E-learning course structure

• US 7,014,467 B2
• Filed: 05/31/2002
• Issued: 03/21/2006
• Est. Priority Date: 02/11/2002
• Status: Expired due to Term

• Current Assignee: SAP SE
• Original Assignee: SAP AG (SAP SE)
• Inventors: Leidig, Torsten, Altenhofen, Michael, Krebs, Andreas, Gerteis, Wolfgang, Schaper, Joachim, Meder, Norbert
• Primary Examiner(s): ADAMS, CHANDA L
• Application Number:
  US10/158,598
• Publication Number:
  US 20030152899A1
• Time in Patent Office: 1,390 Days
• Field of Search: 434/350, 434/362, 434/118
• US Class Current: 434/118
• CPC Class Codes: G09B 5/00 Electrically-operated educational appliances working with questions and answers G09B7/00; simulators G09B9/00; advertising or displaying in general G09F
• CPC Class Codes: G09B 7/00 Electrically-operated teaching apparatus or devices working with questions and answers mechanically operated G09B3/00; computing arrangements G06F

Abstract

An e-learning course may include a number of structural elements that are aggregated into one or more levels. Each higher level may refer to any instance of a lower level. The structural elements include a course, a sub-course, a learning unit, or a knowledge item. The structural elements may include metadata. The structural elements also may include relations between structural elements. The course and its structural elements do not enforce any sequence of structural elements that the learner may use to traverse the course. In addition, the structural elements may be reused and reassembled to form different courses. A content repository is configured to store course data and its structural elements. A content player is configured to access the stored course data and assemble the structural elements.

Claims

1. A method, performed via one or more processing devices, for use in an electronic learning (e-learning) system, the method comprising:

dividing content associated with an e-learning course into two or more structural elements, the structural elements containing attributes, wherein at least one of the attributes relates to content of the structural elements;

aggregating the structural elements into two or more levels, where a higher level structural element refers to a lower level structural element;

assembling the structural elements into the e-learning course for use in the e-learning system; and

obtaining a navigation strategy for the the e-learning course, the navigation strategy comprising a microstrategy that selectively presents content of the structural elements based on the attributes and a macrostrategy comprised of one or more microstrategies, wherein at least one of the attributes relates to the navigation strategy, and wherein the navigation strategy alters an attribute relating to the navigation strategy when presenting content of the structural elements.

2. The method of claim 1, wherein the structural elements comprise a knowledge item.

3. The method of claim 2, wherein the knowledge item comprises content to illustrate an aspect of a topic.

4. The method of claim 2, wherein the knowledge item comprises content to test an aspect of a topic.

5. The method of claim 2, wherein the knowledge item comprises one or more of text, a table, an illustration, a graphic, an animation, an audio clip, and a video clip.

6. The method of claim 1, wherein the structural elements comprise a learning unit which refers to one or more knowledge items to represent a thematically-coherent unit of information.

7. The method of claim 1, wherein the structural elements comprise a sub-course which refers to one or more of a knowledge item, a learning unit, and another sub-course.

8. The method of claim 1, wherein the structural elements comprise a course which refers to one or more of a knowledge item, a learning unit, and a sub-course.

9. The method of claim 1, wherein the structural elements are usable in more than one e-learning course.

10. The method of claim 1, wherein the structural elements comprise extensible markup language files.

11. The method of claim 1, further comprising:

tagging the structural elements with metadata that is used to assemble the structural elements, the metadata defining the attributes.

12. The method of claim 11, wherein the metadata corresponds to knowledge of orientation.

13. The method of claim 12, wherein the metadata corresponds to knowledge of explanation.

14. The method of claim 12, wherein the metadata corresponds to knowledge of reference.

15. The method of claim 12, wherein the metadata corresponds to knowledge of action.

16. The method of claim 12, wherein the metadata corresponds to a competency indicative of performance of a learner who traverses the e-learning course.

17. The method of claim 1, further comprising:

providing one or more relations to indicate dependencies between structural elements.

18. The method of claim 17, wherein the one or more relations comprise a directional relation that is true in one direction only.

19. The method of claim 17, wherein the one or more relations comprise a non-directional relation that is true in either of two directions.

20. The method of claim 17, wherein the one or more relations comprise a subject taxonomic relation.

21. The method of claim 20, wherein the one or more relations comprise a hierarchical relation.

22. The method of claim 21, wherein the hierarchical relation comprises a part/whole relation or an abstraction relation.

23. The method of claim 20, wherein the subject taxonomic relation comprises an associative relation.

24. The method of claim 23, wherein the associative relation comprises a relation that is one of determines, side-by-side, alternative to, opposite to, precedes, context of, process of, values, means of, and affinity.

25. The method of claim 17, wherein the one or more relations comprise a non-subject taxonomic relation.

26. The method of claim 25, wherein the non-subject taxonomic relation comprises a relation that indicates a structural element should be completed before proceeding to a related structural element.

27. The method of claim 25, wherein the non-subject taxonomic relation comprises a relation that indicates that a structural element belongs to another structural element.

28. An electronic learning (e-learning) system comprising:

a content repository for storing a plurality of structural elements associated with an e-learning course, the structural elements being aggregated into two or more levels, where a higher level structural element refers to a lower level structural element, the structural elements containing attributes, wherein at least one of the attributes relates to content of the structural elements; and

a content player for assembling the structural elements into the e-learning course for presentation to a learner, the content player presenting the e-learning course using a navigation strategy, the navigation strategy comprising a microstrategy that selectively presents content of the structural elements based on the attributes and a macrostrategy comprised of one or more microstrategies, wherein at least one of the attributes relates to the navigation strategy, and wherein the navigation strategy alters an attribute relating to the navigation strategy when presenting content of the structural elements.

29. The system of claim 28, wherein a lowest level structural element comprises a knowledge item.

30. The system of claim 29, wherein the knowledge item illustrates an aspect of a topic.

31. The system of claim 29, wherein the knowledge item tests an aspect of a topic.

32. The system of claim 29, wherein the knowledge item includes one or more of text, a table, an illustration, a graphic, an animation, an audio clip, and a video clip.

33. The system of claim 28, wherein the structural elements comprise a learning unit which refers to one or more knowledge items to represent a thematically-coherent unit of information.

34. The system of claim 28, wherein the structural elements comprises a sub-course which refers to one or more of a knowledge item, a learning unit, and another sub-course.

35. The system of claim 28, wherein the structural elements comprise a course which refers to one or more of a knowledge item, a learning unit, and a sub-course.

36. The system of claim 28, wherein the structural elements are usable in more than one course.

37. The system of claim 28, wherein the structural elements comprise extensible markup language files.

38. The system of claim 28, wherein the structural elements are tagged with metadata to assemble the structural elements, the metadata defining the attributes.

39. The system of claim 38, wherein the metadata comprises knowledge of orientation.

40. The system of claim 39, wherein the metadata comprises knowledge of explanation.

41. The system of claim 38, wherein the metadata comprises knowledge of reference.

42. The system of claim 38, wherein the metadata comprises knowledge of action.

43. The system of claim 38, wherein the metadata comprises a competency to indicate performance of a learner who traverses the e-learning course.

44. The system of claim 28, wherein a relation is used to indicate dependencies between structural elements.

45. The system of claim 44, wherein the relation is directional and true in one direction only.

46. The system of claim 44, wherein the relation is non-directional and true in one of two directions.

47. The system of claim 44, wherein the relation comprises a subject taxonomic relation.

48. The system of claim 47, wherein the subject taxonomic relation comprises a hierarchical relation.

49. The system of claim 48, wherein the hierarchical relation is one of a part/whole relation and an abstraction relation.

50. The system of claim 47, wherein the subject taxonomic relation comprises an associative relation.

51. The system of claim 50, wherein the associative relation comprises one of determines, side-by-side, alternative to, opposite to, precedes, context of, process of, values, means of, and affinity.

52. The system of claim 44, wherein the relation comprises a non-subject taxonomic relation.

53. The system of claim 52, wherein the non-subject taxonomic relation comprises a relation that indicates a structural element should be completed before proceeding to a related structural element.

54. The system of claim 52, wherein the non-subject taxonomic relation comprises a relation that indicates that a structural element belongs to another structural element.

55. One or more machine-readable media for storing course data for access by an application program that is executable by a content player of an electronic learning (e-learning) system, the course data comprising:

a plurality of structural elements aggregated into two or more levels, where a higher level structural element refers to a lower level structural element, the structural elements comprising content for presentation to a learner via the e-learning system;

metadata associated with the structural elements, the metadata defining attributes, wherein at least one of the attributes relates to content of the structural elements;

a plurality of relations to indicate dependencies between two or more of the structural elements; and

a navigation strategy comprised of a microstrategy that selectively presents content of the structural elements based on the attributes and a macrostrategy comprised of one or more microstrategies, wherein at least one of the attributes relates to the navigation strategy, and wherein the navigation strategy is configured to alter an attribute relating to the navigation strategy when presenting content of the structural elements.

56. The machine-readable media of claim 55, wherein a lowest level structural element comprises a knowledge item.

57. The machine-readable media of claim 56, wherein the knowledge item illustrates an aspect of a topic.

58. The machine-readable media of claim 56, wherein the knowledge item tests an aspect of a topic.

59. The machine-readable media of claim 56, wherein the knowledge item comprises one or more of text, a table, an illustration, a graphic, an animation, an audio clip, a video clip.

60. The machine-readable media of claim 55, wherein the structural elements comprise a learning unit which refers to one or more knowledge items to represent a thematically-coherent unit of information.

61. The machine-readable media of claim 55, wherein the structural elements comprise a sub-course which refers to one or more of a knowledge item, a learning unit, and another sub-course.

62. The machine-readable media of claim 55, wherein the structural elements comprise a course which refers to one or more of a knowledge item, a learning unit, and a sub-course.

63. The machine-readable media of claim 55, wherein the structural elements are usable in more than one course.

64. The machine-readable media of claim 55, wherein the structural elements comprise extensible markup language files.

65. The machine-readable media of claim 55, wherein the structural elements are tagged with the metadata to assemble the structural elements.

66. The machine-readable media of claim 65, wherein the metadata comprises knowledge of orientation.

67. The machine-readable media of claim 66, wherein the metadata comprises knowledge of explanation.

68. The machine-readable media of claim 66, wherein the metadata comprises knowledge of reference.

69. The machine-readable media of claim 66, wherein the metadata comprises knowledge of action.

70. The machine-readable media of claim 66, wherein the metadata comprises a competency to indicate performance of a learner that traverses an e-learning course of which the application program is a part.

71. The machine-readable media of claim 55, wherein at least one of the relations is directional and true in one direction only.

72. The machine-readable media of claim 55, wherein at least one of the relations is non-directional and true in one of two directions.

73. The machine-readable media of claim 55, wherein at least one of the relations comprises a subject taxonomic relation.

74. The machine-readable media of claim 73, wherein the subject taxonomic relation comprises a hierarchical relation.

75. The machine-readable media of claim 74, wherein the hierarchical relation comprises a part/whole relation or an abstraction relation.

76. The machine-readable media of claim 73, wherein the subject taxonomic relation comprises an associative relation.

77. The machine-readable media of claim 76, wherein the associative relation comprises one of determines, side-by-side, alternative to, opposite to, precedes, context of, process of, values, means of, and affinity.

78. The machine-readable media of claim 55, wherein at least one of the relations comprises a non-subject taxonomic relation.

79. The machine-readable media of claim 78, wherein the non-subject taxonomic relation comprises a relation that indicates a structural element should be completed before proceeding to a related structural element.

80. The machine-readable media of claim 78, wherein the non-subject taxonomic relation comprises a relation that indicates that a structural element belongs to another structural element.