System

Abstract

A system is provided.SOLUTION: This system includes a means for inputting the fundamental information of a child, a generation and AI means for generating a curriculum on the basis of the fundamental information of the child, a AI instructor means for advancing a lesson on the basis of the generated curriculum, a means for analyzing the progress situation of the lesson and the reaction of the child, a means for notifying an analytic result, and a means for linking and sharing information to a protector and an attending school.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] In modern society, parents face many challenges when balancing work and child-rearing. The problem of children on waiting lists for after-school care and ensuring a learning environment for children who do not attend school are particularly serious issues. There is also widespread dissatisfaction with the quality and cost of after-school care facilities and free schools, and there are concerns that these issues will lead to a decline in parents' labor productivity. The present invention aims to solve these problems and provide a more flexible and effective learning environment. [Means for solving the problem]

[0005] The present invention provides a system that includes a means for inputting basic information about a child, an AI generation means for generating a curriculum based on the child's basic information, an AI instructor means for conducting lessons based on the generated curriculum, a means for analyzing the progress of the lesson and the child's responses, a means for notifying the analysis results, and a means for linking and sharing information with parents and the child's school. This system ensures a learning environment at home for children, and addresses the issues of children on waiting lists for after-school care and children who do not attend school. Furthermore, the AI ​​instructor can customize the avatar, voice, and speaking style to suit each child's preferences, and dynamically adjust the curriculum based on the child's responses, enabling individualized and effective learning.

[0006] "Children" refers to children within a certain age range who are to receive education.

[0007] "Basic information" refers to information about a child that can be used to identify the individual, such as their name, age, and grade.

[0008] "Curriculum" refers to a plan that specifically outlines the schedule and content of children's learning and activities.

[0009] "Generative AI" refers to a program that uses artificial intelligence technology to analyze data and generate optimal curriculum.

[0010] An "AI instructor" refers to a virtual educator who conducts lessons and activities for children based on a curriculum created by generative AI.

[0011] "Progress" refers to information that indicates whether lessons or activities are proceeding as planned.

[0012] "Response" refers to feedback such as understanding, behavior, and answers that children show in response to lessons and activities.

[0013] "Analysis" refers to finding specific patterns and trends in collected data and organizing and interpreting the information based on that.

[0014] "Notification" refers to the act of transmitting specific information to a designated recipient (such as a guardian).

[0015] "Collaboration" refers to different systems and people sharing information and functions and working together. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0017] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0020] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0021] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0022] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0029] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0036] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0037] This invention is a learning support system for children, which can be used as an alternative to after-school care or free schools at home. This system uses generative AI to automatically generate learning curricula for children, and has "AI instructors" conduct the lessons.

[0038] System Overview

[0039] The system mainly consists of the following components:

[0040] 1. Server: Generates AI and manages the database.

[0041] 2. Device: A device operated by a user (parent or child). Examples include PCs, tablets, and smartphones.

[0042] 3. Users: Parents and children. Parents configure and monitor the system, while children learn.

[0043] System Implementation

[0044] 1. User registration and initial settings

[0045] The user opens the website or app on their device and enters their name, email address, and password on the "Create an Account" screen. The server saves the entered information in a database and sends a confirmation email. The user clicks on the link in the confirmation email to activate the account. The user then enters the child's basic information (name, age, grade level), and selects an avatar, voice, and speaking style on the "AI Instructor" settings screen. The server receives the selected settings information and reflects it in the generative AI model.

[0046] 2. Curriculum Generation

[0047] The server retrieves the child's basic information from the database and inputs it into the generation AI. The generation AI generates an optimal learning curriculum based on the child's information and stores it in the database. For example, for a 10-year-old child, a curriculum that incorporates a balanced mix of basic math, reading time, and exercise would be generated.

[0048] 3. Classes begin

[0049] When the user (child) presses the "Start Lesson" button on their device, the server retrieves the curriculum and launches the "AI Instructor" lesson program. The AI ​​Instructor conducts the lesson in an interactive format, monitoring the children's answers and reactions. For example, in a math class, the AI ​​Instructor poses a question and when the child enters the answer, the AI ​​Instructor determines whether it is correct or incorrect and moves on to the next step. The AI ​​Instructor also suggests appropriate breaks and playtimes to maintain the children's concentration.

[0050] 4. Status reporting and collaboration

[0051] When the lesson ends, the server analyzes the progress of the lesson and the student's reactions, summarizing the results and notifying parents. The information is also shared with the student's school, which automatically processes attendance certification. For example, the server can report on the areas in which the student struggled in today's lesson and the activities in which the student showed particular interest, allowing parents to understand their child's learning status.

[0052] Specific examples

[0053] For example, if a 10-year-old child uses this system, their parents will create an account through the initial setup process and enter their child's information and preferences. The AI ​​will then generate a curriculum optimized for their child, covering math, reading, and physical education. When the child begins class, an "AI instructor" will conduct the lesson interactively while the child works on the assignments. After the class ends, parents will receive a summary of the child's learning progress and responses, and attendance information will be shared with the school.

[0054] In this way, the system of the present invention provides flexible and effective after-school care and free school functions at home, improving children's learning environment.

[0055] The processing flow will be explained below.

[0056] Step 1:

[0057] The user opens a website or app on their device and enters their name, email address, and password on the "Create an account" screen. The server stores the information in a database and sends a confirmation email. The user clicks on a link in the email to activate their account.

[0058] Step 2:

[0059] The user logs in and enters the child's basic information (name, age, grade). Next, they select the avatar, voice, and speaking style in the "AI instructor" settings. For example, they can choose an anime-style avatar, a gentle voice, and a slow speaking style. The server saves the selected settings in a database and reflects them in the generative AI model.

[0060] Step 3:

[0061] The server retrieves the child's basic information from the database and inputs it into the generation AI. The generation AI generates the optimal learning curriculum based on the child's information. For example, for a 10-year-old child, a curriculum that incorporates a good balance of basic math, reading time, and exercise is generated. The generated curriculum is saved in the database.

[0062] Step 4:

[0063] The user (child) presses the "Start Lesson" button on the device. The server retrieves the curriculum and launches the "AI Instructor" lesson program. The AI ​​Instructor conducts the lesson in an interactive format. For example, in a math class, a question is posed and the child enters the answer, and the AI ​​Instructor determines whether it is correct or incorrect and moves on to the next step.

[0064] Step 5:

[0065] An AI instructor assesses students' understanding and responses in real time during lessons. The device collects the students' responses and sends them to a server. The server analyzes them and dynamically adjusts the curriculum content as needed. For example, if a student struggles with a particular math problem, the AI ​​instructor can provide additional explanation.

[0066] Step 6:

[0067] During the lesson, the AI ​​instructor will suggest appropriate breaks or playtime. When the user (child) presses the "Break" button, relaxing activities will be displayed. For example, simple exercises or mini-games will be suggested.

[0068] Step 7:

[0069] When the user (student) presses the "End Lesson" button, the server records the progress of the lesson and the student's responses. The server analyzes this information and stores it in a database.

[0070] Step 8:

[0071] The server summarizes the highlights of the lesson and the students' reactions, and sends this information to the parents' devices. For example, it can report points that were difficult to understand in today's lesson or parts that the students found particularly interesting.

[0072] Step 9:

[0073] The server connects to the student's school's system and sends information for attendance certification. Once attendance confirmation is complete, the server notifies the parent or guardian of the results. For example, the server can automatically connect to the school's attendance management system and certify the student's attendance.

[0074] Example 1

[0075] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0076] Current home learning support systems lack the means to effectively provide an optimized learning curriculum for each child, while also being able to monitor the progress and reactions of the children in real time. Furthermore, there is insufficient collaboration with parents and schools, making it difficult to effectively share learning outcomes.

[0077] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0078] In this invention, the server includes a means for inputting basic information about each child, an AI generation means for generating a curriculum based on the child's basic information, an AI instructor means for conducting a lesson based on the generated curriculum, a means for starting a lesson program when a lesson start button is pressed, a means for analyzing the progress of the lesson and the child's responses, and a means for summarizing the analysis results and notifying the parents and the child's school of the information. This makes it possible to provide a learning curriculum optimized for each child, realize real-time understanding of learning progress, and effectively share information.

[0079] "Children" refers primarily to school-age children in the primary school education stage.

[0080] "Basic information" refers to the child's name, age, grade, and other personal attribute information related to learning.

[0081] "Generative AI" refers to an artificial intelligence model that automatically generates a curriculum based on input information.

[0082] "Curriculum" refers to an educational plan that systematically and systematically arranges children's learning activities.

[0083] An "AI instructor" refers to a virtual instructor who conducts lessons based on a curriculum generated by generative AI.

[0084] "Class progress" refers to the implementation process for carrying out educational activities as planned.

[0085] "Class program" refers to the specific learning content and activities implemented in each class based on the curriculum.

[0086] The "lesson start button" refers to the operation section on the user interface for starting the lesson program.

[0087] "Progress" refers to the status of whether the lesson is proceeding as planned.

[0088] "Children's reactions" refers to the level of understanding, interest, and participation shown by children during class.

[0089] "Analysis" refers to the act of processing data to evaluate the progress of the lesson and the students' responses.

[0090] "Summary" refers to a brief report that summarizes information about the lesson's progress and the students' responses.

[0091] "Guardian" refers to a parent or guardian whose role is to support and supervise a child's learning activities.

[0092] "School of enrolment" refers to the educational institution in which a child is officially registered.

[0093] "Notification" refers to the means of communication used to inform parents and the student's school of the analysis results.

[0094] This invention is a learning support system for children, which can be used as an alternative to after-school care or free schools at home. This system uses generative AI to automatically generate learning curricula for children, and has "AI instructors" conduct the lessons.

[0095] System configuration

[0096] The system mainly consists of the following components:

[0097] 1. Server: Generates AI and manages the database.

[0098] 2. Device: A device operated by a user (parent or child). Examples include PCs, tablets, and smartphones.

[0099] 3. Users: Parents and children. Parents configure and monitor the system, while children learn.

[0100] User registration and initial settings

[0101] A user opens a website or app on their device and enters their name, email address, and password on the "Create an account" screen. The server then receives this information and stores it in a database. It then automatically generates a confirmation email and sends it to the email address provided. When the user clicks on the link in the confirmation email, the server receives the link and activates the account.

[0102] The user then logs in and enters the child's basic information (name, age, grade). Next, the user customizes the AI ​​instructor's avatar, voice, speaking style, etc. This setting information is received by the server and reflected in the generative AI model. At this time, the settings are generated using an image generation API and a voice synthesis API.

[0103] Curriculum Generation

[0104] The server retrieves basic information about the child from a database, including age, grade, preferences, and interests. The server then inputs this information into a generative AI model (e.g., GPT-4). The specific prompt is as follows:

[0105] "Generate a curriculum that will engage and effectively teach a 10-year-old child. The child's name is Taro, and the curriculum should include a good balance of math, reading, and physical activity."

[0106] The generative AI model generates an optimal curriculum based on the input information. For example, a curriculum such as "Monday: 9:00-10:00 Math, 10:00-11:00 Reading, 11:00-12:00 Exercise..." is generated. The generated curriculum is stored in a database on the server.

[0107] Classes begin

[0108] When a user (child) logs in on their device and presses the "Start Lesson" button, the server retrieves the current curriculum and launches the "AI Instructor" lesson program. The AI ​​Instructor conducts the lesson in an interactive format, monitoring the children's answers and reactions. For example, in a math class, the AI ​​Instructor poses questions, and when the children enter their answers, the AI ​​evaluates them and provides feedback. Appropriate breaks and playtime are also suggested to ensure that the children's concentration is maintained.

[0109] Status reporting and collaboration

[0110] When the lesson ends, the server analyzes the progress of the lesson and the students' responses, summarizes the results, and notifies parents. The server also connects to the configured school system to automatically report attendance and learning content. Specifically, the server records the progress of the lesson and the students' responses as a log, analyzes the log, and generates a summary in natural language. This summary is sent to parents via email or in-app notification, and the information is automatically shared with the school.

[0111] Specific operation example

[0112] For example, if a 10-year-old boy named Taro were to use this system, his parents would create an account with the initial settings and enter Taro's name, age, grade, and interests. The generation AI would then generate an optimized curriculum for Taro (math, reading, exercise, etc.) and store it in a database. When Taro presses the "Start Lesson" button, the "AI Instructor" will conduct the lesson in an interactive format, and Taro will work on the assignment. For example, in a math problem, if Taro answers "12" to the question "What is 5 + 7?", the "AI Instructor" will respond with "That's correct!" After the lesson, parents will be notified of a summary of Taro's learning progress and responses, and attendance information will be shared with the school.

[0113] In this way, the system of the present invention provides flexible and effective after-school care and free school functions at home, improving children's learning environment.

[0114] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0115] Step 1:

[0116] The user opens a website or app on their device and enters their name, email address, and password on the "Create an account" screen. The server receives this information and stores it in a database. The server then automatically generates a confirmation email and sends it to the email address entered. When the user clicks the link in the confirmation email, the server receives the link and activates the account. (Input: Name, email address, password / Output: Sending confirmation email and activating the account)

[0117] Step 2:

[0118] The user logs in and enters the child's basic information (name, age, grade). Next, the user customizes the AI ​​instructor's avatar, voice, speaking style, etc. The server receives this configuration information and reflects it in the generated AI model. Specifically, the customization content is generated using an image generation API and a voice synthesis API. (Input: basic information, avatar settings / Output: reflection of the generated AI model)

[0119] Step 3:

[0120] The server retrieves basic information about the child from a database. This information includes age, grade, preferences, and interests. The server inputs this information into a generative AI model to generate a curriculum. For example, the following prompt might be used: "Please generate a curriculum that will interest a 10-year-old child and help him learn effectively. The child's name is Taro, and the curriculum should include a good balance of math, reading, and exercise." (Input: Basic information / Output: Curriculum generation)

[0121] Step 4:

[0122] The generative AI model generates a curriculum based on the prompt. The generated curriculum is stored in a database on the server. For example, it might look like this: "Monday: 9:00-10:00 Math, 10:00-11:00 Reading, 11:00-12:00 Exercise..." (Input: Prompt / Output: Curriculum)

[0123] Step 5:

[0124] The user (child) logs in to the device and presses the "Start Lesson" button. The server retrieves the current curriculum and launches the "AI Instructor" lesson program. (Input: Pressing the "Start Lesson" button / Output: Launching the lesson program)

[0125] Step 6:

[0126] The AI ​​instructor conducts the lesson in an interactive format, monitoring the students' answers and reactions. For example, in a math class, the AI ​​instructor poses a question, and the students input their answers, which the AI ​​evaluates and provides feedback. It also suggests breaks and playtimes as appropriate. (Input: Student's answers / Output: Feedback, break suggestions)

[0127] Step 7:

[0128] The server records the progress of the lesson and the students' reactions as logs. After the lesson ends, the server analyzes the logs and generates a summary of the progress and reactions. The summary is sent to parents via email or in-app notification. (Input: Log data / Output: Summary report)

[0129] Step 8:

[0130] The server connects to the configured school system and automatically reports attendance and learning content. Specifically, today's lesson content and attendance status are sent to the school, and the student's attendance is certified. (Input: lesson content, attendance status / Output: report to school and certification)

[0131] In this way, the information entered at each step is processed appropriately, providing children with an optimized learning curriculum and enabling real-time understanding of learning progress and information sharing.

[0132] (Application example 1)

[0133] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0134] Conventional learning support systems have problems such as insufficient curriculum generation based on individual student needs, insufficient real-time status reporting, and insufficient collaboration. Furthermore, delays in sharing information with parents and the institution where the student is enrolled make it difficult to properly grasp the student's learning effectiveness and progress. The present invention aims to solve these problems and provide an optimal learning experience for students.

[0135] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0136] In this invention, the server includes means for inputting basic information about the child, generation AI means for generating a curriculum based on the child's basic information, AI instructor means for conducting lessons based on the generated curriculum, means for analyzing the progress of the lesson and the child's responses, means for notifying the analysis results, means for linking and sharing information with parents and the institution where the child is enrolled, and means for delivering content based on the generated curriculum. This enables the automatic generation and progress of a curriculum suited to the child, status reporting and linking, and makes it easier for parents and educational institutions to grasp the child's learning situation in real time.

[0137] "Means for inputting basic information about children" refers to devices or software for inputting basic information about children, such as their age, grade, and interests.

[0138] "Generative AI means" refers to an artificial intelligence processing device or software that automatically generates an optimal learning curriculum based on basic information about the child that is input.

[0139] The "AI instructor means" is an artificial intelligence processing device or software that conducts lessons in an interactive format according to the generated curriculum and provides educational guidance to children.

[0140] "Means for analyzing the progress of lessons and students' responses" refers to devices or software that monitor students' responses and progress during lessons in real time and analyze that information.

[0141] The "means for notifying the analysis results" refers to a device or software for notifying parents or the institution where the student is enrolled of the results of the analysis conducted during the lesson.

[0142] "Means for coordinating and sharing information with parents and the institution where the child is enrolled" refers to a device or software for coordinating and sharing the results of analysis of a child's learning progress and lessons with parents and the institution where the child is enrolled.

[0143] A "means for delivering content based on a generated curriculum" is a device or software that delivers appropriate learning content based on a curriculum generated by generative AI.

[0144] This invention is a learning support system for children, which serves as an alternative to after-school care or free schools at home. This system uses generative AI to automatically generate learning curricula for children, and has "AI instructors" conduct lessons. The system configuration and implementation method are explained below.

[0145] System configuration

[0146] The system mainly consists of the following components:

[0147] 1. Server: Generates AI and manages the database.

[0148] 2. Device: A device operated by a user (parent or child). Examples include PCs, tablets, and smartphones.

[0149] 3. Users: Parents and children. Parents configure and monitor the system, while children learn.

[0150] Initial Setup and User Registration

[0151] When a user opens the website or app on their device and enters their name, email address, and password on the "Create an Account" screen, the server saves the information in a database and sends a confirmation email. The user clicks on the link in the confirmation email to activate the account. The user then enters their child's basic information (name, age, grade), and selects an avatar, voice, and speaking style on the "AI Instructor" settings screen. The server then receives the selected settings information and reflects them in the generative AI model.

[0152] Curriculum Generation

[0153] The server retrieves basic information about the child from the database and inputs it into the generation AI. The generation AI generates an optimal study curriculum based on the child's information and stores it in the database. For example, for a 10-year-old child, a curriculum is generated that incorporates a balanced mix of science, painting, basic mathematics, reading time, and exercise. An example prompt sentence is "Generate a study curriculum for a 10-year-old in grade 4 with interest in science and painting."

[0154] Classes begin

[0155] When the user (child) presses the "Start Lesson" button on their device, the server retrieves the curriculum and launches the "AI Instructor" lesson program. The AI ​​Instructor conducts the lesson in an interactive format, monitoring the children's answers and reactions. For example, in a science class, the AI ​​Instructor poses a question and when the child enters the answer, the AI ​​Instructor determines whether it is correct or incorrect and moves on to the next step. It also suggests appropriate breaks and playtimes to maintain the children's concentration.

[0156] Exams and Assessments

[0157] The server monitors the student's learning progress in real time and evaluates them at certain stages. The evaluation results are stored in a database and notified to parents and the student's institution. For example, the server can report the areas in which the student struggled in today's lesson or the activities in which the student showed particular interest, allowing parents to understand their child's learning status.

[0158] Content Delivery

[0159] The server distributes appropriate learning content based on the curriculum generated by the generative AI. The content is distributed to devices such as smartphones, smart glasses, and head-mounted displays, allowing children to use these devices to advance their studies.

[0160] In this way, the system of the present invention provides flexible and effective after-school care and free school functions at home, improving children's learning environment.

[0161] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0162] Step 1:

[0163] The server provides an interface for users to input basic information about their children (name, age, grade) on their terminals. Users input basic information through this interface, and the data is stored in a database. The input is the basic information of the children, and the output is a data structure that stores the basic information in the database.

[0164] Step 2:

[0165] The server retrieves basic information about the child from the database and inputs it as a prompt to the generative AI model. The basic information retrieved from the database serves as input, and the generative AI model automatically generates a curriculum. An example of a prompt is "Generate a study curriculum for a 10-year-old in grade 4 with interest in science and painting." The generated curriculum is then saved in the database as output.

[0166] Step 3:

[0167] When the user (child) presses the "Start Lesson" button on the device, the server retrieves the generated curriculum from the database and launches the "AI Instructor" lesson program. Curriculum information is acquired as input, and instructions for the AI ​​instructor to conduct the lesson are received as output.

[0168] Step 4:

[0169] The AI ​​instructor conducts interactive lessons with students via their terminals. The server asks questions to students based on instructions from the AI ​​instructor, and the students input their answers. The input is the student's answer, and the output is the AI ​​instructor providing the next question and explanation.

[0170] Step 5:

[0171] The server monitors the progress of lessons and students' responses in real time and collects data. The input is the data collected in real time, and the output is the analysis results. This allows students' learning progress to be understood.

[0172] Step 6:

[0173] The server dynamically adjusts the curriculum based on the collected data and analysis results. Collected data is the input, and an adjusted curriculum is generated as the output. This provides the optimal learning environment for students.

[0174] Step 7:

[0175] The server notifies the parents and the institution using a means for notifying the analysis results. The analysis results are input, and the notification content is sent to the parents and the institution as output.

[0176] Step 8:

[0177] The server distributes appropriate learning content to the device based on the generated curriculum. The generated curriculum is the input, and the learning content is distributed to the device as the output. Students can use this to work on their individual learning content.

[0178] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0179] This invention is a learning support system that can replace after-school care or free schooling at home, automatically generating a child's learning curriculum using generative AI and having an "AI instructor" conduct the lessons. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it has the ability to dynamically adjust the curriculum and teaching methods based on the child's reactions.

[0180] System Overview

[0181] The system mainly consists of the following components:

[0182] 1. Server: Performs generative AI, emotion engine, and database management.

[0183] 2. Device: A device operated by a user (parent or child). Examples include PCs, tablets, and smartphones.

[0184] 3. Users: Parents and children. Parents configure and monitor the system, while children learn.

[0185] System Implementation

[0186] 1. User registration and initial settings

[0187] The user opens the website or app on their device and enters their name, email address, and password on the "Create an Account" screen. The server saves the entered information in a database and sends a confirmation email. The user clicks on the link in the confirmation email to activate the account. The user then enters the child's basic information (name, age, grade) and selects an avatar, voice, and speaking style on the "AI Instructor" settings screen. The server saves the selected settings information in a database and reflects them in the generative AI model.

[0188] 2. Curriculum Generation

[0189] The server retrieves the child's basic information from the database and inputs it into the generation AI. The generation AI generates an optimal learning curriculum based on the child's information and stores it in the database. For example, for a 10-year-old child, a curriculum that incorporates a balanced mix of basic math, reading time, and exercise would be generated.

[0190] 3. Classes begin

[0191] When the user (child) presses the "Start Lesson" button on their device, the server retrieves the curriculum and launches the "AI Instructor" lesson program. The AI ​​instructor conducts the lesson in an interactive format, with the emotion engine recognizing the child's facial expressions and voice to analyze their emotions. For example, in a math class, a question is posed and the child enters the answer, and the AI ​​instructor determines whether it is correct or incorrect and moves on to the next step. Based on the results of the emotion engine's analysis, if the child is confused, additional explanations are provided.

[0192] 4. Functions of the Emotion Engine

[0193] During lessons, the emotion engine recognizes and analyzes students' emotions in real time. The device collects students' facial expressions and voice data and sends it to a server. The server analyzes this data and dynamically adjusts the curriculum content and lesson progress depending on the situation, such as whether the student is feeling stressed or having fun. For example, if a student is bored, it will provide more interesting topics and interactive activities.

[0194] 5. Status reporting and collaboration

[0195] When the lesson ends, the server records the progress of the lesson, the students' reactions, and the results of the emotion analysis performed by the emotion engine. The server analyzes this information and stores it in a database. The server then sends a summary to the parent's device. For example, it may report points in today's lesson that the student found difficult, parts that they showed particular interest in, or specific emotional changes. The server also shares information with the student's school, and automatically processes attendance certification.

[0196] Specific examples

[0197] For example, if a 10-year-old child uses this system, parents create an account through the initial setup process and enter their child's information and preferences. The generating AI then generates an optimized curriculum for math, reading, and physical education for the child. When the child begins class, an "AI instructor" conducts the lesson in an interactive format, and an emotion engine analyzes the child's facial expressions and voice. For example, if a child is having difficulty with a math problem, the AI ​​instructor will provide detailed explanations and hints to help the child understand. After the class ends, parents are notified of a detailed report of the child's learning progress and emotional changes, and the necessary information is shared with the child's school.

[0198] In this way, the system of the present invention provides flexible and effective after-school care and free school functions at home, improving children's learning environments. By combining it with an emotion engine, dynamic instruction can be provided according to the child's emotions, providing a more individually optimized learning experience.

[0199] The processing flow will be explained below.

[0200] Step 1:

[0201] A user opens a website or app on their device and enters their name, email address, and password on the "Create an account" screen. The server stores the information in a database and sends a confirmation email. The user clicks on a link in the confirmation email to activate their account.

[0202] Step 2:

[0203] The user logs in and enters the child's basic information (name, age, grade). Next, they select the avatar, voice, and speaking style in the "AI instructor" settings. For example, they can choose an anime-style avatar, a gentle voice, and a slow speaking style. The server saves the selected settings in a database and reflects them in the generative AI model.

[0204] Step 3:

[0205] The server retrieves the child's basic information from the database and inputs it into the generation AI. The generation AI generates the optimal learning curriculum based on the child's information. For example, for a 10-year-old child, a curriculum that incorporates a good balance of basic math, reading time, and exercise is generated. The generated curriculum is saved in the database.

[0206] Step 4:

[0207] The user (child) presses the "Start Lesson" button on the device. The server retrieves the curriculum and launches the "AI Instructor" lesson program. The AI ​​Instructor conducts the lesson in an interactive format. For example, in a math class, a question is posed and the child enters the answer, and the AI ​​Instructor determines whether it is correct or incorrect and moves on to the next step.

[0208] Step 5:

[0209] During lessons, the emotion engine analyzes the students' facial expressions and voices in real time. The device uses a camera and microphone to collect the students' facial expressions and voice data and sends it to the server. The server uses the emotion engine to analyze the received data and identify the students' emotions. For example, it can identify whether a student is confused or having fun.

[0210] Step 6:

[0211] The server dynamically adjusts the curriculum based on the analysis results: for example, if a child is confused, the AI ​​instructor will provide additional explanation, or if a child is bored, they will be offered more interactive activities.

[0212] Step 7:

[0213] During the lesson, the AI ​​instructor will suggest appropriate breaks or playtime. When the user (child) presses the "Break" button, relaxing activities will be displayed. For example, simple exercises or mini-games will be suggested.

[0214] Step 8:

[0215] When the user (student) presses the "End Lesson" button, the server records the progress of the lesson, the student's reactions, and the results of emotion analysis. The server stores this information in a database.

[0216] Step 9:

[0217] The server summarizes the highlights of the lesson, the students' reactions, and the results of emotional analysis, and sends them to the parents' devices. For example, it reports which parts of today's lesson the student found difficult, which parts they found interesting, etc.

[0218] Step 10:

[0219] The server also connects with the student's school's system and sends information for attendance certification. Once attendance confirmation is complete, the server notifies the parents of the results. For example, the server can automatically connect to the school's attendance management system and certify the student's attendance.

[0220] Example 2

[0221] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0222] Conventional learning support systems have the problem that they are not sufficient to function as a substitute for after-school care at home or free schools. Specifically, they do not adequately provide the automatic generation of individually optimized learning curricula, dynamic instruction according to the child's emotions, or effective progress monitoring and reporting, making it difficult to improve children's learning environments.

[0223] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0224] In this invention, the server includes a means for inputting basic information about the child, a generation AI means for generating an educational plan based on the child's basic information, an AI teaching means for conducting lessons based on the generated educational plan, an emotion engine means for recognizing and analyzing the child's emotions, a means for analyzing the progress of the lesson and the child's reactions, a means for notifying the analysis results, and a means for linking and sharing information with parents and educational institutions. This enables the generation of individually optimized learning curricula, flexible instruction according to the child's emotions, and effective monitoring and reporting of learning progress.

[0225] 1. "Basic information about the child" refers to basic information necessary for learning support, such as the child's name, age, and grade.

[0226] 2. An "educational plan" is a plan that includes specific learning content and schedules, created based on basic information about a child.

[0227] 3. "Generative AI means" refers to artificial intelligence technology that receives basic information about a child as input and automatically generates an optimal educational plan.

[0228] 4. "Artificial intelligence teaching means" refers to an interactive artificial intelligence that conducts lessons based on the generated teaching plan.

[0229] 5. "Emotion engine means" refers to technology for recognizing a child's facial expressions and voice and analyzing their emotional state.

[0230] 6. "Class progress" refers to the progress and progress of a class according to the educational plan.

[0231] 7. "Children's reactions" refers to the children's behavior, facial expressions, vocal responses, etc. during class.

[0232] 8. "Analysis results" refers to data obtained by analyzing the progress of lessons and students' responses.

[0233] 9. "Means of notification" refers to the methods and techniques used to communicate the results of the analysis to parents and educational institutions.

[0234] 10. "Means of information collaboration and sharing" refers to the technologies and methods for sharing analysis results with relevant parents and educational institutions.

[0235] MODE FOR CARRYING OUT THE INVENTION

[0236] This invention is a learning support system that serves as an alternative to after-school care or free schools within the home, and is composed of the following main components and technical elements:

[0237] System configuration

[0238] The system includes the following hardware and software components:

[0239] 1. Server:

[0240] Generative AI means: An artificial intelligence model that generates optimal educational plans based on basic information about children. Specifically, this applies to generative AI models that use machine learning algorithms or natural language processing.

[0241] Emotion engine means: Technology for analyzing a child's facial expressions and voice to recognize their emotional state. Specifically, this includes image recognition technology and voice analysis technology.

[0242] Database: A database for storing basic information about students, generated teaching plans, lesson progress, emotional data, etc.

[0243] 2. Terminal:

[0244] User interface: A device that parents and children use to operate the system. Specific examples include PCs, tablets, and smartphones. These devices interact with the system through web applications or native applications.

[0245] Sensors: Cameras and microphones to collect the child's facial expressions and voice.

[0246] 3. User:

[0247] Parent: Initial setup and monitoring of the system.

[0248] Children: Learning through the system.

[0249] Initial Setup and User Registration

[0250] The user opens the website or app on their device and enters their name, email address, and password on the "Create an account" screen. The server saves the entered information in a database and sends a confirmation email. The user clicks on the link in the confirmation email to activate the account. The user then enters the child's basic information (name, age, grade level), and selects an avatar, voice, and speaking style on the "AI teaching method" settings screen. The server saves the selected settings information in a database and reflects them in the generative AI model.

[0251] Generate a teaching plan

[0252] The server retrieves the child's basic information from the database and inputs it into the generation AI. The generation AI generates an optimal educational plan based on the child's information and stores it in the database. For example, for a 10-year-old child, a plan that incorporates a good balance of basic math, reading time, and exercise is generated.

[0253] Class progress

[0254] When a user (child) presses the "Start Lesson" button on their device, the server retrieves the educational plan and launches the lesson program in the "AI teaching tool." The AI ​​teaching tool conducts the lesson in an interactive format, with the emotion engine recognizing the child's facial expressions and voice to analyze their emotions. For example, in a math lesson, a question is posed and the child enters the answer, and the AI ​​teaching tool determines whether it is correct or incorrect and moves on to the next step. Based on the analysis results of the emotion engine, if the child is confused, additional explanations are provided.

[0255] Sentiment Analysis and Dynamic Adjustment

[0256] During lessons, the emotion engine recognizes and analyzes students' emotions in real time. The device collects students' facial expressions and voice data and sends it to the server. The server analyzes this data and dynamically adjusts the content of the educational plan and the way the lesson is conducted depending on the situation, such as whether the student is feeling stressed or having fun. For example, if the student is bored, it will provide more interesting topics and interactive activities.

[0257] Situation reporting and information sharing

[0258] When the lesson ends, the server records the progress of the lesson, the students' reactions, and the results of the emotion analysis performed by the emotion engine. The server analyzes this information and stores it in a database. The server then sends a summary to the parent's device. For example, it may report points in today's lesson that the student found difficult, parts that they showed particular interest in, or specific emotional changes. The server also shares information with the student's school, and automatically processes attendance certification.

[0259] Examples and prompts

[0260] For example, if a 10-year-old child uses this system, parents can create an account through the initial setup process and enter their child's information and preferences. The generating AI will then generate an optimized educational plan for their child covering math, reading, and exercise. When the child begins class, the AI ​​instructor will conduct the lesson in an interactive format, and the emotion engine will analyze the child's facial expressions and voice. For example, if a child is having difficulty with a math problem, the AI ​​instructor will provide detailed explanations and hints to help the child understand. After the class ends, parents will receive a detailed report on the child's learning progress and emotional changes, and the necessary information will be shared with the child's school.

[0261] Example prompts for generative AI models

[0262] "Generate a one-week learning curriculum for a 10-year-old child. Include a good balance of math, reading, and physical activity."

[0263] "Create new math problem sets and adjust the difficulty based on students' understanding."

[0264] "Please report on today's lesson trends based on the students' emotional data."

[0265] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0266] Step 1: User registration and initial setup

[0267] Input: The user enters their name, email address, and password on the device.

[0268] What it does: The server saves the information you entered in its database and sends you a confirmation email.

[0269] Output: A confirmation email is sent to the user.

[0270] What it does: A user opens a website or app on their device and enters their name, email address, and password on the "Create an account" screen. The server then stores the information in a database and sends a confirmation email.

[0271] Step 2: Activate your account

[0272] Input: User clicks on the link in the confirmation email.

[0273] Action: The server activates the account.

[0274] Output: The account is activated and available to the user.

[0275] What it does: The user clicks on the link in the confirmation email to complete the fast and secure account activation.

[0276] Step 3: Enter your child's information

[0277] Input: The user enters the child's basic information (name, age, grade).

[0278] How it works: The server saves the input information in a database.

[0279] Output: The child's basic information is obtained and the next operation is instructed.

[0280] Specific operation: The user enters basic information about the child into the system, and the server accurately stores it in the database.

[0281] Step 4: Setting up the AI ​​instructor

[0282] Input: The user selects the avatar, voice, and speaking style of the "AI instructor."

[0283] How it works: The server saves the selected configuration information in a database and reflects it in the generative AI model.

[0284] Output: The AI ​​instructor is configured and individual customization is enabled.

[0285] Specific operation: The user selects an avatar, voice, and speaking style, and this information is reflected in the generated AI model by the server and set in the system.

[0286] Step 5: Generate a teaching plan

[0287] Input: The server retrieves basic information about the child from the database.

[0288] How it works: Generative AI generates an educational plan based on the child's information.

[0289] Output: The generated teaching plan is stored in a database.

[0290] Specific operation: The server obtains basic information about the child and inputs it into the generation AI. The AI ​​generates an optimal educational plan, and the server stores the plan in a database.

[0291] Step 6: Start classes

[0292] Input: The user (student) presses the "Start lesson" button on the terminal.

[0293] Operation: The server obtains the teaching plan and starts the AI ​​instructor's lesson program.

[0294] Output: Lesson begins.

[0295] Specific operation: When the user (child) presses "Start lesson," the server retrieves the plan and the AI ​​instructor begins the lesson.

[0296] Step 7: Lesson Progression

[0297] Input: Facial expressions and voice data of students during class.

[0298] How it works: The emotion engine analyzes the child's emotions in real time and sends the results to the server.

[0299] Output: The progress of the lesson is dynamically adjusted based on the results of the sentiment analysis.

[0300] Specific operation: During the lesson, the device collects facial expressions and voice data, and the emotion engine analyzes the emotions and sends them to the server. The server then provides appropriate guidance and feedback based on the analysis results.

[0301] Step 8: Reporting and sharing information

[0302] Input: Lesson progress, student responses, and emotion analysis results.

[0303] How it works: The server records the progress of the lesson and the students' responses and saves them in a database.

[0304] Output: A notification is sent to the parent's device and the information is shared with the educational institution.

[0305] Specific operation: After the lesson ends, the server records the progress, students' reactions, and emotion analysis results, and saves them in a database. It then reports the situation to the parents' devices and automatically shares the information with the educational institution.

[0306] (Application example 2)

[0307] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0308] Conventional learning support systems have limitations in dynamically adjusting curriculum in response to children's emotions and reactions, and in providing learning experiences in virtual environments. Furthermore, many systems require parents to perform setup tasks at a high level, making it difficult to maintain children's interest. Furthermore, the lack of flexibility and interactivity in learning sessions in virtual environments is also a problem.

[0309] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for inputting basic information about the child, a generation AI means for generating a curriculum based on the child's basic information, an AI instructor means for conducting a lesson based on the generated curriculum, a means for analyzing the progress of the lesson and the child's responses, a means for notifying the child of the analysis results, a means for linking and sharing information with parents and the child's school, a means for recognizing and analyzing the child's emotions in real time using an emotion recognition engine and dynamically adjusting the lesson content, and a means for providing lessons and workshops in a virtual environment. This enables the provision of a flexible curriculum that corresponds to each child's individual emotions and learning progress, and a diverse learning experience in a virtual environment.

[0310] The "means for inputting basic information about a child" is a system component that has a function for inputting basic profile data such as a child's name, age, and grade.

[0311] "Generative AI means" refers to an artificial intelligence algorithm or system component that generates an optimal learning curriculum based on the basic information acquired about a child.

[0312] The "artificial intelligence instructor means" is an artificial intelligence-based educational system or software for conducting lessons based on the generated learning curriculum and educating children.

[0313] The "means for analyzing the progress of the lesson and the reactions of the students" is a system component for observing the behavior and reactions of the students during the lesson and analyzing the progress based on that.

[0314] The "means for notifying analysis results" is a system component that has the function of notifying parents and educators of the analysis results regarding the progress of the lesson and the students' reactions.

[0315] "Means for coordinating and sharing information with parents and the school" refers to a system component with communication functions for coordinating and sharing information regarding the progress of lessons, curriculum, and students' reactions with parents and the school.

[0316] An "emotion recognition engine" is an algorithm or system component that analyzes a child's facial expressions and voice data to recognize and analyze their emotional state in real time.

[0317] The "means for dynamically adjusting lesson content" is a system component that has the function of adjusting the lesson progress and curriculum in real time based on the emotional data collected by the emotion recognition engine.

[0318] "Means for providing classes and workshops in a virtual environment" refers to system components for providing classes and workshops in a virtual space using virtual reality (VR) and augmented reality (AR).

[0319] This invention is a learning support system for home or virtual environments, equipped with technology to provide flexible and effective education to children. The system uses a generative AI model to automatically generate a learning curriculum for children and an "artificial intelligence instructor" to conduct the lessons. It also uses an emotion recognition engine to analyze children's emotions in real time and dynamically adjust the lesson content.

[0320] System Overview

[0321] The system mainly consists of the following components:

[0322] 1. Server: Manages generative AI models, emotion recognition engines, and databases.

[0323] 2. Device: A device used by users (parents and children). Examples include PCs, tablets, smartphones, and head-mounted displays.

[0324] 3. Users: Parents and children. Parents configure and monitor the system, while children learn.

[0325] System Implementation

[0326] User Registration and Settings

[0327] The user (parent) accesses the registration form from their device and enters their name, email address, password, and child information (name, age, grade). The server stores this information in a database and sends a confirmation email. When the user clicks the link in the confirmation email, the account is activated. The parent then sets the avatar, voice, and speaking style of the "artificial intelligence instructor" according to their child's preferences. These settings are reflected in the generative AI model.

[0328] Curriculum Generation

[0329] The server retrieves basic information about the child from the database and inputs it into the generative AI model, which then generates a curriculum using, for example, the following prompt:

[0330] Generate a diverse and engaging curriculum for a 10 year old in grade 5. Curriculum should include subjects like math, reading, and physical activities.

[0331] The generated curriculum is stored in a database. For example, for a 10-year-old child, a curriculum that incorporates a balanced mix of math basics, reading time, and physical activity is generated.

[0332] Start and progress of lessons

[0333] When a user (child) presses the "Start Lesson" button on their device, the server retrieves the curriculum and launches the "AI Instructor." The AI ​​Instructor conducts the lesson in an interactive format, with an emotion recognition engine collecting and analyzing the child's facial expressions and voice in real time. For example, in a math class, a question is posed and the child enters the answer, and the AI ​​Instructor determines whether it is correct or incorrect and moves on to the next step. If the emotion recognition engine detects that the child is confused, it provides additional explanation.

[0334] Emotion Recognition Engine and Dynamic Adjustment

[0335] During lessons, an emotion recognition engine analyzes students' emotions in real time and sends the results to the server. For example, if a student is bored, the system will introduce more interactive activities. If a student is having trouble understanding, the system will provide detailed explanations or hints.

[0336] Reporting and collaboration

[0337] After the lesson is over, the server records the progress of the lesson, the students' reactions, and the results of emotional analysis. The server analyzes this information and notifies parents and the student's school. For example, it reports if a student had difficulty with a particular task or if a part of the lesson showed particular interest. This allows parents and educators to understand the student's learning progress.

[0338] This system allows children to enjoy a personalized learning experience and allows parents and educators to effectively support their children's learning progress.

[0339] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0340] Step 1: User registration and initial setup

[0341] The user (guardian) accesses the registration form from their device and enters their name, email address, password, and child information (name, age, grade). This input data is sent to the server and stored in a database. The server generates a confirmation email and sends it to the entered email address. When the user clicks the link in the confirmation email, the account is activated. Next, the user (guardian) sets the avatar, voice, and speaking style of the "artificial intelligence instructor" according to their child's preferences. This setting information is also sent to the server and reflected in the generated AI model.

[0342] Step 2: Curriculum generation

[0343] The server retrieves basic information about the child (age, grade, etc.) from the database and inputs this information into the generative AI model. For example, the server sends the following prompt to the generative AI model to generate the optimal curriculum.

[0344] Generate a diverse and engaging curriculum for a 10 year old in grade 5. Curriculum should include subjects like math, reading, and physical activities.

[0345] The generative AI model generates a curriculum based on the input information, and the server receives the generated curriculum and stores it in a database. For example, a curriculum that balances basic math, reading time, and exercise for a 10-year-old child would be generated.

[0346] Step 3: Start classes

[0347] When the user (child) presses the "Start Lesson" button on their device, the server retrieves a pre-generated curriculum from the database and launches the "AI instructor" lesson program. The AI ​​instructor begins the lesson based on the retrieved curriculum and provides the child with learning content in an interactive format. The device collects the child's facial expressions and voice data in real time and sends it to the server.

[0348] Step 4: Emotion recognition and dynamic regulation

[0349] The server inputs facial expressions and voice data sent from the device into an emotion recognition engine to analyze the child's emotions in real time. For example, if the emotion recognition engine detects a child's confusion or boredom, the server generates appropriate feedback and additional explanations and provides them to the child through an AI instructor. This allows the child to continue learning with appropriate support.

[0350] Step 5: Learning Records and Notifications

[0351] After the lesson is over, the server records the progress of the lesson, the students' reactions, and the results of emotional analysis. This information is stored in a database as a profile and used for future learning. The server also generates a report summarizing the lesson and highlighting key points, which is sent to parents and the student's school to share the student's learning status. For example, it reports if a student had difficulty with a particular problem or if a topic of particular interest occurred.

[0352] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0353] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0354] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0355] [Second embodiment]

[0356] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0357] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0358] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0359] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0360] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0361] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0362] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0363] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0364] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0365] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0366] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0367] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0368] This invention is a learning support system for children, which can be used as an alternative to after-school care or free schools at home. This system uses generative AI to automatically generate learning curricula for children, and has "AI instructors" conduct the lessons.

[0369] System Overview

[0370] The system mainly consists of the following components:

[0371] 1. Server: Generates AI and manages the database.

[0372] 2. Device: A device operated by a user (parent or child). Examples include PCs, tablets, and smartphones.

[0373] 3. Users: Parents and children. Parents configure and monitor the system, while children learn.

[0374] System Implementation

[0375] 1. User registration and initial settings

[0376] The user opens the website or app on their device and enters their name, email address, and password on the "Create an Account" screen. The server saves the entered information in a database and sends a confirmation email. The user clicks on the link in the confirmation email to activate the account. The user then enters the child's basic information (name, age, grade level), and selects an avatar, voice, and speaking style on the "AI Instructor" settings screen. The server receives the selected settings information and reflects it in the generative AI model.

[0377] 2. Curriculum Generation

[0378] The server retrieves the child's basic information from the database and inputs it into the generation AI. The generation AI generates an optimal learning curriculum based on the child's information and stores it in the database. For example, for a 10-year-old child, a curriculum that incorporates a balanced mix of basic math, reading time, and exercise would be generated.

[0379] 3. Classes begin

[0380] When the user (child) presses the "Start Lesson" button on their device, the server retrieves the curriculum and launches the "AI Instructor" lesson program. The AI ​​Instructor conducts the lesson in an interactive format, monitoring the children's answers and reactions. For example, in a math class, the AI ​​Instructor poses a question and when the child enters the answer, the AI ​​Instructor determines whether it is correct or incorrect and moves on to the next step. The AI ​​Instructor also suggests appropriate breaks and playtimes to maintain the children's concentration.

[0381] 4. Status reporting and collaboration

[0382] When the lesson ends, the server analyzes the progress of the lesson and the student's reactions, summarizing the results and notifying parents. The information is also shared with the student's school, which automatically processes attendance certification. For example, the server can report on the areas in which the student struggled in today's lesson and the activities in which the student showed particular interest, allowing parents to understand their child's learning status.

[0383] Specific examples

[0384] For example, if a 10-year-old child uses this system, their parents will create an account through the initial setup process and enter their child's information and preferences. The AI ​​will then generate a curriculum optimized for their child, covering math, reading, and physical education. When the child begins class, an "AI instructor" will conduct the lesson interactively while the child works on the assignments. After the class ends, parents will receive a summary of the child's learning progress and responses, and attendance information will be shared with the school.

[0385] In this way, the system of the present invention provides flexible and effective after-school care and free school functions at home, improving children's learning environment.

[0386] The processing flow will be explained below.

[0387] Step 1:

[0388] The user opens a website or app on their device and enters their name, email address, and password on the "Create an account" screen. The server stores the information in a database and sends a confirmation email. The user clicks on a link in the email to activate their account.

[0389] Step 2:

[0390] The user logs in and enters the child's basic information (name, age, grade). Next, they select the avatar, voice, and speaking style in the "AI instructor" settings. For example, they can choose an anime-style avatar, a gentle voice, and a slow speaking style. The server saves the selected settings in a database and reflects them in the generative AI model.

[0391] Step 3:

[0392] The server retrieves the child's basic information from the database and inputs it into the generation AI. The generation AI generates the optimal learning curriculum based on the child's information. For example, for a 10-year-old child, a curriculum that incorporates a good balance of basic math, reading time, and exercise is generated. The generated curriculum is saved in the database.

[0393] Step 4:

[0394] The user (child) presses the "Start Lesson" button on the device. The server retrieves the curriculum and launches the "AI Instructor" lesson program. The AI ​​Instructor conducts the lesson in an interactive format. For example, in a math class, a question is posed and the child enters the answer, and the AI ​​Instructor determines whether it is correct or incorrect and moves on to the next step.

[0395] Step 5:

[0396] An AI instructor assesses students' understanding and responses in real time during lessons. The device collects the students' responses and sends them to a server. The server analyzes them and dynamically adjusts the curriculum content as needed. For example, if a student struggles with a particular math problem, the AI ​​instructor can provide additional explanation.

[0397] Step 6:

[0398] During the lesson, the AI ​​instructor will suggest appropriate breaks or playtime. When the user (child) presses the "Break" button, relaxing activities will be displayed. For example, simple exercises or mini-games will be suggested.

[0399] Step 7:

[0400] When the user (student) presses the "End Lesson" button, the server records the progress of the lesson and the student's responses. The server analyzes this information and stores it in a database.

[0401] Step 8:

[0402] The server summarizes the highlights of the lesson and the students' reactions, and sends this information to the parents' devices. For example, it can report points that were difficult to understand in today's lesson or parts that the students found particularly interesting.

[0403] Step 9:

[0404] The server connects to the student's school's system and sends information for attendance certification. Once attendance confirmation is complete, the server notifies the parent or guardian of the results. For example, the server can automatically connect to the school's attendance management system and certify the student's attendance.

[0405] Example 1

[0406] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0407] Current home learning support systems lack the means to effectively provide an optimized learning curriculum for each child, while also being able to monitor the progress and reactions of the children in real time. Furthermore, there is insufficient collaboration with parents and schools, making it difficult to effectively share learning outcomes.

[0408] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0409] In this invention, the server includes a means for inputting basic information about each child, an AI generation means for generating a curriculum based on the child's basic information, an AI instructor means for conducting a lesson based on the generated curriculum, a means for starting a lesson program when a lesson start button is pressed, a means for analyzing the progress of the lesson and the child's responses, and a means for summarizing the analysis results and notifying the parents and the child's school of the information. This makes it possible to provide a learning curriculum optimized for each child, realize real-time understanding of learning progress, and effectively share information.

[0410] "Children" refers primarily to school-age children in the primary school education stage.

[0411] "Basic information" refers to the child's name, age, grade, and other personal attribute information related to learning.

[0412] "Generative AI" refers to an artificial intelligence model that automatically generates a curriculum based on input information.

[0413] "Curriculum" refers to an educational plan that systematically and systematically arranges children's learning activities.

[0414] An "AI instructor" refers to a virtual instructor who conducts lessons based on a curriculum generated by generative AI.

[0415] "Class progress" refers to the implementation process for carrying out educational activities as planned.

[0416] "Class program" refers to the specific learning content and activities implemented in each class based on the curriculum.

[0417] The "lesson start button" refers to the operation section on the user interface for starting the lesson program.

[0418] "Progress" refers to the status of whether the lesson is proceeding as planned.

[0419] "Children's reactions" refers to the level of understanding, interest, and participation shown by children during class.

[0420] "Analysis" refers to the act of processing data to evaluate the progress of the lesson and the students' responses.

[0421] "Summary" refers to a brief report that summarizes information about the lesson's progress and the students' responses.

[0422] "Guardian" refers to a parent or guardian whose role is to support and supervise a child's learning activities.

[0423] "School of enrolment" refers to the educational institution in which a child is officially registered.

[0424] "Notification" refers to the means of communication used to inform parents and the student's school of the analysis results.

[0425] This invention is a learning support system for children, which can be used as an alternative to after-school care or free schools at home. This system uses generative AI to automatically generate learning curricula for children, and has "AI instructors" conduct the lessons.

[0426] System configuration

[0427] The system mainly consists of the following components:

[0428] 1. Server: Generates AI and manages the database.

[0429] 2. Device: A device operated by a user (parent or child). Examples include PCs, tablets, and smartphones.

[0430] 3. Users: Parents and children. Parents configure and monitor the system, while children learn.

[0431] User registration and initial settings

[0432] A user opens a website or app on their device and enters their name, email address, and password on the "Create an account" screen. The server then receives this information and stores it in a database. It then automatically generates a confirmation email and sends it to the email address provided. When the user clicks on the link in the confirmation email, the server receives the link and activates the account.

[0433] The user then logs in and enters the child's basic information (name, age, grade). Next, the user customizes the AI ​​instructor's avatar, voice, speaking style, etc. This setting information is received by the server and reflected in the generative AI model. At this time, the settings are generated using an image generation API and a voice synthesis API.

[0434] Curriculum Generation

[0435] The server retrieves basic information about the child from a database, including age, grade, preferences, and interests. The server then inputs this information into a generative AI model (e.g., GPT-4). The specific prompt is as follows:

[0436] "Generate a curriculum that will engage and effectively teach a 10-year-old child. The child's name is Taro, and the curriculum should include a good balance of math, reading, and physical activity."

[0437] The generative AI model generates an optimal curriculum based on the input information. For example, a curriculum such as "Monday: 9:00-10:00 Math, 10:00-11:00 Reading, 11:00-12:00 Exercise..." is generated. The generated curriculum is stored in a database on the server.

[0438] Classes begin

[0439] When a user (child) logs in on their device and presses the "Start Lesson" button, the server retrieves the current curriculum and launches the "AI Instructor" lesson program. The AI ​​Instructor conducts the lesson in an interactive format, monitoring the children's answers and reactions. For example, in a math class, the AI ​​Instructor poses questions, and when the children enter their answers, the AI ​​evaluates them and provides feedback. Appropriate breaks and playtime are also suggested to ensure that the children's concentration is maintained.

[0440] Status reporting and collaboration

[0441] When the lesson ends, the server analyzes the progress of the lesson and the students' responses, summarizes the results, and notifies parents. The server also connects to the configured school system to automatically report attendance and learning content. Specifically, the server records the progress of the lesson and the students' responses as a log, analyzes the log, and generates a summary in natural language. This summary is sent to parents via email or in-app notification, and the information is automatically shared with the school.

[0442] Specific operation example

[0443] For example, if a 10-year-old boy named Taro were to use this system, his parents would create an account with the initial settings and enter Taro's name, age, grade, and interests. The generation AI would then generate an optimized curriculum for Taro (math, reading, exercise, etc.) and store it in a database. When Taro presses the "Start Lesson" button, the "AI Instructor" will conduct the lesson in an interactive format, and Taro will work on the assignment. For example, in a math problem, if Taro answers "12" to the question "What is 5 + 7?", the "AI Instructor" will respond with "That's correct!" After the lesson, parents will be notified of a summary of Taro's learning progress and responses, and attendance information will be shared with the school.

[0444] In this way, the system of the present invention provides flexible and effective after-school care and free school functions at home, improving children's learning environment.

[0445] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0446] Step 1:

[0447] The user opens a website or app on their device and enters their name, email address, and password on the "Create an account" screen. The server receives this information and stores it in a database. The server then automatically generates a confirmation email and sends it to the email address entered. When the user clicks the link in the confirmation email, the server receives the link and activates the account. (Input: Name, email address, password / Output: Sending confirmation email and activating the account)

[0448] Step 2:

[0449] The user logs in and enters the child's basic information (name, age, grade). Next, the user customizes the AI ​​instructor's avatar, voice, speaking style, etc. The server receives this configuration information and reflects it in the generated AI model. Specifically, the customization content is generated using an image generation API and a voice synthesis API. (Input: basic information, avatar settings / Output: reflection of the generated AI model)

[0450] Step 3:

[0451] The server retrieves basic information about the child from a database. This information includes age, grade, preferences, and interests. The server inputs this information into a generative AI model to generate a curriculum. For example, the following prompt might be used: "Please generate a curriculum that will interest a 10-year-old child and help him learn effectively. The child's name is Taro, and the curriculum should include a good balance of math, reading, and exercise." (Input: Basic information / Output: Curriculum generation)

[0452] Step 4:

[0453] The generative AI model generates a curriculum based on the prompt. The generated curriculum is stored in a database on the server. For example, it might look like this: "Monday: 9:00-10:00 Math, 10:00-11:00 Reading, 11:00-12:00 Exercise..." (Input: Prompt / Output: Curriculum)

[0454] Step 5:

[0455] The user (child) logs in to the device and presses the "Start Lesson" button. The server retrieves the current curriculum and launches the "AI Instructor" lesson program. (Input: Pressing the "Start Lesson" button / Output: Launching the lesson program)

[0456] Step 6:

[0457] The AI ​​instructor conducts the lesson in an interactive format, monitoring the students' answers and reactions. For example, in a math class, the AI ​​instructor poses a question, and the students input their answers, which the AI ​​evaluates and provides feedback. It also suggests breaks and playtimes as appropriate. (Input: Student's answers / Output: Feedback, break suggestions)

[0458] Step 7:

[0459] The server records the progress of the lesson and the students' reactions as logs. After the lesson ends, the server analyzes the logs and generates a summary of the progress and reactions. The summary is sent to parents via email or in-app notification. (Input: Log data / Output: Summary report)

[0460] Step 8:

[0461] The server connects to the configured school system and automatically reports attendance and learning content. Specifically, today's lesson content and attendance status are sent to the school, and the student's attendance is certified. (Input: lesson content, attendance status / Output: report to school and certification)

[0462] In this way, the information entered at each step is processed appropriately, providing children with an optimized learning curriculum and enabling real-time understanding of learning progress and information sharing.

[0463] (Application example 1)

[0464] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0465] Conventional learning support systems have problems such as insufficient curriculum generation based on individual student needs, insufficient real-time status reporting, and insufficient collaboration. Furthermore, delays in sharing information with parents and the institution where the student is enrolled make it difficult to properly grasp the student's learning effectiveness and progress. The present invention aims to solve these problems and provide an optimal learning experience for students.

[0466] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0467] In this invention, the server includes means for inputting basic information about the child, generation AI means for generating a curriculum based on the child's basic information, AI instructor means for conducting lessons based on the generated curriculum, means for analyzing the progress of the lesson and the child's responses, means for notifying the analysis results, means for linking and sharing information with parents and the institution where the child is enrolled, and means for delivering content based on the generated curriculum. This enables the automatic generation and progress of a curriculum suited to the child, status reporting and linking, and makes it easier for parents and educational institutions to grasp the child's learning situation in real time.

[0468] "Means for inputting basic information about children" refers to devices or software for inputting basic information about children, such as their age, grade, and interests.

[0469] "Generative AI means" refers to an artificial intelligence processing device or software that automatically generates an optimal learning curriculum based on basic information about the child that is input.

[0470] The "AI instructor means" is an artificial intelligence processing device or software that conducts lessons in an interactive format according to the generated curriculum and provides educational guidance to children.

[0471] "Means for analyzing the progress of lessons and students' responses" refers to devices or software that monitor students' responses and progress during lessons in real time and analyze that information.

[0472] The "means for notifying the analysis results" refers to a device or software for notifying parents or the institution where the student is enrolled of the results of the analysis conducted during the lesson.

[0473] "Means for coordinating and sharing information with parents and the institution where the child is enrolled" refers to a device or software for coordinating and sharing the results of analysis of a child's learning progress and lessons with parents and the institution where the child is enrolled.

[0474] A "means for delivering content based on a generated curriculum" is a device or software that delivers appropriate learning content based on a curriculum generated by generative AI.

[0475] This invention is a learning support system for children, which serves as an alternative to after-school care or free schools at home. This system uses generative AI to automatically generate learning curricula for children, and has "AI instructors" conduct lessons. The system configuration and implementation method are explained below.

[0476] System configuration

[0477] The system mainly consists of the following components:

[0478] 1. Server: Generates AI and manages the database.

[0479] 2. Device: A device operated by a user (parent or child). Examples include PCs, tablets, and smartphones.

[0480] 3. Users: Parents and children. Parents configure and monitor the system, while children learn.

[0481] Initial Setup and User Registration

[0482] When a user opens the website or app on their device and enters their name, email address, and password on the "Create an Account" screen, the server saves the information in a database and sends a confirmation email. The user clicks on the link in the confirmation email to activate the account. The user then enters their child's basic information (name, age, grade), and selects an avatar, voice, and speaking style on the "AI Instructor" settings screen. The server then receives the selected settings information and reflects them in the generative AI model.

[0483] Curriculum Generation

[0484] The server retrieves basic information about the child from the database and inputs it into the generation AI. The generation AI generates an optimal study curriculum based on the child's information and stores it in the database. For example, for a 10-year-old child, a curriculum is generated that incorporates a balanced mix of science, painting, basic mathematics, reading time, and exercise. An example prompt sentence is "Generate a study curriculum for a 10-year-old in grade 4 with interest in science and painting."

[0485] Classes begin

[0486] When the user (child) presses the "Start Lesson" button on their device, the server retrieves the curriculum and launches the "AI Instructor" lesson program. The AI ​​Instructor conducts the lesson in an interactive format, monitoring the children's answers and reactions. For example, in a science class, the AI ​​Instructor poses a question and when the child enters the answer, the AI ​​Instructor determines whether it is correct or incorrect and moves on to the next step. It also suggests appropriate breaks and playtimes to maintain the children's concentration.

[0487] Exams and Assessments

[0488] The server monitors the student's learning progress in real time and evaluates them at certain stages. The evaluation results are stored in a database and notified to parents and the student's institution. For example, the server can report the areas in which the student struggled in today's lesson or the activities in which the student showed particular interest, allowing parents to understand their child's learning status.

[0489] Content Delivery

[0490] The server distributes appropriate learning content based on the curriculum generated by the generative AI. The content is distributed to devices such as smartphones, smart glasses, and head-mounted displays, allowing children to use these devices to advance their studies.

[0491] In this way, the system of the present invention provides flexible and effective after-school care and free school functions at home, improving children's learning environment.

[0492] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0493] Step 1:

[0494] The server provides an interface for users to input basic information about their children (name, age, grade) on their terminals. Users input basic information through this interface, and the data is stored in a database. The input is the basic information of the children, and the output is a data structure that stores the basic information in the database.

[0495] Step 2:

[0496] The server retrieves basic information about the child from the database and inputs it as a prompt to the generative AI model. The basic information retrieved from the database serves as input, and the generative AI model automatically generates a curriculum. An example of a prompt is "Generate a study curriculum for a 10-year-old in grade 4 with interest in science and painting." The generated curriculum is then saved in the database as output.

[0497] Step 3:

[0498] When the user (child) presses the "Start Lesson" button on the device, the server retrieves the generated curriculum from the database and launches the "AI Instructor" lesson program. Curriculum information is acquired as input, and instructions for the AI ​​instructor to conduct the lesson are received as output.

[0499] Step 4:

[0500] The AI ​​instructor conducts interactive lessons with students via their terminals. The server asks questions to students based on instructions from the AI ​​instructor, and the students input their answers. The input is the student's answer, and the output is the AI ​​instructor providing the next question and explanation.

[0501] Step 5:

[0502] The server monitors the progress of lessons and students' responses in real time and collects data. The input is the data collected in real time, and the output is the analysis results. This allows students' learning progress to be understood.

[0503] Step 6:

[0504] The server dynamically adjusts the curriculum based on the collected data and analysis results. Collected data is the input, and an adjusted curriculum is generated as the output. This provides the optimal learning environment for students.

[0505] Step 7:

[0506] The server notifies the parents and the institution using a means for notifying the analysis results. The analysis results are input, and the notification content is sent to the parents and the institution as output.

[0507] Step 8:

[0508] The server distributes appropriate learning content to the device based on the generated curriculum. The generated curriculum is the input, and the learning content is distributed to the device as the output. Students can use this to work on their individual learning content.

[0509] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0510] This invention is a learning support system that can replace after-school care or free schooling at home, automatically generating a child's learning curriculum using generative AI and having an "AI instructor" conduct the lessons. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it has the ability to dynamically adjust the curriculum and teaching methods based on the child's reactions.

[0511] System Overview

[0512] The system mainly consists of the following components:

[0513] 1. Server: Performs generative AI, emotion engine, and database management.

[0514] 2. Device: A device operated by a user (parent or child). Examples include PCs, tablets, and smartphones.

[0515] 3. Users: Parents and children. Parents configure and monitor the system, while children learn.

[0516] System Implementation

[0517] 1. User registration and initial settings

[0518] The user opens the website or app on their device and enters their name, email address, and password on the "Create an Account" screen. The server saves the entered information in a database and sends a confirmation email. The user clicks on the link in the confirmation email to activate the account. The user then enters the child's basic information (name, age, grade) and selects an avatar, voice, and speaking style on the "AI Instructor" settings screen. The server saves the selected settings information in a database and reflects them in the generative AI model.

[0519] 2. Curriculum Generation

[0520] The server retrieves the child's basic information from the database and inputs it into the generation AI. The generation AI generates an optimal learning curriculum based on the child's information and stores it in the database. For example, for a 10-year-old child, a curriculum that incorporates a balanced mix of basic math, reading time, and exercise would be generated.

[0521] 3. Classes begin

[0522] When the user (child) presses the "Start Lesson" button on their device, the server retrieves the curriculum and launches the "AI Instructor" lesson program. The AI ​​instructor conducts the lesson in an interactive format, with the emotion engine recognizing the child's facial expressions and voice to analyze their emotions. For example, in a math class, a question is posed and the child enters the answer, and the AI ​​instructor determines whether it is correct or incorrect and moves on to the next step. Based on the results of the emotion engine's analysis, if the child is confused, additional explanations are provided.

[0523] 4. Functions of the Emotion Engine

[0524] During lessons, the emotion engine recognizes and analyzes students' emotions in real time. The device collects students' facial expressions and voice data and sends it to a server. The server analyzes this data and dynamically adjusts the curriculum content and lesson progress depending on the situation, such as whether the student is feeling stressed or having fun. For example, if a student is bored, it will provide more interesting topics and interactive activities.

[0525] 5. Status reporting and collaboration

[0526] When the lesson ends, the server records the progress of the lesson, the students' reactions, and the results of the emotion analysis performed by the emotion engine. The server analyzes this information and stores it in a database. The server then sends a summary to the parent's device. For example, it may report points in today's lesson that the student found difficult, parts that they showed particular interest in, or specific emotional changes. The server also shares information with the student's school, and automatically processes attendance certification.

[0527] Specific examples

[0528] For example, if a 10-year-old child uses this system, parents create an account through the initial setup process and enter their child's information and preferences. The generating AI then generates an optimized curriculum for math, reading, and physical education for the child. When the child begins class, an "AI instructor" conducts the lesson in an interactive format, and an emotion engine analyzes the child's facial expressions and voice. For example, if a child is having difficulty with a math problem, the AI ​​instructor will provide detailed explanations and hints to help the child understand. After the class ends, parents are notified of a detailed report of the child's learning progress and emotional changes, and the necessary information is shared with the child's school.

[0529] In this way, the system of the present invention provides flexible and effective after-school care and free school functions at home, improving children's learning environments. By combining it with an emotion engine, dynamic instruction can be provided according to the child's emotions, providing a more individually optimized learning experience.

[0530] The processing flow will be explained below.

[0531] Step 1:

[0532] A user opens a website or app on their device and enters their name, email address, and password on the "Create an account" screen. The server stores the information in a database and sends a confirmation email. The user clicks on a link in the confirmation email to activate their account.

[0533] Step 2:

[0534] The user logs in and enters the child's basic information (name, age, grade). Next, they select the avatar, voice, and speaking style in the "AI instructor" settings. For example, they can choose an anime-style avatar, a gentle voice, and a slow speaking style. The server saves the selected settings in a database and reflects them in the generative AI model.

[0535] Step 3:

[0536] The server retrieves the child's basic information from the database and inputs it into the generation AI. The generation AI generates the optimal learning curriculum based on the child's information. For example, for a 10-year-old child, a curriculum that incorporates a good balance of basic math, reading time, and exercise is generated. The generated curriculum is saved in the database.

[0537] Step 4:

[0538] The user (child) presses the "Start Lesson" button on the device. The server retrieves the curriculum and launches the "AI Instructor" lesson program. The AI ​​Instructor conducts the lesson in an interactive format. For example, in a math class, a question is posed and the child enters the answer, and the AI ​​Instructor determines whether it is correct or incorrect and moves on to the next step.

[0539] Step 5:

[0540] During lessons, the emotion engine analyzes the students' facial expressions and voices in real time. The device uses a camera and microphone to collect the students' facial expressions and voice data and sends it to the server. The server uses the emotion engine to analyze the received data and identify the students' emotions. For example, it can identify whether a student is confused or having fun.

[0541] Step 6:

[0542] The server dynamically adjusts the curriculum based on the analysis results: for example, if a child is confused, the AI ​​instructor will provide additional explanation, or if a child is bored, they will be offered more interactive activities.

[0543] Step 7:

[0544] During the lesson, the AI ​​instructor will suggest appropriate breaks or playtime. When the user (child) presses the "Break" button, relaxing activities will be displayed. For example, simple exercises or mini-games will be suggested.

[0545] Step 8:

[0546] When the user (student) presses the "End Lesson" button, the server records the progress of the lesson, the student's reactions, and the results of emotion analysis. The server stores this information in a database.

[0547] Step 9:

[0548] The server summarizes the highlights of the lesson, the students' reactions, and the results of emotional analysis, and sends them to the parents' devices. For example, it reports which parts of today's lesson the student found difficult, which parts they found interesting, etc.

[0549] Step 10:

[0550] The server also connects with the student's school's system and sends information for attendance certification. Once attendance confirmation is complete, the server notifies the parents of the results. For example, the server can automatically connect to the school's attendance management system and certify the student's attendance.

[0551] Example 2

[0552] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0553] Conventional learning support systems have the problem that they are not sufficient to function as a substitute for after-school care at home or free schools. Specifically, they do not adequately provide the automatic generation of individually optimized learning curricula, dynamic instruction according to the child's emotions, or effective progress monitoring and reporting, making it difficult to improve children's learning environments.

[0554] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0555] In this invention, the server includes a means for inputting basic information about the child, a generation AI means for generating an educational plan based on the child's basic information, an AI teaching means for conducting lessons based on the generated educational plan, an emotion engine means for recognizing and analyzing the child's emotions, a means for analyzing the progress of the lesson and the child's reactions, a means for notifying the analysis results, and a means for linking and sharing information with parents and educational institutions. This enables the generation of individually optimized learning curricula, flexible instruction according to the child's emotions, and effective monitoring and reporting of learning progress.

[0556] 1. "Basic information about the child" refers to basic information necessary for learning support, such as the child's name, age, and grade.

[0557] 2. An "educational plan" is a plan that includes specific learning content and schedules, created based on basic information about a child.

[0558] 3. "Generative AI means" refers to artificial intelligence technology that receives basic information about a child as input and automatically generates an optimal educational plan.

[0559] 4. "Artificial intelligence teaching means" refers to an interactive artificial intelligence that conducts lessons based on the generated teaching plan.

[0560] 5. "Emotion engine means" refers to technology for recognizing a child's facial expressions and voice and analyzing their emotional state.

[0561] 6. "Class progress" refers to the progress and progress of a class according to the educational plan.

[0562] 7. "Children's reactions" refers to the children's behavior, facial expressions, vocal responses, etc. during class.

[0563] 8. "Analysis results" refers to data obtained by analyzing the progress of lessons and students' responses.

[0564] 9. "Means of notification" refers to the methods and techniques used to communicate the results of the analysis to parents and educational institutions.

[0565] 10. "Means of information collaboration and sharing" refers to the technologies and methods for sharing analysis results with relevant parents and educational institutions.

[0566] MODE FOR CARRYING OUT THE INVENTION

[0567] This invention is a learning support system that serves as an alternative to after-school care or free schools within the home, and is composed of the following main components and technical elements:

[0568] System configuration

[0569] The system includes the following hardware and software components:

[0570] 1. Server:

[0571] Generative AI means: An artificial intelligence model that generates optimal educational plans based on basic information about children. Specifically, this applies to generative AI models that use machine learning algorithms or natural language processing.

[0572] Emotion engine means: Technology for analyzing a child's facial expressions and voice to recognize their emotional state. Specifically, this includes image recognition technology and voice analysis technology.

[0573] Database: A database for storing basic information about students, generated teaching plans, lesson progress, emotional data, etc.

[0574] 2. Terminal:

[0575] User interface: A device that parents and children use to operate the system. Specific examples include PCs, tablets, and smartphones. These devices interact with the system through web applications or native applications.

[0576] Sensors: Cameras and microphones to collect the child's facial expressions and voice.

[0577] 3. User:

[0578] Parent: Initial setup and monitoring of the system.

[0579] Children: Learning through the system.

[0580] Initial Setup and User Registration

[0581] The user opens the website or app on their device and enters their name, email address, and password on the "Create an account" screen. The server saves the entered information in a database and sends a confirmation email. The user clicks on the link in the confirmation email to activate the account. The user then enters the child's basic information (name, age, grade level), and selects an avatar, voice, and speaking style on the "AI teaching method" settings screen. The server saves the selected settings information in a database and reflects them in the generative AI model.

[0582] Generate a teaching plan

[0583] The server retrieves the child's basic information from the database and inputs it into the generation AI. The generation AI generates an optimal educational plan based on the child's information and stores it in the database. For example, for a 10-year-old child, a plan that incorporates a good balance of basic math, reading time, and exercise is generated.

[0584] Class progress

[0585] When a user (child) presses the "Start Lesson" button on their device, the server retrieves the educational plan and launches the lesson program in the "AI teaching tool." The AI ​​teaching tool conducts the lesson in an interactive format, with the emotion engine recognizing the child's facial expressions and voice to analyze their emotions. For example, in a math lesson, a question is posed and the child enters the answer, and the AI ​​teaching tool determines whether it is correct or incorrect and moves on to the next step. Based on the analysis results of the emotion engine, if the child is confused, additional explanations are provided.

[0586] Sentiment Analysis and Dynamic Adjustment

[0587] During lessons, the emotion engine recognizes and analyzes students' emotions in real time. The device collects students' facial expressions and voice data and sends it to the server. The server analyzes this data and dynamically adjusts the content of the educational plan and the way the lesson is conducted depending on the situation, such as whether the student is feeling stressed or having fun. For example, if the student is bored, it will provide more interesting topics and interactive activities.

[0588] Situation reporting and information sharing

[0589] When the lesson ends, the server records the progress of the lesson, the students' reactions, and the results of the emotion analysis performed by the emotion engine. The server analyzes this information and stores it in a database. The server then sends a summary to the parent's device. For example, it may report points in today's lesson that the student found difficult, parts that they showed particular interest in, or specific emotional changes. The server also shares information with the student's school, and automatically processes attendance certification.

[0590] Examples and prompts

[0591] For example, if a 10-year-old child uses this system, parents can create an account through the initial setup process and enter their child's information and preferences. The generating AI will then generate an optimized educational plan for their child covering math, reading, and exercise. When the child begins class, the AI ​​instructor will conduct the lesson in an interactive format, and the emotion engine will analyze the child's facial expressions and voice. For example, if a child is having difficulty with a math problem, the AI ​​instructor will provide detailed explanations and hints to help the child understand. After the class ends, parents will receive a detailed report on the child's learning progress and emotional changes, and the necessary information will be shared with the child's school.

[0592] Example prompts for generative AI models

[0593] "Generate a one-week learning curriculum for a 10-year-old child. Include a good balance of math, reading, and physical activity."

[0594] "Create new math problem sets and adjust the difficulty based on students' understanding."

[0595] "Please report on today's lesson trends based on the students' emotional data."

[0596] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0597] Step 1: User registration and initial setup

[0598] Input: The user enters their name, email address, and password on the device.

[0599] What it does: The server saves the information you entered in its database and sends you a confirmation email.

[0600] Output: A confirmation email is sent to the user.

[0601] What it does: A user opens a website or app on their device and enters their name, email address, and password on the "Create an account" screen. The server then stores the information in a database and sends a confirmation email.

[0602] Step 2: Activate your account

[0603] Input: User clicks on the link in the confirmation email.

[0604] Action: The server activates the account.

[0605] Output: The account is activated and available to the user.

[0606] What it does: The user clicks on the link in the confirmation email to complete the fast and secure account activation.

[0607] Step 3: Enter your child's information

[0608] Input: The user enters the child's basic information (name, age, grade).

[0609] How it works: The server saves the input information in a database.

[0610] Output: The child's basic information is obtained and the next operation is instructed.

[0611] Specific operation: The user enters basic information about the child into the system, and the server accurately stores it in the database.

[0612] Step 4: Setting up the AI ​​instructor

[0613] Input: The user selects the avatar, voice, and speaking style of the "AI instructor."

[0614] How it works: The server saves the selected configuration information in a database and reflects it in the generative AI model.

[0615] Output: The AI ​​instructor is configured and individual customization is enabled.

[0616] Specific operation: The user selects an avatar, voice, and speaking style, and this information is reflected in the generated AI model by the server and set in the system.

[0617] Step 5: Generate a teaching plan

[0618] Input: The server retrieves basic information about the child from the database.

[0619] How it works: Generative AI generates an educational plan based on the child's information.

[0620] Output: The generated teaching plan is stored in a database.

[0621] Specific operation: The server obtains basic information about the child and inputs it into the generation AI. The AI ​​generates an optimal educational plan, and the server stores the plan in a database.

[0622] Step 6: Start classes

[0623] Input: The user (student) presses the "Start lesson" button on the terminal.

[0624] Operation: The server obtains the teaching plan and starts the AI ​​instructor's lesson program.

[0625] Output: Lesson begins.

[0626] Specific operation: When the user (child) presses "Start lesson," the server retrieves the plan and the AI ​​instructor begins the lesson.

[0627] Step 7: Lesson Progression

[0628] Input: Facial expressions and voice data of students during class.

[0629] How it works: The emotion engine analyzes the child's emotions in real time and sends the results to the server.

[0630] Output: The progress of the lesson is dynamically adjusted based on the results of the sentiment analysis.

[0631] Specific operation: During the lesson, the device collects facial expressions and voice data, and the emotion engine analyzes the emotions and sends them to the server. The server then provides appropriate guidance and feedback based on the analysis results.

[0632] Step 8: Reporting and sharing information

[0633] Input: Lesson progress, student responses, and emotion analysis results.

[0634] How it works: The server records the progress of the lesson and the students' responses and saves them in a database.

[0635] Output: A notification is sent to the parent's device and the information is shared with the educational institution.

[0636] Specific operation: After the lesson ends, the server records the progress, students' reactions, and emotion analysis results, and saves them in a database. It then reports the situation to the parents' devices and automatically shares the information with the educational institution.

[0637] (Application example 2)

[0638] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0639] Conventional learning support systems have limitations in dynamically adjusting curriculum in response to children's emotions and reactions, and in providing learning experiences in virtual environments. Furthermore, many systems require parents to perform setup tasks at a high level, making it difficult to maintain children's interest. Furthermore, the lack of flexibility and interactivity in learning sessions in virtual environments is also a problem.

[0640] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for inputting basic information about the child, a generation AI means for generating a curriculum based on the child's basic information, an AI instructor means for conducting a lesson based on the generated curriculum, a means for analyzing the progress of the lesson and the child's responses, a means for notifying the child of the analysis results, a means for linking and sharing information with parents and the child's school, a means for recognizing and analyzing the child's emotions in real time using an emotion recognition engine and dynamically adjusting the lesson content, and a means for providing lessons and workshops in a virtual environment. This enables the provision of a flexible curriculum that corresponds to each child's individual emotions and learning progress, and a diverse learning experience in a virtual environment.

[0641] The "means for inputting basic information about a child" is a system component that has a function for inputting basic profile data such as a child's name, age, and grade.

[0642] "Generative AI means" refers to an artificial intelligence algorithm or system component that generates an optimal learning curriculum based on the basic information acquired about a child.

[0643] The "artificial intelligence instructor means" is an artificial intelligence-based educational system or software for conducting lessons based on the generated learning curriculum and educating children.

[0644] The "means for analyzing the progress of the lesson and the reactions of the students" is a system component for observing the behavior and reactions of the students during the lesson and analyzing the progress based on that.

[0645] The "means for notifying analysis results" is a system component that has the function of notifying parents and educators of the analysis results regarding the progress of the lesson and the students' reactions.

[0646] "Means for coordinating and sharing information with parents and the school" refers to a system component with communication functions for coordinating and sharing information regarding the progress of lessons, curriculum, and students' reactions with parents and the school.

[0647] An "emotion recognition engine" is an algorithm or system component that analyzes a child's facial expressions and voice data to recognize and analyze their emotional state in real time.

[0648] The "means for dynamically adjusting lesson content" is a system component that has the function of adjusting the lesson progress and curriculum in real time based on the emotional data collected by the emotion recognition engine.

[0649] "Means for providing classes and workshops in a virtual environment" refers to system components for providing classes and workshops in a virtual space using virtual reality (VR) and augmented reality (AR).

[0650] This invention is a learning support system for home or virtual environments, equipped with technology to provide flexible and effective education to children. The system uses a generative AI model to automatically generate a learning curriculum for children and an "artificial intelligence instructor" to conduct the lessons. It also uses an emotion recognition engine to analyze children's emotions in real time and dynamically adjust the lesson content.

[0651] System Overview

[0652] The system mainly consists of the following components:

[0653] 1. Server: Manages generative AI models, emotion recognition engines, and databases.

[0654] 2. Device: A device used by users (parents and children). Examples include PCs, tablets, smartphones, and head-mounted displays.

[0655] 3. Users: Parents and children. Parents configure and monitor the system, while children learn.

[0656] System Implementation

[0657] User Registration and Settings

[0658] The user (parent) accesses the registration form from their device and enters their name, email address, password, and child information (name, age, grade). The server stores this information in a database and sends a confirmation email. When the user clicks the link in the confirmation email, the account is activated. The parent then sets the avatar, voice, and speaking style of the "artificial intelligence instructor" according to their child's preferences. These settings are reflected in the generative AI model.

[0659] Curriculum Generation

[0660] The server retrieves basic information about the child from the database and inputs it into the generative AI model, which then generates a curriculum using, for example, the following prompt:

[0661] Generate a diverse and engaging curriculum for a 10 year old in grade 5. Curriculum should include subjects like math, reading, and physical activities.

[0662] The generated curriculum is stored in a database. For example, for a 10-year-old child, a curriculum that incorporates a balanced mix of math basics, reading time, and physical activity is generated.

[0663] Start and progress of lessons

[0664] When a user (child) presses the "Start Lesson" button on their device, the server retrieves the curriculum and launches the "AI Instructor." The AI ​​Instructor conducts the lesson in an interactive format, with an emotion recognition engine collecting and analyzing the child's facial expressions and voice in real time. For example, in a math class, a question is posed and the child enters the answer, and the AI ​​Instructor determines whether it is correct or incorrect and moves on to the next step. If the emotion recognition engine detects that the child is confused, it provides additional explanation.

[0665] Emotion Recognition Engine and Dynamic Adjustment

[0666] During lessons, an emotion recognition engine analyzes students' emotions in real time and sends the results to the server. For example, if a student is bored, the system will introduce more interactive activities. If a student is having trouble understanding, the system will provide detailed explanations or hints.

[0667] Reporting and collaboration

[0668] After the lesson is over, the server records the progress of the lesson, the students' reactions, and the results of emotional analysis. The server analyzes this information and notifies parents and the student's school. For example, it reports if a student had difficulty with a particular task or if a part of the lesson showed particular interest. This allows parents and educators to understand the student's learning progress.

[0669] This system allows children to enjoy a personalized learning experience and allows parents and educators to effectively support their children's learning progress.

[0670] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0671] Step 1: User registration and initial setup

[0672] The user (guardian) accesses the registration form from their device and enters their name, email address, password, and child information (name, age, grade). This input data is sent to the server and stored in a database. The server generates a confirmation email and sends it to the entered email address. When the user clicks the link in the confirmation email, the account is activated. Next, the user (guardian) sets the avatar, voice, and speaking style of the "artificial intelligence instructor" according to their child's preferences. This setting information is also sent to the server and reflected in the generated AI model.

[0673] Step 2: Curriculum generation

[0674] The server retrieves basic information about the child (age, grade, etc.) from the database and inputs this information into the generative AI model. For example, the server sends the following prompt to the generative AI model to generate the optimal curriculum.

[0675] Generate a diverse and engaging curriculum for a 10 year old in grade 5. Curriculum should include subjects like math, reading, and physical activities.

[0676] The generative AI model generates a curriculum based on the input information, and the server receives the generated curriculum and stores it in a database. For example, a curriculum that balances basic math, reading time, and exercise for a 10-year-old child would be generated.

[0677] Step 3: Start classes

[0678] When the user (child) presses the "Start Lesson" button on their device, the server retrieves a pre-generated curriculum from the database and launches the "AI instructor" lesson program. The AI ​​instructor begins the lesson based on the retrieved curriculum and provides the child with learning content in an interactive format. The device collects the child's facial expressions and voice data in real time and sends it to the server.

[0679] Step 4: Emotion recognition and dynamic regulation

[0680] The server inputs facial expressions and voice data sent from the device into an emotion recognition engine to analyze the child's emotions in real time. For example, if the emotion recognition engine detects a child's confusion or boredom, the server generates appropriate feedback and additional explanations and provides them to the child through an AI instructor. This allows the child to continue learning with appropriate support.

[0681] Step 5: Learning Records and Notifications

[0682] After the lesson is over, the server records the progress of the lesson, the students' reactions, and the results of emotional analysis. This information is stored in a database as a profile and used for future learning. The server also generates a report summarizing the lesson and highlighting key points, which is sent to parents and the student's school to share the student's learning status. For example, it reports if a student had difficulty with a particular problem or if a topic of particular interest occurred.

[0683] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0684] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0685] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0686] [Third embodiment]

[0687] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0688] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0689] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0690] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0691] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0692] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0693] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0694] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0695] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0696] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0697] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0698] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0699] This invention is a learning support system for children, which can be used as an alternative to after-school care or free schools at home. This system uses generative AI to automatically generate learning curricula for children, and has "AI instructors" conduct the lessons.

[0700] System Overview

[0701] The system mainly consists of the following components:

[0702] 1. Server: Generates AI and manages the database.

[0703] 2. Device: A device operated by a user (parent or child). Examples include PCs, tablets, and smartphones.

[0704] 3. Users: Parents and children. Parents configure and monitor the system, while children learn.

[0705] System Implementation

[0706] 1. User registration and initial settings

[0707] The user opens the website or app on their device and enters their name, email address, and password on the "Create an Account" screen. The server saves the entered information in a database and sends a confirmation email. The user clicks on the link in the confirmation email to activate the account. The user then enters the child's basic information (name, age, grade level), and selects an avatar, voice, and speaking style on the "AI Instructor" settings screen. The server receives the selected settings information and reflects it in the generative AI model.

[0708] 2. Curriculum Generation

[0709] The server retrieves the child's basic information from the database and inputs it into the generation AI. The generation AI generates an optimal learning curriculum based on the child's information and stores it in the database. For example, for a 10-year-old child, a curriculum that incorporates a balanced mix of basic math, reading time, and exercise would be generated.

[0710] 3. Classes begin

[0711] When the user (child) presses the "Start Lesson" button on their device, the server retrieves the curriculum and launches the "AI Instructor" lesson program. The AI ​​Instructor conducts the lesson in an interactive format, monitoring the children's answers and reactions. For example, in a math class, the AI ​​Instructor poses a question and when the child enters the answer, the AI ​​Instructor determines whether it is correct or incorrect and moves on to the next step. The AI ​​Instructor also suggests appropriate breaks and playtimes to maintain the children's concentration.

[0712] 4. Status reporting and collaboration

[0713] When the lesson ends, the server analyzes the progress of the lesson and the student's reactions, summarizing the results and notifying parents. The information is also shared with the student's school, which automatically processes attendance certification. For example, the server can report on the areas in which the student struggled in today's lesson and the activities in which the student showed particular interest, allowing parents to understand their child's learning status.

[0714] Specific examples

[0715] For example, if a 10-year-old child uses this system, their parents will create an account through the initial setup process and enter their child's information and preferences. The AI ​​will then generate a curriculum optimized for their child, covering math, reading, and physical education. When the child begins class, an "AI instructor" will conduct the lesson interactively while the child works on the assignments. After the class ends, parents will receive a summary of the child's learning progress and responses, and attendance information will be shared with the school.

[0716] In this way, the system of the present invention provides flexible and effective after-school care and free school functions at home, improving children's learning environment.

[0717] The processing flow will be explained below.

[0718] Step 1:

[0719] The user opens a website or app on their device and enters their name, email address, and password on the "Create an account" screen. The server stores the information in a database and sends a confirmation email. The user clicks on a link in the email to activate their account.

[0720] Step 2:

[0721] The user logs in and enters the child's basic information (name, age, grade). Next, they select the avatar, voice, and speaking style in the "AI instructor" settings. For example, they can choose an anime-style avatar, a gentle voice, and a slow speaking style. The server saves the selected settings in a database and reflects them in the generative AI model.

[0722] Step 3:

[0723] The server retrieves the child's basic information from the database and inputs it into the generation AI. The generation AI generates the optimal learning curriculum based on the child's information. For example, for a 10-year-old child, a curriculum that incorporates a good balance of basic math, reading time, and exercise is generated. The generated curriculum is saved in the database.

[0724] Step 4:

[0725] The user (child) presses the "Start Lesson" button on the device. The server retrieves the curriculum and launches the "AI Instructor" lesson program. The AI ​​Instructor conducts the lesson in an interactive format. For example, in a math class, a question is posed and the child enters the answer, and the AI ​​Instructor determines whether it is correct or incorrect and moves on to the next step.

[0726] Step 5:

[0727] An AI instructor assesses students' understanding and responses in real time during lessons. The device collects the students' responses and sends them to a server. The server analyzes them and dynamically adjusts the curriculum content as needed. For example, if a student struggles with a particular math problem, the AI ​​instructor can provide additional explanation.

[0728] Step 6:

[0729] During the lesson, the AI ​​instructor will suggest appropriate breaks or playtime. When the user (child) presses the "Break" button, relaxing activities will be displayed. For example, simple exercises or mini-games will be suggested.

[0730] Step 7:

[0731] When the user (student) presses the "End Lesson" button, the server records the progress of the lesson and the student's responses. The server analyzes this information and stores it in a database.

[0732] Step 8:

[0733] The server summarizes the highlights of the lesson and the students' reactions, and sends this information to the parents' devices. For example, it can report points that were difficult to understand in today's lesson or parts that the students found particularly interesting.

[0734] Step 9:

[0735] The server connects to the student's school's system and sends information for attendance certification. Once attendance confirmation is complete, the server notifies the parent or guardian of the results. For example, the server can automatically connect to the school's attendance management system and certify the student's attendance.

[0736] Example 1

[0737] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0738] Current home learning support systems lack the means to effectively provide an optimized learning curriculum for each child, while also being able to monitor the progress and reactions of the children in real time. Furthermore, there is insufficient collaboration with parents and schools, making it difficult to effectively share learning outcomes.

[0739] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0740] In this invention, the server includes a means for inputting basic information about each child, an AI generation means for generating a curriculum based on the child's basic information, an AI instructor means for conducting a lesson based on the generated curriculum, a means for starting a lesson program when a lesson start button is pressed, a means for analyzing the progress of the lesson and the child's responses, and a means for summarizing the analysis results and notifying the parents and the child's school of the information. This makes it possible to provide a learning curriculum optimized for each child, realize real-time understanding of learning progress, and effectively share information.

[0741] "Children" refers primarily to school-age children in the primary school education stage.

[0742] "Basic information" refers to the child's name, age, grade, and other personal attribute information related to learning.

[0743] "Generative AI" refers to an artificial intelligence model that automatically generates a curriculum based on input information.

[0744] "Curriculum" refers to an educational plan that systematically and systematically arranges children's learning activities.

[0745] An "AI instructor" refers to a virtual instructor who conducts lessons based on a curriculum generated by generative AI.

[0746] "Class progress" refers to the implementation process for carrying out educational activities as planned.

[0747] "Class program" refers to the specific learning content and activities implemented in each class based on the curriculum.

[0748] The "lesson start button" refers to the operation section on the user interface for starting the lesson program.

[0749] "Progress" refers to the status of whether the lesson is proceeding as planned.

[0750] "Children's reactions" refers to the level of understanding, interest, and participation shown by children during class.

[0751] "Analysis" refers to the act of processing data to evaluate the progress of the lesson and the students' responses.

[0752] "Summary" refers to a brief report that summarizes information about the lesson's progress and the students' responses.

[0753] "Guardian" refers to a parent or guardian whose role is to support and supervise a child's learning activities.

[0754] "School of enrolment" refers to the educational institution in which a child is officially registered.

[0755] "Notification" refers to the means of communication used to inform parents and the student's school of the analysis results.

[0756] This invention is a learning support system for children, which can be used as an alternative to after-school care or free schools at home. This system uses generative AI to automatically generate learning curricula for children, and has "AI instructors" conduct the lessons.

[0757] System configuration

[0758] The system mainly consists of the following components:

[0759] 1. Server: Generates AI and manages the database.

[0760] 2. Device: A device operated by a user (parent or child). Examples include PCs, tablets, and smartphones.

[0761] 3. Users: Parents and children. Parents configure and monitor the system, while children learn.

[0762] User registration and initial settings

[0763] A user opens a website or app on their device and enters their name, email address, and password on the "Create an account" screen. The server then receives this information and stores it in a database. It then automatically generates a confirmation email and sends it to the email address provided. When the user clicks on the link in the confirmation email, the server receives the link and activates the account.

[0764] The user then logs in and enters the child's basic information (name, age, grade). Next, the user customizes the AI ​​instructor's avatar, voice, speaking style, etc. This setting information is received by the server and reflected in the generative AI model. At this time, the settings are generated using an image generation API and a voice synthesis API.

[0765] Curriculum Generation

[0766] The server retrieves basic information about the child from a database, including age, grade, preferences, and interests. The server then inputs this information into a generative AI model (e.g., GPT-4). The specific prompt is as follows:

[0767] "Generate a curriculum that will engage and effectively teach a 10-year-old child. The child's name is Taro, and the curriculum should include a good balance of math, reading, and physical activity."

[0768] The generative AI model generates an optimal curriculum based on the input information. For example, a curriculum such as "Monday: 9:00-10:00 Math, 10:00-11:00 Reading, 11:00-12:00 Exercise..." is generated. The generated curriculum is stored in a database on the server.

[0769] Classes begin

[0770] When a user (child) logs in on their device and presses the "Start Lesson" button, the server retrieves the current curriculum and launches the "AI Instructor" lesson program. The AI ​​Instructor conducts the lesson in an interactive format, monitoring the children's answers and reactions. For example, in a math class, the AI ​​Instructor poses questions, and when the children enter their answers, the AI ​​evaluates them and provides feedback. Appropriate breaks and playtime are also suggested to ensure that the children's concentration is maintained.

[0771] Status reporting and collaboration

[0772] When the lesson ends, the server analyzes the progress of the lesson and the students' responses, summarizes the results, and notifies parents. The server also connects to the configured school system to automatically report attendance and learning content. Specifically, the server records the progress of the lesson and the students' responses as a log, analyzes the log, and generates a summary in natural language. This summary is sent to parents via email or in-app notification, and the information is automatically shared with the school.

[0773] Specific operation example

[0774] For example, if a 10-year-old boy named Taro were to use this system, his parents would create an account with the initial settings and enter Taro's name, age, grade, and interests. The generation AI would then generate an optimized curriculum for Taro (math, reading, exercise, etc.) and store it in a database. When Taro presses the "Start Lesson" button, the "AI Instructor" will conduct the lesson in an interactive format, and Taro will work on the assignment. For example, in a math problem, if Taro answers "12" to the question "What is 5 + 7?", the "AI Instructor" will respond with "That's correct!" After the lesson, parents will be notified of a summary of Taro's learning progress and responses, and attendance information will be shared with the school.

[0775] In this way, the system of the present invention provides flexible and effective after-school care and free school functions at home, improving children's learning environment.

[0776] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0777] Step 1:

[0778] The user opens a website or app on their device and enters their name, email address, and password on the "Create an account" screen. The server receives this information and stores it in a database. The server then automatically generates a confirmation email and sends it to the email address entered. When the user clicks the link in the confirmation email, the server receives the link and activates the account. (Input: Name, email address, password / Output: Sending confirmation email and activating the account)

[0779] Step 2:

[0780] The user logs in and enters the child's basic information (name, age, grade). Next, the user customizes the AI ​​instructor's avatar, voice, speaking style, etc. The server receives this configuration information and reflects it in the generated AI model. Specifically, the customization content is generated using an image generation API and a voice synthesis API. (Input: basic information, avatar settings / Output: reflection of the generated AI model)

[0781] Step 3:

[0782] The server retrieves basic information about the child from a database. This information includes age, grade, preferences, and interests. The server inputs this information into a generative AI model to generate a curriculum. For example, the following prompt might be used: "Please generate a curriculum that will interest a 10-year-old child and help him learn effectively. The child's name is Taro, and the curriculum should include a good balance of math, reading, and exercise." (Input: Basic information / Output: Curriculum generation)

[0783] Step 4:

[0784] The generative AI model generates a curriculum based on the prompt. The generated curriculum is stored in a database on the server. For example, it might look like this: "Monday: 9:00-10:00 Math, 10:00-11:00 Reading, 11:00-12:00 Exercise..." (Input: Prompt / Output: Curriculum)

[0785] Step 5:

[0786] The user (child) logs in to the device and presses the "Start Lesson" button. The server retrieves the current curriculum and launches the "AI Instructor" lesson program. (Input: Pressing the "Start Lesson" button / Output: Launching the lesson program)

[0787] Step 6:

[0788] The AI ​​instructor conducts the lesson in an interactive format, monitoring the students' answers and reactions. For example, in a math class, the AI ​​instructor poses a question, and the students input their answers, which the AI ​​evaluates and provides feedback. It also suggests breaks and playtimes as appropriate. (Input: Student's answers / Output: Feedback, break suggestions)

[0789] Step 7:

[0790] The server records the progress of the lesson and the students' reactions as logs. After the lesson ends, the server analyzes the logs and generates a summary of the progress and reactions. The summary is sent to parents via email or in-app notification. (Input: Log data / Output: Summary report)

[0791] Step 8:

[0792] The server connects to the configured school system and automatically reports attendance and learning content. Specifically, today's lesson content and attendance status are sent to the school, and the student's attendance is certified. (Input: lesson content, attendance status / Output: report to school and certification)

[0793] In this way, the information entered at each step is processed appropriately, providing children with an optimized learning curriculum and enabling real-time understanding of learning progress and information sharing.

[0794] (Application example 1)

[0795] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0796] Conventional learning support systems have problems such as insufficient curriculum generation based on individual student needs, insufficient real-time status reporting, and insufficient collaboration. Furthermore, delays in sharing information with parents and the institution where the student is enrolled make it difficult to properly grasp the student's learning effectiveness and progress. The present invention aims to solve these problems and provide an optimal learning experience for students.

[0797] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0798] In this invention, the server includes means for inputting basic information about the child, generation AI means for generating a curriculum based on the child's basic information, AI instructor means for conducting lessons based on the generated curriculum, means for analyzing the progress of the lesson and the child's responses, means for notifying the analysis results, means for linking and sharing information with parents and the institution where the child is enrolled, and means for delivering content based on the generated curriculum. This enables the automatic generation and progress of a curriculum suited to the child, status reporting and linking, and makes it easier for parents and educational institutions to grasp the child's learning situation in real time.

[0799] "Means for inputting basic information about children" refers to devices or software for inputting basic information about children, such as their age, grade, and interests.

[0800] "Generative AI means" refers to an artificial intelligence processing device or software that automatically generates an optimal learning curriculum based on basic information about the child that is input.

[0801] The "AI instructor means" is an artificial intelligence processing device or software that conducts lessons in an interactive format according to the generated curriculum and provides educational guidance to children.

[0802] "Means for analyzing the progress of lessons and students' responses" refers to devices or software that monitor students' responses and progress during lessons in real time and analyze that information.

[0803] The "means for notifying the analysis results" refers to a device or software for notifying parents or the institution where the student is enrolled of the results of the analysis conducted during the lesson.

[0804] "Means for coordinating and sharing information with parents and the institution where the child is enrolled" refers to a device or software for coordinating and sharing the results of analysis of a child's learning progress and lessons with parents and the institution where the child is enrolled.

[0805] A "means for delivering content based on a generated curriculum" is a device or software that delivers appropriate learning content based on a curriculum generated by generative AI.

[0806] This invention is a learning support system for children, which serves as an alternative to after-school care or free schools at home. This system uses generative AI to automatically generate learning curricula for children, and has "AI instructors" conduct lessons. The system configuration and implementation method are explained below.

[0807] System configuration

[0808] The system mainly consists of the following components:

[0809] 1. Server: Generates AI and manages the database.

[0810] 2. Device: A device operated by a user (parent or child). Examples include PCs, tablets, and smartphones.

[0811] 3. Users: Parents and children. Parents configure and monitor the system, while children learn.

[0812] Initial Setup and User Registration

[0813] When a user opens the website or app on their device and enters their name, email address, and password on the "Create an Account" screen, the server saves the information in a database and sends a confirmation email. The user clicks on the link in the confirmation email to activate the account. The user then enters their child's basic information (name, age, grade), and selects an avatar, voice, and speaking style on the "AI Instructor" settings screen. The server then receives the selected settings information and reflects them in the generative AI model.

[0814] Curriculum Generation

[0815] The server retrieves basic information about the child from the database and inputs it into the generation AI. The generation AI generates an optimal study curriculum based on the child's information and stores it in the database. For example, for a 10-year-old child, a curriculum is generated that incorporates a balanced mix of science, painting, basic mathematics, reading time, and exercise. An example prompt sentence is "Generate a study curriculum for a 10-year-old in grade 4 with interest in science and painting."

[0816] Classes begin

[0817] When the user (child) presses the "Start Lesson" button on their device, the server retrieves the curriculum and launches the "AI Instructor" lesson program. The AI ​​Instructor conducts the lesson in an interactive format, monitoring the children's answers and reactions. For example, in a science class, the AI ​​Instructor poses a question and when the child enters the answer, the AI ​​Instructor determines whether it is correct or incorrect and moves on to the next step. It also suggests appropriate breaks and playtimes to maintain the children's concentration.

[0818] Exams and Assessments

[0819] The server monitors the student's learning progress in real time and evaluates them at certain stages. The evaluation results are stored in a database and notified to parents and the student's institution. For example, the server can report the areas in which the student struggled in today's lesson or the activities in which the student showed particular interest, allowing parents to understand their child's learning status.

[0820] Content Delivery

[0821] The server distributes appropriate learning content based on the curriculum generated by the generative AI. The content is distributed to devices such as smartphones, smart glasses, and head-mounted displays, allowing children to use these devices to advance their studies.

[0822] In this way, the system of the present invention provides flexible and effective after-school care and free school functions at home, improving children's learning environment.

[0823] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0824] Step 1:

[0825] The server provides an interface for users to input basic information about their children (name, age, grade) on their terminals. Users input basic information through this interface, and the data is stored in a database. The input is the basic information of the children, and the output is a data structure that stores the basic information in the database.

[0826] Step 2:

[0827] The server retrieves basic information about the child from the database and inputs it as a prompt to the generative AI model. The basic information retrieved from the database serves as input, and the generative AI model automatically generates a curriculum. An example of a prompt is "Generate a study curriculum for a 10-year-old in grade 4 with interest in science and painting." The generated curriculum is then saved in the database as output.

[0828] Step 3:

[0829] When the user (child) presses the "Start Lesson" button on the device, the server retrieves the generated curriculum from the database and launches the "AI Instructor" lesson program. Curriculum information is acquired as input, and instructions for the AI ​​instructor to conduct the lesson are received as output.

[0830] Step 4:

[0831] The AI ​​instructor conducts interactive lessons with students via their terminals. The server asks questions to students based on instructions from the AI ​​instructor, and the students input their answers. The input is the student's answer, and the output is the AI ​​instructor providing the next question and explanation.

[0832] Step 5:

[0833] The server monitors the progress of lessons and students' responses in real time and collects data. The input is the data collected in real time, and the output is the analysis results. This allows students' learning progress to be understood.

[0834] Step 6:

[0835] The server dynamically adjusts the curriculum based on the collected data and analysis results. Collected data is the input, and an adjusted curriculum is generated as the output. This provides the optimal learning environment for students.

[0836] Step 7:

[0837] The server notifies the parents and the institution using a means for notifying the analysis results. The analysis results are input, and the notification content is sent to the parents and the institution as output.

[0838] Step 8:

[0839] The server distributes appropriate learning content to the device based on the generated curriculum. The generated curriculum is the input, and the learning content is distributed to the device as the output. Students can use this to work on their individual learning content.

[0840] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0841] This invention is a learning support system that can replace after-school care or free schooling at home, automatically generating a child's learning curriculum using generative AI and having an "AI instructor" conduct the lessons. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it has the ability to dynamically adjust the curriculum and teaching methods based on the child's reactions.

[0842] System Overview

[0843] The system mainly consists of the following components:

[0844] 1. Server: Performs generative AI, emotion engine, and database management.

[0845] 2. Device: A device operated by a user (parent or child). Examples include PCs, tablets, and smartphones.

[0846] 3. Users: Parents and children. Parents configure and monitor the system, while children learn.

[0847] System Implementation

[0848] 1. User registration and initial settings

[0849] The user opens the website or app on their device and enters their name, email address, and password on the "Create an Account" screen. The server saves the entered information in a database and sends a confirmation email. The user clicks on the link in the confirmation email to activate the account. The user then enters the child's basic information (name, age, grade) and selects an avatar, voice, and speaking style on the "AI Instructor" settings screen. The server saves the selected settings information in a database and reflects them in the generative AI model.

[0850] 2. Curriculum Generation

[0851] The server retrieves the child's basic information from the database and inputs it into the generation AI. The generation AI generates an optimal learning curriculum based on the child's information and stores it in the database. For example, for a 10-year-old child, a curriculum that incorporates a balanced mix of basic math, reading time, and exercise would be generated.

[0852] 3. Classes begin

[0853] When the user (child) presses the "Start Lesson" button on their device, the server retrieves the curriculum and launches the "AI Instructor" lesson program. The AI ​​instructor conducts the lesson in an interactive format, with the emotion engine recognizing the child's facial expressions and voice to analyze their emotions. For example, in a math class, a question is posed and the child enters the answer, and the AI ​​instructor determines whether it is correct or incorrect and moves on to the next step. Based on the results of the emotion engine's analysis, if the child is confused, additional explanations are provided.

[0854] 4. Functions of the Emotion Engine

[0855] During lessons, the emotion engine recognizes and analyzes students' emotions in real time. The device collects students' facial expressions and voice data and sends it to a server. The server analyzes this data and dynamically adjusts the curriculum content and lesson progress depending on the situation, such as whether the student is feeling stressed or having fun. For example, if a student is bored, it will provide more interesting topics and interactive activities.

[0856] 5. Status reporting and collaboration

[0857] When the lesson ends, the server records the progress of the lesson, the students' reactions, and the results of the emotion analysis performed by the emotion engine. The server analyzes this information and stores it in a database. The server then sends a summary to the parent's device. For example, it may report points in today's lesson that the student found difficult, parts that they showed particular interest in, or specific emotional changes. The server also shares information with the student's school, and automatically processes attendance certification.

[0858] Specific examples

[0859] For example, if a 10-year-old child uses this system, parents create an account through the initial setup process and enter their child's information and preferences. The generating AI then generates an optimized curriculum for math, reading, and physical education for the child. When the child begins class, an "AI instructor" conducts the lesson in an interactive format, and an emotion engine analyzes the child's facial expressions and voice. For example, if a child is having difficulty with a math problem, the AI ​​instructor will provide detailed explanations and hints to help the child understand. After the class ends, parents are notified of a detailed report of the child's learning progress and emotional changes, and the necessary information is shared with the child's school.

[0860] In this way, the system of the present invention provides flexible and effective after-school care and free school functions at home, improving children's learning environments. By combining it with an emotion engine, dynamic instruction can be provided according to the child's emotions, providing a more individually optimized learning experience.

[0861] The processing flow will be explained below.

[0862] Step 1:

[0863] A user opens a website or app on their device and enters their name, email address, and password on the "Create an account" screen. The server stores the information in a database and sends a confirmation email. The user clicks on a link in the confirmation email to activate their account.

[0864] Step 2:

[0865] The user logs in and enters the child's basic information (name, age, grade). Next, they select the avatar, voice, and speaking style in the "AI instructor" settings. For example, they can choose an anime-style avatar, a gentle voice, and a slow speaking style. The server saves the selected settings in a database and reflects them in the generative AI model.

[0866] Step 3:

[0867] The server retrieves the child's basic information from the database and inputs it into the generation AI. The generation AI generates the optimal learning curriculum based on the child's information. For example, for a 10-year-old child, a curriculum that incorporates a good balance of basic math, reading time, and exercise is generated. The generated curriculum is saved in the database.

[0868] Step 4:

[0869] The user (child) presses the "Start Lesson" button on the device. The server retrieves the curriculum and launches the "AI Instructor" lesson program. The AI ​​Instructor conducts the lesson in an interactive format. For example, in a math class, a question is posed and the child enters the answer, and the AI ​​Instructor determines whether it is correct or incorrect and moves on to the next step.

[0870] Step 5:

[0871] During lessons, the emotion engine analyzes the students' facial expressions and voices in real time. The device uses a camera and microphone to collect the students' facial expressions and voice data and sends it to the server. The server uses the emotion engine to analyze the received data and identify the students' emotions. For example, it can identify whether a student is confused or having fun.

[0872] Step 6:

[0873] The server dynamically adjusts the curriculum based on the analysis results: for example, if a child is confused, the AI ​​instructor will provide additional explanation, or if a child is bored, they will be offered more interactive activities.

[0874] Step 7:

[0875] During the lesson, the AI ​​instructor will suggest appropriate breaks or playtime. When the user (child) presses the "Break" button, relaxing activities will be displayed. For example, simple exercises or mini-games will be suggested.

[0876] Step 8:

[0877] When the user (student) presses the "End Lesson" button, the server records the progress of the lesson, the student's reactions, and the results of emotion analysis. The server stores this information in a database.

[0878] Step 9:

[0879] The server summarizes the highlights of the lesson, the students' reactions, and the results of emotional analysis, and sends them to the parents' devices. For example, it reports which parts of today's lesson the student found difficult, which parts they found interesting, etc.

[0880] Step 10:

[0881] The server also connects with the student's school's system and sends information for attendance certification. Once attendance confirmation is complete, the server notifies the parents of the results. For example, the server can automatically connect to the school's attendance management system and certify the student's attendance.

[0882] Example 2

[0883] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0884] Conventional learning support systems have the problem that they are not sufficient to function as a substitute for after-school care at home or free schools. Specifically, they do not adequately provide the automatic generation of individually optimized learning curricula, dynamic instruction according to the child's emotions, or effective progress monitoring and reporting, making it difficult to improve children's learning environments.

[0885] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0886] In this invention, the server includes a means for inputting basic information about the child, a generation AI means for generating an educational plan based on the child's basic information, an AI teaching means for conducting lessons based on the generated educational plan, an emotion engine means for recognizing and analyzing the child's emotions, a means for analyzing the progress of the lesson and the child's reactions, a means for notifying the analysis results, and a means for linking and sharing information with parents and educational institutions. This enables the generation of individually optimized learning curricula, flexible instruction according to the child's emotions, and effective monitoring and reporting of learning progress.

[0887] 1. "Basic information about the child" refers to basic information necessary for learning support, such as the child's name, age, and grade.

[0888] 2. An "educational plan" is a plan that includes specific learning content and schedules, created based on basic information about a child.

[0889] 3. "Generative AI means" refers to artificial intelligence technology that receives basic information about a child as input and automatically generates an optimal educational plan.

[0890] 4. "Artificial intelligence teaching means" refers to an interactive artificial intelligence that conducts lessons based on the generated teaching plan.

[0891] 5. "Emotion engine means" refers to technology for recognizing a child's facial expressions and voice and analyzing their emotional state.

[0892] 6. "Class progress" refers to the progress and progress of a class according to the educational plan.

[0893] 7. "Children's reactions" refers to the children's behavior, facial expressions, vocal responses, etc. during class.

[0894] 8. "Analysis results" refers to data obtained by analyzing the progress of lessons and students' responses.

[0895] 9. "Means of notification" refers to the methods and techniques used to communicate the results of the analysis to parents and educational institutions.

[0896] 10. "Means of information collaboration and sharing" refers to the technologies and methods for sharing analysis results with relevant parents and educational institutions.

[0897] MODE FOR CARRYING OUT THE INVENTION

[0898] This invention is a learning support system that serves as an alternative to after-school care or free schools within the home, and is composed of the following main components and technical elements:

[0899] System configuration

[0900] The system includes the following hardware and software components:

[0901] 1. Server:

[0902] Generative AI means: An artificial intelligence model that generates optimal educational plans based on basic information about children. Specifically, this applies to generative AI models that use machine learning algorithms or natural language processing.

[0903] Emotion engine means: Technology for analyzing a child's facial expressions and voice to recognize their emotional state. Specifically, this includes image recognition technology and voice analysis technology.

[0904] Database: A database for storing basic information about students, generated teaching plans, lesson progress, emotional data, etc.

[0905] 2. Terminal:

[0906] User interface: A device that parents and children use to operate the system. Specific examples include PCs, tablets, and smartphones. These devices interact with the system through web applications or native applications.

[0907] Sensors: Cameras and microphones to collect the child's facial expressions and voice.

[0908] 3. User:

[0909] Parent: Initial setup and monitoring of the system.

[0910] Children: Learning through the system.

[0911] Initial Setup and User Registration

[0912] The user opens the website or app on their device and enters their name, email address, and password on the "Create an account" screen. The server saves the entered information in a database and sends a confirmation email. The user clicks on the link in the confirmation email to activate the account. The user then enters the child's basic information (name, age, grade level), and selects an avatar, voice, and speaking style on the "AI teaching method" settings screen. The server saves the selected settings information in a database and reflects them in the generative AI model.

[0913] Generate a teaching plan

[0914] The server retrieves the child's basic information from the database and inputs it into the generation AI. The generation AI generates an optimal educational plan based on the child's information and stores it in the database. For example, for a 10-year-old child, a plan that incorporates a good balance of basic math, reading time, and exercise is generated.

[0915] Class progress

[0916] When a user (child) presses the "Start Lesson" button on their device, the server retrieves the educational plan and launches the lesson program in the "AI teaching tool." The AI ​​teaching tool conducts the lesson in an interactive format, with the emotion engine recognizing the child's facial expressions and voice to analyze their emotions. For example, in a math lesson, a question is posed and the child enters the answer, and the AI ​​teaching tool determines whether it is correct or incorrect and moves on to the next step. Based on the analysis results of the emotion engine, if the child is confused, additional explanations are provided.

[0917] Sentiment Analysis and Dynamic Adjustment

[0918] During lessons, the emotion engine recognizes and analyzes students' emotions in real time. The device collects students' facial expressions and voice data and sends it to the server. The server analyzes this data and dynamically adjusts the content of the educational plan and the way the lesson is conducted depending on the situation, such as whether the student is feeling stressed or having fun. For example, if the student is bored, it will provide more interesting topics and interactive activities.

[0919] Situation reporting and information sharing

[0920] When the lesson ends, the server records the progress of the lesson, the students' reactions, and the results of the emotion analysis performed by the emotion engine. The server analyzes this information and stores it in a database. The server then sends a summary to the parent's device. For example, it may report points in today's lesson that the student found difficult, parts that they showed particular interest in, or specific emotional changes. The server also shares information with the student's school, and automatically processes attendance certification.

[0921] Examples and prompts

[0922] For example, if a 10-year-old child uses this system, parents can create an account through the initial setup process and enter their child's information and preferences. The generating AI will then generate an optimized educational plan for their child covering math, reading, and exercise. When the child begins class, the AI ​​instructor will conduct the lesson in an interactive format, and the emotion engine will analyze the child's facial expressions and voice. For example, if a child is having difficulty with a math problem, the AI ​​instructor will provide detailed explanations and hints to help the child understand. After the class ends, parents will receive a detailed report on the child's learning progress and emotional changes, and the necessary information will be shared with the child's school.

[0923] Example prompts for generative AI models

[0924] "Generate a one-week learning curriculum for a 10-year-old child. Include a good balance of math, reading, and physical activity."

[0925] "Create new math problem sets and adjust the difficulty based on students' understanding."

[0926] "Please report on today's lesson trends based on the students' emotional data."

[0927] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0928] Step 1: User registration and initial setup

[0929] Input: The user enters their name, email address, and password on the device.

[0930] What it does: The server saves the information you entered in its database and sends you a confirmation email.

[0931] Output: A confirmation email is sent to the user.

[0932] What it does: A user opens a website or app on their device and enters their name, email address, and password on the "Create an account" screen. The server then stores the information in a database and sends a confirmation email.

[0933] Step 2: Activate your account

[0934] Input: User clicks on the link in the confirmation email.

[0935] Action: The server activates the account.

[0936] Output: The account is activated and available to the user.

[0937] What it does: The user clicks on the link in the confirmation email to complete the fast and secure account activation.

[0938] Step 3: Enter your child's information

[0939] Input: The user enters the child's basic information (name, age, grade).

[0940] How it works: The server saves the input information in a database.

[0941] Output: The child's basic information is obtained and the next operation is instructed.

[0942] Specific operation: The user enters basic information about the child into the system, and the server accurately stores it in the database.

[0943] Step 4: Setting up the AI ​​instructor

[0944] Input: The user selects the avatar, voice, and speaking style of the "AI instructor."

[0945] How it works: The server saves the selected configuration information in a database and reflects it in the generative AI model.

[0946] Output: The AI ​​instructor is configured and individual customization is enabled.

[0947] Specific operation: The user selects an avatar, voice, and speaking style, and this information is reflected in the generated AI model by the server and set in the system.

[0948] Step 5: Generate a teaching plan

[0949] Input: The server retrieves basic information about the child from the database.

[0950] How it works: Generative AI generates an educational plan based on the child's information.

[0951] Output: The generated teaching plan is stored in a database.

[0952] Specific operation: The server obtains basic information about the child and inputs it into the generation AI. The AI ​​generates an optimal educational plan, and the server stores the plan in a database.

[0953] Step 6: Start classes

[0954] Input: The user (student) presses the "Start lesson" button on the terminal.

[0955] Operation: The server obtains the teaching plan and starts the AI ​​instructor's lesson program.

[0956] Output: Lesson begins.

[0957] Specific operation: When the user (child) presses "Start lesson," the server retrieves the plan and the AI ​​instructor begins the lesson.

[0958] Step 7: Lesson Progression

[0959] Input: Facial expressions and voice data of students during class.

[0960] How it works: The emotion engine analyzes the child's emotions in real time and sends the results to the server.

[0961] Output: The progress of the lesson is dynamically adjusted based on the results of the sentiment analysis.

[0962] Specific operation: During the lesson, the device collects facial expressions and voice data, and the emotion engine analyzes the emotions and sends them to the server. The server then provides appropriate guidance and feedback based on the analysis results.

[0963] Step 8: Reporting and sharing information

[0964] Input: Lesson progress, student responses, and emotion analysis results.

[0965] How it works: The server records the progress of the lesson and the students' responses and saves them in a database.

[0966] Output: A notification is sent to the parent's device and the information is shared with the educational institution.

[0967] Specific operation: After the lesson ends, the server records the progress, students' reactions, and emotion analysis results, and saves them in a database. It then reports the situation to the parents' devices and automatically shares the information with the educational institution.

[0968] (Application example 2)

[0969] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0970] Conventional learning support systems have limitations in dynamically adjusting curriculum in response to children's emotions and reactions, and in providing learning experiences in virtual environments. Furthermore, many systems require parents to perform setup tasks at a high level, making it difficult to maintain children's interest. Furthermore, the lack of flexibility and interactivity in learning sessions in virtual environments is also a problem.

[0971] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for inputting basic information about the child, a generation AI means for generating a curriculum based on the child's basic information, an AI instructor means for conducting a lesson based on the generated curriculum, a means for analyzing the progress of the lesson and the child's responses, a means for notifying the child of the analysis results, a means for linking and sharing information with parents and the child's school, a means for recognizing and analyzing the child's emotions in real time using an emotion recognition engine and dynamically adjusting the lesson content, and a means for providing lessons and workshops in a virtual environment. This enables the provision of a flexible curriculum that corresponds to each child's individual emotions and learning progress, and a diverse learning experience in a virtual environment.

[0972] The "means for inputting basic information about a child" is a system component that has a function for inputting basic profile data such as a child's name, age, and grade.

[0973] "Generative AI means" refers to an artificial intelligence algorithm or system component that generates an optimal learning curriculum based on the basic information acquired about a child.

[0974] The "artificial intelligence instructor means" is an artificial intelligence-based educational system or software for conducting lessons based on the generated learning curriculum and educating children.

[0975] The "means for analyzing the progress of the lesson and the reactions of the students" is a system component for observing the behavior and reactions of the students during the lesson and analyzing the progress based on that.

[0976] The "means for notifying analysis results" is a system component that has the function of notifying parents and educators of the analysis results regarding the progress of the lesson and the students' reactions.

[0977] "Means for coordinating and sharing information with parents and the school" refers to a system component with communication functions for coordinating and sharing information regarding the progress of lessons, curriculum, and students' reactions with parents and the school.

[0978] An "emotion recognition engine" is an algorithm or system component that analyzes a child's facial expressions and voice data to recognize and analyze their emotional state in real time.

[0979] The "means for dynamically adjusting lesson content" is a system component that has the function of adjusting the lesson progress and curriculum in real time based on the emotional data collected by the emotion recognition engine.

[0980] "Means for providing classes and workshops in a virtual environment" refers to system components for providing classes and workshops in a virtual space using virtual reality (VR) and augmented reality (AR).

[0981] This invention is a learning support system for home or virtual environments, equipped with technology to provide flexible and effective education to children. The system uses a generative AI model to automatically generate a learning curriculum for children and an "artificial intelligence instructor" to conduct the lessons. It also uses an emotion recognition engine to analyze children's emotions in real time and dynamically adjust the lesson content.

[0982] System Overview

[0983] The system mainly consists of the following components:

[0984] 1. Server: Manages generative AI models, emotion recognition engines, and databases.

[0985] 2. Device: A device used by users (parents and children). Examples include PCs, tablets, smartphones, and head-mounted displays.

[0986] 3. Users: Parents and children. Parents configure and monitor the system, while children learn.

[0987] System Implementation

[0988] User Registration and Settings

[0989] The user (parent) accesses the registration form from their device and enters their name, email address, password, and child information (name, age, grade). The server stores this information in a database and sends a confirmation email. When the user clicks the link in the confirmation email, the account is activated. The parent then sets the avatar, voice, and speaking style of the "artificial intelligence instructor" according to their child's preferences. These settings are reflected in the generative AI model.

[0990] Curriculum Generation

[0991] The server retrieves basic information about the child from the database and inputs it into the generative AI model, which then generates a curriculum using, for example, the following prompt:

[0992] Generate a diverse and engaging curriculum for a 10 year old in grade 5. Curriculum should include subjects like math, reading, and physical activities.

[0993] The generated curriculum is stored in a database. For example, for a 10-year-old child, a curriculum that incorporates a balanced mix of math basics, reading time, and physical activity is generated.

[0994] Start and progress of lessons

[0995] When a user (child) presses the "Start Lesson" button on their device, the server retrieves the curriculum and launches the "AI Instructor." The AI ​​Instructor conducts the lesson in an interactive format, with an emotion recognition engine collecting and analyzing the child's facial expressions and voice in real time. For example, in a math class, a question is posed and the child enters the answer, and the AI ​​Instructor determines whether it is correct or incorrect and moves on to the next step. If the emotion recognition engine detects that the child is confused, it provides additional explanation.

[0996] Emotion Recognition Engine and Dynamic Adjustment

[0997] During lessons, an emotion recognition engine analyzes students' emotions in real time and sends the results to the server. For example, if a student is bored, the system will introduce more interactive activities. If a student is having trouble understanding, the system will provide detailed explanations or hints.

[0998] Reporting and collaboration

[0999] After the lesson is over, the server records the progress of the lesson, the students' reactions, and the results of emotional analysis. The server analyzes this information and notifies parents and the student's school. For example, it reports if a student had difficulty with a particular task or if a part of the lesson showed particular interest. This allows parents and educators to understand the student's learning progress.

[1000] This system allows children to enjoy a personalized learning experience and allows parents and educators to effectively support their children's learning progress.

[1001] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1002] Step 1: User registration and initial setup

[1003] The user (guardian) accesses the registration form from their device and enters their name, email address, password, and child information (name, age, grade). This input data is sent to the server and stored in a database. The server generates a confirmation email and sends it to the entered email address. When the user clicks the link in the confirmation email, the account is activated. Next, the user (guardian) sets the avatar, voice, and speaking style of the "artificial intelligence instructor" according to their child's preferences. This setting information is also sent to the server and reflected in the generated AI model.

[1004] Step 2: Curriculum generation

[1005] The server retrieves basic information about the child (age, grade, etc.) from the database and inputs this information into the generative AI model. For example, the server sends the following prompt to the generative AI model to generate the optimal curriculum.

[1006] Generate a diverse and engaging curriculum for a 10 year old in grade 5. Curriculum should include subjects like math, reading, and physical activities.

[1007] The generative AI model generates a curriculum based on the input information, and the server receives the generated curriculum and stores it in a database. For example, a curriculum that balances basic math, reading time, and exercise for a 10-year-old child would be generated.

[1008] Step 3: Start classes

[1009] When the user (child) presses the "Start Lesson" button on their device, the server retrieves a pre-generated curriculum from the database and launches the "AI instructor" lesson program. The AI ​​instructor begins the lesson based on the retrieved curriculum and provides the child with learning content in an interactive format. The device collects the child's facial expressions and voice data in real time and sends it to the server.

[1010] Step 4: Emotion recognition and dynamic regulation

[1011] The server inputs facial expressions and voice data sent from the device into an emotion recognition engine to analyze the child's emotions in real time. For example, if the emotion recognition engine detects a child's confusion or boredom, the server generates appropriate feedback and additional explanations and provides them to the child through an AI instructor. This allows the child to continue learning with appropriate support.

[1012] Step 5: Learning Records and Notifications

[1013] After the lesson is over, the server records the progress of the lesson, the students' reactions, and the results of emotional analysis. This information is stored in a database as a profile and used for future learning. The server also generates a report summarizing the lesson and highlighting key points, which is sent to parents and the student's school to share the student's learning status. For example, it reports if a student had difficulty with a particular problem or if a topic of particular interest occurred.

[1014] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1015] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1016] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1017] [Fourth embodiment]

[1018] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1019] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1020] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1021] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1022] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1023] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1024] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1025] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1026] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1027] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1028] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1029] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1030] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1031] This invention is a learning support system for children, which can be used as an alternative to after-school care or free schools at home. This system uses generative AI to automatically generate learning curricula for children, and has "AI instructors" conduct the lessons.

[1032] System Overview

[1033] The system mainly consists of the following components:

[1034] 1. Server: Generates AI and manages the database.

[1035] 2. Device: A device operated by a user (parent or child). Examples include PCs, tablets, and smartphones.

[1036] 3. Users: Parents and children. Parents configure and monitor the system, while children learn.

[1037] System Implementation

[1038] 1. User registration and initial settings

[1039] The user opens the website or app on their device and enters their name, email address, and password on the "Create an Account" screen. The server saves the entered information in a database and sends a confirmation email. The user clicks on the link in the confirmation email to activate the account. The user then enters the child's basic information (name, age, grade level), and selects an avatar, voice, and speaking style on the "AI Instructor" settings screen. The server receives the selected settings information and reflects it in the generative AI model.

[1040] 2. Curriculum Generation

[1041] The server retrieves the child's basic information from the database and inputs it into the generation AI. The generation AI generates an optimal learning curriculum based on the child's information and stores it in the database. For example, for a 10-year-old child, a curriculum that incorporates a balanced mix of basic math, reading time, and exercise would be generated.

[1042] 3. Classes begin

[1043] When the user (child) presses the "Start Lesson" button on their device, the server retrieves the curriculum and launches the "AI Instructor" lesson program. The AI ​​Instructor conducts the lesson in an interactive format, monitoring the children's answers and reactions. For example, in a math class, the AI ​​Instructor poses a question and when the child enters the answer, the AI ​​Instructor determines whether it is correct or incorrect and moves on to the next step. The AI ​​Instructor also suggests appropriate breaks and playtimes to maintain the children's concentration.

[1044] 4. Status reporting and collaboration

[1045] When the lesson ends, the server analyzes the progress of the lesson and the student's reactions, summarizing the results and notifying parents. The information is also shared with the student's school, which automatically processes attendance certification. For example, the server can report on the areas in which the student struggled in today's lesson and the activities in which the student showed particular interest, allowing parents to understand their child's learning status.

[1046] Specific examples

[1047] For example, if a 10-year-old child uses this system, their parents will create an account through the initial setup process and enter their child's information and preferences. The AI ​​will then generate a curriculum optimized for their child, covering math, reading, and physical education. When the child begins class, an "AI instructor" will conduct the lesson interactively while the child works on the assignments. After the class ends, parents will receive a summary of the child's learning progress and responses, and attendance information will be shared with the school.

[1048] In this way, the system of the present invention provides flexible and effective after-school care and free school functions at home, improving children's learning environment.

[1049] The processing flow will be explained below.

[1050] Step 1:

[1051] The user opens a website or app on their device and enters their name, email address, and password on the "Create an account" screen. The server stores the information in a database and sends a confirmation email. The user clicks on a link in the email to activate their account.

[1052] Step 2:

[1053] The user logs in and enters the child's basic information (name, age, grade). Next, they select the avatar, voice, and speaking style in the "AI instructor" settings. For example, they can choose an anime-style avatar, a gentle voice, and a slow speaking style. The server saves the selected settings in a database and reflects them in the generative AI model.

[1054] Step 3:

[1055] The server retrieves the child's basic information from the database and inputs it into the generation AI. The generation AI generates the optimal learning curriculum based on the child's information. For example, for a 10-year-old child, a curriculum that incorporates a good balance of basic math, reading time, and exercise is generated. The generated curriculum is saved in the database.

[1056] Step 4:

[1057] The user (child) presses the "Start Lesson" button on the device. The server retrieves the curriculum and launches the "AI Instructor" lesson program. The AI ​​Instructor conducts the lesson in an interactive format. For example, in a math class, a question is posed and the child enters the answer, and the AI ​​Instructor determines whether it is correct or incorrect and moves on to the next step.

[1058] Step 5:

[1059] An AI instructor assesses students' understanding and responses in real time during lessons. The device collects the students' responses and sends them to a server. The server analyzes them and dynamically adjusts the curriculum content as needed. For example, if a student struggles with a particular math problem, the AI ​​instructor can provide additional explanation.

[1060] Step 6:

[1061] During the lesson, the AI ​​instructor will suggest appropriate breaks or playtime. When the user (child) presses the "Break" button, relaxing activities will be displayed. For example, simple exercises or mini-games will be suggested.

[1062] Step 7:

[1063] When the user (student) presses the "End Lesson" button, the server records the progress of the lesson and the student's responses. The server analyzes this information and stores it in a database.

[1064] Step 8:

[1065] The server summarizes the highlights of the lesson and the students' reactions, and sends this information to the parents' devices. For example, it can report points that were difficult to understand in today's lesson or parts that the students found particularly interesting.

[1066] Step 9:

[1067] The server connects to the student's school's system and sends information for attendance certification. Once attendance confirmation is complete, the server notifies the parent or guardian of the results. For example, the server can automatically connect to the school's attendance management system and certify the student's attendance.

[1068] Example 1

[1069] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1070] Current home learning support systems lack the means to effectively provide an optimized learning curriculum for each child, while also being able to monitor the progress and reactions of the children in real time. Furthermore, there is insufficient collaboration with parents and schools, making it difficult to effectively share learning outcomes.

[1071] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1072] In this invention, the server includes a means for inputting basic information about each child, an AI generation means for generating a curriculum based on the child's basic information, an AI instructor means for conducting a lesson based on the generated curriculum, a means for starting a lesson program when a lesson start button is pressed, a means for analyzing the progress of the lesson and the child's responses, and a means for summarizing the analysis results and notifying the parents and the child's school of the information. This makes it possible to provide a learning curriculum optimized for each child, realize real-time understanding of learning progress, and effectively share information.

[1073] "Children" refers primarily to school-age children in the primary school education stage.

[1074] "Basic information" refers to the child's name, age, grade, and other personal attribute information related to learning.

[1075] "Generative AI" refers to an artificial intelligence model that automatically generates a curriculum based on input information.

[1076] "Curriculum" refers to an educational plan that systematically and systematically arranges children's learning activities.

[1077] An "AI instructor" refers to a virtual instructor who conducts lessons based on a curriculum generated by generative AI.

[1078] "Class progress" refers to the implementation process for carrying out educational activities as planned.

[1079] "Class program" refers to the specific learning content and activities implemented in each class based on the curriculum.

[1080] The "lesson start button" refers to the operation section on the user interface for starting the lesson program.

[1081] "Progress" refers to the status of whether the lesson is proceeding as planned.

[1082] "Children's reactions" refers to the level of understanding, interest, and participation shown by children during class.

[1083] "Analysis" refers to the act of processing data to evaluate the progress of the lesson and the students' responses.

[1084] "Summary" refers to a brief report that summarizes information about the lesson's progress and the students' responses.

[1085] "Guardian" refers to a parent or guardian whose role is to support and supervise a child's learning activities.

[1086] "School of enrolment" refers to the educational institution in which a child is officially registered.

[1087] "Notification" refers to the means of communication used to inform parents and the student's school of the analysis results.

[1088] This invention is a learning support system for children, which can be used as an alternative to after-school care or free schools at home. This system uses generative AI to automatically generate learning curricula for children, and has "AI instructors" conduct the lessons.

[1089] System configuration

[1090] The system mainly consists of the following components:

[1091] 1. Server: Generates AI and manages the database.

[1092] 2. Device: A device operated by a user (parent or child). Examples include PCs, tablets, and smartphones.

[1093] 3. Users: Parents and children. Parents configure and monitor the system, while children learn.

[1094] User registration and initial settings

[1095] A user opens a website or app on their device and enters their name, email address, and password on the "Create an account" screen. The server then receives this information and stores it in a database. It then automatically generates a confirmation email and sends it to the email address provided. When the user clicks on the link in the confirmation email, the server receives the link and activates the account.

[1096] The user then logs in and enters the child's basic information (name, age, grade). Next, the user customizes the AI ​​instructor's avatar, voice, speaking style, etc. This setting information is received by the server and reflected in the generative AI model. At this time, the settings are generated using an image generation API and a voice synthesis API.

[1097] Curriculum Generation

[1098] The server retrieves basic information about the child from a database, including age, grade, preferences, and interests. The server then inputs this information into a generative AI model (e.g., GPT-4). The specific prompt is as follows:

[1099] "Generate a curriculum that will engage and effectively teach a 10-year-old child. The child's name is Taro, and the curriculum should include a good balance of math, reading, and physical activity."

[1100] The generative AI model generates an optimal curriculum based on the input information. For example, a curriculum such as "Monday: 9:00-10:00 Math, 10:00-11:00 Reading, 11:00-12:00 Exercise..." is generated. The generated curriculum is stored in a database on the server.

[1101] Classes begin

[1102] When a user (child) logs in on their device and presses the "Start Lesson" button, the server retrieves the current curriculum and launches the "AI Instructor" lesson program. The AI ​​Instructor conducts the lesson in an interactive format, monitoring the children's answers and reactions. For example, in a math class, the AI ​​Instructor poses questions, and when the children enter their answers, the AI ​​evaluates them and provides feedback. Appropriate breaks and playtime are also suggested to ensure that the children's concentration is maintained.

[1103] Status reporting and collaboration

[1104] When the lesson ends, the server analyzes the progress of the lesson and the students' responses, summarizes the results, and notifies parents. The server also connects to the configured school system to automatically report attendance and learning content. Specifically, the server records the progress of the lesson and the students' responses as a log, analyzes the log, and generates a summary in natural language. This summary is sent to parents via email or in-app notification, and the information is automatically shared with the school.

[1105] Specific operation example

[1106] For example, if a 10-year-old boy named Taro were to use this system, his parents would create an account with the initial settings and enter Taro's name, age, grade, and interests. The generation AI would then generate an optimized curriculum for Taro (math, reading, exercise, etc.) and store it in a database. When Taro presses the "Start Lesson" button, the "AI Instructor" will conduct the lesson in an interactive format, and Taro will work on the assignment. For example, in a math problem, if Taro answers "12" to the question "What is 5 + 7?", the "AI Instructor" will respond with "That's correct!" After the lesson, parents will be notified of a summary of Taro's learning progress and responses, and attendance information will be shared with the school.

[1107] In this way, the system of the present invention provides flexible and effective after-school care and free school functions at home, improving children's learning environment.

[1108] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1109] Step 1:

[1110] The user opens a website or app on their device and enters their name, email address, and password on the "Create an account" screen. The server receives this information and stores it in a database. The server then automatically generates a confirmation email and sends it to the email address entered. When the user clicks the link in the confirmation email, the server receives the link and activates the account. (Input: Name, email address, password / Output: Sending confirmation email and activating the account)

[1111] Step 2:

[1112] The user logs in and enters the child's basic information (name, age, grade). Next, the user customizes the AI ​​instructor's avatar, voice, speaking style, etc. The server receives this configuration information and reflects it in the generated AI model. Specifically, the customization content is generated using an image generation API and a voice synthesis API. (Input: basic information, avatar settings / Output: reflection of the generated AI model)

[1113] Step 3:

[1114] The server retrieves basic information about the child from a database. This information includes age, grade, preferences, and interests. The server inputs this information into a generative AI model to generate a curriculum. For example, the following prompt might be used: "Please generate a curriculum that will interest a 10-year-old child and help him learn effectively. The child's name is Taro, and the curriculum should include a good balance of math, reading, and exercise." (Input: Basic information / Output: Curriculum generation)

[1115] Step 4:

[1116] The generative AI model generates a curriculum based on the prompt. The generated curriculum is stored in a database on the server. For example, it might look like this: "Monday: 9:00-10:00 Math, 10:00-11:00 Reading, 11:00-12:00 Exercise..." (Input: Prompt / Output: Curriculum)

[1117] Step 5:

[1118] The user (child) logs in to the device and presses the "Start Lesson" button. The server retrieves the current curriculum and launches the "AI Instructor" lesson program. (Input: Pressing the "Start Lesson" button / Output: Launching the lesson program)

[1119] Step 6:

[1120] The AI ​​instructor conducts the lesson in an interactive format, monitoring the students' answers and reactions. For example, in a math class, the AI ​​instructor poses a question, and the students input their answers, which the AI ​​evaluates and provides feedback. It also suggests breaks and playtimes as appropriate. (Input: Student's answers / Output: Feedback, break suggestions)

[1121] Step 7:

[1122] The server records the progress of the lesson and the students' reactions as logs. After the lesson ends, the server analyzes the logs and generates a summary of the progress and reactions. The summary is sent to parents via email or in-app notification. (Input: Log data / Output: Summary report)

[1123] Step 8:

[1124] The server connects to the configured school system and automatically reports attendance and learning content. Specifically, today's lesson content and attendance status are sent to the school, and the student's attendance is certified. (Input: lesson content, attendance status / Output: report to school and certification)

[1125] In this way, the information entered at each step is processed appropriately, providing children with an optimized learning curriculum and enabling real-time understanding of learning progress and information sharing.

[1126] (Application example 1)

[1127] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1128] Conventional learning support systems have problems such as insufficient curriculum generation based on individual student needs, insufficient real-time status reporting, and insufficient collaboration. Furthermore, delays in sharing information with parents and the institution where the student is enrolled make it difficult to properly grasp the student's learning effectiveness and progress. The present invention aims to solve these problems and provide an optimal learning experience for students.

[1129] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1130] In this invention, the server includes means for inputting basic information about the child, generation AI means for generating a curriculum based on the child's basic information, AI instructor means for conducting lessons based on the generated curriculum, means for analyzing the progress of the lesson and the child's responses, means for notifying the analysis results, means for linking and sharing information with parents and the institution where the child is enrolled, and means for delivering content based on the generated curriculum. This enables the automatic generation and progress of a curriculum suited to the child, status reporting and linking, and makes it easier for parents and educational institutions to grasp the child's learning situation in real time.

[1131] "Means for inputting basic information about children" refers to devices or software for inputting basic information about children, such as their age, grade, and interests.

[1132] "Generative AI means" refers to an artificial intelligence processing device or software that automatically generates an optimal learning curriculum based on basic information about the child that is input.

[1133] The "AI instructor means" is an artificial intelligence processing device or software that conducts lessons in an interactive format according to the generated curriculum and provides educational guidance to children.

[1134] "Means for analyzing the progress of lessons and students' responses" refers to devices or software that monitor students' responses and progress during lessons in real time and analyze that information.

[1135] The "means for notifying the analysis results" refers to a device or software for notifying parents or the institution where the student is enrolled of the results of the analysis conducted during the lesson.

[1136] "Means for coordinating and sharing information with parents and the institution where the child is enrolled" refers to a device or software for coordinating and sharing the results of analysis of a child's learning progress and lessons with parents and the institution where the child is enrolled.

[1137] A "means for delivering content based on a generated curriculum" is a device or software that delivers appropriate learning content based on a curriculum generated by generative AI.

[1138] This invention is a learning support system for children, which serves as an alternative to after-school care or free schools at home. This system uses generative AI to automatically generate learning curricula for children, and has "AI instructors" conduct lessons. The system configuration and implementation method are explained below.

[1139] System configuration

[1140] The system mainly consists of the following components:

[1141] 1. Server: Generates AI and manages the database.

[1142] 2. Device: A device operated by a user (parent or child). Examples include PCs, tablets, and smartphones.

[1143] 3. Users: Parents and children. Parents configure and monitor the system, while children learn.

[1144] Initial Setup and User Registration

[1145] When a user opens the website or app on their device and enters their name, email address, and password on the "Create an Account" screen, the server saves the information in a database and sends a confirmation email. The user clicks on the link in the confirmation email to activate the account. The user then enters their child's basic information (name, age, grade), and selects an avatar, voice, and speaking style on the "AI Instructor" settings screen. The server then receives the selected settings information and reflects them in the generative AI model.

[1146] Curriculum Generation

[1147] The server retrieves basic information about the child from the database and inputs it into the generation AI. The generation AI generates an optimal study curriculum based on the child's information and stores it in the database. For example, for a 10-year-old child, a curriculum is generated that incorporates a balanced mix of science, painting, basic mathematics, reading time, and exercise. An example prompt sentence is "Generate a study curriculum for a 10-year-old in grade 4 with interest in science and painting."

[1148] Classes begin

[1149] When the user (child) presses the "Start Lesson" button on their device, the server retrieves the curriculum and launches the "AI Instructor" lesson program. The AI ​​Instructor conducts the lesson in an interactive format, monitoring the children's answers and reactions. For example, in a science class, the AI ​​Instructor poses a question and when the child enters the answer, the AI ​​Instructor determines whether it is correct or incorrect and moves on to the next step. It also suggests appropriate breaks and playtimes to maintain the children's concentration.

[1150] Exams and Assessments

[1151] The server monitors the student's learning progress in real time and evaluates them at certain stages. The evaluation results are stored in a database and notified to parents and the student's institution. For example, the server can report the areas in which the student struggled in today's lesson or the activities in which the student showed particular interest, allowing parents to understand their child's learning status.

[1152] Content Delivery

[1153] The server distributes appropriate learning content based on the curriculum generated by the generative AI. The content is distributed to devices such as smartphones, smart glasses, and head-mounted displays, allowing children to use these devices to advance their studies.

[1154] In this way, the system of the present invention provides flexible and effective after-school care and free school functions at home, improving children's learning environment.

[1155] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1156] Step 1:

[1157] The server provides an interface for users to input basic information about their children (name, age, grade) on their terminals. Users input basic information through this interface, and the data is stored in a database. The input is the basic information of the children, and the output is a data structure that stores the basic information in the database.

[1158] Step 2:

[1159] The server retrieves basic information about the child from the database and inputs it as a prompt to the generative AI model. The basic information retrieved from the database serves as input, and the generative AI model automatically generates a curriculum. An example of a prompt is "Generate a study curriculum for a 10-year-old in grade 4 with interest in science and painting." The generated curriculum is then saved in the database as output.

[1160] Step 3:

[1161] When the user (child) presses the "Start Lesson" button on the device, the server retrieves the generated curriculum from the database and launches the "AI Instructor" lesson program. Curriculum information is acquired as input, and instructions for the AI ​​instructor to conduct the lesson are received as output.

[1162] Step 4:

[1163] The AI ​​instructor conducts interactive lessons with students via their terminals. The server asks questions to students based on instructions from the AI ​​instructor, and the students input their answers. The input is the student's answer, and the output is the AI ​​instructor providing the next question and explanation.

[1164] Step 5:

[1165] The server monitors the progress of lessons and students' responses in real time and collects data. The input is the data collected in real time, and the output is the analysis results. This allows students' learning progress to be understood.

[1166] Step 6:

[1167] The server dynamically adjusts the curriculum based on the collected data and analysis results. Collected data is the input, and an adjusted curriculum is generated as the output. This provides the optimal learning environment for students.

[1168] Step 7:

[1169] The server notifies the parents and the institution using a means for notifying the analysis results. The analysis results are input, and the notification content is sent to the parents and the institution as output.

[1170] Step 8:

[1171] The server distributes appropriate learning content to the device based on the generated curriculum. The generated curriculum is the input, and the learning content is distributed to the device as the output. Students can use this to work on their individual learning content.

[1172] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1173] This invention is a learning support system that can replace after-school care or free schooling at home, automatically generating a child's learning curriculum using generative AI and having an "AI instructor" conduct the lessons. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it has the ability to dynamically adjust the curriculum and teaching methods based on the child's reactions.

[1174] System Overview

[1175] The system mainly consists of the following components:

[1176] 1. Server: Performs generative AI, emotion engine, and database management.

[1177] 2. Device: A device operated by a user (parent or child). Examples include PCs, tablets, and smartphones.

[1178] 3. Users: Parents and children. Parents configure and monitor the system, while children learn.

[1179] System Implementation

[1180] 1. User registration and initial settings

[1181] The user opens the website or app on their device and enters their name, email address, and password on the "Create an Account" screen. The server saves the entered information in a database and sends a confirmation email. The user clicks on the link in the confirmation email to activate the account. The user then enters the child's basic information (name, age, grade) and selects an avatar, voice, and speaking style on the "AI Instructor" settings screen. The server saves the selected settings information in a database and reflects them in the generative AI model.

[1182] 2. Curriculum Generation

[1183] The server retrieves the child's basic information from the database and inputs it into the generation AI. The generation AI generates an optimal learning curriculum based on the child's information and stores it in the database. For example, for a 10-year-old child, a curriculum that incorporates a balanced mix of basic math, reading time, and exercise would be generated.

[1184] 3. Classes begin

[1185] When the user (child) presses the "Start Lesson" button on their device, the server retrieves the curriculum and launches the "AI Instructor" lesson program. The AI ​​instructor conducts the lesson in an interactive format, with the emotion engine recognizing the child's facial expressions and voice to analyze their emotions. For example, in a math class, a question is posed and the child enters the answer, and the AI ​​instructor determines whether it is correct or incorrect and moves on to the next step. Based on the results of the emotion engine's analysis, if the child is confused, additional explanations are provided.

[1186] 4. Functions of the Emotion Engine

[1187] During lessons, the emotion engine recognizes and analyzes students' emotions in real time. The device collects students' facial expressions and voice data and sends it to a server. The server analyzes this data and dynamically adjusts the curriculum content and lesson progress depending on the situation, such as whether the student is feeling stressed or having fun. For example, if a student is bored, it will provide more interesting topics and interactive activities.

[1188] 5. Status reporting and collaboration

[1189] When the lesson ends, the server records the progress of the lesson, the students' reactions, and the results of the emotion analysis performed by the emotion engine. The server analyzes this information and stores it in a database. The server then sends a summary to the parent's device. For example, it may report points in today's lesson that the student found difficult, parts that they showed particular interest in, or specific emotional changes. The server also shares information with the student's school, and automatically processes attendance certification.

[1190] Specific examples

[1191] For example, if a 10-year-old child uses this system, parents create an account through the initial setup process and enter their child's information and preferences. The generating AI then generates an optimized curriculum for math, reading, and physical education for the child. When the child begins class, an "AI instructor" conducts the lesson in an interactive format, and an emotion engine analyzes the child's facial expressions and voice. For example, if a child is having difficulty with a math problem, the AI ​​instructor will provide detailed explanations and hints to help the child understand. After the class ends, parents are notified of a detailed report of the child's learning progress and emotional changes, and the necessary information is shared with the child's school.

[1192] In this way, the system of the present invention provides flexible and effective after-school care and free school functions at home, improving children's learning environments. By combining it with an emotion engine, dynamic instruction can be provided according to the child's emotions, providing a more individually optimized learning experience.

[1193] The processing flow will be explained below.

[1194] Step 1:

[1195] A user opens a website or app on their device and enters their name, email address, and password on the "Create an account" screen. The server stores the information in a database and sends a confirmation email. The user clicks on a link in the confirmation email to activate their account.

[1196] Step 2:

[1197] The user logs in and enters the child's basic information (name, age, grade). Next, they select the avatar, voice, and speaking style in the "AI instructor" settings. For example, they can choose an anime-style avatar, a gentle voice, and a slow speaking style. The server saves the selected settings in a database and reflects them in the generative AI model.

[1198] Step 3:

[1199] The server retrieves the child's basic information from the database and inputs it into the generation AI. The generation AI generates the optimal learning curriculum based on the child's information. For example, for a 10-year-old child, a curriculum that incorporates a good balance of basic math, reading time, and exercise is generated. The generated curriculum is saved in the database.

[1200] Step 4:

[1201] The user (child) presses the "Start Lesson" button on the device. The server retrieves the curriculum and launches the "AI Instructor" lesson program. The AI ​​Instructor conducts the lesson in an interactive format. For example, in a math class, a question is posed and the child enters the answer, and the AI ​​Instructor determines whether it is correct or incorrect and moves on to the next step.

[1202] Step 5:

[1203] During lessons, the emotion engine analyzes the students' facial expressions and voices in real time. The device uses a camera and microphone to collect the students' facial expressions and voice data and sends it to the server. The server uses the emotion engine to analyze the received data and identify the students' emotions. For example, it can identify whether a student is confused or having fun.

[1204] Step 6:

[1205] The server dynamically adjusts the curriculum based on the analysis results: for example, if a child is confused, the AI ​​instructor will provide additional explanation, or if a child is bored, they will be offered more interactive activities.

[1206] Step 7:

[1207] During the lesson, the AI ​​instructor will suggest appropriate breaks or playtime. When the user (child) presses the "Break" button, relaxing activities will be displayed. For example, simple exercises or mini-games will be suggested.

[1208] Step 8:

[1209] When the user (student) presses the "End Lesson" button, the server records the progress of the lesson, the student's reactions, and the results of emotion analysis. The server stores this information in a database.

[1210] Step 9:

[1211] The server summarizes the highlights of the lesson, the students' reactions, and the results of emotional analysis, and sends them to the parents' devices. For example, it reports which parts of today's lesson the student found difficult, which parts they found interesting, etc.

[1212] Step 10:

[1213] The server also connects with the student's school's system and sends information for attendance certification. Once attendance confirmation is complete, the server notifies the parents of the results. For example, the server can automatically connect to the school's attendance management system and certify the student's attendance.

[1214] Example 2

[1215] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1216] Conventional learning support systems have the problem that they are not sufficient to function as a substitute for after-school care at home or free schools. Specifically, they do not adequately provide the automatic generation of individually optimized learning curricula, dynamic instruction according to the child's emotions, or effective progress monitoring and reporting, making it difficult to improve children's learning environments.

[1217] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1218] In this invention, the server includes a means for inputting basic information about the child, a generation AI means for generating an educational plan based on the child's basic information, an AI teaching means for conducting lessons based on the generated educational plan, an emotion engine means for recognizing and analyzing the child's emotions, a means for analyzing the progress of the lesson and the child's reactions, a means for notifying the analysis results, and a means for linking and sharing information with parents and educational institutions. This enables the generation of individually optimized learning curricula, flexible instruction according to the child's emotions, and effective monitoring and reporting of learning progress.

[1219] 1. "Basic information about the child" refers to basic information necessary for learning support, such as the child's name, age, and grade.

[1220] 2. An "educational plan" is a plan that includes specific learning content and schedules, created based on basic information about a child.

[1221] 3. "Generative AI means" refers to artificial intelligence technology that receives basic information about a child as input and automatically generates an optimal educational plan.

[1222] 4. "Artificial intelligence teaching means" refers to an interactive artificial intelligence that conducts lessons based on the generated teaching plan.

[1223] 5. "Emotion engine means" refers to technology for recognizing a child's facial expressions and voice and analyzing their emotional state.

[1224] 6. "Class progress" refers to the progress and progress of a class according to the educational plan.

[1225] 7. "Children's reactions" refers to the children's behavior, facial expressions, vocal responses, etc. during class.

[1226] 8. "Analysis results" refers to data obtained by analyzing the progress of lessons and students' responses.

[1227] 9. "Means of notification" refers to the methods and techniques used to communicate the results of the analysis to parents and educational institutions.

[1228] 10. "Means of information collaboration and sharing" refers to the technologies and methods for sharing analysis results with relevant parents and educational institutions.

[1229] MODE FOR CARRYING OUT THE INVENTION

[1230] This invention is a learning support system that serves as an alternative to after-school care or free schools within the home, and is composed of the following main components and technical elements:

[1231] System configuration

[1232] The system includes the following hardware and software components:

[1233] 1. Server:

[1234] Generative AI means: An artificial intelligence model that generates optimal educational plans based on basic information about children. Specifically, this applies to generative AI models that use machine learning algorithms or natural language processing.

[1235] Emotion engine means: Technology for analyzing a child's facial expressions and voice to recognize their emotional state. Specifically, this includes image recognition technology and voice analysis technology.

[1236] Database: A database for storing basic information about students, generated teaching plans, lesson progress, emotional data, etc.

[1237] 2. Terminal:

[1238] User interface: A device that parents and children use to operate the system. Specific examples include PCs, tablets, and smartphones. These devices interact with the system through web applications or native applications.

[1239] Sensors: Cameras and microphones to collect the child's facial expressions and voice.

[1240] 3. User:

[1241] Parent: Initial setup and monitoring of the system.

[1242] Children: Learning through the system.

[1243] Initial Setup and User Registration

[1244] The user opens the website or app on their device and enters their name, email address, and password on the "Create an account" screen. The server saves the entered information in a database and sends a confirmation email. The user clicks on the link in the confirmation email to activate the account. The user then enters the child's basic information (name, age, grade level), and selects an avatar, voice, and speaking style on the "AI teaching method" settings screen. The server saves the selected settings information in a database and reflects them in the generative AI model.

[1245] Generate a teaching plan

[1246] The server retrieves the child's basic information from the database and inputs it into the generation AI. The generation AI generates an optimal educational plan based on the child's information and stores it in the database. For example, for a 10-year-old child, a plan that incorporates a good balance of basic math, reading time, and exercise is generated.

[1247] Class progress

[1248] When a user (child) presses the "Start Lesson" button on their device, the server retrieves the educational plan and launches the lesson program in the "AI teaching tool." The AI ​​teaching tool conducts the lesson in an interactive format, with the emotion engine recognizing the child's facial expressions and voice to analyze their emotions. For example, in a math lesson, a question is posed and the child enters the answer, and the AI ​​teaching tool determines whether it is correct or incorrect and moves on to the next step. Based on the analysis results of the emotion engine, if the child is confused, additional explanations are provided.

[1249] Sentiment Analysis and Dynamic Adjustment

[1250] During lessons, the emotion engine recognizes and analyzes students' emotions in real time. The device collects students' facial expressions and voice data and sends it to the server. The server analyzes this data and dynamically adjusts the content of the educational plan and the way the lesson is conducted depending on the situation, such as whether the student is feeling stressed or having fun. For example, if the student is bored, it will provide more interesting topics and interactive activities.

[1251] Situation reporting and information sharing

[1252] When the lesson ends, the server records the progress of the lesson, the students' reactions, and the results of the emotion analysis performed by the emotion engine. The server analyzes this information and stores it in a database. The server then sends a summary to the parent's device. For example, it may report points in today's lesson that the student found difficult, parts that they showed particular interest in, or specific emotional changes. The server also shares information with the student's school, and automatically processes attendance certification.

[1253] Examples and prompts

[1254] For example, if a 10-year-old child uses this system, parents can create an account through the initial setup process and enter their child's information and preferences. The generating AI will then generate an optimized educational plan for their child covering math, reading, and exercise. When the child begins class, the AI ​​instructor will conduct the lesson in an interactive format, and the emotion engine will analyze the child's facial expressions and voice. For example, if a child is having difficulty with a math problem, the AI ​​instructor will provide detailed explanations and hints to help the child understand. After the class ends, parents will receive a detailed report on the child's learning progress and emotional changes, and the necessary information will be shared with the child's school.

[1255] Example prompts for generative AI models

[1256] "Generate a one-week learning curriculum for a 10-year-old child. Include a good balance of math, reading, and physical activity."

[1257] "Create new math problem sets and adjust the difficulty based on students' understanding."

[1258] "Please report on today's lesson trends based on the students' emotional data."

[1259] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1260] Step 1: User registration and initial setup

[1261] Input: The user enters their name, email address, and password on the device.

[1262] What it does: The server saves the information you entered in its database and sends you a confirmation email.

[1263] Output: A confirmation email is sent to the user.

[1264] What it does: A user opens a website or app on their device and enters their name, email address, and password on the "Create an account" screen. The server then stores the information in a database and sends a confirmation email.

[1265] Step 2: Activate your account

[1266] Input: User clicks on the link in the confirmation email.

[1267] Action: The server activates the account.

[1268] Output: The account is activated and available to the user.

[1269] What it does: The user clicks on the link in the confirmation email to complete the fast and secure account activation.

[1270] Step 3: Enter your child's information

[1271] Input: The user enters the child's basic information (name, age, grade).

[1272] How it works: The server saves the input information in a database.

[1273] Output: The child's basic information is obtained and the next operation is instructed.

[1274] Specific operation: The user enters basic information about the child into the system, and the server accurately stores it in the database.

[1275] Step 4: Setting up the AI ​​instructor

[1276] Input: The user selects the avatar, voice, and speaking style of the "AI instructor."

[1277] How it works: The server saves the selected configuration information in a database and reflects it in the generative AI model.

[1278] Output: The AI ​​instructor is configured and individual customization is enabled.

[1279] Specific operation: The user selects an avatar, voice, and speaking style, and this information is reflected in the generated AI model by the server and set in the system.

[1280] Step 5: Generate a teaching plan

[1281] Input: The server retrieves basic information about the child from the database.

[1282] How it works: Generative AI generates an educational plan based on the child's information.

[1283] Output: The generated teaching plan is stored in a database.

[1284] Specific operation: The server obtains basic information about the child and inputs it into the generation AI. The AI ​​generates an optimal educational plan, and the server stores the plan in a database.

[1285] Step 6: Start classes

[1286] Input: The user (student) presses the "Start lesson" button on the terminal.

[1287] Operation: The server obtains the teaching plan and starts the AI ​​instructor's lesson program.

[1288] Output: Lesson begins.

[1289] Specific operation: When the user (child) presses "Start lesson," the server retrieves the plan and the AI ​​instructor begins the lesson.

[1290] Step 7: Lesson Progression

[1291] Input: Facial expressions and voice data of students during class.

[1292] How it works: The emotion engine analyzes the child's emotions in real time and sends the results to the server.

[1293] Output: The progress of the lesson is dynamically adjusted based on the results of the sentiment analysis.

[1294] Specific operation: During the lesson, the device collects facial expressions and voice data, and the emotion engine analyzes the emotions and sends them to the server. The server then provides appropriate guidance and feedback based on the analysis results.

[1295] Step 8: Reporting and sharing information

[1296] Input: Lesson progress, student responses, and emotion analysis results.

[1297] How it works: The server records the progress of the lesson and the students' responses and saves them in a database.

[1298] Output: A notification is sent to the parent's device and the information is shared with the educational institution.

[1299] Specific operation: After the lesson ends, the server records the progress, students' reactions, and emotion analysis results, and saves them in a database. It then reports the situation to the parents' devices and automatically shares the information with the educational institution.

[1300] (Application example 2)

[1301] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1302] Conventional learning support systems have limitations in dynamically adjusting curriculum in response to children's emotions and reactions, and in providing learning experiences in virtual environments. Furthermore, many systems require parents to perform setup tasks at a high level, making it difficult to maintain children's interest. Furthermore, the lack of flexibility and interactivity in learning sessions in virtual environments is also a problem.

[1303] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for inputting basic information about the child, a generation AI means for generating a curriculum based on the child's basic information, an AI instructor means for conducting a lesson based on the generated curriculum, a means for analyzing the progress of the lesson and the child's responses, a means for notifying the child of the analysis results, a means for linking and sharing information with parents and the child's school, a means for recognizing and analyzing the child's emotions in real time using an emotion recognition engine and dynamically adjusting the lesson content, and a means for providing lessons and workshops in a virtual environment. This enables the provision of a flexible curriculum that corresponds to each child's individual emotions and learning progress, and a diverse learning experience in a virtual environment.

[1304] The "means for inputting basic information about a child" is a system component that has a function for inputting basic profile data such as a child's name, age, and grade.

[1305] "Generative AI means" refers to an artificial intelligence algorithm or system component that generates an optimal learning curriculum based on the basic information acquired about a child.

[1306] The "artificial intelligence instructor means" is an artificial intelligence-based educational system or software for conducting lessons based on the generated learning curriculum and educating children.

[1307] The "means for analyzing the progress of the lesson and the reactions of the students" is a system component for observing the behavior and reactions of the students during the lesson and analyzing the progress based on that.

[1308] The "means for notifying analysis results" is a system component that has the function of notifying parents and educators of the analysis results regarding the progress of the lesson and the students' reactions.

[1309] "Means for coordinating and sharing information with parents and the school" refers to a system component with communication functions for coordinating and sharing information regarding the progress of lessons, curriculum, and students' reactions with parents and the school.

[1310] An "emotion recognition engine" is an algorithm or system component that analyzes a child's facial expressions and voice data to recognize and analyze their emotional state in real time.

[1311] The "means for dynamically adjusting lesson content" is a system component that has the function of adjusting the lesson progress and curriculum in real time based on the emotional data collected by the emotion recognition engine.

[1312] "Means for providing classes and workshops in a virtual environment" refers to system components for providing classes and workshops in a virtual space using virtual reality (VR) and augmented reality (AR).

[1313] This invention is a learning support system for home or virtual environments, equipped with technology to provide flexible and effective education to children. The system uses a generative AI model to automatically generate a learning curriculum for children and an "artificial intelligence instructor" to conduct the lessons. It also uses an emotion recognition engine to analyze children's emotions in real time and dynamically adjust the lesson content.

[1314] System Overview

[1315] The system mainly consists of the following components:

[1316] 1. Server: Manages generative AI models, emotion recognition engines, and databases.

[1317] 2. Device: A device used by users (parents and children). Examples include PCs, tablets, smartphones, and head-mounted displays.

[1318] 3. Users: Parents and children. Parents configure and monitor the system, while children learn.

[1319] System Implementation

[1320] User Registration and Settings

[1321] The user (parent) accesses the registration form from their device and enters their name, email address, password, and child information (name, age, grade). The server stores this information in a database and sends a confirmation email. When the user clicks the link in the confirmation email, the account is activated. The parent then sets the avatar, voice, and speaking style of the "artificial intelligence instructor" according to their child's preferences. These settings are reflected in the generative AI model.

[1322] Curriculum Generation

[1323] The server retrieves basic information about the child from the database and inputs it into the generative AI model, which then generates a curriculum using, for example, the following prompt:

[1324] Generate a diverse and engaging curriculum for a 10 year old in grade 5. Curriculum should include subjects like math, reading, and physical activities.

[1325] The generated curriculum is stored in a database. For example, for a 10-year-old child, a curriculum that incorporates a balanced mix of math basics, reading time, and physical activity is generated.

[1326] Start and progress of lessons

[1327] When a user (child) presses the "Start Lesson" button on their device, the server retrieves the curriculum and launches the "AI Instructor." The AI ​​Instructor conducts the lesson in an interactive format, with an emotion recognition engine collecting and analyzing the child's facial expressions and voice in real time. For example, in a math class, a question is posed and the child enters the answer, and the AI ​​Instructor determines whether it is correct or incorrect and moves on to the next step. If the emotion recognition engine detects that the child is confused, it provides additional explanation.

[1328] Emotion Recognition Engine and Dynamic Adjustment

[1329] During lessons, an emotion recognition engine analyzes students' emotions in real time and sends the results to the server. For example, if a student is bored, the system will introduce more interactive activities. If a student is having trouble understanding, the system will provide detailed explanations or hints.

[1330] Reporting and collaboration

[1331] After the lesson is over, the server records the progress of the lesson, the students' reactions, and the results of emotional analysis. The server analyzes this information and notifies parents and the student's school. For example, it reports if a student had difficulty with a particular task or if a part of the lesson showed particular interest. This allows parents and educators to understand the student's learning progress.

[1332] This system allows children to enjoy a personalized learning experience and allows parents and educators to effectively support their children's learning progress.

[1333] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1334] Step 1: User registration and initial setup

[1335] The user (guardian) accesses the registration form from their device and enters their name, email address, password, and child information (name, age, grade). This input data is sent to the server and stored in a database. The server generates a confirmation email and sends it to the entered email address. When the user clicks the link in the confirmation email, the account is activated. Next, the user (guardian) sets the avatar, voice, and speaking style of the "artificial intelligence instructor" according to their child's preferences. This setting information is also sent to the server and reflected in the generated AI model.

[1336] Step 2: Curriculum generation

[1337] The server retrieves basic information about the child (age, grade, etc.) from the database and inputs this information into the generative AI model. For example, the server sends the following prompt to the generative AI model to generate the optimal curriculum.

[1338] Generate a diverse and engaging curriculum for a 10 year old in grade 5. Curriculum should include subjects like math, reading, and physical activities.

[1339] The generative AI model generates a curriculum based on the input information, and the server receives the generated curriculum and stores it in a database. For example, a curriculum that balances basic math, reading time, and exercise for a 10-year-old child would be generated.

[1340] Step 3: Start classes

[1341] When the user (child) presses the "Start Lesson" button on their device, the server retrieves a pre-generated curriculum from the database and launches the "AI instructor" lesson program. The AI ​​instructor begins the lesson based on the retrieved curriculum and provides the child with learning content in an interactive format. The device collects the child's facial expressions and voice data in real time and sends it to the server.

[1342] Step 4: Emotion recognition and dynamic regulation

[1343] The server inputs facial expressions and voice data sent from the device into an emotion recognition engine to analyze the child's emotions in real time. For example, if the emotion recognition engine detects a child's confusion or boredom, the server generates appropriate feedback and additional explanations and provides them to the child through an AI instructor. This allows the child to continue learning with appropriate support.

[1344] Step 5: Learning Records and Notifications

[1345] After the lesson is over, the server records the progress of the lesson, the students' reactions, and the results of emotional analysis. This information is stored in a database as a profile and used for future learning. The server also generates a report summarizing the lesson and highlighting key points, which is sent to parents and the student's school to share the student's learning status. For example, it reports if a student had difficulty with a particular problem or if a topic of particular interest occurred.

[1346] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1347] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1348] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1349] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1350] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1351] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1352] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1353] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1354] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1355] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1356] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1357] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1358] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1359] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1360] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1361] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1362] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1363] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1364] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1365] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, in order to avoid confusion and to facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1366] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1367] The following is further disclosed regarding the above embodiment.

[1368] (Claim 1)

[1369] A means for inputting basic information about the child;

[1370] A generating AI means for generating a curriculum based on basic information of a child;

[1371] An AI instructor means for conducting lessons based on the generated curriculum;

[1372] A means of analyzing the progress of lessons and students' reactions;

[1373] a means for communicating the results of the analysis;

[1374] A means of communicating and sharing information with parents and the school where the student is enrolled,

[1375] A system including:

[1376] (Claim 2)

[1377] 2. The system according to claim 1, wherein the AI ​​instructor means includes means for allowing a child to customize an avatar, voice, and speaking style to suit the child's preferences.

[1378] (Claim 3)

[1379] 10. The system of claim 1, further comprising means for dynamically adjusting the curriculum in response to student responses.

[1380] "Example 1"

[1381] (Claim 1)

[1382] A means for inputting basic information about the child;

[1383] A generating AI means for generating a curriculum based on basic information of a child;

[1384] An AI instructor means for conducting lessons based on the generated curriculum;

[1385] A means for starting a lesson program by pressing the lesson start button;

[1386] A means of analyzing the progress of lessons and students' reactions;

[1387] A means of summarizing the results of the analysis and communicating this information to parents and the school where the student is enrolled;

[1388] A system including:

[1389] (Claim 2)

[1390] 2. The system according to claim 1, wherein the AI ​​instructor means includes means for allowing a child to customize an avatar, voice, and speaking style to suit the child's preferences.

[1391] (Claim 3)

[1392] 10. The system of claim 1, further comprising means for dynamically adjusting the curriculum in response to student responses.

[1393] "Application Example 1"

[1394] (Claim 1)

[1395] A means for inputting basic information about the child;

[1396] A generating AI means for generating a curriculum based on basic information of a child;

[1397] An AI instructor means for conducting lessons based on the generated curriculum;

[1398] A means of analyzing the progress of lessons and students' reactions;

[1399] a means for communicating the results of the analysis;

[1400] A means of communicating and sharing information with parents and institutions;

[1401] means for delivering content based on the generated curriculum;

[1402] A system including:

[1403] (Claim 2)

[1404] 2. The system according to claim 1, wherein the AI ​​instructor means includes means for allowing a child to customize an avatar, voice, and speaking style to suit the child's preferences.

[1405] (Claim 3)

[1406] 10. The system of claim 1, further comprising means for dynamically adjusting the curriculum in response to student responses.

[1407] "Example 2: Combining Emotion Engines"

[1408] (Claim 1)

[1409] A means for inputting basic information about the child;

[1410] A generating AI means for generating an educational plan based on basic information of a child;

[1411] An artificial intelligence teaching means for conducting a lesson based on the generated teaching plan;

[1412] an emotion engine means for recognizing and analyzing the emotions of a child;

[1413] A means of analyzing the progress of lessons and students' reactions;

[1414] a means for communicating the results of the analysis;

[1415] A means of connecting and sharing information with parents and educational institutions;

[1416] A system including:

[1417] (Claim 2)

[1418] 2. The system of claim 1, wherein the artificial intelligence instruction means includes means for configuring a visual avatar, voice, and speaking style to suit a child's preferences.

[1419] (Claim 3)

[1420] 10. The system of claim 1, further comprising means for dynamically adjusting the instructional plan in response to the child's response.

[1421] "Application example 2 when combining emotion engines"

[1422] (Claim 1)

[1423] A means for inputting basic information about the child;

[1424] A generating AI means for generating a curriculum based on basic information of a child;

[1425] an artificial intelligence instructor means for conducting a lesson based on the generated curriculum;

[1426] A means of analyzing the progress of lessons and students' reactions;

[1427] a means for communicating the results of the analysis;

[1428] A means of communicating and sharing information with parents and the school where the student is enrolled,

[1429] An emotion recognition engine is used to recognize and analyze students' emotions in real time, and dynamically adjust the content of lessons.

[1430] A system that includes the means to deliver classes and workshops in a virtual environment.

[1431] (Claim 2)

[1432] 2. The system according to claim 1, wherein the artificial intelligence instructor means includes means for setting an avatar, a voice, and a way of speaking that suit the preferences of the child.

[1433] (Claim 3)

[1434] 10. The system of claim 1, further comprising means for dynamically adjusting the curriculum in response to student responses. [Explanation of symbols]

[1435] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for inputting basic information about the child; A generating AI means for generating a curriculum based on basic information of a child; An AI instructor means for conducting lessons based on the generated curriculum; A means of analyzing the progress of lessons and students' reactions; a means for communicating the results of the analysis; A means of coordinating and sharing information with parents and the school where the student is enrolled, A system including:

2. 2. The system according to claim 1, wherein the AI ​​instructor means includes means for setting an avatar, voice, and speaking style to suit the preferences of the child.

3. 10. The system of claim 1, further comprising means for dynamically adjusting the curriculum in response to student responses.

Images