In the prediction device, the acquisition means acquires student data related to the student. The preprocessing means generates training data based on the student data. The learning means generates at least one model that predicts the promotion situation of students based on the training data, by machine learning. The prediction means predicts the promotion situation of a subject student from the student data of the subject student using the generated model.

A skills learning method for a student gathers objective data relating to the student in response to various stimuli, and produces a predicted feedback units as a function of the objective data using a machine learning-base classifier. The method can include training a neural network using objective data of student interactions and associated subjective assessments of a skill of each objective data. The method includes receiving a new dataset with objective data of a new student and an associated subjective assessment of a skill of the first student represented by the new objective data. A predicted assessment of the skill of the new objective data is calculated by inputting the new objective data into the neural network. The method can include updating the neural network by combining the initial dataset and the new dataset and recompiling the neural network to fit the model dataset based on a learning algorithm.

A method of configuring a smart booklet to encourage adherence to a treatment and/or educational program is disclosed, wherein the smart booklet is “off the grid” (e.g., not connected to an electrical or networking grid) and includes an integrated behavior incentivization feature. Based on an activation of a detection feature of the smart booklet, it is detected whether a state of one or more pages of the smart booklet has changed. Based on the determination that the state of the one or more pages has changed, a set of data items pertaining to the adherence to the treatment and/or educational program is created or updated. Based on an identification that the set of data items is indicative of a failure or a success with respect to the adherence to the treatment program, a message pertaining to the failure or the success is communicated via an output component of the smart booklet (e.g., to encourage the adherence to the treatment and/or educational program).

Methods, systems and computer storage media are disclosed for providing resources to a platform issue. Embodiments describe associating educational resources and an event resource to resolve the platform issue.

The present invention relates to a user knowledge tracking method with more improved accuracy. An operation method of a user drop-out rate prediction system including a plurality of encoder neural networks and a plurality of decoder neural networks may include the steps of: inputting question information to a k.sup.th encoder neural network and inputting response information to a k.sup.th decoder neural network; generating query data, which is information about a question of which the correct answer probability is desired to be identified by the user, by reflecting a weight to the response information, and generating attention information to be used as a weight for the query data by reflecting a weight to the question information; and learning the user drop-out rate prediction system using the attention information as a weight for the query data.

Provided is an information processing device including an acquisition unit that acquires subjective evaluation information from a second user about each performance performed by at least part of a body of a first user moving, a learning unit that performs machine learning on a relationship between the each performance and the corresponding subjective evaluation information and generates relationship information between the each performance and the corresponding subjective evaluation information, and a presentation unit that presents feedback information to the second user based on the relationship information.

A method for assessing learning comprehension regarding a topic includes modifying a fundamental illustrative model to illustrate a first set of assessment assets of a first learning object of learning objects to produce a first assessment illustrative model. The fundamental illustrative model is based on illustrative assets of a lesson that includes the learning objects. The method further includes obtaining a first assessment response for the first assessment illustrative model. When the first assessment response is favorable, the method further includes modifying the fundamental illustrative model to illustrate a second set of assessment assets of a second learning object of the learning objects to produce a second assessment illustrative model and obtaining a second assessment response for the second assessment illustrative model.

A device, system and method for positioning monitors in schools is provided. One or more memories store: adversarial relationship data identifying adversarial relationships between students at a school; and schedule data indicative of spatiotemporal locations of the students having the adversarial relationships. A device accesses the adversarial relationship data and the schedule data. The device determines, based on the schedule data, spatiotemporal crosspaths at the school of the students having the adversarial relationships. The device determines a ranking of the spatiotemporal crosspaths. The device assigns one or more monitors to one or more of the spatiotemporal crosspaths. The device transmits notifications to communication devices associated with the one or more monitors, the notifications to instruct the one or more monitors to move to a respective assigned spatiotemporal crosspath.

A service use system includes circuitry to set, for each of a plurality of attribute types, a corresponding one of a plurality of connection destinations of a service. Each of the plurality of attribute types is to be obtained from a user terminal reading a touch point through which the service is to be provided. Each of the plurality of connection destinations is indicated by connection destination information with which the user terminal is to be connected to the corresponding one of the plurality of connection destinations. The circuitry generates touch point information to be obtained in response to the user terminal reading the touch point. The touch point information includes the connection destination information.

Evaluating examination scoring performance of exam evaluators is provided. Simulated examination sheets are generated that include new answer versions corresponding to examination questions regarding a particular subject matter for scoring by an exam evaluator. Each new answer version is generated based on a selected answer type comprised of a plurality of levels of a plurality of answer generating factors. A score is generated for each respective new answer version based on manipulation of model answers to the examination questions. An exam evaluation model of the exam evaluator scoring the new answer versions to the examination questions on the simulated examination sheets is formulated based on detected scoring deviations between computer-generated scores and evaluator-assigned scores for the new answer versions. Scores assigned by the exam evaluator to answers provided by a group of examinees to questions on the particular subject matter are adjusted based on the detected scoring deviations.