A method, a device, an apparatus and a storage medium of displaying information on video are provided. The method includes acquiring a touchable element to be displayed in a process of playing video and configuration information of the touchable element sent from a server; determining, based on the configuration information of the touchable element, display time of the touchable element in the process of playing video and a display location of the touchable element on video interface, and displaying the touchable element based on the display time and the display location; and when a touch operation on the touchable element which is displayed is detected, responding to the touch operation based on a preset response tactic.

A system for creating educational assessments from content files using an API and inserting the educational assessments into learning programs using tokens.

A system for creating educational assessments from content files using an API and inserting the educational assessments into learning programs using tokens.

To efficiently assess, prioritize, and re-assess individuals respectively for intervention OR for ongoing programs/activities OR for personalized rehabilitation or training activities: A Computerized Interactive Psychological Assessment Protocol including the steps of: using a predetermined interactive media, interfacing with a client, (A) accepting some predetermined goal-relevant self-assessment responses from the client, regarding the client's respective motivation, belief, know-how, state-of-mind, activity, etc.; (B) accepting self-characterization responses from the client, regarding the client's respective personality; (C) preferably electronically characterizing the responses according to at least one metric from the list: client's response time, client's preference, among interactive task/query modes, and client's respective response physiology; and (D) electronically storing a data representation of the responses and characterizations, along with a time stamping, for use in a longitudinal analysis of the client psychological development.

To efficiently assess, prioritize, and re-assess individuals respectively for intervention OR for ongoing programs/activities OR for personalized rehabilitation or training activities: A Computerized Interactive Psychological Assessment Protocol including the steps of: using a predetermined interactive media, interfacing with a client, (A) accepting some predetermined goal-relevant self-assessment responses from the client, regarding the client's respective motivation, belief, know-how, state-of-mind, activity, etc.; (B) accepting self-characterization responses from the client, regarding the client's respective personality; (C) preferably electronically characterizing the responses according to at least one metric from the list: client's response time, client's preference, among interactive task/query modes, and client's respective response physiology; and (D) electronically storing a data representation of the responses and characterizations, along with a time stamping, for use in a longitudinal analysis of the client psychological development.

Cognitive and mood states of a real world person are assessed according to activity in a virtual world environment with which the person interacts. The virtual world is configured to provide interactive experiences for assessing the person's cognitive and/or mood states. The system requires configuration of a session avatar during each virtual world session to provide then-current insight into the person's mood state. The system may require configuration of an avatar reflective of the person's state. The system requires the person to configure the virtual world environment during each virtual session to provide then-current insight into the person's mood state. The system permits the user to visit destinations, perform tasks and play games that are included in the environment for the purpose of providing insight into the person's cognitive and/or mood states according to the person's selections and/or performance.

Cognitive and mood states of a real world person are assessed according to activity in a virtual world environment with which the person interacts. The virtual world is configured to provide interactive experiences for assessing the person's cognitive and/or mood states. The system requires configuration of a session avatar during each virtual world session to provide then-current insight into the person's mood state. The system may require configuration of an avatar reflective of the person's state. The system requires the person to configure the virtual world environment during each virtual session to provide then-current insight into the person's mood state. The system permits the user to visit destinations, perform tasks and play games that are included in the environment for the purpose of providing insight into the person's cognitive and/or mood states according to the person's selections and/or performance.

The present disclosure provides systems and methods for providing interface rendering of passages for test item generation. Methods and systems can utilize natural language processing (NLP) and machine learning (ML) models to analyze passages that were provided in historical testing environments (e.g., first passage), determine one or more similar search strings that are also found in a current passage (e.g., second passage), and provide the first and second passages to a user interface of a user device. On the display, the search string in the historical and current passages may be highlighted at the user interface to identify the similarities.

Apparatus, systems, and methods are provided for generating a quantified indicator of cognitive skills in an individual. In certain configurations, the apparatus, systems, and methods can be implemented for enhancing cognitive skills in an individual.

A learner engagement engine provides a unique way to track and measure a learner's engagement across a plurality of different learning resources. In preferred embodiments, the learning engagement engine measures learner's engagement activities at the most detailed level (such as at a paragraph level, instead of a chapter or book level). This allows the learner engagement engine to easily aggregate learner activities, even when a course structure or context are changed during the course.