Systems and methods for increasing learning via transcutaneous auricular vagus nerve stimulation is presented. The disclosure can include positioning a device within a human ear and delivering specifically timed and modulated pulses of electrical energy to the auricular vagus nerve transcutaneously, avoiding invasive procedures commonly associated with vagus nerve stimulation. The present disclosure can enhance reading comprehension, facilitate the learning letter-sound relationships, and provide for increased retention of new languages for a patient, all without surgically implanting a device into a patient.

This disclosure relates to the field of recommendation of learning competencies. The usage of competency-based learning platforms is growing as it provides a safe learning environment where learners/users can learn from the comfort of their homes at a convenient time. However, one of the challenges with competency-based learning platforms is to identify learning competencies/courses relevant to a learner as exhaustive material is available on the internet. The disclosure addresses the challenges by providing techniques for personalized recommendation of cognitive based learning competencies and skill based learning competencies. The disclosed techniques recommend cognitive based learning competencies and skill based learning competencies based on several techniques that include a machine learning, Natural Language Processing (NLP), a skill based recommendation technique and a collaborative cognitive recommendation technique. Hence the disclosure is an approach to enable a learner to assess the learner's current competencies and identify learning competencies required for a desired role.

Apparatus and methods for proactively and preemptively communicating with a user interacting with a software application are provided. The apparatus and methods may include an artificial intelligence/machine learning communication engine monitoring and tracking a user's interactions. The apparatus and methods may include the communication engine determining if the user requires further training, if the interaction is fraudulent, and pre-empting requests for information the user may commence. The apparatus and methods may include the communication engine creating and displaying training materials for the user to complete, revoking access if fraud is present, and proactively providing information before the user requests the information.

Method, apparatus and computer program for providing a personalized study plan to a learner through cognitive and behavioral diagnosis of the learner. A learner who uses a data input device such as a smart pen and a stylus pen by using data obtained from the data input device. The method, apparatus and computer program relate to technology for obtaining input data based on information inputted by a user for at least one question with the data input device, creating test behavior data on the user from the obtained input data, analyzing cognition and behavior of the user based on at least one of metadata on the at least one question and the created test behavior data, and providing a personalized study plan to the user through an algorithm using machine learning based on the cognition and behavior analysis.

Method, apparatus and computer program for providing a personalized study plan to a learner through cognitive and behavioral diagnosis of the learner. A learner who uses a data input device such as a smart pen and a stylus pen by using data obtained from the data input device. The method, apparatus and computer program relate to technology for obtaining input data based on information inputted by a user for at least one question with the data input device, creating test behavior data on the user from the obtained input data, analyzing cognition and behavior of the user based on at least one of metadata on the at least one question and the created test behavior data, and providing a personalized study plan to the user through an algorithm using machine learning based on the cognition and behavior analysis.

A method includes conserving processor resources by reducing a number of exercises presented to a student by applying a set of exercises performed by the student and the student's performance on those exercises to a neural network. A respective time period for each exercise in the set of exercises is applied to the neural network wherein each time period represents an amount of time since the student performed the exercise associated with the time period. For a candidate next exercise, a likelihood of the student successfully performing the candidate next exercise is obtained from the neural network and is used to select an exercise to present to the student next.

A method of providing learning to a user by a terminal includes the steps of: receiving user information from the user; displaying a first area for delivering information provided by a server to the user on the basis of the user information; displaying a second area for delivering a learning journey of the user to the user, wherein the second area includes a first icon representing a score predicted through a first test, one or more second icons representing a score predicted for each learning cycle, and a third icon representing a target score of the user; displaying an icon representing a learning cycle being performed by the user in the second area; and displaying a third area for delivering information related to the learning cycle being performed by the user.

A method of providing learning to a user by a terminal includes the steps of: receiving user information from the user; displaying a first area for delivering information provided by a server to the user on the basis of the user information; displaying a second area for delivering a learning journey of the user to the user, wherein the second area includes a first icon representing a score predicted through a first test, one or more second icons representing a score predicted for each learning cycle, and a third icon representing a target score of the user; displaying an icon representing a learning cycle being performed by the user in the second area; and displaying a third area for delivering information related to the learning cycle being performed by the user.

In an aspect a system for assessing entity expertise is presented. A system includes at least one entity. A system includes an entity intercommunication device. A system includes an entity conveyance system. An entity conveyance system includes a plurality of assessment devices. Each assessment device of a plurality of assessment devices is configured to receive an entity input and communicate the entity input to an entity intercommunication device. An entity conveyance system is configured to validate an entity input as a function of an exterior a data set and score the entity input as a function of the validation of the entity input.

In an aspect a system for assessing entity expertise is presented. A system includes at least one entity. A system includes an entity intercommunication device. A system includes an entity conveyance system. An entity conveyance system includes a plurality of assessment devices. Each assessment device of a plurality of assessment devices is configured to receive an entity input and communicate the entity input to an entity intercommunication device. An entity conveyance system is configured to validate an entity input as a function of an exterior a data set and score the entity input as a function of the validation of the entity input.