METHOD AND PLATFORM FOR OPTIMIZING LEARNING AND LEARNING RESOURCE AVAILABILITY
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Abstract
A platform and method for improving learning within a learning model uses a mathematical optimization algorithm to maximize learning gains through efficient resource allocation that accounts for practical constraints, such as teacher or other resource availability, and probability of success for individual learners on learning nodes given learner profile and resource and instructional configurations. One practical output from this platform and method is a schedule that contains an assignment of learners to learning nodes and teaching resources by learning session over the course of several days.
28 Citations
31 Claims
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1-10. -10. (canceled)
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11. A computer-implemented method for automated optimization of learning content delivery and learning resource allocation comprising:
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(a) identifying a plurality of input data; (b) pre-processing said plurality of input data via a data pre-processing module into a series of possible input data combinations; (c) assigning a utility value to each possible data combination; (d) utilizing said utility values to optimally allocate learning resources and learning content for one or more students via a mathematical optimization algorithm; (e) generating an assignment schedule reflecting said optimal allocation for said one or more students; and (f) exporting said assignment schedule to an end user. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19, 20, 21)
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22. A computer-implemented method for automated optimization of learning content delivery and learning resource allocation comprising:
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(a) identifying input data comprising a plurality of students to be assigned a schedule, the learning content available to be assigned to said plurality of students, and the learning modalities available to teach said plurality of students said learning content; (b) pre-processing said input data to generate one or more student-learning content-learning modality combinations for each student; (c) assigning each student-learning content-learning modality combination a utility value; (d) utilizing a mathematical optimization algorithm to generate an assignment schedule by selecting a student-learning content-learning modality combination that maximizes the total sum of utility values for all students; (e) storing each selected student-learning content-learning modality combination in a data store; (f) exporting said assignment schedule to an end user; and (g) updating said stored student-learning content-learning modality combination to reflect mastery or non-mastery of said student-learning content-learning modality combination following each student mastery attempt. - View Dependent Claims (23, 24)
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25. A computer-implemented method for automated optimization of learning content delivery and learning resource allocation to a plurality of students, wherein the learning content comprises a plurality of learning targets, said method comprising:
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A. providing, as input, data relating to; 1. learning modalities for delivering instruction relating to learning content 2. learning resources available for delivery of the instruction; 3. at least one learning model for the content which expresses interrelationships between the learning targets; 4. proficiency status of each student for each of the learning targets of the content; B. with a computerized optimization algorithm, manipulating the input data provided in step A to automatically generate, for each student, a schedule of learning content delivery comprising; 1. at least one unlearned learning target for which the student is not presently proficient; 2. a learning modality by which instruction relating to said unlearned learning target will be delivered to the student; and 3. a learning resource with which instruction relating to said unlearned learning target will be delivered to the student; C. delivering instruction relating to the unlearned learning target to each student in accordance with each student'"'"'s schedule generated in step B; D. after step C, assessing each student'"'"'s proficiency in the unlearned learning target included in the schedule generated in step B; and E. updating the input data relating to the proficiency of each student for the unlearned learning target. - View Dependent Claims (26, 27, 28, 29, 30, 31)
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Specification