Personalized electronic education

A computer-implemented method for employing an adaptive concept learning profile, the method comprising:

• assigning a concept from a set of stored concepts to a data matrix fields corresponding to a user profile, the concept including a competency from a competency template;
• determining a first concept learning profile from a set of stored concept learning profiles associated with the user profile, the concept learning profile including a confidence interval and a concept identifier from a plurality of concept identifiers stored within a learner profile;
• retrieving a plurality of explanations for association with the user profile within the data matrix fields based on the first concept learning profile, the plurality of explanations ranked based on a success metric indicating a relative strength of the plurality of explanations associated with the concept;
• providing an explanation from the plurality of explanations and an assessment associated with the concept to the user profile via a first output on a client device based on the concept identifier, wherein the explanation is associated with the largest success metric and the assessment includes at least one question to establish a percentage of correct response;
• determining an outcome of the assessment indicated by the percentage of correct response;
• and
• if the percentage of correct response is below a percentage threshold value, modifying the first concept learning profile to a second concept learning profile based on at least one of the data matrix fields when the confidence interval is below a confidence threshold value.

A computing device for defining an adaptive concept learning profile comprising:

• a memory capable of storing a concept learning profile data template that includes a data template sequence;
• and
• a processor in communication with the memory, configured to read the adaptive concept learning profile data template stored in the memory and cause the processor to:
• assign a concept from a set of stored concepts to a data matrix associated with a user profile, the concept including a competency from a competency template;
• determine a learning profile from a set of stored learning profiles associated with the user profile, the learning profile including a concept identifier from a sequence of concept identifiers associated with the competency template;
• retrieve a first explanation for association with the user profile based on the learning profile, the concept identifier, and a success metric indicating a relative strength of the first explanation as compared to at least one additional explanation;
• provide the first explanation to the user profile via a first output on a client device;
• retrieve a first assessment for association with the user profile based on the concept identifier, the first assessment including at least one probative question directed to the concept identifier;
• provide the first assessment for completion to the user profile via a second output on the client device and determining an outcome of the first assessment indicated by a percentage of correct responses to the first assessment;
• and
• if the outcome of the first assessment includes the percentage above a percentage threshold:
• provide an indication within the data matrix corresponding to the user profile indicating successful completion of the first assessment and updating the learning profile associated with the concept identifier to account for successful completion of the concept;
• and
• if the outcome of the first assessment includes the percentage below the percentage threshold:
• determine a number of attempted assessments completed by the user profile;
• update the learning profile associated with the concept identifier based on the number of attempted assessments being greater than an attempt threshold;
• retrieve a second explanation for association with the user profile based on the updated learning profile, the concept identifier, and the success metric indicating a relative strength of the second explanation as compared to at least the first explanation;
• provide the second explanation to the user profile via a third output on the client device and provide a second assessment for completion to the user profile via a fourth output on the client device;
• and
• determine a second outcome of the second assessment indicated by a percentage of correct responses to the second assessment.