Pearson Education, Inc.

Sean York

Scott Hellman

David Strong

Tim Stewart

William M Murray

Steven H Hill

James Wyatt

Marko Rodriguez

Mark Potter

Brian Moriarty

Angela McAllister

Systems and methods for content aggregation creation are disclosed herein. The system can include memory having a content database and an aggregation database. The system can include a user device having a first network interface and a first I/O subsystem. The system can include a server that can: provide content to the user device via a first electrical signal; receive a selection of a portion of the provided content from the user device via a second electrical signal; automatically extract sentences from the selected portion of the provided content via a natural language processor; automatically generate a parse tree for one of the automatically extracted sentences; identify noun phrases from the part of speech tags within the parse tree; place content associated with one of the noun phrase in a content aggregation; and output the content aggregation to the user device.

System and method for automatic content aggregation generation

System and method for automatic content aggregation evaluation

System and method for decay-based content provisioning

Methods and systems for network-based intervention are disclosed. The methods can include receiving a user response and analyzing the user response and other user data to determine a user typology. The user typology can be compared with risk data that indicates the user's risk of failing to achieve a target outcome based on the identified user typology. If the user's risk of failing to achieve the target outcome exceeds a desired level, a mitigation plan can be generated and provided to the user to thereby facilitate in the attainment of the target outcome.

Network based intervention

System and method for automatic content aggregation database evaluation

Systems and method for alerting a user device based on a proposed anonymization of a contribution to a conversation thread via one or several location-based anonymization rules are disclosed herein. The system can include a user device that can have location-determining features that can determine a physical location of the user device; a network interface that can exchange data with a server via a communication network; and an I/O subsystem that can convert electrical signals to user-interpretable outputs in a user interface. The system can include a server that can: receive a contribution from the user device; determine an anonymization level for applying to the contribution; identify a potential identifier in the content of the contribution; anonymize the potential identifier according to the determined anonymization level; and generate and provide an alert to the user device.

Methods and systems for network-based analysis, intervention, and anonymization

Methods and systems for educational intervention are disclosed. The methods can include receiving a user response and analyzing the user response and other user data to determine a user typology. The user typology can be compared with risk data that indicates the user's risk of failing to achieve a target outcome based on the identified user typology. If the user's risk of failing to achieve the target outcome exceeds a desired level, a mitigation plan can be generated and provided to the user to thereby facilitate in the attainment of the target outcome.

Educational network based intervention

Growing community of inventors

San Diego, CA, United States of America

Sean York