Software for online active learning receives content posted to an online stream at a website. The software converts the content into an elemental representation and inputs the elemental representation into a probit model to obtain a predictive probability that the content is abusive. The software also calculates an importance weight based on the elemental representation. And the software updates the probit model using the content, the importance weight, and an acquired label if a condition is met. The condition depends on an instrumental distribution. The software removes the content from the online stream if a condition is met. The condition depends on the predictive probability, if an acquired label is unavailable.

Software for online active learning receives content posted to an online stream at a website. The software converts the content into an elemental representation and inputs the elemental representation into a probit model to obtain a predictive probability that the content is abusive. The software also calculates an importance weight based on the elemental representation. And the software updates the probit model using the content, the importance weight, and an acquired label if a condition is met. The condition depends on an instrumental distribution. The software removes the content from the online stream if a condition is met. The condition depends on the predictive probability, if an acquired label is unavailable.

The output means 81 outputs a threshold value indicating a proficiency level of a skill required to answer a target question in association with the proficiency level of the skill that the learner is assumed to have.

The output means 81 outputs a threshold value indicating a proficiency level of a skill required to answer a target question in association with the proficiency level of the skill that the learner is assumed to have.

The present disclosure provides a method, a system, and a storage medium for benchmarking-based intelligent analysis of an exam paper. The method includes the following steps: building a curriculum standard knowledge point database by analyzing the subject curriculum standard; and inputting an exam paper by using an image acquisition device, recognizing the exam paper by calling an optical character recognition (OCR) algorithm, building a mathematical model of the exam paper and comparing it with the curriculum standard knowledge base, and generating a personalized study condition diagnosis report. The present disclosure can objectively evaluate how well the examinees master the subject knowledge, so as to provide data support for the examinees to formulate a personalized flexible study plan.

A method, device and non-transitory computer-readable recording medium provide an audio engagement service for collecting pronunciations by accent. An audio engagement service method includes setting an accent indicating a country, an ethnic group, or a geographic region of a participant; generating audio uttered by the participant of a given example text into pronunciation content of the accent; and providing the pronunciation content with information on the accent.

The present disclosure provides a method and system for providing continuity of learning for early-age learners using a digital platform providing communication between educators and parents. The method comprises providing an educator interface; providing a parent interface; selecting a school activity completed in school using the educator interface; presenting said school activity completed to parents using the parent interface; presenting a media listing associated with said school activity completed to parents using the parent interface; viewing at least one item from said media listing using the parent interface; receiving, using the parent interface, input representing learning appreciation regarding said at least one item viewed using the parent interface; and displaying a result of said input representing learning appreciation using the educator interface.

A computer that selectively provides a recommendation is described. During operation, the computer may obtain game information associated with one or more video games played by an individual, where the game information specifies decisions and behaviors in the one or more video games while the individual played the one or more video games. Then, the computer may compute, for the individual, scores for a set of predefined attributes associated with occupations based at least in part on the decisions and/or the behaviors. Next, the computer may selectively provide the recommendation based at least in part on the computed scores, where the recommendation is associated with: an academic area of study for the individual, an employment opportunity for the individual, and/or an occupation for the individual.

A method and system for representing usage of an electronic learning system. The method and system involve receiving an input indicative of a selection of a property of the electronic learning system to be represented, the property including a course content provided by the electronic learning system and an activity available for that course content; receiving representation parameters that define a scope of the usage to be represented; determining an event count for the property during the period of interest; and generating a usage indicator for the property based at least on the event count. The usage indicator is generally reflective of at least a usage amount of the property during the period of interest.

A method and system for representing usage of an electronic learning system. The method and system involve receiving an input indicative of a selection of a property of the electronic learning system to be represented, the property including a course content provided by the electronic learning system and an activity available for that course content; receiving representation parameters that define a scope of the usage to be represented; determining an event count for the property during the period of interest; and generating a usage indicator for the property based at least on the event count. The usage indicator is generally reflective of at least a usage amount of the property during the period of interest.