This application relates to a method of constructing a training program for improving symptoms of a mild cognitive impairment patient. In one aspect, the method includes arranging, on designated days, direct training algorithms regarding at least one of visualization, fusion, or semantic word fluency directly related to a cognitive function area and controlling the arranged direct training algorithms to be output to a user terminal according to the designated days, and receiving a result value from the user terminal. The method may also include calculating an achievement level for each direct training algorithm, based on the result value, and determining one of the direct training algorithms based on the calculated achievement level. The method may further include rearranging the direct training algorithms, together with the determined direct training algorithm based on both the calculated achievement level and a training algorithm matched to the determined direct training algorithm.

This application relates to a method of constructing a training program for improving symptoms of a mild cognitive impairment patient. In one aspect, the method includes arranging, on designated days, direct training algorithms regarding at least one of visualization, fusion, or semantic word fluency directly related to a cognitive function area and controlling the arranged direct training algorithms to be output to a user terminal according to the designated days, and receiving a result value from the user terminal. The method may also include calculating an achievement level for each direct training algorithm, based on the result value, and determining one of the direct training algorithms based on the calculated achievement level. The method may further include rearranging the direct training algorithms, together with the determined direct training algorithm based on both the calculated achievement level and a training algorithm matched to the determined direct training algorithm.

The present invention relates to a mathematical learning module for educating students learning arithmetic through kinesthetic learning and relates particularly to a system that explains the concept of regrouping in carrying forward and borrowing by introducing the concept for two- or three-digit number regrouping. This type of learning can lead to increased retention of the material and is a way for students to practice developing their problem-solving skills.

The present invention relates to a mathematical learning module for educating students learning arithmetic through kinesthetic learning and relates particularly to a system that explains the concept of regrouping in carrying forward and borrowing by introducing the concept for two- or three-digit number regrouping. This type of learning can lead to increased retention of the material and is a way for students to practice developing their problem-solving skills.

Systems and methods of automatically distilling concepts from math problems and dynamically constructing and testing the creation of math problems from a collection of math concepts comprising: providing a user interface to a user; receiving as input: a math problem; one or more math concepts; and/or a user data packet; extracting and compiling a concept cloud of one or more CLIs that comprise the mathematical concepts embodied in the input, describe the operation of the one or more math concepts, or relate to the UDP, respectively; generating one or more math problem building blocks from the concept cloud CLIs; applying a mathematical rules engine to the one or more math problem building blocks to build one or more additional math problems; and returning to the user, through the user interface, the one or more additional math problems built from the CLIs that define the concept cloud extracted from the input.

A method includes conserving processor resources by reducing a number of exercises presented to a student by applying a set of exercises performed by the student and the student's performance on those exercises to a neural network. A respective time period for each exercise in the set of exercises is applied to the neural network wherein each time period represents an amount of time since the student performed the exercise associated with the time period. For a candidate next exercise, a likelihood of the student successfully performing the candidate next exercise is obtained from the neural network and is used to select an exercise to present to the student next.

Systems and methods for cognitive training using voice command are described. One aspect includes a device to repeatedly present visual stimuli to a user that require performance of a task. A microphone may be positioned to provide audio input from the user to the device, with the audio input from the user providing input required to measure task performance. A processing system may perform real-time analysis of measured task performance.

Systems and methods for education instrumentation can include one or more servers configured generate a plurality of models for modeling various aspects of an education process using training data related to academic performance of students. The one or more servers can collect data from client devices associated with various education institutions or stakeholders throughout a life cycle of the education process. The one or more servers can use the generated models and the collected data to assess the addressing of education standards and predict or estimate performance metrics associated with the education process. The one or more servers can provide computed metrics or assessments of how well education standards are addressed to one or more client devices for display.

A non-transitory recording medium records a program that causes a computer to execute a process of causing a display to display, in response to one or more input operations accepted via an input device, one first mathematical expression display area including one first mathematical expression, one first graph display area associated with the one first mathematical expression display area, one first slider display area associated with the one first graph display area, one second mathematical expression display area including one second mathematical expression, one second graph display area which is associated with the one second mathematical expression display area and is an area different from the one first graph display area, and one second slider display area which is associated with the one second graph display area and is an area different from the one first slider display area.

This application relates to a method of constructing a training program for improving symptoms of a mild cognitive impairment patient. In one aspect, the method includes arranging, on designated days, direct training algorithms regarding at least one of visualization, fusion, or semantic word fluency directly related to a cognitive function area and controlling the arranged direct training algorithms to be output to a user terminal according to the designated days, and receiving a result value from the user terminal. The method may also include calculating an achievement level for each direct training algorithm, based on the result value, and determining one of the direct training algorithms based on the calculated achievement level. The method may further include rearranging the direct training algorithms, together with the determined direct training algorithm based on both the calculated achievement level and a training algorithm matched to the determined direct training algorithm.