresponding problem is greater than a performance number corresponding to said different problem.

24. Apparatus as in claim 12, wherein a selected problem is a problem to be solved.

25. Apparatus as in claim 12, wherein a selected problem is a subpart of a problem to be solved.

26. Apparatus as in claim 25, wherein said problem to be solved is one of a plurality of problem types, said plurality of problem types comprising advanced addition, advanced subtraction, advanced multiplication, long division, and counting by multiples.

27. Apparatus as in claim 12, wherein said performance number corresponding to a given one of said plurality of problems represents at least one of a plurality of measurements.

28. Apparatus as in claim 27, said at least one of a plurality of measurements comprising:

a. the number of consecutive times said student has correctly solved said given one of said plurality of problems; and

b. an average time it takes said student to correctly solve said given one of said plurality of problems.

29. Apparatus as in claim 12, wherein said plurality of problems is a subset of a problem set, wherein the number of problems in a said subset is greater if said student'"'"'s performance on problems in said problem set is greater, and said number of problems in a said subset is lower if said student'"'"'s performance on problems in said problem set is lower.

30. An apparatus as in claim 12, wherein said each of said plurality of problems is one of a plurality of subjects, said subjects comprising:

a. math;

b. spelling;

c. geography; and

d. chemistry.

31. An apparatus for selecting a problem, comprising:

a. means for determining a performance number for each of a plurality of problems, wherein;

i. a given performance number corresponds to a given one of said plurality of problems; and

ii. said given performance number is a measurement of a student'"'"'s performance on said given one of said plurality of problems; and

b. means for making a biased random selection of a problem, wherein said biased random selection means comprises means for a performance number to bias the selection of its corresponding problem in said biased random selection.

32. Apparatus as in claim 31, wherein said bias means comprises means for said given performance number to bias the selection of its corresponding problem in said biased random selection such that said corresponding problem has a higher probability of being selected than a different problem if a performance number corresponding to said corresponding problem is less than a performance number corresponding to said different problem.

33. Apparatus as in claim 31, wherein said bias means comprises means for said given performance number to bias the selection of its corresponding problem in said biased random selection such that said corresponding problem has a higher probability of being selected than a different problem if a performance number corresponding to said corresponding problem is greater than a performance number corresponding to said different problem.

34. A method for selecting a problem, comprising:

a. determining a performance number for each of a plurality of problems, wherein;

i. a given performance number corresponds to a given one of a plurality of problems; and

ii. said given performance number represents a student'"'"'s performance on said given one of a plurality of problems; and

b. making a biased random selection of a problem, wherein each performance number biases the selection of its corresponding problem in said biased random selection.

35. A method as in claim 34, wherein a given performance number biases the selection of its corresponding problem in said biased random selection such that said corresponding problem has a higher probability of selection than a different problem if a performance number corresponding to said corresponding problem is less than a performance number corresponding to said different problem.

36. A method as in claim 34, wherein a given performance number biases the selection of its corresponding problem in said biased random selection such that said corresponding problem has a higher probability of selection than a different problem if a performance number corresponding to said corresponding problem is greater than a performance number corresponding to said different problem.

37. A method for selecting a category, comprising:

a. determining a category performance determinant for each of a plurality of categories, wherein;

i. a given category performance determinant corresponds to a given one of a plurality of categories; and

ii. said given category performance determinant represents a measurement associated with said given one of a plurality of categories; and

b. making a biased random selection of a category, wherein each category performance determinant biases the selection of its corresponding category in said biased random selection.

38. A method as in claim 37, wherein a given category performance determinant biases the selection of its corresponding category in said biased random selection such that said corresponding category has a higher probability of selection than a different category if a category performance determinant corresponding to said corresponding category is greater than a category performance determinant corresponding to said different problem.

39. A method as in claim 37, wherein said measurement associated with a given one of said plurality of categories is a measurement of a student'"'"'s performance.

40. A computer data signal embodied in a carrier wave, comprising:

a. a category performance determinant determination source code segment comprising code for generating a category performance determinant for each of a plurality of categories, wherein said each of a plurality of categories comprises a number of elements, and wherein;

i. a given said category performance determinant corresponds to a given one of a plurality of categories;

ii. said given category performance determinant represents a measurement associated with said given one of a plurality of categories; and

b. a category selection source code segment comprising code for making a biased random selection of a category from said plurality of categories, wherein each category performance determinant biases the selection of its corresponding category in said biased random selection.