The present invention relates to a method, system, and non-transitory computer-readable recording medium for supporting learning. According to one aspect of the invention, there is provided a method for supporting learning, the method comprising the steps of: acquiring a learner's score for at least one assessment item included in a scoring table, wherein the learner has solved a question for learning and the scoring table is applied to a descriptive answer of the learner; determining a weak learning element of the learner with reference to the acquired score and at least one learning element associated with the at least one assessment item; and determining a supplementary learning path to be provided to the learner with reference to the determined weak learning element.

The present invention relates to a method, system, and non-transitory computer-readable recording medium for supporting learning. According to one aspect of the invention, there is provided a method for supporting learning, the method comprising the steps of: acquiring a learner's score for at least one assessment item included in a scoring table, wherein the learner has solved a question for learning and the scoring table is applied to a descriptive answer of the learner; determining a weak learning element of the learner with reference to the acquired score and at least one learning element associated with the at least one assessment item; and determining a supplementary learning path to be provided to the learner with reference to the determined weak learning element.

Various embodiments provide methods and devices for utilizing content conversion for the communication of content. In an embodiment, method, performed by a user device, includes receiving a user input comprising one or more user preferences to facilitate at least one output content; Further, the method includes receiving at least one input content from at least one content source based on the one or more user preferences. Thereafter, the method includes separating the at least one input content from the at least one content source using delimiters, and generating the at least one output content from the at least one input content based on one or more content characteristics. The at least one output content has data size less than the data size of the at least one input content. Furthermore, the method includes transmitting, the at least one output content to another user device.

A computer-implemented method for customizing training contents for a user, including: establishing a user profile and a personal learning corpus for the user; generating a first baseline indicating that the user is interested and a second baseline indicating that the user is not interested; monitoring the user's reactions when the user is consuming contents related to a second topic, wherein the reactions include the one or more of biometrical indicators, facial expressions, and body language; comparing the reactions with the first baseline and the second baseline to determine an interest level; and recommending additional contents related to the second topic if the interest level is higher than a predefined threshold.

A computer-implemented method for customizing training contents for a user, including: establishing a user profile and a personal learning corpus for the user; generating a first baseline indicating that the user is interested and a second baseline indicating that the user is not interested; monitoring the user's reactions when the user is consuming contents related to a second topic, wherein the reactions include the one or more of biometrical indicators, facial expressions, and body language; comparing the reactions with the first baseline and the second baseline to determine an interest level; and recommending additional contents related to the second topic if the interest level is higher than a predefined threshold.

Disclosed herein are embodiments for managing a task including one or more skills. A server stores a virtual environment, software agents configured to collect data generated when a user interacts with the virtual environment to perform the task, and a predictive machine learning model. The server generates virtual entities during the performance of the task, and executes the predictive machine learning model to configure the virtual entities based upon data generated when the user interacts with the virtual environment. The server generates the virtual environment and the virtual entities configured for interaction with the user during display by the client device, and receives the data collected by the software agents. The system displays a user interface at the client device to indicate a measurement of each of the skills during performance of the task. The server trains the predictive machine learning model using this measurement of skills during task performance.

A computer-implemented adaptive group training method a computer accessing a virtual system and initiating a group training exercise for training a trainee group comprising one or more trainees, the group training exercise including one or more challenges to the virtual system, each of the one or more challenges including a pre-defined sequence of one or more injectable events; the computer controlling subsequent execution of the group training exercise comprising injecting the injectable events; and the computer evaluating performance of the trainee group during the subsequent execution of the group training exercise, including analyzing actions taken by the trainee group in response to each of the injections, and attributing one or more of the actions taken to a trainee.

A computer-implemented adaptive group training method a computer accessing a virtual system and initiating a group training exercise for training a trainee group comprising one or more trainees, the group training exercise including one or more challenges to the virtual system, each of the one or more challenges including a pre-defined sequence of one or more injectable events; the computer controlling subsequent execution of the group training exercise comprising injecting the injectable events; and the computer evaluating performance of the trainee group during the subsequent execution of the group training exercise, including analyzing actions taken by the trainee group in response to each of the injections, and attributing one or more of the actions taken to a trainee.

Disclosed are various embodiments of a module publication application, interactive modules, and student user interfaces that make lectures more interactive. An instructor user interface generated by the module publication application captures a video of a lecture. Interactive modules including video segments and segment metadata are generated based on the video. A student user interface can render a presentation of the video segments and an interactive region showing questions that are related to the presentation. The questions shown in the interactive region can be updated based on a current timecode of the presentation.

An on-line education platform according to an embodiment of the present disclosure includes a main teacher video transmission system, an assistant teacher image management system, and a learning management system. The main teacher video transmission system unidirectionally provides a main teacher's teaching video to a plurality of student terminals. The assistant teacher image management system provides a bidirectional image or video together with each of the plurality of student terminals in response to event signals generated from the main teacher video transmission system and the plurality of student terminals based on the main teacher's teaching video. The learning management system provides control signals based on the event signals generated from the main teacher video transmission system and the plurality of student terminals and a remote support signal provided from the assistant teacher image management system.