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US 12,645,957 B2Granted
Course content data analysis and prediction
AssigneePearson Education, Inc.
InventorsDinesh De Silva, Irfan Fuard, Madushika Wijethunga, Vinothan Nadarajah
Life of this patent
Estimating the term…
Abstract
Systems and methods of the present invention provide for receiving, from a content activity agent on a first client device, a content usage data; input, into a machine learning model, at least one content activity parameter, translated from the content usage data; generating, using an output from the machine learning model, a graphical user interface (GUI), displayed on a second client device, and including a report of: the output, a recommendation for an update to a course content, and a prediction of an increase to an average assessment score associated with the course content if the updated content is used.
Claims20
A system comprising:
- a database coupled to a network and storing:
- a course content;
- a course content activity agent stored in association with the course content, wherein the course content activity agent includes software instructions to monitor user activity related to the course content;
- a content structure data related to a manner of presentation of the course content;
- and
- a machine learning model configured to generate a recommendation for an update to the course content based on an input feature set;
- a first client device coupled to the network and configured to, responsive to a request for the course content, (a) access the course content and the course content activity agent and (b) execute the software instructions of the course content activity agent to identify, in association with the course content, a content usage data related to user interaction with the course content, the content usage data comprising:
- an assessment score;
- and
- a user interaction time data;
- a server comprising at least one computing device coupled to the network and comprising at least one processor executing instructions within memory which, when executed, cause the system to:
- receive, through the network from the course content activity agent, the content usage data;
- receive, through the network, the content structure data;
- convert the content usage data and the content structure data into a feature set for the machine learning model;
- input the feature set into the machine learning model as the input feature set;
- and
- generate, using an output from the machine learning model, a graphical user interface (GUI), transmitted through the network and displayed on a second client device, comprising:
- a report of the output;
- the recommendation for the update to the course content, the recommendation including an identification of portions of the course content or of the content structure data that affect the assessment score;
- and
- a prediction, in response to the update, of an increase to an average assessment score associated with the course content.
18 more elements
A method comprising:
- storing, by a server comprising at least one computing device coupled to a network and comprising at least one processor executing instructions within memory, within a database coupled to the network:
- a course content;
- a course content activity agent stored in association with the course content, wherein the course content activity agent includes software instructions to monitor user activity related to the course content;
- a content structure data related to a manner of presentation of the course content;
- and
- a machine learning model configured to generate a recommendation for an update to the course content based on an input feature set;
- receiving, by the server, through the network from a first client device, a request for the course content;
- responsive to the request, providing, by the server, through the network to the first client device, the course content and the course content activity agent, wherein the first client device executes the software instructions of the course content activity agent while providing the course content to a user of the first client device;
- receiving, by the server, through the network from the course content activity agent executing on the first client device, a content usage data relating to user interaction with the course content, identified in association with the course content, the content usage data comprising:
- an assessment score;
- and
- a user interaction time data;
- receiving, by the server, through the network, the content structure data;
- converting, by the server, the content usage data and the content structure data into at least one feature set for the machine learning model;
- inputting, by the server, the at least one feature set into the machine learning model as the input feature set;
- and
- generating, by the server using an output from the machine learning model, a graphical user interface (GUI), transmitted through the network and displayed on a second client device, comprising:
- a report of the output;
- the recommendation for the update to the course content, the recommendation including an identification of portions of the course content or of the content structure data that affect the assessment score;
- and
- a prediction, in response to the update, of an increase to an average assessment score associated with the course content.
18 more elements
A system comprising a server, comprising at least one computing device coupled to a network and comprising at least one processor executing instructions within memory, the server being configured to:
- store, within a database coupled to the network:
- a course content;
- a course content activity agent stored in association with the course content, wherein the course content activity agent includes software instructions to monitor user activity related to the course content;
- a content structure data related to a manner of presentation of the course content;
- and
- a machine learning model configured to generate a recommendation for an update to the course content based on an input feature set;
- receive, through the network from a first client device, a request for the course content;
- responsive to the request, provide, through the network to the first client device, the course content and the course content activity agent, wherein the first client device executes the software instructions of the course content activity agent while providing the course content to a user of the first client device;
- receive, through the network from the course content activity agent executing on the first client device, a content usage data relating to user interaction with the course content, identified in association with the course content, the content usage data comprising:
- an assessment score;
- and
- a user interaction time data;
- receive, through the network, the content structure data;
- convert the content usage data and the content structure data into a set of feature vectors;
- input the set of feature vectors into the machine learning model as the input feature set;
- generate, using an output from the machine learning model, a graphical user interface (GUI), transmitted through the network and displayed on a second client device, comprising:
- a report of the output;
- the recommendation for the update to the course content, the recommendation including an identification of portions of the course content or of the content structure data that affect the assessment score;
- and
- a prediction, in response to the update, of an increase to an average assessment score associated with the course content.
17 more elements
Dependencies are inferred from the claim text.