Decision based learning

• US 10,088,984 B2
• Filed: 06/12/2015
• Issued: 10/02/2018
• Est. Priority Date: 06/12/2014
• Status: Active Grant

• Current Assignee: Brigham Young University (The Church of Jesus Christ of Latter-Day Saints)
• Original Assignee: Brigham Young University (The Church of Jesus Christ of Latter-Day Saints)
• Inventors: Plummer, Kenneth J., Fischer, Lane, Swan, Richard, Johnson, Michael C.
• Primary Examiner(s): Misir, Dave
• Application Number:
  US14/738,166
• Publication Number:
  US 20150363692A1
• Time in Patent Office: 1,208 Days
• Field of Search: 706 11
• CPC Class Codes: G06F 3/0484 for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
• CPC Class Codes: G06N 20/00 Machine learning

Abstract

A decision based learning apparatus can include a decision module configured to implement a decision model associated with a problem, the decision model including a plurality of decisions associated with solving the problem, a problem profile module configured to store a problem profile, the problem profile defining the problem and a solution to the problem, a learning storage module configured to store at least one learning module associated with at least one of the plurality of decisions, and a decision scenario interface module configured to generate a scenario based on the decision model and the problem profile and to present the scenario based on the decision model and the problem profile to a user.

Claims

1. A decision based learning apparatus implemented by at least one processor and comprising:

a decision module configured to implement a decision model associated with a domain of problems, the decision model being implemented as a decision tree including a plurality of decisions as nodes in the decision tree that represent a step-wise decision-making process of an expert for a plurality of problems,

each of the plurality of decisions organized and retrieved according to conditional relationships in contrast to conceptual or procedural relationships,

each of the plurality of decisions having two or more valid conditions each of which leads to one or more possible subsequent decision nodes until a final decision leading to problem resolution, wherein one of the plurality of decisions is included in a problem and a correct path is determined based on a problem type;

a problem profile module configured to store a problem profile, the problem profile defining the problem type according to a set of conditions, wherein the correct path through the decision tree includes a resolution to the problem;

a learning storage module configured to store at least one learning module associated with at least one of the plurality of decisions, the at least one learning module defining stored conditional information and related conceptual information to distinguish a condition present in the problem from a plurality of valid conditions at a decision node; and

a decision scenario interface module configured to generate a scenario based on the decision model and the problem profile and to present the scenario based on the decision model and the problem profile in a graphical user interface (GUI), wherein

the GUI is configured to interact with the decision based learning apparatus when a learner operates the GUI,

the GUI is configured to configure the decision based learning apparatus when an instructor operates the GUI, and

the decision scenario interface module is further configured to receive, via the GUI, input associated with a learner, interpret the input associated with the learner, and track a progress of the learner.

2. The decision based learning apparatus of claim 1, further comprising:

an authoring interface module configured to elicit and to represent a conditional schema of an expert as a decision model, to generate the problem profile, and configured to associate the at least one learning module to a corresponding at least one of the plurality of decisions; and

a reporting and scoring interface configured to allow viewing of a progress of a learner, and view, edit and report a score associated with the learner.

3. The decision based learning apparatus of claim 1, wherein

the decision model corresponds to a decision-making process of a subject matter expert associated with solving the problem, and

the decision model is based on a structure associated with a presentation of information for each of the of the plurality of decisions and a decision path corresponding to the presentation of information.

4. The decision based learning apparatus of claim 1, wherein

the problem profile defines a structure of at least one scenario related to the solution of the problem, and

the problem profile includes information related to a characteristic of the problem and an indication of a preferred path through the decision model.

5. The decision based learning apparatus of claim 1, wherein the at least one learning module includes a media file.

6. The decision based learning apparatus of claim 1, wherein one or more of the plurality of decisions define a decision path between the problem and the solution to the problem.

7. The decision based learning apparatus of claim 1, wherein the decision model, the problem profile and the scenario are implemented in a data-structure of a database.

8. A non-transitory computer readable medium including code segments that, when executed by a processor, cause the processor to:

implement a decision model associated with solving a problem, the decision model including a plurality of model being implemented as a decision tree including a plurality of decisions as nodes in the decision tree,

each of the plurality of decisions implementing stored conditional information associated with solving the problem, each of the plurality of decisions organized and retrieved according to conditional relationships in contrast to conceptual or procedural relationships,

each of the plurality of decisions having;

a correct answer linking to one of a solution to the problem or a first next decision in the plurality of decisions, the first next decision being associated with a first path in the decision tree, or

at least one incorrect answer linking to a second next decision in the plurality of decisions, the second next decision being associated with a second path in the decision tree, the first path being a more direct path to the solution to the problem as compared to the second path;

store a problem profile, the problem profile defining the problem and the solution to the problem;

store at least one learning module associated with at least one of the plurality of decisions, the at least one learning module defining stored conceptual information associated with a corresponding one of the plurality of decisions, the at least one learning module defining conceptual information to distinguish a condition present in the problem from a plurality of valid conditions at a decision node;

generate a scenario based on the decision model and the problem profile and to present the scenario based on the decision model and the problem profile in a graphical user interface (GUI);

provide an authoring tool configured to generate the decision model, to generate the problem profile, and to associate the at least one learning module to a corresponding at least one of the plurality of decisions; and

provide a reporting and scoring interface configured to allow viewing of a progress, view, edit and report a score on the GUI wherein

the GUI is configured to interact with the decision based learning apparatus when a learner operates the GUI,

the GUI is configured to configure the decision based learning apparatus when an instructor operates the GUI, and

the decision scenario interface module is further configured to receive, via the GUI, input associated with a learner, interpret the input associated with the learner, and track a progress of the learner.

9. The non-transitory computer readable medium of claim 8, wherein

the decision model corresponds to a decision-making process of a subject matter expert associated with solving the problem, and

the decision model is based on an algorithmic structure associated with a presentation of information for each of the of the plurality of decisions and a decision path corresponding to the presentation of information.

10. The non-transitory computer readable medium of claim 8, wherein

the problem profile defines a structure of at least one scenario related to the solution of the problem, and

the problem profile includes information related to a characteristic of the problem and an indication of a preferred path through the decision model.

11. A decision based learning apparatus comprising:

a Decision-Based Learning Markup Language (DBLML) module configured to define;

at least one conditional data element of a given decision model, and to allow an instructor to markup language corresponding to an individual problem as an instance of the at least one conditional data element, the decision model being implemented as a decision tree including a plurality of decisions as nodes in the decision tree that represent a step-wise decision-making process of an expert for a plurality of problems,

each of the plurality of decisions organized and retrieved according to conditional relationships in contrast to conceptual or procedural relationships,

each of the plurality of decisions having two or more valid conditions each of which leads to one or more possible subsequent decision nodes until a final decision leading to problem resolution, wherein one of the plurality of decisions is included in a problem and a correct path is determined based on a problem type

enabling the decision based learning apparatus to identify and process the marked up natural language string as a data element, and

enabling the decision based learning apparatus to process the marked up natural language string as an interactive object, wherein

the decision model includes a contextual component and an instructional component,

the DBLML module is further configured to present the contextual component and the instructional component to a learner using a graphical user interface (GUI),

the GUI is configured to allow the learner to interact with the decision based learning apparatus and the instructor to configure the decision based learning apparatus, and

the DBLML module is further configured to receive, via the GUI, input associated with a learner, interpret the input associated with the learner, and track progress of the learner; and

a learning storage module configured to store at least one learning module associated with at least one of the plurality of decisions, the at least one learning module defining stored conditional information and related conceptual information to distinguish a condition present in the problem from a plurality of valid conditions at a decision node.

12. The decision based learning apparatus of claim 11, wherein

the decision model corresponds to a decision-making process of a subject matter expert associated with solving the problem, and

the decision model is based on an algorithmic structure associated with a presentation of information for each of the of a plurality of decisions and a decision path corresponding to the presentation of information.

13. The decision based learning apparatus of claim 11, wherein

a problem profile defines a structure of at least one scenario related to the solution of the problem, and

the problem profile includes information related to a characteristic of the problem and an indication of a preferred path through the decision model.

14. The decision based learning apparatus of claim 11, wherein one or more of a plurality of decisions define a decision path between the problem and the solution to the problem.

15. The decision based learning apparatus of claim 11, wherein a decision model, a problem profile and the scenario are defined in a data-structure of a markup language file.