US 12,755,198 B2Granted

Intent-driven adaptive learning delivery

AssigneeDell Products L.P.

InventorsEloy Francisco Macha, Stephen James Todd, Robert Anthony Lincourt, Jr.

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Abstract

A method and system for intent-driven adaptive learning delivery. Intent-driven adaptive learning delivery may entail the conveyance of a learning curriculum surrounding a learning topic and a learning intent reflecting the reason for pursuing the learning topic. A learning curriculum, in turn, may generally refer to an ordered (or sequenced) manifest of learning materials and/or content that may progressively advance user proficiency in at least the learning topic. Existing systems or solutions offering learning curriculums today advance individual skills based on inferred educational goals for, and provide a static presentation of materials/content to, any given user. As an improvement over said existing systems/solutions, embodiments disclosed herein provide learning curriculums accounting for user learning preferences, the sought learning intent, and the user talent information.

Claims12

Dependent claims

A method for intent-driven adaptive learning delivery, the method comprising:

receiving a learning query comprising a learning topic and a learning intent;
obtaining a user profile for an organization user,
wherein the learning query originates from the organization user, and
wherein the user profile comprises:
user learning preferences associated with the organization user and user access permissions associated with the organization user;
obtaining a metadata graph representative of an asset catalog;
filtering, based on the learning topic, the metadata graph to identify a node subset;
selecting, based on the learning intent, a reduced node subset from the node subset;
generating a k-partite metadata graph using the reduced node subset;
and
creating a learning curriculum based on the k-partite metadata graph,
wherein creating the learning curriculum based on the k-partite metadata graph, comprises:
identifying at least one key node in the k-partite metadata graph;
adjusting an edge weight associated with at least one edge in the k-partite metadata graph to obtain at least one adjusted edge weight,
wherein the edge weight is adjusted based on the user learning preferences;
determining, based on the at least one key node and the at least one adjusted edge weight, a learning path traversing at least a portion of the k-partite metadata graph;
identifying a set of learning path nodes positioned along the learning path;
after identifying the set of learning path nodes and prior to creating the learning curriculum:
for each learning path node in the set of learning path nodes, and to identify the set of assets and to complete a set of assessments respective to the set of assets:
extracting asset metadata from an asset catalog entry of the asset catalog, wherein the asset metadata describes an asset in the set of assets and the asset catalog entry corresponds to the learning path node;
and
performing an assessment, in the set of assessments, of the user access permissions against compliance information associated with the asset, wherein the asset metadata comprises the compliance information;
producing access remarks based on the set of assessments, wherein the learning curriculum further comprises the access remarks;
and
creating the learning curriculum comprising a manifest of assets listing a set of assets corresponding, respectively, to the set of learning path nodes.

22 more elements

A non-transitory computer readable medium (CRM) comprising computer readable program code, which when executed by a computer processor, enables the computer processor to perform a method for intent-driven adaptive learning delivery, the method comprising:

receiving a learning query comprising a learning topic and a learning intent;
obtaining a user profile for an organization user,
wherein the learning query originates from the organization user, and
wherein the user profile comprises:
user learning preferences associated with the organization user and user access permissions associated with the organization user;
obtaining a metadata graph representative of an asset catalog;
filtering, based on the learning topic, the metadata graph to identify a node subset;
selecting, based on the learning intent, a reduced node subset from the node subset;
generating a k-partite metadata graph using the reduced node subset;
and
creating a learning curriculum based on the k-partite metadata graph,
wherein creating the learning curriculum based on the k-partite metadata graph, comprises:
identifying at least one key node in the k-partite metadata graph;
adjusting an edge weight associated with at least one edge in the k-partite metadata graph to obtain at least one adjusted edge weight,
wherein the edge weight is adjusted based on the user learning preferences;
determining, based on the at least one key node and the at least one adjusted edge weight, a learning path traversing at least a portion of the k-partite metadata graph;
identifying a set of learning path nodes positioned along the learning path;
after identifying the set of learning path nodes and prior to creating the learning curriculum:
for each learning path node in the set of learning path nodes, and to identify the set of assets and to complete a set of assessments respective to the set of assets:
extracting asset metadata from an asset catalog entry of the asset catalog, wherein the asset metadata describes an asset in the set of assets and the asset catalog entry corresponds to the learning path node;
and
performing an assessment, in the set of assessments, of the user access permissions against compliance information associated with the asset, wherein the asset metadata comprises the compliance information;
producing access remarks based on the set of assessments, wherein the learning curriculum further comprises the access remarks;
and
creating the learning curriculum comprising a manifest of assets listing a set of assets corresponding, respectively, to the set of learning path nodes.

22 more elements

A system, the system comprising:

a client device;
and
an insight service operatively connected to the client device, and comprising a computer processor configured to perform a method for intent-driven adaptive learning delivery, the method comprising:
receiving a learning query comprising a learning topic and a learning intent;
obtaining a user profile for an organization user,
wherein the learning query originates from the organization user, and
wherein the user profile comprises:
user learning preferences associated with the organization user and user access permissions associated with the organization user;
obtaining a metadata graph representative of an asset catalog;
filtering, based on the learning topic, the metadata graph to identify a node subset;
selecting, based on the learning intent, a reduced node subset from the node subset;
generating a k-partite metadata graph using the reduced node subset;
and
creating a learning curriculum based on the k-partite metadata graph,
wherein creating the learning curriculum based on the k-partite metadata graph, comprises:
identifying at least one key node in the k-partite metadata graph;
adjusting an edge weight associated with at least one edge in the k-partite metadata graph to obtain at least one adjusted edge weight,
wherein the edge weight is adjusted based on the user learning preferences;
determining, based on the at least one key node and the at least one adjusted edge weight, a learning path traversing at least a portion of the k-partite metadata graph;
identifying a set of learning path nodes positioned along the learning path;
after identifying the set of learning path nodes and prior to creating the learning curriculum:
for each learning path node in the set of learning path nodes, and to identify the set of assets and to complete a set of assessments respective to the set of assets:
extracting asset metadata from an asset catalog entry of the asset catalog, wherein the asset metadata describes an asset in the set of assets and the asset catalog entry corresponds to the learning path node;
and
performing an assessment, in the set of assessments, of the user access permissions against compliance information associated with the asset, wherein the asset metadata comprises the compliance information;
producing access remarks based on the set of assessments, wherein the learning curriculum further comprises the access remarks;
and
creating the learning curriculum comprising a manifest of assets listing a set of assets corresponding, respectively, to the set of learning path nodes.

25 more elements

Dependencies are inferred from the claim text.