SYSTEMS AND METHODS FOR AUTHORING AN INTEGRATED AND INDIVIDUALIZED COURSE OR TEXTBOOK

• US 20160049083A1
• Filed: 08/18/2015
• Published: 02/18/2016
• Est. Priority Date: 08/13/2015
• Status: Abandoned Application

• Current Assignee: Zoomi, Inc.
• Original Assignee: Zoomi, Inc.
• Inventors: Chiang, Mung, Ju, William D., Rill, Stefan Rudiger, Brinton, Christopher Greg, Ha, Sangtae, Walker, James Craig
• Application Number:
  US14/829,202
• Publication Number:
  US 20160049083A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G09B 5/12 different stations being capable of presenting different information simultaneously G09B5/14 takes precedence
• 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

The present invention is directed towards methods and systems to assist an author in constructing an electronic course or textbook (referred to generally as a course). The system allows an author to integrate various types of content into his/her course, and to specify a set of rules that will determine if and how the content will be individualized to each end user; the resultant courses are thus termed Integrated and Individualized Courses (IIC). Through the system, an author is able to import content files into an authoring application, and then use this application to edit the files, arrange them into segments, and define the course structure as a sequence of these segments, all through drag and drop functionality.

Claims

1. A method for a processor with access to stored content to organize and customizably deliver learning materials to a student, comprising the steps of:

obtaining a plurality of learning modules, each said learning module comprising student-downloadable learning materials for a syllabus topic;

tagging each learning module with a tag indicative of said syllabus topic;

forming a sequence map of said learning modules and potential transitions between learning modules, each said transition assigned a transition vector based on said tags and potential student performance in said course;

calculating at least one preferred navigation path through said map based on known learning attributes of a set of students;

delivering a learning module to a student based on said preferred path;

developing a user-specific path based on assessing said student'"'"'s performance in delivered learning modules; and

determining a subsequent module for delivery to said student based on comparing said student'"'"'s performance to said transition vectors;

wherein each learning module comprises at least one of text, image, video, or audio content.

2. The method of claim 1, wherein said user model is amended based on tracking student durations in watching learning modules comprising video.

3. The method of claim 1, where a student'"'"'s performance is scored and said score is used in determining the next learning module for said student.

4. The method of claim 3, where said user model is used to amend the preferred path.

5. The method of claim 3, where said user model is amended at least in part on student responses to questions delivered in learning modules.

6. The method of claim 1, where said tagging is based on analysis of the audio or textual content of the learning module.

7. The method of claim 1, where said tagging is based on analysis of the visual content of each learning module.

8. The method of claim 1, wherein said tag represent at least one of content identification and complexity.

9. A system for determining a delivery sequence of learning modules to a particular student based on scoring student performance, comprising:

a data store for storing learning module content and

a processor;

wherein said processor is configured for

tagging and organizing a plurality of learning modules for a course, each said learning module comprising student-downloadable learning materials for a subset of the course and comprising at least one of text, images, video, or audio content;

arranging possible delivery sequences of said learning modules by relating each tag to a syllabus;

forming a map of learning modules and potential transitions between said learning modules by assigning values for each transition, said values assigned based on a likelihood of being the next deliverable learning module for a student;

establishing a preferred navigation path through said map based on said values;

delivering a first learning module to the student;

scoring student performance in said learning module;

comparing a student score to said values; and

customizing the navigation path for said student based on said comparing; and

delivering the next module in sequence with the highest likelihood of success.

10. The system of claim 9, wherein said likelihood is related to possible student scores.

11. The system of claim 9, where said processor determines scoring based in part on tracking a student'"'"'s duration in watching learning modules comprising video.

12. The system of claim 9, wherein said processor repeats the steps of scoring, comparing, and customizing after the student completes a subsequent learning module.

13. The system of claim 9, where said processor determines performance at least in part based on student responses to questions delivered in learning modules.

14. A method for a process with access to a data store to adjust the online delivery sequence of learning modules of a course, adjusted based on student performance, comprising the steps of:

organizing a plurality of learning modules and transitions into a map, each said learning module including student-downloadable learning materials for a subset of a course and each transition including criteria for learning module selection based on learning attributes of a group of students;

calculating a preferred navigation path through said map encompassing all syllabus topics; and

adjusting said preferred path for a particular student based on said criteria and on measured student'"'"'s performance in delivered content in said course;

wherein each learning module comprises at least one of text, image, video, or audio content.

15. The method of claim 14, wherein each of said learning modules is tagged so as to identify content and said tags correspond to a syllabus topic.

16. The method of claim 15, where determining said tags are determined based on an analysis of the audio or textual content of each learning module.

17. The method of claim 14, where said student'"'"'s performance is based on tracking student durations in watching learning modules comprising video.

18. The method of claim 17, where said student'"'"'s performance is scored, and said score is used for comparison to transition criteria.

19. The method of claim 18, where said adjusting the preferred path is determined based on a student'"'"'s score following completion of each learning module.

20. The method of claim 14, where said student performance is determined at least in part based on student responses to questions delivered in learning modules.