Techniques described herein provide intelligent context-based testing. One or more implementations receive an image that includes content. In turn, some implementations process the image to extract test information from the content, such as questions, answers, learning material, and so forth. By analyzing the test information, various implementations determine one or more characteristics associated with the test information, and dynamically generate new test information based on the determined one or more characteristics. As one example, some implementations obtain new content by searching for content that includes the one or more characteristics and generate new test information based on the new content and the extracted test information.

Techniques described herein provide intelligent context-based testing. One or more implementations receive an image that includes content. In turn, some implementations process the image to extract test information from the content, such as questions, answers, learning material, and so forth. By analyzing the test information, various implementations determine one or more characteristics associated with the test information, and dynamically generate new test information based on the determined one or more characteristics. As one example, some implementations obtain new content by searching for content that includes the one or more characteristics and generate new test information based on the new content and the extracted test information.

Techniques described herein provide intelligent context-based testing. One or more implementations receive an image that includes content. In turn, some implementations process the image to extract test information from the content, such as questions, answers, learning material, and so forth. By analyzing the test information, various implementations determine one or more characteristics associated with the test information, and dynamically generate new test information based on the determined one or more characteristics. As one example, some implementations obtain new content by searching for content that includes the one or more characteristics and generate new test information based on the new content and the extracted test information.

Techniques described herein provide intelligent context-based testing. One or more implementations receive an image that includes content. In turn, some implementations process the image to extract test information from the content, such as questions, answers, learning material, and so forth. By analyzing the test information, various implementations determine one or more characteristics associated with the test information, and dynamically generate new test information based on the determined one or more characteristics. As one example, some implementations obtain new content by searching for content that includes the one or more characteristics and generate new test information based on the new content and the extracted test information.

The present disclosure pertains to a system configured to generate an adaptive embodied conversational agent to provide interactive virtual coaching to a subject. The system comprises a user interface, one or more hardware processors, and a display. The user interface is configured to obtain input information related to the subject. The one or more hardware processors are configured by machine-readable instructions to: determine a customized digital coaching plan for the subject; and generate visual and/or audio signals that convey the appearance and behavior of the adaptive embodied conversational agent based on the customized digital coaching plan, and/or based on a relationship parameter. The display is configured to receive the generated visual and/or audio signals and cause presentation of the adaptive embodied conversational agent on the display to provide the customized digital coaching plan to the subject interactively.

The present disclosure pertains to a system configured to generate an adaptive embodied conversational agent to provide interactive virtual coaching to a subject. The system comprises a user interface, one or more hardware processors, and a display. The user interface is configured to obtain input information related to the subject. The one or more hardware processors are configured by machine-readable instructions to: determine a customized digital coaching plan for the subject; and generate visual and/or audio signals that convey the appearance and behavior of the adaptive embodied conversational agent based on the customized digital coaching plan, and/or based on a relationship parameter. The display is configured to receive the generated visual and/or audio signals and cause presentation of the adaptive embodied conversational agent on the display to provide the customized digital coaching plan to the subject interactively.

Tree-diagram design interface processes for creating surveys, simulations, and intelligent tutoring systems are disclosed. The tree-diagram design interface processes create surveys, simulations, and intelligent tutoring systems in a highly intuitive manner that can be nearly universally understood with minimal instruction. Moreover, the tree-diagram design interface utilizes an easily understood 1:1 ratio of inputs between graphical elements in the design interface and actual elements of the survey, simulation, or intelligent tutoring system, whereby each input in the design phase has a clear and identical output in the survey, simulation, or intelligent tutoring system itself.

Tree-diagram design interface processes for creating surveys, simulations, and intelligent tutoring systems are disclosed. The tree-diagram design interface processes create surveys, simulations, and intelligent tutoring systems in a highly intuitive manner that can be nearly universally understood with minimal instruction. Moreover, the tree-diagram design interface utilizes an easily understood 1:1 ratio of inputs between graphical elements in the design interface and actual elements of the survey, simulation, or intelligent tutoring system, whereby each input in the design phase has a clear and identical output in the survey, simulation, or intelligent tutoring system itself.

Systems and processes are provided for analyzing a test taker's knowledge, skills, and cognitive function. The systems and processes include smart questions (i.e., SmartItems) programmed with coded variables, or for multiple choice varieties, variable sets of options to cover an entire skill set being tested. The systems and processes generate questions in real time during administration of the test, by formulating and displaying, to a test taker, random combinations of a question stem and randomly-selected question components. This smart question content is unpredictably and randomly presented, as representations of the skill to be tested. The systems and processes analyze the test taker's knowledge, skills, and cognitive function about the entire domain of the skill, rather than a single fact. The systems and processes provide security to test administration.

Systems and processes are provided for analyzing a test taker's knowledge, skills, and cognitive function. The systems and processes include smart questions (i.e., SmartItems) programmed with coded variables, or for multiple choice varieties, variable sets of options to cover an entire skill set being tested. The systems and processes generate questions in real time during administration of the test, by formulating and displaying, to a test taker, random combinations of a question stem and randomly-selected question components. This smart question content is unpredictably and randomly presented, as representations of the skill to be tested. The systems and processes analyze the test taker's knowledge, skills, and cognitive function about the entire domain of the skill, rather than a single fact. The systems and processes provide security to test administration.