Student specific learning graph

Patent metadata

Field	Value
Publication number	US-10347151-B2
Application number	US-201414537344-A
Country	US
Kind code	B2
Filing date	Nov 10, 2014
Priority date	Nov 10, 2014
Publication date	Jul 9, 2019
Grant date	Jul 9, 2019

Abstract

Methods and arrangements for generating a learning graph. A contemplated method includes: utilizing at least one processor to execute instructions to perform the steps of: receiving a proficiency input relating to a student; receiving a target knowledge node, wherein the target knowledge node represents at least one skill the student does not currently possess; determining at least one skill requirement of the at least one skill; identifying at least one path between the proficiency input and the target knowledge node based upon the at least one determined skill requirement; calculating a gap between the proficiency input and the target knowledge node at the at least one identified path; and recommending at least one learning content module based upon the calculated gap.

First claim

What is claimed is:

1. A method of generating a learning graph, said method comprising:
utilizing at least one processor to execute instructions to perform the steps of:
receiving a proficiency input relating to a student, wherein the proficiency input identifies at least one current skill that the student currently possesses;
representing the proficiency input as at least one node of a generated learning graph comprising a plurality of nodes and a plurality of edges, wherein each node of the generated learning graph comprises a data structure comprising information related to comprehension qualification score, difficulty level quantification score, content, and prerequisites and wherein each of the plurality of edges connects two of the nodes and represents a relationship between the connected nodes, wherein the proficiency input represented as at least one node comprises a proficiency score, wherein the proficiency score comprises a decay value that reduces the proficiency score based upon a passage of time since use of the current skill represented by the proficiency input;
receiving a target knowledge node, wherein the target knowledge node represents at least one skill the student does not currently possess;
determining at least one skill requirement of the at least one skill the student does not currently possess, wherein the determining comprises identifying a comprehension difficulty score, proficiency requirement, and prerequisite of the at least one skill the student does not currently possess by identifying the nodes within the generated learning graph connected to the target knowledge node by one of the plurality of edges associated with the at least one skill the student does not currently possess;
identifying a plurality of alternate paths between the proficiency input and the target knowledge node based upon the at least one determined skill requirement, wherein each of the alternate paths identifies skills and proficiencies required for traversing a corresponding path and wherein at least one of the identified paths comprises a path requiring a least amount of total effort by the student;
calculating a gap between the proficiency input and the target knowledge node for each of the alternate paths, wherein the calculating a gap comprises determining at least one deficiency of the student between the at least one node corresponding to the proficiency input and the target knowledge node; and
selecting, based upon identifying one of the alternate paths having a least calculated gap, one of the alternate paths and recommending at least one learning content module based upon the selected path and the calculated gap corresponding to the selected path, wherein the recommended at least one learning content module would correct the determined at least one deficiency.

2. The method of claim 1 , wherein the calculating a gap comprises:
associating a known value with a node, wherein the known value represents a student proficiency based upon the proficiency input;
associating a required value with a node, wherein the required value represents a necessary proficiency based upon the target knowledge node; and
comparing the known value with the required value.

3. The method of claim 1 , further comprising:
displaying a knowledge graph comprising the selected path, wherein the selected path comprises the target knowledge node, at least one prerequisite node, and a connecting path between the target knowledge node and the at least one prerequisite node,
the at least one prerequisite node representing a skill within the selected path, and the connecting path representing a required proficiency associated with the at least one skill the student does not currently possess.

4. The method of claim 1 , further comprising identifying a preferred learning graph, wherein the preferred learning graph comprises at least one path where the calculated gap between the proficiency input and the target knowledge node is determined to be the least.

5. The method of claim 1 , wherein the recommending comprises identifying requirements of at least one learning graph based upon the calculated gap, wherein the requirements identify at least one skill the student does not currently possess.

6. The method of claim 1 , wherein the determining at least one skill requirement comprises identifying at least one concept as a prerequisite for the target knowledge node.

7. The method of claim 6 , wherein the determining at least one skill requirement further comprises identifying a necessary proficiency for the at least one concept.

8. The method of claim 1 , wherein the proficiency input comprises at least one of: a previously completed course, a retention ability score, a learning style, and a comprehension ability.

9. The method of claim 8 , wherein the proficiency input comprises a previously completed course and the previously completed course comprises a decay value, wherein the decay value reduces a proficiency score associated with a previously completed course.

10. The method of claim 1 , wherein the at least one skill requirement comprises a proficiency requirement for the prerequisite skill.

11. An apparatus for generating a learning graph, said apparatus comprising:
at least one processor; and
a non-transitory computer readable storage medium having computer readable program code embodied therewith and executable by the at least one processor, the computer readable program code comprising:
computer readable program code configured to receive a proficiency input relating to a student, wherein the proficiency input identifies at least one current skill that the student currently possesses;
computer readable program code configured to represent the proficiency input as at least one node of a generated learning graph comprising a plurality of nodes and a plurality of edges, wherein each node of the generated learning graph comprises a data structure comprising information related to comprehension qualification score, difficulty level quantification score, content, and prerequisites and wherein each of the plurality of edges connects two of the nodes and represents a relationship between the connected nodes, wherein the proficiency input represented as at least one node comprises a proficiency score, wherein the proficiency score comprises a decay value that reduces the proficiency score based upon a passage of time since use of the current skill represented by the proficiency input;
computer readable program code configured to receive a target knowledge node, wherein the target knowledge node represents at least one skill the student does not currently possess;
computer readable program code configured to determine at least one skill requirement of the at least one skill the student does not currently possess, wherein the determining comprises identifying a comprehension difficulty score, proficiency requirement, and prerequisite of the at least one skill the student does not currently possess by identifying the nodes within the generated learning graph connected to the target knowledge node by one of the plurality of edges associated with the at least one skill the student does not currently possess;
computer readable program code configured to identify a plurality of alternate paths between the proficiency input and the target knowledge node based upon the at least one determined skill requirement, wherein each of the alternate paths identifies skills and proficiencies required for traversing a corresponding path and wherein at least one of the identified paths comprises a path requiring a least amount of total effort by the student;
computer readable program code configured to calculate a gap between the pro

Assignees

• IBM

Inventors

• Contractor Danish
• Gopinath Ramesh Ambat
• Mohania Mukesh Kumar
• Negi Sumit
• Rajput Nitendra

Classifications

• G09B19/00 Primary

  Teaching not covered by other main groups of this subclass (teaching or practice apparatus for gun-aiming or gun-laying F41G3/26) · CPC title