Conveying questions with content

• US 9,536,439 B1
• Filed: 06/27/2012
• Issued: 01/03/2017
• Est. Priority Date: 06/27/2012
• Status: Active Grant

• Current Assignee: Audible Incorporated (Amazon.com, Inc.)
• Original Assignee: Audible Incorporated (Amazon.com, Inc.)
• Inventors: Goldstein, Douglas S., Arora, Ajay, Hwang, Douglas, Story, Guy A. Jr., Yang, Shirley C.
• Primary Examiner(s): Frisby, Kesha
• Application Number:
  US13/535,260
• Time in Patent Office: 1,651 Days
• Field of Search: 434/322, 434/323, 434/156, 434/157
• US Class Current: 1/1
• 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

A service for conveying questions with an item of content is disclosed. The content question service may analyze a portion of an item of content, select a question task, and then generate a question about the portion of the item of content using the selected question task. The content question service may receive a user'"'"'s response to the conveyed question, analyze the response, and track the user'"'"'s skill level for the selected question task.

Claims

1. A computer-implemented method comprising:

determining, by a computing system comprising one or more computing devices, a difficulty level of an item of content, wherein the difficulty level is determined based on an analysis of at least a portion of text of the item of content using machine techniques;

determining, by the computing system, a skill level of a user with respect to the item of content, wherein the skill level is determined based at least in part on retrieved information from a stored user profile associated with the user;

selecting, by the computing system, a question task fitting at least one of the difficulty level of the item of content or the skill level of the user, wherein the question task represents a skill to be tested by a question to be generated;

analyzing, by the computing system, the portion of text of the item of content to identify a question subject within the portion, wherein the portion of text is analyzed using at least one of natural language processing or semantic analysis;

generating, by the computing system, a question about the item of content and a correct answer to the question, wherein the question is generated based at least in part on the question task, the question subject and the portion of text; and

generating, by the computing system, a user interface for display, wherein the user interface includes display of (a) at least the portion of text of the item of content, (b) the question generated by the computing system, and (c) two or more selectable controls that each display a different response to the question, wherein one of the two or more selectable controls displays the correct answer generated by the computing system.

2. The computer-implemented method of claim 1 further comprising receiving a selection of a language;

and wherein the generated question is included in the user interface in the selected language.

3. The computer-implemented method of claim 2, wherein the selected language is different from the item of content'"'"'s language.

4. The computer-implemented method of claim 1 further comprising receiving a user'"'"'s response to the generated question.

5. The computer-implemented method of claim 4 further comprising adjusting, by the computing system, the user'"'"'s skill level based on the received user'"'"'s response.

6. The computer-implemented method of claim 5 further comprising:

making a comparison, by the computing system, between the adjusted skill level of the user and a skill level of one or more members of a peer group of the user; and

based at least in part on the comparison, suggesting, by the computing system, one or more goals for the user.

7. The computer-implemented method of claim 1 further comprising:

generating, by the computing system, a hint for the generated question; and

including, by the computing system, the generated hint in the user interface.

8. The computer-implemented method of claim 1, wherein the difficulty level of the item of content is determined by at least one of:

an educational standard for which the item of content is recommended;

a Flesch-Kincaid readability score of the item of content;

or

a Gunning fog index of the item of content.

9. The computer-implemented method of claim 1 further comprising identifying, by the computing system, a question task from which a previously conveyed question was generated;

wherein the selected question task is not the identified question task.

10. The computer-implemented method of claim 1, wherein

analyzing the portion of text of the item of content comprises identifying, in the portion of text of the item of content, a noun and an adjective that modifies the noun, wherein the generated question includes the noun and the generated answer includes the adjective.

11. The computer-implemented method of claim 1, wherein the question subject within the portion of text is further identified based at least in part by applying named entity extraction.

12. A system comprising:

an electronic data store configured to at least store content; and

a computing system comprising one or more hardware computing devices executing specific computer-executable instructions, said computing system in communication with the electronic data store and configured to at least;

determine a difficulty level of an item of content, wherein the difficulty level is determined based on an analysis of at least a portion of text of the item of content using machine techniques;

determine a skill level of a user with respect to the item of content, wherein the skill level is determined based at least in part on retrieved information from a stored user profile associated with the user;

select a question task fitting at least one of the difficulty level of the item of content or the skill level of the user, wherein the question task represents a skill to be tested by a question to be generated;

analyze the portion of text of the item of content to identify a question subject within the portion, wherein the portion of text is analyzed using at least one of natural language processing or semantic analysis;

generate a question about the item of content and a correct answer to the question, wherein the question is generated based at least in part on the question task, the question subject and the portion of text; and

generate a user interface for display, wherein the user interface includes display of (a) at least the portion of text, (b) the question generated by the computing system, and (c) two or more selectable controls that each display a different response to the question, wherein one of the two or more selectable controls displays the correct answer generated by the computing system.

13. The system of claim 12, wherein the computing system is further configured to:

receive a selection of a language; and

wherein the generated question is included in the user interface in the selected language.

14. The system of claim 13, wherein the selected language is different from the item of content'"'"'s language.

15. The system of claim 12, wherein the computing system is further configured to receive a user'"'"'s response to the generated question.

16. The system of claim 15, wherein the computing system is further configured to adjust the user'"'"'s skill level based on the received user'"'"'s response.

17. The system of claim 16, wherein the computing system is further configured to:

make a comparison between the adjusted skill level of the user and a skill level of one or more members of a peer group of the user; and

based at least in part on the comparison, suggest one or more goals for the user.

18. The system of claim 12, wherein the computing system is further configured to:

generate a hint for the generated question; and

include the hint for display in the user interface.

19. The system of claim 12, wherein the difficulty level of the item of content is determined by at least one of:

an educational standard for which the item of content is recommended;

a Flesch-Kincaid readability score of the item of content;

or

a Gunning fog index of the item of content.

20. The system of claim 12, wherein the computing system is further configured to identify a question task from which a previously conveyed question was generated;

wherein the selected question task is not the identified question task.

21. A computer-readable, non-transitory storage medium storing computer executable instructions that, when executed by one or more computing devices, configure the one or more computing devices to perform operations comprising:

determining a difficulty level of an item of content, wherein the difficulty level is determined based on an analysis of at least a portion of text of the item of content using machine techniques;

determining a skill level of a user with respect to the item of content, wherein the skill level is determined based at least in part on retrieved information from a stored user profile associated with the user;

selecting a question task fitting at least one of the difficulty level of the item of content or the skill level of the user, wherein the question task represents a skill to be tested by a question to be generated;

analyzing the portion of text of the item of content to identify a question subject within the portion, wherein the portion of text is analyzed using at least one of natural language processing or semantic analysis;

generating a question about the item of content and a correct answer to the question, wherein the question is generated based at least in part on the question task, the question subject and the portion of text; and

generating a user interface for display, wherein the user interface includes display of (a) at least the portion of text, (b) the question, and (c) two or more selectable controls that each display a different response to the question, wherein one of the two or more selectable controls displays the correct answer.

22. The computer-readable, non-transitory storage medium of claim 21, wherein the operations further comprise:

receiving a selection of a language; and

wherein the generated question is included in the user interface in the selected language.

23. The computer-readable, non-transitory storage medium of claim 22, wherein the selected language is different from the item of content'"'"'s language.

24. The computer-readable, non-transitory storage medium of claim 21, wherein the operations further comprise receiving a user'"'"'s response to the generated question.

25. The computer-readable, non-transitory storage medium of claim 24, wherein the operations further comprise adjusting the user'"'"'s skill level based on the received user'"'"'s response.

26. The computer-readable, non-transitory storage medium of claim 25, wherein the operations further comprise:

making a comparison between the adjusted skill level of the user and a skill level of one or more members of a peer group of the user; and

based at least in part on the comparison, suggesting one or more goals for the user.

27. The computer-readable, non-transitory storage medium of claim 21, wherein the operations further comprise:

generating a hint for the generated question; and

including the generated hint in the user interface.

28. The computer-readable, non-transitory storage medium of claim 21, wherein the difficulty level of the item of content is determined by at least one of:

an educational standard for which the item of content is recommended;

a Flesch-Kincaid readability score of the item of content;

or

a Gunning fog index of the item of content.

29. The computer-readable, non-transitory storage medium of claim 21, wherein the operations further comprise identifying a question task from which a previously conveyed question was generated;

wherein the selected question task is not the identified question task.