Systems and methods for automated bayesian-network based mastery determination

Patent metadata

Field	Value
Publication number	US-11113616-B2
Application number	US-201815895951-A
Country	US
Kind code	B2
Filing date	Feb 13, 2018
Priority date	Feb 13, 2017
Publication date	Sep 7, 2021
Grant date	Sep 7, 2021

Abstract

Systems and methods for determining mastery in a Bayesian network are disclosed herein. The system can include memory including a content library database containing content for delivery to a user. The system can include at least one processor that can receive an assertion from a user device and identify one or several nodes relevant to the received assertion. The at least one processor can further evaluate the assertion and calculate a node mastery probability for the identified one or several relevant nodes. The at least one processor can calculate mastery of related nodes and determine mastery of an objective based on the mastery of the relevant nodes and the related nodes. The at least one processor can generate a mastery bar and update the mastery bar with the determined mastery of the objective.

First claim

What is claimed is:

1. A system for determining mastery in a Bayesian network, the system comprising:
memory comprising: a content library database comprising content for delivery to a user; and
at least one processor configured to:
receive an assertion, comprising a response to a prompt or a question, from a user device;
identify one or several nodes relevant to the received assertion;
evaluate the assertion;
calculate a node mastery probability for the identified one or several relevant nodes;
identify related nodes, comprising a plurality of connected nodes connecting, either directly or via at least one additional node, to a common learning objective, wherein the related nodes are connected to the relevant nodes via conditional dependencies, which identify the likelihood of the relevant nodes being mastered if the related nodes are likewise mastered or unmastered;
calculate mastery of the related nodes according to the node mastery probability and the conditional dependencies;
determine mastery of an objective based on the mastery of the relevant nodes and the related nodes;
generate a mastery bar in a user interface, wherein the mastery bar provides a visual indicator of progress through content and a visual indicator of mastery of the objective; and
update the mastery bar with the determined mastery of the objective.

2. The system of claim 1 , wherein the at least one processor is further configured to parse the received assertion.

3. The system of claim 2 , wherein the parsing of the received assertion comprises natural language processing of the received assertion.

4. The system of claim 3 , wherein the at least one processor is further configured to select a node and determine mastery of the selected node.

5. The system of claim 4 , wherein the at least one processor is further configured to generate and provide supplemental prompts when mastery of the selected node is not determined.

6. The system of claim 5 , wherein determining mastery of an objective based on the mastery of the relevant nodes and the related nodes comprises: retrieving a mastery threshold; and comparing an attribute of the objective to a mastery threshold.

7. The system of claim 5 , wherein determining mastery of an objective based on the mastery of the relevant nodes and the related nodes comprises:
determining mastery of the identified relevant nodes;
determining a total number of nodes relating to an objective;
determining a percent of the total number of nodes that are mastered; and
comparing the percent of the total number of nodes that are mastered to a mastery threshold.

8. The system of claim 7 , wherein updating the mastery bar comprises:
determining a present state of the mastery bar; determining a change in a mastery level; and
controlling pixels in a display to reflect the change in mastery level.

9. The system of claim 8 , wherein the mastery bar comprises a first portion quantifying unstarted nodes, a second portions quantifying started but unmastered nodes, and a third portion quantifying mastered nodes.

10. The system of claim 9 , wherein the at least one processor is further configured to:
provide content to the user;
receive a user response to the provided content;
determine to intervene based on an evaluation of the user response to the provided content; and
provide a prompt to the user via the user interface, wherein the assertion is received in response to the provided prompt.

11. A method of determining mastery in a Bayesian network, the method comprising:
receiving an assertion, comprising a response to a prompt or a question, from a user device;
identifying one or several nodes relevant to the received assertion;
evaluating the assertion;
calculating a node mastery probability for the identified one or several relevant nodes;
identifying related nodes, comprising a plurality of connected nodes connecting, either directly or via at least one additional node, to a common learning objective, wherein the related nodes are connected to the relevant nodes via conditional dependencies, which identify the likelihood of the relevant nodes being mastered if the related nodes are likewise mastered or unmastered;
calculating mastery of the related nodes according to the node mastery probability and the conditional dependencies;
determining mastery of an objective based on the mastery of the relevant nodes and the related nodes;
generating a mastery bar in a user interface, wherein the mastery bar provides a visual indicator of progress through content and a visual indicator of mastery of the objective; and
updating the mastery bar with the determined mastery of the objective.

12. The method of claim 11 , further comprising parsing the received assertion.

13. The method of claim 12 , wherein the parsing of the received assertion comprises natural language processing of the received assertion.

14. The method of claim 13 , further comprising selecting a node and determine mastery of the selected node.

15. The method of claim 14 , further comprising generating and providing supplemental prompts when mastery of the selected node is not determined.

16. The method of claim 15 , wherein determining mastery of an objective based on the mastery of the relevant nodes and the related nodes comprises: retrieving a mastery threshold; and comparing an attribute of the objective to a mastery threshold.

17. The method of claim 15 , wherein determining mastery of an objective based on the mastery of the relevant nodes and the related nodes comprises:
determining mastery of the identified relevant nodes;
determining a total number of nodes relating to an objective;
determining a percent of the total number of nodes that are mastered; and
comparing the percent of the total number of nodes that are mastered to a mastery threshold.

18. The method of claim 17 , wherein updating the mastery bar comprises:
determining a present state of the mastery bar; determining a change in a mastery level; and
controlling pixels in a display to reflect the change in mastery level.

19. The method of claim 18 , wherein the mastery bar comprises a first portion quantifying unstarted nodes, a second portions quantifying started but unmastered nodes, and a third portion quantifying mastered nodes.

20. The method of claim 19 , further comprising:
providing content to the user;
receiving a user response to the provided content;
determining to intervene based on an evaluation of the user response to the provided content; and
providing a prompt to the user via the user interface, wherein the assertion is received in response to the provided prompt.

Assignees

• Pearson Education Inc

Inventors

• Potter Mark
• Runyon Kimberly
• Pionek Laura

Classifications

• G06N7/01 Primary

  Probabilistic graphical models, e.g. probabilistic networks · CPC title

• G06F16/435 Primary

  Filtering based on additional data, e.g. user or group profiles · CPC title

• H04L51/216

  Handling conversation history, e.g. grouping of messages in sessions or threads · CPC title

• H04L67/535

  Tracking the activity of the user (network monitoring arrangements H04L43/00; recording of computer activity G06F11/34) · CPC title

• G06F3/04847

  Interaction techniques to control parameter settings, e.g. interaction with sliders or dials · CPC title