Use of machine learning to provide answer patterns and context descriptions

1. A method for providing relevant context in order to assist with solving a problem, comprising:

identifying a graph with a topical problem statement to be solved and plurality of section groups representing sub-topics, wherein the section groups contain a plurality of topical arguments in a plurality of nodes, wherein the topical arguments are at least one of a topical question or an investigative statement;

receiving a first request for an answer pattern associated with a topical argument;

providing a first response with the answer pattern for the topical argument and a description of the answer pattern for a user answer to the topical argument; and

receiving a second request for a context explanation field associated with the topical argument;

providing a context explanation field which explains a context for asking the topical argument; and

providing an interface control that when activated displays a goal statement for the topical argument which explains at least one of: why the topical argument is being asked or a goal for asking the topical argument.

2. The method as in claim 1 , further comprising providing an answer pattern that is an example user answer.

3. The method as in claim 1 , further comprising providing the first response for an answer pattern describing how a correct user answer to the topical argument is to be patterned.

4. The method as in claim 1 , further comprising using an indicator of access to the answer pattern and context explanation field as additional inputs to machine learning to identify at least one of: additional section groups or topical arguments to be presented.

5. A non-transitory machine readable storage medium including instructions embodied thereon to provide relevant context in a graphical user interface in order to assist with solving a problem, wherein the instructions, when executed by at least one processor, comprising:

displaying a portion of a graph with a topical problem statement to be solved and plurality of section groups representing sub-topics, wherein the section groups contain a plurality of topical questions or investigative statements in a plurality of nodes;

enabling a user to access a topical question or investigative statement in a section group;

providing a first interface control that when activated displays an example answer for a topical question or investigative statement and presents how a correct user answer to the topical question is to be patterned; and

providing a second interface control that when activated displays a goal statement for the topical question or topical statement which explains why the topical question is being asked or a goal for asking the topical question or investigative statement.

6. The non-transitory machine readable storage medium as in claim 5 , wherein the example answer and the goal statement are linked to the topical question or investigative statement.

7. The non-transitory machine readable storage medium as in claim 5 , further comprising using indicators of access to an answer pattern and context explanation field as additional inputs to machine learning to identify at least one of: additional section groups or additional topical arguments to be presented.

8. The non-transitory machine readable storage medium as in claim 5 , further comprising retrieving the example answer for a topical question and a goal statement using a topic of the section group.

9. The non-transitory machine readable storage medium as in claim 5 , further comprising retrieving the example answer for a topical question and a goal statement using the topical problem statement.

10. The non-transitory machine readable storage medium as in claim 5 , further comprising:

identifying a use pattern of questions and investigative statements by a user;

using a machine learning model to classify the use pattern; and

presenting an additional section group in the graph in the graphical user interface using the use pattern to determine which additional sub-topics to present.

11. The non-transitory machine readable storage medium as in claim 5 , further comprising:

identifying a use pattern for questions, investigative statements, the first interface control to access an example answer, and the second interface control to access the goal statement;

matching the use pattern to an expert pattern of use by an expert using the questions to solve a problem; and

determining a level of expertise of a user based on an amount of use of the first interface control to access an example answer, and the second interface control to access goal statement.

12. The non-transitory machine readable storage medium as in claim 5 , further comprising tracking use of the topical questions and investigative statements by tracking interactions with the topical questions and investigative statements through a user interface.

13. The non-transitory machine readable storage medium as in claim 5 , further comprising presenting additional training material to a user about a topic of a section group based on example answers and correct answer patterns viewed.

14. The non-transitory machine readable storage medium as in claim 5 , wherein the graph is a tree graph with a topical problem statement at a root of the graph.

15. A system to provide relevant context via a graphical user interface in order to assist with solving a problem, comprising:

at least one processor;

a memory device including instructions that, when executed by the at least one processor, cause the system to:

identify a graph with a topical problem statement to be solved and plurality of section groups representing sub-topics, wherein the section groups contain a plurality of topical questions or investigative statements in a plurality of nodes;

enable a user to access a topical question in a section group;

provide a first interface control that when activated displays an example answer for a topical question or topical statement and presents how a correct user answer to the topical question will be patterned; and

provide a second interface control that when activated displays a goal statement for the topical question or topical statement which explains why the topical question is being asked or a goal for asking a topical question or investigative statement.

16. The system as in claim 15 , wherein the example answer and the goal statement are linked to the question or investigative statement.

17. The system as in claim 15 , further comprising retrieving the example answer for a topical question and a goal statement using a topic of the section group or a problem statement of the graph.

18. The system as in claim 15 , further comprising:

identifying a use pattern of questions and investigative statements;

using a machine learning model to classify the use pattern; and

presenting an additional section group in the graph in the graphical user interface using the use pattern to determine an additional section group to present.