ADAPTIVE TEACHING AND LEARNING UTILIZING SMART DIGITAL LEARNING OBJECTS

• US 20100190143A1
• Filed: 01/28/2009
• Published: 07/29/2010
• Est. Priority Date: 01/28/2009
• Status: Abandoned Application

• Current Assignee: Time To Know Ltd.
• Original Assignee: Time To Know Ltd.
• Inventors: Weiss, Dov, Shalom, Tsila, Gal, Michael
• Application Number:
  US12/360,956
• Publication Number:
  US 20100190143A1
• Time in Patent Office: Days
• US Class Current: 434/322
• 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

Adaptive teaching and learning utilizing smart digital learning objects. For example, a system for adaptive computerized teaching includes: a computer station to present to a student an interactive digital learning activity based on a structure representing a molecular digital learning object which comprises one or more atomic digital learning objects, wherein at least one action within a first of the atomic digital learning objects modifies performance of a second of the atomic digital learning objects.

Claims

1. A system for adaptive computerized teaching, the system comprising:

a computer station to present to a student an interactive digital learning activity based on a structure representing a molecular digital learning object which comprises one or more atomic digital learning objects, wherein at least one action within a first of the atomic digital learning objects modifies performance of a second of the atomic digital learning objects.

2. The system of claim 1, wherein a first atomic digital learning object of said molecular digital learning object is to generate an output to be used as an input of a second atomic digital learning object of said molecular digital learning object.

3. The system of claim 1, wherein a first atomic digital learning object of said molecular digital learning object is to generate an output which triggers activation of a second atomic digital learning object of said molecular digital learning object.

4. The system of claim 1, wherein the molecular digital learning object comprises a managerial component to handle one or more communications among two or more atomic digital learning objects of said molecular digital learning object.

5. The system of claim 1, wherein the molecular digital learning object is a high-level molecular digital learning object comprising two or more molecular digital learning objects.

6. The system of claim 1, further comprising:

a computer-aided assessment module to dynamically assess one or more pedagogic parameters of said student, based on one or more logged interactions of said student via said computer station with one or more digital learning objects; and

an educational content generation module to automatically generate the structure representing said molecular digital learning object, based on an output of said computer-aided assessment module.

7. The system of claim 6, wherein the educational content generation module is to select, based on the output of said computer-aided assessment module, a digital learning object template, a digital learning object layout, and a learning design script;

to create said molecular digital learning object from one or more atomic digital learning objects stored in a repository of educational content items; and

to insert digital educational content into said molecular digital learning object.

8. The system of claim 6, wherein the educational content generation module is to activate said molecular digital learning object in a correction cycle performed on said computer station associated with said student.

9. The system of claim 6, wherein the educational content generation module is to automatically insert digital educational content into said molecular digital learning object based on estimated contribution of the inserted digital educational content to topic-related knowledge of said student.

10. The system of claim 9, wherein the educational content generation module is to select said digital educational content based on tagging of atomic digital learning objects with tags of a concept-based ontology.

11. The system of claim 6, wherein the educational content generation module is to select, based on concept-based ontology tags:

a digital learning object template, a digital learning object layout, and a learning design script;

to generate said molecular digital learning object; and

to insert digital educational content into said molecular digital learning object based on estimated contribution of the inserted digital educational content to development of at least one of;

a skill of said student, and a competency of said student.

12. An apparatus for adaptive computerized teaching, the apparatus comprising:

a live text module comprising a multi-layer presenter associated with a text layer and an index layer, wherein the index layer comprises an index of said text layer,

wherein the multi-layer presenter is further associated with one or more information layers associated with said text,

wherein the multi-layer presenter is to selectively present at least a portion of said text layer based on said index layer and based on one or more parameters corresponding to said one or more information layers.

13. The apparatus of claim 12, wherein the live text module comprises an atomic digital learning object, and wherein said atomic digital learning object and at least one more atomic digital learning object are comprised in a molecular digital learning object.

14. The apparatus of claim 13, wherein said atomic digital learning object is able to communicate with said at least one more atomic digital learning object.

15. The apparatus of claim 13, wherein said atomic digital learning object is to be managed by a managerial component of said molecular digital learning object.

16. The apparatus of claim 13, wherein said atomic digital learning object is tagged with one or more tags of a concept-based ontology, and wherein said atomic digital learning object is inserted into said molecular digital learning object based on at least one of said tags.

17. The apparatus of claim 12, comprising:

a text engine to selectively present, using an emphasizing style, a portion of said text layer corresponding to a textual characteristic.

18. The apparatus of claim 12, comprising:

a linguistic navigator to present one or more cascading menus comprising selectable menu items, wherein at least one of the menu items corresponds to a linguistic phenomena.

19. The apparatus of claim 18, wherein the linguistic navigator is to present a menu comprising at least one of:

a command to emphasize all words in said text layer which meet a selectable linguistic property;

a command to emphasize all terms in said text layer which meet a selectable linguistic property;

a command to emphasize all sentences in said text layer which meet a selectable linguistic property;

a command to emphasize all paragraphs in said text layer which meet a selectable linguistic property;

a command to emphasize all text-portions in said text layer which meet a selectable grammar-related property; and

a command to emphasize all text-portions in said text layer which meet a selectable vocabulary-related property;

20. The apparatus of claim 18, wherein the linguistic navigator is to present a menu comprising at least one of:

a command to emphasize verbs in said text layer,

a command to emphasize nouns in said text layer,

a command to emphasize adverbs in said text layer,

a command to emphasize adjectives in said text layer,

a command to emphasize questions in said text layer,

a command to emphasize thoughts in said text layer,

a command to emphasize feelings in said text layer,

a command to emphasize actions in said text layer,

a command to emphasize past-time portions in said text layer,

a command to emphasize present-time portions in said text layer, and

a command to emphasize future-time portions in said text layer.

21. The apparatus of claim 12, comprising:

an interaction generator to generate an interaction between a student utilizing a student station and said text layer.

22. The apparatus of claim 21, wherein the interaction comprises an interaction selected from the group consisting of:

ordering of text portions,

dragging and dropping of text portions,

matching among text portions,

moving a text portion into a type-in field, and

moving into said text layer a text portion external to said text layer.

23. A method of adaptive computerized teaching, the method comprising:

presenting to a student an interactive digital learning activity based on a structure representing a molecular digital learning object which comprises one or more atomic digital learning objects, wherein at least one action within a first of the atomic digital learning objects modifies performance of a second of the atomic digital learning objects.

24. The method of claim 23, wherein a first atomic digital learning object of said molecular digital learning object is to generate an output to be used as an input of a second atomic digital learning object of said molecular digital learning object.

25. The method of claim 23, wherein a first atomic digital learning object of said molecular digital learning object is to generate an output which triggers activation of a second atomic digital learning object of said molecular digital learning object.

26. The method of claim 23, comprising:

operating a managerial component of the molecular digital learning object to handle one or more communications among two or more atomic digital learning objects of said molecular digital learning object.

27. The method of claim 23, wherein the molecular digital learning object is a high-level molecular digital learning object comprising two or more molecular digital learning objects.

28. The method of claim 23, further comprising:

dynamically assessing one or more pedagogic parameters of said student, based on one or more logged interactions of said student via said computer station with one or more digital learning objects; and

automatically generating the structure representing said molecular digital learning object, based on an output of said computer-aided assessment module.

29. The method of claim 28, comprising:

based on the results of the assessing, selecting a digital learning object template, a digital learning object layout, and a learning design script;

creating said molecular digital learning object from one or more atomic digital learning objects stored in a repository of educational content items; and

inserting digital educational content into said molecular digital learning object.

30. The method of claim 28, comprising:

activating said molecular digital learning object in a correction cycle performed on said computer station associated with said student.

31. The method of claim 28, comprising:

automatically inserting digital educational content into said molecular digital learning object based on estimated contribution of the inserted digital educational content to topic-related knowledge of said student.

32. The method of claim 31, comprising:

selecting said digital educational content based on tagging of atomic digital learning objects with tags of a concept-based ontology.

33. The method of claim 28, comprising:

based on concept-based ontology tags, selecting;

a digital learning object template, a digital learning object layout, and a learning design script;

generating said molecular digital learning object; and

inserting digital educational content into said molecular digital learning object based on estimated contribution of the inserted digital educational content to development of at least one of;

a skill of said student, and a competency of said student.