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US 2015/0147741 A1Published application
Learning system self-optimization
AssigneePearson Education, Inc.
InventorPerry M. Spagnola
Life of this patent
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Abstract
A method/system for learning system self-optimization is disclosed. The learning system can include a plurality of learning objects that are connected to each other by a plurality of learning vectors. The learning vectors can identify a prerequisite relationship between the connected learning objects and include data indicating a likelihood of success of a student in traversing the learning vector and/or an expected speed for traversing the learning vector. Data generated from a student's traversal of one of the learning vectors can be used to strengthen or weaken the traversed learning vector based on the student experience.
Claims28
A method of maintaining a learning vector comprising:
- identifying on a processor a first learning object, wherein the first learning object comprises a first aggregation of learning content, wherein the aggregation of learning content is associated with an assessment;
- identifying on the processor a second learning object, wherein the second learning object comprises a second aggregation of learning content, wherein the aggregation of learning content is associated with an assessment;
- identifying on the processor a prerequisite relationship between the first learning object and the second learning object, wherein the first learning object is a prerequisite to the second learning object;
- generating on the processor a learning vector connecting the first learning object and the second learning object, the learning vector comprising a direction and a strength, wherein the direction of the learning vector indicates that the first learning object is a prerequisite of the second learning object, and the strength of the learning vector indicates a likelihood of a student successfully traversing the learning vector, wherein the strength of the learning vector varies with respect to a student context, wherein the student context describes an attribute of the student;
- receiving at the processor an input indicative of the traversal of the learning vector, wherein the input identifies a student property and the effectiveness of the learning vector;
- determining on the processor a value according to a Boolean function, wherein the value comprises a first value if the input indicative of the traversal of the learning vector indicates a desired outcome and wherein the value comprises a second value if the input indicative of the traversal of the learning vector indicates an undesired outcome, and
- determining if the student context of the student corresponds to a context of a first at least one student that previously traversed the learning vector if the first value is determined;
- strengthening the learning vector if the first value is determined and if the student context of the student corresponds to the context of the first at least one student that previously traversed the learning vector.
5 more elements
A method of optimizing a learning vector within a learning object network, the method comprising:
- identifying on a processor an incident learning object, wherein the incident learning object comprises an initial position of a student within the learning object network;
- identifying on the processor a plurality of potential terminal learning objects, wherein the potential terminal learning objects each comprise an aggregation of learning content associated with an assessment, and wherein the incident learning object is a prerequisite to each of the potential terminal learning objects;
- identifying on the processor a plurality of learning vectors, each of the plurality of learning vectors extending from the incident learning object to one of the potential terminal learning objects, wherein each of the plurality of learning vectors indicates the prerequisite relationship with the incident learning object and identifies the strength of the learning vector, wherein the strength of the learning vector varies with respect to a student context, wherein the student context describes an attribute of the student;
- selecting with the processor one of the plurality of potential terminal learning objects as the terminal learning object;
- providing the terminal learning object to the student;
- adding an identifier to memory associating the terminal learning object with the student;
- receiving at the processor an indicator of the completion of the learning object, wherein the indicator identifies a student property and the effectiveness of the learning vector;
- determining with the processor a value according to a Boolean function, wherein the value comprises a first value if the indicator of the completion of the learning object indicates a desired outcome and wherein the value comprises a second value if the indicator of the completion of the learning object indicates an undesired outcome,
- determining if the student context of the student corresponds to a context of at least one student that previously traversed the learning vector if the first value is determined;
- and
- adjusting the strength of the learning vector according to the value, wherein the learning vector is strengthened if the value comprises the first value and if the student context of the student corresponds to the context of the at least one student that previously traversed the learning vector.
8 more elements
Dependencies are inferred from the claim text.