Techniques are provided for machine learning-based educational content adaptation based on user personal characteristics. One method comprises obtaining personal characteristics of at least one user; applying the personal characteristics of the at least one user to at least one machine learning model to automatically adapt at least one educational content item for the at least one user using one or more of the applied personal characteristics of the at least one user; and initiating a provision of the at least one automatically adapted educational content item to the at least one user. Technology-related characteristics of the at least one user may also be applied to the at least one machine learning model to further adapt the at least one educational content item for the at least one user using the applied technology-related characteristics.

The invention provides a method and system for using a machine learning technique for identifying and outputting most relevant articles for a learning program.

The invention provides a method and system for using a machine learning technique for identifying and outputting most relevant articles for a learning program.

A method of managing an interaction of a student with a class about a subject, the subject having at least one lesson having at least one topic, the topic having at least one of exposition content, demonstration content and test content, the test content having a query and a scheme for mapping a response to a result, comprising: presenting content to the student and storing the interaction of the student with the content presented.

A method of managing an interaction of a student with a class about a subject, the subject having at least one lesson having at least one topic, the topic having at least one of exposition content, demonstration content and test content, the test content having a query and a scheme for mapping a response to a result, comprising: presenting content to the student and storing the interaction of the student with the content presented.

A processor on an industrial vehicle is programmed to identify a metric that characterizes an event associated with an operator of the industrial vehicle, where the metric has a performance parameter to evaluate against the event, and a behavior modification action that defines a desired operator behavior in response to the event. The processor is further operatively programmed to monitor for the event, and record event data that characterizes a response of the vehicle operator to the event. In response to detecting an event, the processor evaluates the recorded event data against the performance parameter to determine whether the vehicle operator demonstrated appropriate behavior for the event, computes a vehicle operator score based upon the evaluation, and performs the behavior modification action where the operator has not been inculcated to respond to the event.

A processor on an industrial vehicle is programmed to identify a metric that characterizes an event associated with an operator of the industrial vehicle, where the metric has a performance parameter to evaluate against the event, and a behavior modification action that defines a desired operator behavior in response to the event. The processor is further operatively programmed to monitor for the event, and record event data that characterizes a response of the vehicle operator to the event. In response to detecting an event, the processor evaluates the recorded event data against the performance parameter to determine whether the vehicle operator demonstrated appropriate behavior for the event, computes a vehicle operator score based upon the evaluation, and performs the behavior modification action where the operator has not been inculcated to respond to the event.

Example systems, methods, and apparatus are provided for using data collected from the responses of an individual with the computerized tasks of a cognitive platform to derive performance metrics as an indicator of cognitive abilities, and applying predictive models to generate an indication of neurodegenerative condition. The example systems, methods, and apparatus also can be configured to adapt the computerized tasks to enhance the individual's cognitive abilities, and for using data collected from the responses of an individual with the adapted computerized tasks to derive performance metrics and applying predictive models to generate the indication of neurodegenerative condition.

In one aspect, a device includes at least one processor and storage accessible to the at least one processor. The storage includes instructions executable by the at least one processor to receive input from at least one sensor, identify a characteristic of a user based on the input from the at least one sensor, and alter at least one setting of the device based on the identification of the characteristic. The at least one setting is related to presentation of content using the device.

A social electronic learning system, including a plurality of computing devices for communicating with a plurality of users in an educational community, and at least one server in communication with each of the plurality of computing devices, each server in communication with at least one data storage device configured to host a plurality of electronic portfolios, each electronic portfolio associated with one or more users of the plurality of users in the educational community, wherein each server is configured such that one or more users may associate one or more digital items with each electronic portfolio, and the plurality of users may take actions on the digital items in each electronic portfolio depending on authorization criteria.