system

Abstract

We provide a system that provides learning support optimized for each individual user and can be a lifelong learning partner. [Solution] The system includes a means for receiving basic information entered by a user and saving it in a database, a means for displaying a questionnaire for entering the user's interests and learning goals and collecting the results, a means for sending the collected data to an AI module to generate a curriculum based on the collected data, a means for storing the curriculum generated by the AI ​​module in a database and notifying the user, a means for displaying daily learning reminders and learning materials to the user, a means for tracking the user's learning progress and saving it in a database, a means for the AI ​​module to adjust the curriculum based on the learning progress data, a means for periodically compiling the user's learning progress and generating a performance evaluation report, and a means for displaying the performance evaluation report to the user and providing advice.

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] Providing optimal learning curricula for individual users across regions and generations where educational opportunities are limited is a difficult challenge. In particular, a uniform educational program cannot produce satisfactory results for users with different interests and learning goals. Furthermore, managing each user's learning progress and providing appropriate feedback is not easy due to limited human resources. In these circumstances, a comprehensive and personalized educational support system using AI is needed. [Means for solving the problem]

[0005] The present invention solves the above problems by providing the following means. Specifically, the system includes a means for receiving basic information entered by a user and saving it in a database, and a means for displaying a questionnaire for entering the user's interests and learning goals and collecting the results. It also includes a means for sending data to an AI module to generate a curriculum based on the collected data, and a means for storing the curriculum generated by the AI ​​module in a database and notifying the user. The system further includes a means for displaying daily learning reminders and learning materials to the user, a means for tracking the user's learning progress and saving it in a database, a means for the AI ​​module to adjust the curriculum based on the learning progress data, a means for periodically compiling the user's learning progress and generating a performance evaluation report, and a means for displaying the performance evaluation report to the user and providing advice. This allows the system to provide learning support optimized for each individual user and become a lifelong learning partner.

[0006] "User" refers to a person who uses the system.

[0007] "Basic information" refers to data such as the user's name, age, country of residence, and email address.

[0008] "Database" refers to a digital system for storing basic information about users and learning progress data.

[0009] "Survey" refers to a question-based input method used to understand a user's interests and learning goals.

[0010] A "curriculum" is a written plan designed for a user's learning, including the learning content, materials, and pace of learning.

[0011] "AI Module" refers to a software component that uses artificial intelligence to generate and tailor curriculum for each user.

[0012] "Generative AI" refers to artificial intelligence that has the ability to automatically generate new curricula and learning content based on data.

[0013] "Study reminder" refers to a reminder system that notifies users of the time and content to study.

[0014] "Learning materials" refers to learning materials and learning content provided to users.

[0015] "Study progress" refers to data that indicates the results and progress achieved by a user during the learning process.

[0016] "Performance evaluation report" refers to a report that compiles a user's learning progress and provides a comprehensive evaluation result.

[0017] "Advice" refers to suggestions or guidance provided about improving learning or next steps in learning.

[0018] The above are definitions of important terms included in the scope of this patent claim. [Brief explanation of the drawings]

[0019] [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

[0020] 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.

[0021] First, the terms used in the following description will be explained.

[0022] 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).

[0023] 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.

[0024] 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.

[0025] 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.

[0026] 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."

[0027] [First embodiment]

[0028] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0029] 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.

[0030] 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).

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 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.

[0037] 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.

[0038] 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.

[0039] 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."

[0040] This invention relates to an AI tutoring system that supports daily learning by providing users with individually customized learning curricula based on their specific interests and goals. Below, we will explain the program processing of this system in natural language and provide specific examples.

[0041] System Configuration

[0042] 1. User registration and initial settings

[0043] A user accesses the system and proceeds to the account creation page. First, the user enters basic information such as their name, age, country of residence, email address, etc. This information is sent to the server via the terminal, and the server stores the received information in a database.

[0044] The device then displays a questionnaire to the user asking about their interests and learning goals. When the user answers the questionnaire, the results are sent from the device to the server and stored in a database.

[0045] 2. Curriculum Generation

[0046] The server sends a curriculum generation request to the AI ​​module based on the user's basic information and survey results. The AI ​​module uses generative AI to design a curriculum that is optimal for the user. This curriculum includes learning topics, materials, and learning pace.

[0047] The generated curriculum is sent to the server, which stores it in a database and notifies the user.

[0048] 3. Daily learning support

[0049] For daily learning, the device displays daily learning reminders and the day's study materials to the user. For example, a reminder such as "Today's learning content: Planets of the solar system" is displayed. The user confirms this and begins studying.

[0050] Once the user has completed their learning, the device will send progress information to the server, which will store it in a database and send it to the AI ​​module in a timely manner.

[0051] 4. Learning progress management and curriculum adjustment

[0052] The AI ​​module analyzes the user's progress data to check whether the learning content is appropriate. If necessary, it adjusts the curriculum and suggests new materials and a learning pace. The adjusted curriculum is saved in a database on the server and notified to the user.

[0053] 5. Grading and Advice

[0054] The server periodically aggregates the user's learning progress and generates a performance evaluation report, which includes the user's learning progress, performance evaluation, improvement points, and next steps.

[0055] The device displays this performance evaluation report to the user and provides advice, such as "Next time, focus on the topic of XX."

[0056] Specific examples

[0057] Example 1: Elementary school students learning about space

[0058] A user (elementary school student) wants to learn about space. He enters basic information and answers "space" in a questionnaire about his interests.

[0059] The terminal sends the survey results to the server, and the server requests the AI ​​module to generate a curriculum.

[0060] The AI ​​module generates a curriculum including "Space Basics," "Planets of the Solar System," and "Simple Space Experiments."

[0061] Each day, the device displays reminders and educational materials, such as "Today's learning: Planets in the solar system."

[0062] Users study and report their progress, and the server records the progress data and adjusts the curriculum as needed.

[0063] Example 2: Working adults seeking an MBA

[0064] The user (a working adult) aims to obtain an MBA, enters basic information, and answers "business administration" to a questionnaire about interests.

[0065] The server requests the AI ​​module to generate a curriculum, and the AI ​​module generates a curriculum including "business strategy," "financial analysis," and "marketing."

[0066] Each day, the device displays reminders and learning materials such as "Today's learning topic: Financial analysis."

[0067] Users study and report their progress. The server records the progress data and generates a performance report that includes next steps and areas for improvement.

[0068] In this way, this system provides a learning curriculum that is individually customized based on the user's interests and goals, thereby supporting lifelong learning. This invention improves the quality of education and allows users to continue learning in a way that is best suited to them.

[0069] The above is the "Mode for Carrying Out the Invention."

[0070] The processing flow will be explained below.

[0071] Step 1:

[0072] A user accesses the system and proceeds to the account creation page. The terminal displays a form for entering basic information such as name, age, country of residence, email address, etc. The user enters the information and clicks the submit button.

[0073] Step 2:

[0074] The device sends the entered basic information to the server, which stores the received information in a database and notifies the user via the device that account creation has been completed.

[0075] Step 3:

[0076] The terminal displays a questionnaire to the new user asking about their interests and learning goals. The user answers the questionnaire and submits the results.

[0077] Step 4:

[0078] The device sends the survey results to the server, which stores them in a database and sends the data to the AI ​​module.

[0079] Step 5:

[0080] The server sends a curriculum generation request to the AI ​​module based on the user's basic information and the survey results. The AI ​​module uses the generation AI to design the optimal curriculum for the user.

[0081] Step 6:

[0082] The AI ​​module sends the generated curriculum to the server, which stores it in a database and notifies the user.

[0083] Step 7:

[0084] The device displays daily study reminders and the day's study materials to the user, who then begins studying with the materials presented.

[0085] Step 8:

[0086] When the user completes the study, he / she enters the study progress into the terminal and clicks the send button.

[0087] Step 9:

[0088] The device sends learning progress data to the server, which stores this data in a database and sends it to the AI ​​module as needed.

[0089] Step 10:

[0090] The AI ​​module analyzes the user's progress data, determines whether the learning content is appropriate, adjusts the curriculum as necessary, and sends the adjusted curriculum to the server.

[0091] Step 11:

[0092] The server stores the adjusted curriculum in a database and notifies the user.

[0093] Step 12:

[0094] The server periodically aggregates the user's learning progress and generates a performance evaluation report, which includes the user's learning progress, performance evaluation, improvement points, and next steps.

[0095] Step 13:

[0096] The device displays the performance evaluation report to the user and provides advice, allowing the user to adjust their learning methods and goals based on the evaluation results.

[0097] The above is a concrete explanation of the processing steps of the program.

[0098] Example 1

[0099] 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."

[0100] Conventional learning support systems are unable to respond to the individual learning needs and progress of each user, and are limited to providing a uniform curriculum. In addition, it is difficult for users to manage their learning progress and receive appropriate feedback and advice, which hinders effective learning.

[0101] 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.

[0102] In this invention, the server includes means for receiving personal information entered by the user and storing it in a storage device, means for displaying a survey form for entering the user's interests and learning goals and collecting the results, and means for transmitting the collected data to an AI module to generate a curriculum based on the data. This allows for the provision of a curriculum that meets the individual learning needs of each user, enabling effective learning.

[0103] "Personal information" refers to information necessary to identify an individual, such as a user's name, age, country of residence, and email address.

[0104] A "memory device" is a device that electronically stores and manages information, such as a database or storage.

[0105] A "survey" is a questionnaire or form used to gather information about a user's interests, learning goals, etc.

[0106] An "AI module" is a component that uses artificial intelligence to perform processes such as curriculum generation and learning progress analysis.

[0107] A "curriculum" is a collection of learning plans and materials organized around a user's learning goals.

[0108] "Study reminders" are messages and alerts that inform users of their daily learning content and progress.

[0109] "Study progress" is data on the progress status that indicates how far the user has progressed toward the learning goal set by the user.

[0110] A "performance evaluation report" is a document that evaluates a user's learning progress and lists their grades, areas for improvement, and next steps.

[0111] "Advice" is specific advice or instruction provided to support the user's learning.

[0112] "Generative AI" is an artificial intelligence technology that generates optimal curriculum and advice based on data entered by the user.

[0113] This invention relates to an AI tutoring system that supports daily learning by providing users with individually customized learning curricula based on their specific interests and goals. The program processing of this system is explained below in natural language.

[0114] System Overview

[0115] This system mainly consists of the following elements:

[0116] server

[0117] Terminal

[0118] User

[0119] Generative AI Models

[0120] storage device

[0121] Registering users and saving basic information

[0122] When a user accesses the system, an account creation page is displayed. The user enters personal information such as name, age, country of residence, and email address. This information is sent to the server via the terminal, and the server stores it in a storage device. The terminal then displays a survey form about the user's interests and learning goals, which the user answers. The survey results are again sent to the server via the terminal and stored in a storage device.

[0123] Curriculum generation

[0124] The server sends a curriculum generation request to the generative AI model based on the user's basic information and the survey results. Specifically, the following prompt sentence is used:

[0125] "Please create a curriculum for elementary school students to learn about space. Specifically, please include the basics of space, planets in the solar system, and simple space experiments."

[0126] "Please create a curriculum for working professionals seeking an MBA. Specifically, please include business strategy, financial analysis, and marketing."

[0127] The generative AI model generates a curriculum based on these prompts and sends it to the server. The server stores the received curriculum in a storage device and notifies the user. The device then informs the user that "a curriculum has been generated."

[0128] Daily learning support

[0129] During daily learning, the server sends the day's learning content and reminders to the device. For example, the device displays a reminder such as "Today's learning content: Planets of the solar system." This allows the user to start learning with the specified learning material. Once the learning is complete, the user enters progress information into the device, which then sends it to the server. The progress information is stored in a storage device.

[0130] Learning progress management and curriculum adjustment

[0131] The server periodically sends the user's learning progress data to the generative AI model for analysis. The generative AI model adjusts the curriculum based on the user's progress and suggests new learning paces and materials. The adjusted curriculum is saved in a storage device from the server and notified to the user.

[0132] Grading and Advice

[0133] The server periodically collects the user's learning progress data and generates a performance evaluation report, which includes a performance evaluation, areas for improvement, and next steps. The terminal displays the performance evaluation report to the user and provides specific advice, such as "Next time, focus on the topic of XX."

[0134] Specific examples

[0135] When elementary school students learn about space

[0136] The user (elementary school student) enters basic information and answers "space" to a questionnaire about interests.

[0137] The terminal sends the survey results to the server and requests the AI ​​module to generate a curriculum.

[0138] The generative AI model generates a curriculum including "Space Basics," "Planets of the Solar System," and "Simple Space Experiments."

[0139] Each day, the device displays reminders and educational materials, such as "Today's learning: Planets in the solar system."

[0140] Users study and report their progress, and the server records the progress data and adjusts the curriculum as needed.

[0141] The above is a specific embodiment for carrying out the invention. This system allows users to continue learning in a way that is optimal for them.

[0142] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0143] Step 1: Enter and save basic user information

[0144] When a user accesses the system, they are presented with an account creation page.

[0145] The user enters personal information such as name, age, country of residence, email address, etc. This input data is sent to the terminal.

[0146] The terminal transmits the entered personal information to the server.

[0147] The server stores the received personal information in a storage device.

[0148] Output: The registered user's personal information is saved to the storage device.

[0149] Step 2: View the survey and save the results

[0150] The terminal presents the user with a survey of interests and learning goals.

[0151] The user answers the survey and the results are sent to the terminal.

[0152] The terminal transmits the results of the survey to the server.

[0153] The server stores the results of the investigation in a storage device.

[0154] Output: Data about the user's interests and learning goals is saved to a storage device.

[0155] Step 3: Submit a curriculum generation request

[0156] The server creates prompts for curriculum generation based on the user's basic information and survey results.

[0157] Input: User basic information and survey results

[0158] Output: Curriculum-generated prompt

[0159] The server sends the generated prompt sentence as a request to the generative AI model.

[0160] Example: "Generate a curriculum for elementary school students to learn about space. Specifically, include the basics of space, planets in the solar system, and simple space experiments."

[0161] Step 4: Generate and save the curriculum

[0162] The generative AI model generates a learning curriculum based on the prompt sentence.

[0163] Input: Curriculum generation prompt

[0164] Output: Generated learning curriculum

[0165] The server receives the generated curriculum and stores it in a storage device.

[0166] The terminal notifies the user that "The curriculum has been generated."

[0167] Step 5: View study reminders and materials

[0168] The server sends the day's learning content and reminders to the device.

[0169] The device displays reminders and educational materials to the user, such as "Today's learning: Planets in the solar system."

[0170] Input: Today's learning content and reminders

[0171] Output: Reminders and educational materials displayed to the user

[0172] Step 6: Enter and save your learning progress

[0173] The user checks the reminder and continues studying.

[0174] When the user has completed the learning, the terminal displays a "Learning Completed" button.

[0175] When the user clicks the button, progress information is sent to the terminal.

[0176] The terminal sends progress information to the server.

[0177] The server stores the progress information in a storage device.

[0178] Input: Learning progress information

[0179] Output: Learning progress information stored in memory.

[0180] Step 7: Analyze learning progress data and adjust curriculum

[0181] The server periodically sends progress data to the generative AI model.

[0182] The generative AI model analyzes the user's progress data to ensure that the learning content is appropriate.

[0183] Input: Learning progress data

[0184] Output: Analysis results and adjustment suggestions

[0185] If necessary, the generative AI model will adjust the curriculum.

[0186] The server receives the tailored curriculum and stores it in a storage device.

[0187] The terminal notifies the user of the adjusted curriculum.

[0188] Step 8: Generate and view the grading report

[0189] The server periodically compiles the user's learning progress data and generates a performance evaluation report.

[0190] Input: Learning progress data

[0191] Output: Grade evaluation report

[0192] The terminal displays the performance evaluation report to the user and provides specific advice.

[0193] For example, advice such as "Next time, let's focus on the topic of XX."

[0194] The above are the specific processing steps of this system's program. This makes it possible to provide an optimal curriculum for each user, manage learning progress, and provide appropriate feedback.

[0195] (Application example 1)

[0196] 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."

[0197] Conventional tutoring systems lack the ability to customize to meet the individual learning needs and goals of users, resulting in a decline in learning effectiveness. Furthermore, the lack of interactive learning content utilizing smart devices has led to issues such as difficulty in maintaining motivation to learn.

[0198] 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.

[0199] In this invention, the server includes means for receiving basic information input by a user and storing it in a data management device, means for displaying a survey for inputting the user's interests and learning goals and collecting the results, means for transmitting the collected data to an intelligence module for generating an educational plan based on the collected data, means for storing the educational plan generated by the intelligence module in the data management device and notifying the user, means for displaying daily learning notifications and educational materials to the user, means for tracking the user's learning progress and storing it in the data management device, means for the intelligence module to adjust the educational plan based on the learning progress data, means for periodically compiling the user's learning progress and generating a performance evaluation report, means for displaying the performance evaluation report to the user and providing advice, and means for delivering interactive learning content on devices such as smart glasses and mobile terminals, thereby enabling a highly customized learning experience tailored to the user's individual needs.

[0200] "User" refers to any individual or entity that uses the System.

[0201] "Basic information" refers to personal information such as the user's name, age, place of residence, and email address.

[0202] "Data Management Device" refers to a system or device for storing and managing information collected from users.

[0203] "Survey" refers to a questionnaire-style interface that includes questions about the user's interests and learning goals.

[0204] "Intelligence Module" refers to a program containing artificial intelligence algorithms for generating an optimal training plan based on user input data.

[0205] "Educational Plan" means a plan including curriculum, materials, and learning pace designed to achieve a user's learning goals.

[0206] "Notification" refers to the action of sending important information or reminders from the system to the user.

[0207] "Educational materials" refers to teaching materials and content used for learning, such as texts, videos, and quizzes.

[0208] "Study progress" refers to data indicating how much of the learning content a user has completed.

[0209] "Performance evaluation report" refers to a report that compiles and evaluates a user's learning outcomes and progress.

[0210] "Advice" refers to advice on the user's learning and suggestions for next steps.

[0211] "Smart glasses" refers to a glasses-type device equipped with augmented reality and information display functions.

[0212] "Mobile device" refers to a portable electronic device such as a smartphone or tablet.

[0213] "Interactive learning content" refers to educational content that allows users to actively participate and learn while receiving feedback.

[0214] This invention relates to an AI tutoring system that supports daily learning by providing a personalized learning curriculum based on a user's specific interests and goals. The system can deliver interactive learning content on devices such as smart glasses and mobile terminals.

[0215] System Configuration

[0216] 1. User registration and initial settings

[0217] The user navigates to an account creation page on the device. First, the user enters basic information such as their name, age, place of residence, and email address. This information is sent to the server via the device, and the server stores the received information in a data management device. The device then displays a survey asking the user about their interests and learning goals. After the user completes the survey, the results are sent from the device to the server and stored in the data management device.

[0218] 2. Curriculum Generation

[0219] The server sends a request to the intelligent module to generate a learning plan based on the user's basic information and survey results. The intelligent module uses the generative AI model to design an optimal learning plan for the user. This learning plan includes learning topics, materials, and learning pace. The generated learning plan is sent to the server, stored in the data management device, and notified to the user.

[0220] 3. Daily learning support

[0221] During daily learning, the device displays daily learning notifications and the day's educational materials to the user. For example, a notification such as "Today's learning content: Planets in the solar system" is displayed. The user confirms this and begins learning. When the user completes their learning, the device sends progress information to the server. The server stores this information in the data management device and transmits it to the intelligent module in a timely manner.

[0222] 4. Managing learning progress and adjusting educational plans

[0223] The intelligent module analyzes the user's progress data to determine whether the learning content is appropriate. If necessary, it adjusts the learning plan and suggests new learning materials and a learning pace. The adjusted learning plan is then stored in the data management device from the server and notified to the user.

[0224] 5. Grading and Advice

[0225] The server periodically compiles the user's learning progress and generates a performance evaluation report. This report includes the user's learning progress, performance evaluation, areas for improvement, and next steps. The device displays this performance evaluation report to the user and provides advice. For example, specific advice such as "Next time, focus on topic XX" may be included.

[0226] Detailed processing

[0227] The basic information and survey results entered by the user are sent to the server via the terminal. The server stores this data in a data management device and sends it to an intelligence module (a generative AI model such as GPT-3 (registered trademark)). The intelligence module generates an optimal educational plan for the user based on the prompt sentence. As a specific example, the following prompt sentence can be used:

[0228] Prompt Sentence Examples

[0229] User information: Name = Taro Tanaka, Age = 25, Interests = Programming, Level = Beginner

[0230] Survey results: Learning goal = Web development, Hobby = Game development, Study time = 1 hour / day

[0231] Generated curriculum:

[0232] Week 1: HTML / CSS Basics

[0233] Week 2: JavaScript® Basics

[0234] Week 3: Simple web application development

[0235] Week 4: Game Development Fundamentals

[0236] The generated educational plan is stored in a data management device and sent to the user's device. The user receives daily learning notifications and begins studying. Learning progress is sent to the server in real time, and an intelligent module analyzes it and periodically adjusts the educational plan. Overall, this system provides users with a customized learning experience, enabling them to continue learning while maintaining their motivation.

[0237] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0238] Step 1:

[0239] The user accesses the account creation page using a terminal and enters basic information (name, age, place of residence, email address, etc.). The terminal sends the entered basic information to the server, which then stores the information in the data management device.

[0240] Input: Basic information such as name, age, place of residence, and email address

[0241] Output: Basic information of the user stored in the data management device

[0242] Step 2:

[0243] The device displays a survey to the user asking about their interests and learning goals. After the user completes the survey, the device transmits the results to a server, which stores the survey results in a data management device.

[0244] Input: Survey results about user interests and learning goals

[0245] Output: Survey results stored in the data management device

[0246] Step 3:

[0247] The server sends a request for generating an educational plan to the intelligence module based on the user's basic information and the survey results. The intelligence module uses the generative AI model to generate the optimal educational plan for the user. This process is based on the prompt text.

[0248] Input: User basic information and survey results stored in the data management device

[0249] Output: The training plan generated by the intelligence module

[0250] Step 4:

[0251] The intelligent module sends the generated training plan to the server, which stores it in the data management device and notifies the user, who then displays the notification to the terminal, allowing the user to confirm the training plan.

[0252] Input: Educational plan generated by the intelligence module

[0253] Output: Education plan stored in the data management device and notification displayed to the user

[0254] Step 5:

[0255] Every day, the device displays a learning notification and the day's educational material to the user. The user checks the notification and begins learning.

[0256] Input: Educational materials for the day stored in the data management device

[0257] Output: Learning notifications and educational materials displayed on the device

[0258] Step 6:

[0259] When the user completes the learning, the terminal transmits the progress information to the server, which stores the progress information in the data management device.

[0260] Input: User learning progress information

[0261] Output: Learning progress information stored in the data management device

[0262] Step 7:

[0263] The server periodically transmits the learning progress data to the intelligent module, which analyzes the data and adjusts the educational plan, which is then stored in the data management device by the server and notified to the user.

[0264] Input: Learning progress data stored in the data management device

[0265] Output: Coordinated educational plan

[0266] Step 8:

[0267] The server periodically compiles the user's learning progress and generates a performance evaluation report, which includes the user's learning progress, performance evaluation, areas for improvement, and next steps. The terminal displays the performance evaluation report to the user and provides advice.

[0268] Input: Aggregated data based on learning progress stored in the data management device

[0269] Output: A grading report and advice displayed to the user

[0270] The above are the specific processing steps of this system.

[0271] 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.

[0272] This invention relates to an AI tutoring system that supports daily learning by providing a personalized learning curriculum based on the user's specific interests and goals. Furthermore, this system combines an emotion engine that recognizes the user's emotions, enabling more flexible and personalized instruction.

[0273] System Configuration

[0274] 1. User registration and initial settings

[0275] A user accesses the system and proceeds to the account creation page. First, the user enters basic information such as their name, age, country of residence, email address, etc. The device sends the entered information to the server, which stores it in a database.

[0276] Next, the device displays a questionnaire to the user asking about their interests and learning goals. After the user answers the questionnaire, the results are sent to the server and stored in a database.

[0277] 2. Curriculum Generation

[0278] The server sends a curriculum generation request to the AI ​​module based on the user's basic information and survey results. The AI ​​module uses generative AI to design a curriculum that is optimal for the user. This curriculum includes learning topics, materials, and learning pace.

[0279] The generated curriculum is sent to the server and stored in a database, and the server notifies the user.

[0280] 3. Emotion engine integration

[0281] The device is equipped with an emotion engine that analyzes the user's emotions from their facial expressions and voice. The emotion engine collects emotional data as the user progresses through the learning process and analyzes it in real time.

[0282] Emotion analysis data is sent from the device to a server. The server stores the emotional data in a database and sends it to an AI module. The AI ​​module adjusts the curriculum and learning content according to the user's emotions.

[0283] 4. Daily study support

[0284] For daily study, the device displays study reminders and the day's study materials to the user. For example, a reminder such as "Today's study topic: Planets in the solar system" is displayed. The user confirms this and begins studying.

[0285] The device analyzes the user's facial expressions and voice and sends emotional data to the server, which stores it in a database and sends it to the AI ​​module, which then adjusts its learning content accordingly.

[0286] 5. Learning progress management and curriculum adjustment

[0287] When a user completes their study, they input their progress into the device and send it. The device then sends the progress data to the server and stores it in a database. Based on the emotional data and learning progress data, the AI ​​module adjusts the curriculum and learning pace.

[0288] 6. Grading and Advice

[0289] The server periodically collects the user's learning progress and emotion data and generates a performance evaluation report, which includes the user's learning progress, performance evaluation, improvement points, and next steps. The terminal displays the performance evaluation report to the user and provides advice.

[0290] Specific examples

[0291] Example 1: Elementary school students learning about space

[0292] A user (elementary school student) wants to learn about space. He enters basic information and answers "space" in a questionnaire about his interests.

[0293] The server requests the AI ​​module to generate a curriculum, and the AI ​​module generates a curriculum including "Basics of the Universe," "Planets in the Solar System," and "Simple Experiments."

[0294] Every day, the device displays "Today's learning content: Planets of the solar system," and as the user progresses, the emotion engine analyzes the user's facial expressions and voice. If it determines that the user has lost interest, the AI ​​module adjusts the curriculum and suggests new topics.

[0295] When the user completes the study, the study progress and emotional data are input into the terminal and transmitted to the server.

[0296] The server generates a performance evaluation report based on progress data and emotion data, and suggests next learning steps and areas for improvement.

[0297] Example 2: Working adults seeking an MBA

[0298] The user (a working adult) aims to obtain an MBA, enters basic information, and answers "business administration" to a questionnaire about interests.

[0299] The server requests the AI ​​module to generate a curriculum, and the AI ​​module generates a curriculum including "business strategy," "financial analysis," and "marketing."

[0300] Every day, the device displays "Today's learning content: Financial analysis," and as the user progresses through the learning process, the emotion engine analyzes the user's facial expressions and voice. If the AI ​​module determines that the user's concentration is declining, it adjusts the learning content and encourages them to take a break at the appropriate time.

[0301] The user inputs learning progress and emotional data into the terminal and transmits it to the server.

[0302] The server generates a performance evaluation report based on progress data and emotion data, and suggests next learning steps and areas for improvement.

[0303] This system provides a personalized learning curriculum based on the user's interests and goals, and responds flexibly through real-time emotion analysis, enabling lifelong learning support. This invention improves the quality of education and allows users to continue learning in a way that is best suited to them.

[0304] The above is the "Mode for Carrying Out the Invention."

[0305] The processing flow will be explained below.

[0306] Step 1:

[0307] A user accesses the system and proceeds to the account creation page. The terminal displays a form for entering basic information such as name, age, country of residence, email address, etc. The user enters the information and clicks the submit button.

[0308] Step 2:

[0309] The device sends the entered basic information to the server, which stores the received information in a database and notifies the user via the device that account creation has been completed.

[0310] Step 3:

[0311] The terminal displays a questionnaire to the new user asking about their interests and learning goals. The user answers the questionnaire and submits the results.

[0312] Step 4:

[0313] The device sends the survey results to the server, which stores them in a database and sends the data to the AI ​​module.

[0314] Step 5:

[0315] The server sends a curriculum generation request to the AI ​​module based on the user's basic information and the survey results. The AI ​​module uses the generation AI to design the optimal curriculum for the user.

[0316] Step 6:

[0317] The AI ​​module sends the generated curriculum to the server, which stores it in a database and notifies the user.

[0318] Step 7:

[0319] The device displays daily study reminders and the day's learning materials to the user. For example, a reminder might say, "Today's learning content: Planets in the solar system." The user then begins studying the materials provided.

[0320] Step 8:

[0321] While the user is learning, the device's built-in emotion engine analyzes the user's facial expressions and voice to collect emotional data, including facial expression analysis and voice tone analysis.

[0322] Step 9:

[0323] The device sends the collected emotional data to a server, which stores the data in a database and sends it to an AI module.

[0324] Step 10:

[0325] The AI ​​module analyzes emotional and learning progress data and adjusts learning content and methods based on the user's current emotional state. For example, if the user is tired, it will suggest a break or switch to a less difficult problem.

[0326] Step 11:

[0327] The server stores the adjusted curriculum in a database and notifies the user.

[0328] Step 12:

[0329] When the user completes the study, they input their study progress into the device and click the send button. The device then sends the study progress data and emotion data to the server.

[0330] Step 13:

[0331] The server stores the learning progress data and emotion data in a database and periodically aggregates them to generate a performance evaluation report, which includes the user's learning progress, performance evaluation, improvement points, and next steps.

[0332] Step 14:

[0333] The device displays a performance evaluation report to the user and offers advice, such as "Next time, try taking breaks to improve your concentration."

[0334] Step 15:

[0335] The server collects user feedback and sends it to the AI ​​module for further curriculum optimization.

[0336] The above is a concrete explanation of the processing steps of the system that integrates the emotion engine.

[0337] Example 2

[0338] 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."

[0339] In recent years, there has been a demand for individually customized learning support systems, but existing systems lack the flexibility to respond sufficiently to users' interests and goals. Furthermore, they lack the ability to analyze users' emotions in real time and adjust the curriculum accordingly, resulting in the problem of only being able to provide uniform instruction. Furthermore, the management of learning progress and grade evaluation are still done manually, which is inefficient and affects users' ability to continue learning. There is a need for a comprehensive learning support system that can solve these issues.

[0340] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving basic information entered by a user and storing it in a database, means for displaying a questionnaire for entering the user's interests and learning goals and collecting the results, means for transmitting data to an artificial intelligence module to generate a curriculum based on the collected data, means for storing the curriculum generated by the artificial intelligence module in a database and notifying the user, means for displaying daily learning reminders and learning materials to the user, means for tracking the user's learning progress and storing it in a database, means for the artificial intelligence module to adjust the curriculum based on learning progress data, means for analyzing emotions from the user's facial expressions and voice, sending the analyzed data to the server and storing it in a database, means for adjusting the curriculum and learning content based on the emotion data, means for periodically compiling the user's learning progress and emotion data and generating a performance evaluation report, and means for displaying the performance evaluation report to the user and providing advice. This enables the provision of a customized learning curriculum tailored to the user's interests and goals and flexible learning support based on emotion analysis.

[0341] "Basic information" refers to personal information such as name, age, country of residence, and email address that a user enters when registering with the system.

[0342] A "survey" is a collection of questions displayed to gather information about a user's interests and learning goals.

[0343] An "artificial intelligence module" is a program that includes artificial intelligence capabilities to generate a curriculum based on collected data and tailor it to the user's individual needs.

[0344] A "curriculum" is a set of learning plans, including learning content, learning materials, and learning pace, designed based on a user's learning goals.

[0345] "Reminder" is a system function that notifies users of the day's study content and schedule.

[0346] "Study progress" is information indicating the results achieved by the user in the course of studying and the current progress status.

[0347] "Emotion data" is data that indicates the emotional state of the user analyzed from facial expressions, voice, etc.

[0348] The "performance evaluation report" is a report that compiles the user's learning progress and emotional data, and includes an evaluation of the learning content and suggestions for the next learning step.

[0349] "Generative AI" is AI that has the ability to generate new information or content based on instructions such as prompts.

[0350] The present invention is a system that supports daily learning by providing an individually customized learning curriculum based on the user's specific interests and goals. Furthermore, this system combines an emotion engine that recognizes the user's emotions, enabling more flexible and personalized instruction.

[0351] System Configuration

[0352] 1. User registration and initial settings

[0353] A user accesses the system and proceeds to the account creation page. Here, the user enters basic information such as name, age, country of residence, and email address. The device sends this information to the server, which stores the data in a database. The device then displays a survey asking about the user's interests and learning goals. After the user answers the survey, the results are sent to the server and stored in the database.

[0354] 2. Curriculum Generation

[0355] The server sends a curriculum generation request to the artificial intelligence module based on the user's basic information and the survey results. The artificial intelligence module uses the generative AI model to design the optimal curriculum for the user. The generated curriculum is sent to the server and stored in the database. The server then notifies the user.

[0356] 3. Emotion engine integration

[0357] The device is equipped with an emotion engine that analyzes emotions from the user's facial expressions and voice. The emotion engine collects emotional data as the user progresses through the study and analyzes it in real time. The analyzed emotional data is sent from the device to a server and stored in a database. This data is then sent to an artificial intelligence module, which adjusts the curriculum and learning content according to the user's emotions.

[0358] 4. Daily study support

[0359] During daily learning, the device displays learning reminders and the day's learning materials to the user. For example, a reminder such as "Today's learning content: Planets in the solar system" may be displayed. The user confirms this and begins learning. The device analyzes the user's facial expressions and voice and sends emotional data to the server. The server stores this data in a database and sends it to the artificial intelligence module. The artificial intelligence module adjusts the learning content accordingly based on the emotional data.

[0360] 5. Learning progress management and curriculum adjustment

[0361] When a user completes their learning, they input their progress data into the device and send it to the server, which then sends it to the server and stores it in a database. The server then sends this progress data and emotion data to an AI module, which then adjusts the curriculum and learning pace based on the month.

[0362] 6. Grading and Advice

[0363] The server periodically collects the user's learning progress and emotional data and generates a performance evaluation report, which includes the user's learning progress, performance evaluation, improvement points, and next steps. The device displays this report to the user and provides advice.

[0364] Specific examples

[0365] Example 1: Elementary school students learning about space

[0366] A user (elementary school student) wishes to learn about space, enters basic information, and answers "space" to a questionnaire about their interests.

[0367] The server requests the artificial intelligence module to generate a curriculum, and the artificial intelligence module generates the curriculum using the prompt "Please generate a space-related learning curriculum for 10-year-old elementary school students."

[0368] The device displays "Today's lesson: Planets of the solar system" and uses an emotion engine to analyze the user's emotions while they are learning. The emotion data is sent to a server, and the curriculum is adjusted as needed.

[0369] The user completes the study and enters the progress data into the terminal and transmits it to the server.

[0370] The server generates a performance evaluation report based on progress data and emotional data, and displays advice such as "Next learning step: The basics of the universe" on the device.

[0371] Example 2: Working adults seeking an MBA

[0372] The user (a working adult) enters basic information and a questionnaire, and answers that they are interested in "business management."

[0373] The server requests the artificial intelligence module to generate a curriculum, and the artificial intelligence module generates a curriculum including content such as "business strategy" and "financial analysis."

[0374] The device displays "Today's Study Topic: Financial Analysis," and the emotion engine analyzes the user's concentration while they are studying. If it determines that their concentration is declining, the AI ​​module will suggest new study topics or a break.

[0375] The user inputs the learning progress into the terminal and sends it to the server.

[0376] The server generates a performance evaluation report based on progress and emotion data and provides advice such as "Next step: Marketing."

[0377] In this way, the system provides an individually customized learning curriculum based on the user's interests and goals, and responds flexibly through real-time emotion analysis, thereby realizing lifelong learning support.

[0378] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0379] Specific processing of the system program

[0380] User registration and initial settings

[0381] Step 1:

[0382] A user accesses the system and proceeds to the account creation page. Input: Basic information such as name, age, country of residence, email address, etc. Output: An input form displayed on the terminal.

[0383] What happens: The user enters basic information such as name, age, country of residence, and email address.

[0384] Step 2:

[0385] The terminal sends the entered basic information to the server. Input: User's basic information. Output: User data sent to the server.

[0386] Specific operation: The device sends data to the server via the API.

[0387] Step 3:

[0388] The server stores the received basic information in a database. Input: User data sent to the server. Output: Basic information stored in the database.

[0389] Specific operation: The server calls the database save function and saves the basic information.

[0390] Step 4:

[0391] The device displays a questionnaire asking about the user's interests and learning goals. Input: Information accessed by the user. Output: Display of the questionnaire screen.

[0392] Specific operation: The terminal displays a predefined questionnaire form to the user.

[0393] Step 5:

[0394] The user answers the survey. Input: User's survey answers. Output: Survey data entered into the terminal.

[0395] What happens: The user answers questions about their interests and learning goals and submits the survey form.

[0396] Step 6:

[0397] The terminal sends the survey results to the server. Input: User's survey response data. Output: Survey data sent to the server.

[0398] Specific operation: The device sends the survey results to the server's API.

[0399] Step 7:

[0400] The server stores the survey results in a database. Input: Survey data sent to the server. Output: Survey results stored in a database.

[0401] Specific operation: The server calls the save function and saves the survey results in the database.

[0402] Curriculum Generation

[0403] Step 8:

[0404] The server sends a curriculum generation request to the AI ​​module based on the user's basic information and survey results. Input: Basic information, survey result data. Output: Request to the AI ​​module.

[0405] Specific operation: The server sends an API request for curriculum generation to the artificial intelligence module.

[0406] Step 9:

[0407] The artificial intelligence module uses a generative AI model to design a curriculum. Input: A prompt for curriculum generation (e.g., "Please generate a space-related curriculum for 10-year-old elementary school students."). Output: The generated curriculum.

[0408] Specific operation: The artificial intelligence module inputs prompt sentences into the generation AI and generates an appropriate curriculum.

[0409] Step 10:

[0410] The generated curriculum is sent to the server and stored in the database. Input: Generated curriculum data. Output: Curriculum stored in the database.

[0411] Specific operation: The artificial intelligence module sends the generated curriculum data to the server, which stores it in a database.

[0412] Step 11:

[0413] The server notifies the user of the curriculum generation. Input: Notification data of the generated curriculum. Output: Notification sent to the user.

[0414] Specific behavior: The server uses the notification system to notify the user of the curriculum creation.

[0415] Emotion engine integration

[0416] Step 12:

[0417] The device uses an emotion engine to analyze the user's emotions. Input: User's facial and voice data. Output: Analyzed emotion data.

[0418] Specific operation: The device uses a camera and microphone to collect facial expressions and voice, and performs real-time analysis using an emotion engine.

[0419] Step 13:

[0420] The device sends emotion data to the server. Input: Analyzed emotion data. Output: Emotion data sent to the server.

[0421] Specific operation: The device sends emotion data to the server's API.

[0422] Step 14:

[0423] The server stores the emotion data in a database. Input: Emotion data sent to the server. Output: Emotion data stored in the database.

[0424] Specific operation: The server calls the save function and saves the emotion data in the database.

[0425] Step 15:

[0426] The server sends the emotion data to the AI ​​module. Input: Emotion data stored in the database. Output: Data sent to the AI ​​module.

[0427] Specific operation: The server calls an API that sends emotion data to the artificial intelligence module.

[0428] Step 16:

[0429] The AI ​​module adjusts the curriculum and learning content based on the emotional data. Input: Emotional data. Output: Adjusted curriculum.

[0430] How it works: The AI ​​module analyzes emotional data and adjusts the user's learning content and pace.

[0431] Daily learning support

[0432] Step 17:

[0433] The device displays the study reminder to the user. Input: Study reminder data. Output: Display of reminder screen.

[0434] What it does: The device displays a reminder to the user, such as "Today's lesson: Planets in the solar system."

[0435] Step 18:

[0436] User starts learning. Input: Show reminder. Output: Start learning.

[0437] Specific Action: The user engages in the assigned learning content.

[0438] Step 19:

[0439] The device analyzes the emotion data being learned and sends it to the server. Input: Facial expression and voice data of the user being learned. Output: Emotion data sent to the server.

[0440] Specific operation: The device continuously analyzes the user's facial expressions and voice during training and sends emotional data to the server.

[0441] Step 20:

[0442] The server stores the emotion data in a database and sends it to the AI ​​module. Input: Emotion data sent during training. Output: Emotion data stored in the database.

[0443] Specific operation: The server saves the emotion data in a database and calls an API to send it to the artificial intelligence module.

[0444] Step 21:

[0445] The AI ​​module adjusts the learning content based on the emotional data. Input: Emotional data sent during learning. Output: Adjusted learning content.

[0446] Specific operation: The AI ​​module adjusts its learning content appropriately based on emotional data.

[0447] Learning progress management and curriculum adjustment

[0448] Step 22:

[0449] The user completes the study and inputs the progress data into the terminal. Input: Study progress data. Output: Progress data input into the terminal.

[0450] Specific operation: After completing the study, the user enters their progress into the terminal.

[0451] Step 23:

[0452] The device sends progress data to the server. Input: Progress data entered by the user. Output: Progress data sent to the server.

[0453] Specific operation: The device sends progress data to the server's API.

[0454] Step 24:

[0455] The server stores the progress data in a database. Input: Progress data sent to the server. Output: Progress data stored in the database.

[0456] Specific behavior: The server calls the save function to save the progress data to the database.

[0457] Step 25:

[0458] The server sends the progress data to the AI ​​module. Input: Progress data stored in the database. Output: Data sent to the AI ​​module.

[0459] Specific operation: The server calls an API that sends progress data to the artificial intelligence module.

[0460] Step 26:

[0461] The AI ​​module adjusts the curriculum based on progress data and emotion data. Input: progress data, emotion data. Output: adjusted curriculum.

[0462] Specific operation: The AI ​​module adjusts the curriculum based on progress data and emotional data.

[0463] Grading and Advice

[0464] Step 27:

[0465] The server aggregates the progress data and emotion data and generates a performance evaluation report. Input: Progress data, emotion data. Output: Performance evaluation report.

[0466] Specific operation: The server aggregates the progress data and emotion data and generates a performance evaluation report.

[0467] Step 28:

[0468] The server sends the grading report to the terminal. Input: grading report. Output: Report sent to the user.

[0469] Specific operation: The server calls an API to send the grade evaluation report to the terminal.

[0470] Step 29:

[0471] The terminal displays the performance evaluation report to the user and provides advice. Input: Performance evaluation report sent from the server. Output: Report and advice displayed to the user.

[0472] Specific operation: The device displays the performance evaluation report and advice to the user.

[0473] The above are the specific processing steps of the program for this system. This system responds to the individual needs of users and flexibly adjusts the curriculum to provide effective learning support.

[0474] (Application example 2)

[0475] 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."

[0476] Conventional learning support systems can generate a curriculum based on a user's learning progress and interests. However, they are unable to flexibly respond to the user's emotional and concentration states, making it difficult to maximize learning effectiveness. The present invention aims to provide more effective learning support by monitoring the user's emotional state in real time and adjusting the learning curriculum as needed.

[0477] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0478] In this invention, the server includes means for receiving basic information entered by a user and storing it in a database, means for displaying a questionnaire for entering the user's interests and learning goals and collecting the results, means for transmitting the collected data to an AI module for generating a curriculum based on the collected data, means for storing the curriculum generated by the AI ​​module in a database and notifying the user, means for displaying daily learning reminders and learning materials to the user, means for tracking the user's learning progress and storing it in a database, means for the AI ​​module to adjust the curriculum based on the learning progress data, means for periodically compiling the user's learning progress and generating a performance evaluation report, means for displaying the performance evaluation report to the user and providing advice, means for analyzing the user's emotions from facial expressions or voice, and means for transmitting data to the AI ​​module for adjusting the curriculum based on the analyzed emotional data. This enables more personalized and effective learning support by analyzing the user's emotional state in real time and adjusting the learning curriculum in a timely manner.

[0479] "Basic information" refers to data such as name, age, country of residence, and email address that a user enters into the system.

[0480] A "database" is a storage device that stores basic information about users, survey results, learning progress data, curriculum, and so on.

[0481] A "survey" is a question-based survey used to understand a user's interests and learning goals.

[0482] A "curriculum" is a plan of learning content and teaching materials generated by an AI module based on the user's interests and learning goals.

[0483] An "AI module" is an artificial intelligence component that analyzes user data and generates the optimal curriculum.

[0484] "Study reminders" are notifications and messages that encourage users to study every day.

[0485] "Study progress" is data indicating how far the user has progressed in their studies.

[0486] The "grade evaluation report" is a report on the evaluation of learning grades that is created based on the user's learning progress and emotional data.

[0487] "Emotion analysis" is the process of analyzing a user's emotional state from their facial expressions and voice.

[0488] A "generative AI model" is an artificial intelligence model used by an AI module to generate a curriculum.

[0489] To implement this invention, the following system configuration and program implementation are required: In particular, a database for managing basic user information and learning progress, an AI module for generating a curriculum, and an emotion engine for analyzing emotions are combined.

[0490] System Configuration

[0491] 1. Terminals and Servers

[0492] Users access the system using a smartphone, tablet, or PC (hereinafter referred to as the "terminal"). The terminal receives input from the user and transmits the data to the server. The server is the core of the system, including the database, AI module, and emotion engine.

[0493] 2. User registration and initial settings

[0494] Users enter basic information such as their name, age, country of residence, and email address, and send it to the server via their device. The server stores this information in a database. Users also answer a questionnaire to enter their interests and learning goals, and the results are also sent to the server and stored in the database.

[0495] 3. Curriculum Generation

[0496] The server sends a curriculum generation request to the AI ​​module based on the user's basic information and survey results. The AI ​​module uses the generative AI model to design an optimal curriculum for the user. This curriculum includes learning topics, materials, and learning pace. The generated curriculum is stored in a database via the server and notified to the user.

[0497] 4. Emotion engine integration

[0498] The device is equipped with an emotion engine that analyzes emotions from the user's facial expressions and voice. The emotion engine collects and analyzes the user's emotional data in real time while they are learning. The analysis results are sent to a server and stored in a database. The server then sends the emotional data to an AI module, which then adjusts the curriculum and learning content.

[0499] 5. Daily study support

[0500] During daily study, the device displays study reminders and the day's study materials to the user. The user confirms this and begins studying. The device analyzes the user's facial expressions and voice while studying and sends emotional data to the server. The server stores the emotional data in a database and sends it to the AI ​​module. The AI ​​module adjusts the study content as needed based on the emotional data.

[0501] 6. Learning progress management and curriculum adjustment

[0502] When a user completes their study, they input their progress into the device and send it. The device then sends the progress data to the server and stores it in a database. Based on the emotional data and learning progress data, the AI ​​module adjusts the curriculum and learning pace.

[0503] 7. Grading and Advice

[0504] The server periodically collects the user's learning progress and emotion data and generates a performance evaluation report, which includes the user's learning progress, performance evaluation, improvement points, and next steps. The terminal displays the performance evaluation report to the user and provides advice.

[0505] Specific examples

[0506] Example 1: Elementary school students learning about space

[0507] A user (elementary school student) wishes to learn about space, so he enters his basic information and answers "space" in the questionnaire.

[0508] The server requests the AI ​​module to generate a curriculum, and the AI ​​module generates a curriculum including "Basics of the Universe," "Planets in the Solar System," and "Simple Experiments."

[0509] The device displays daily study reminders, and an emotional engine analyzes the user's facial expressions and voice as they study. If it determines they have lost interest, the AI ​​module will adjust the curriculum and suggest new topics.

[0510] When the user completes the study, the study progress and emotional data are input into the terminal and transmitted to the server.

[0511] The server generates a performance evaluation report based on progress data and emotion data, and suggests next learning steps and areas for improvement.

[0512] Example 2: When a working adult studies business administration

[0513] A user (working adult) wishes to study business administration, enters basic information, and answers "business administration" in the questionnaire.

[0514] The server requests the AI ​​module to generate a curriculum, and the AI ​​module generates a curriculum including "business strategy," "financial analysis," and "marketing."

[0515] The device displays daily study reminders, and while the user is studying, the emotion engine analyzes the user's facial expressions and voice. If it determines that the user's concentration is declining, the AI ​​module will adjust the study content and encourage appropriate breaks.

[0516] When the user completes the study, the study progress and emotional data are input into the terminal and transmitted to the server.

[0517] The server generates a performance evaluation report based on progress data and emotion data, and suggests next learning steps and areas for improvement.

[0518] In this way, the system of the present invention provides a learning curriculum that is individually customized based on the user's interests and goals, and responds flexibly through real-time emotion analysis, thereby realizing lifelong learning support.

[0519] Examples of prompt statements

[0520] "Use generative AI models for curriculum generation."

[0521] "Please suggest the next learning step based on the sentiment analysis data."

[0522] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0523] Step 1:

[0524] The user uses the device to enter basic information (name, age, country of residence, email address) and submits it.

[0525] Input: Basic information entered by the user

[0526] Output: Basic information is sent to the server and stored in the database

[0527] Specific operation: The basic information entered on the terminal is sent to the server, which then stores it in a database.

[0528] Step 2:

[0529] The user answers and submits a survey on the device, entering their interests and learning goals.

[0530] Input: Survey results of interests and learning goals entered by users

[0531] Output: Survey results are sent to the server and stored in the database.

[0532] Specific operation: The user answers a questionnaire displayed on the terminal, and the data is sent to the server, which stores it in a database.

[0533] Step 3:

[0534] The server sends a curriculum generation request to the AI ​​module based on the user's basic information and survey results.

[0535] Input: User's basic information and survey results

[0536] Output: Send a curriculum generation request to the AI ​​module

[0537] Specific operation: The server references the user's basic information and survey results from the database and sends a request to the AI ​​module to design the optimal curriculum using a generative AI model.

[0538] Step 4:

[0539] The AI ​​module uses the generative AI model to design an optimal curriculum for the user and transmits the curriculum to the server.

[0540] Input: Curriculum generation request, user basic information and survey results

[0541] Output: Generated curriculum

[0542] Specific operation: The AI ​​module uses the generative AI model to analyze the data, generate a curriculum including learning topics, materials, and learning pace, and send it to the server.

[0543] Step 5:

[0544] The server stores the generated curriculum in a database and notifies the user.

[0545] Input: Generated curriculum

[0546] Output: Save the curriculum in the database and notify the user

[0547] Specific operation: The server saves the generated curriculum in a database and sends a notification to the terminal to inform the user of the new curriculum.

[0548] Step 6:

[0549] The device displays study reminders and the day's study materials to the user.

[0550] Input: Generated curriculum

[0551] Output: Display of study reminders and learning materials

[0552] Specific operation: The terminal displays daily study reminders and the day's learning materials to the user based on the curriculum received from the server.

[0553] Step 7:

[0554] The terminal uses an emotion engine to analyze emotions from the user's facial expressions and voice, and transmits the emotion data to the server.

[0555] Input: Facial expressions and voice of the user during training

[0556] Output: Parsed emotion data

[0557] Specific operation: The device uses a camera and microphone to capture the user's facial expressions and voice, and the emotion engine analyzes the data to recognize the user's emotional state and sends it to the server.

[0558] Step 8:

[0559] The server stores the emotional data in a database and sends it to an AI module to adjust the curriculum.

[0560] Input: Parsed emotion data

[0561] Output: Curriculum adjustment

[0562] How it works: The server stores the emotional data in a database and sends it to the AI ​​module, which then adjusts the content and pace of the curriculum based on the emotional data.

[0563] Step 9:

[0564] When the user completes the study, he / she inputs the study progress into the terminal and transmits it.

[0565] Input: Learning progress data

[0566] Output: Study progress data sent to server and saved in database

[0567] Specific operation: When the user completes learning, he / she inputs the progress data into the terminal, which then sends it to the server, which stores it in the database.

[0568] Step 10:

[0569] The server generates a performance evaluation report based on the learning progress data and emotion data and notifies the user.

[0570] Input: learning progress data, emotion data

[0571] Output: Generate and notify grade evaluation report

[0572] Specific operation: The server analyzes the progress data and emotion data, generates a performance evaluation report, and notifies the user via the terminal.

[0573] Examples of prompt statements

[0574] "Use generative AI models for curriculum generation."

[0575] "Please suggest the next learning step based on the sentiment analysis data."

[0576] 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.

[0577] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (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.

[0578] 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.

[0579] [Second embodiment]

[0580] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0581] 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.

[0582] 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).

[0583] 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.

[0584] 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.

[0585] 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).

[0586] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for 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.

[0587] 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.

[0588] 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.

[0589] 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.

[0590] In the smart glasses 214, the 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.

[0591] 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."

[0592] This invention relates to an AI tutoring system that supports daily learning by providing users with individually customized learning curricula based on their specific interests and goals. Below, we will explain the program processing of this system in natural language and provide specific examples.

[0593] System Configuration

[0594] 1. User registration and initial settings

[0595] A user accesses the system and proceeds to the account creation page. First, the user enters basic information such as their name, age, country of residence, email address, etc. This information is sent to the server via the terminal, and the server stores the received information in a database.

[0596] The device then displays a questionnaire to the user asking about their interests and learning goals. When the user answers the questionnaire, the results are sent from the device to the server and stored in a database.

[0597] 2. Curriculum Generation

[0598] The server sends a curriculum generation request to the AI ​​module based on the user's basic information and survey results. The AI ​​module uses generative AI to design a curriculum that is optimal for the user. This curriculum includes learning topics, materials, and learning pace.

[0599] The generated curriculum is sent to the server, which stores it in a database and notifies the user.

[0600] 3. Daily learning support

[0601] For daily learning, the device displays daily learning reminders and the day's study materials to the user. For example, a reminder such as "Today's learning content: Planets of the solar system" is displayed. The user confirms this and begins studying.

[0602] Once the user has completed their learning, the device will send progress information to the server, which will store it in a database and send it to the AI ​​module in a timely manner.

[0603] 4. Learning progress management and curriculum adjustment

[0604] The AI ​​module analyzes the user's progress data to check whether the learning content is appropriate. If necessary, it adjusts the curriculum and suggests new materials and a learning pace. The adjusted curriculum is saved in a database on the server and notified to the user.

[0605] 5. Grading and Advice

[0606] The server periodically aggregates the user's learning progress and generates a performance evaluation report, which includes the user's learning progress, performance evaluation, improvement points, and next steps.

[0607] The device displays this performance evaluation report to the user and provides advice, such as "Next time, focus on the topic of XX."

[0608] Specific examples

[0609] Example 1: Elementary school students learning about space

[0610] A user (elementary school student) wants to learn about space. He enters basic information and answers "space" in a questionnaire about his interests.

[0611] The terminal sends the survey results to the server, and the server requests the AI ​​module to generate a curriculum.

[0612] The AI ​​module generates a curriculum including "Space Basics," "Planets of the Solar System," and "Simple Space Experiments."

[0613] Each day, the device displays reminders and educational materials, such as "Today's learning: Planets in the solar system."

[0614] Users study and report their progress, and the server records the progress data and adjusts the curriculum as needed.

[0615] Example 2: Working adults seeking an MBA

[0616] The user (a working adult) aims to obtain an MBA, enters basic information, and answers "business administration" to a questionnaire about interests.

[0617] The server requests the AI ​​module to generate a curriculum, and the AI ​​module generates a curriculum including "business strategy," "financial analysis," and "marketing."

[0618] Each day, the device displays reminders and learning materials such as "Today's learning topic: Financial analysis."

[0619] Users study and report their progress. The server records the progress data and generates a performance report that includes next steps and areas for improvement.

[0620] In this way, this system provides a learning curriculum that is individually customized based on the user's interests and goals, thereby supporting lifelong learning. This invention improves the quality of education and allows users to continue learning in a way that is best suited to them.

[0621] The above is the "Mode for Carrying Out the Invention."

[0622] The processing flow will be explained below.

[0623] Step 1:

[0624] A user accesses the system and proceeds to the account creation page. The terminal displays a form for entering basic information such as name, age, country of residence, email address, etc. The user enters the information and clicks the submit button.

[0625] Step 2:

[0626] The device sends the entered basic information to the server, which stores the received information in a database and notifies the user via the device that account creation has been completed.

[0627] Step 3:

[0628] The terminal displays a questionnaire to the new user asking about their interests and learning goals. The user answers the questionnaire and submits the results.

[0629] Step 4:

[0630] The device sends the survey results to the server, which stores them in a database and sends the data to the AI ​​module.

[0631] Step 5:

[0632] The server sends a curriculum generation request to the AI ​​module based on the user's basic information and the survey results. The AI ​​module uses the generation AI to design the optimal curriculum for the user.

[0633] Step 6:

[0634] The AI ​​module sends the generated curriculum to the server, which stores it in a database and notifies the user.

[0635] Step 7:

[0636] The device displays daily study reminders and the day's study materials to the user, who then begins studying with the materials presented.

[0637] Step 8:

[0638] When the user completes the study, he / she enters the study progress into the terminal and clicks the send button.

[0639] Step 9:

[0640] The device sends learning progress data to the server, which stores this data in a database and sends it to the AI ​​module as needed.

[0641] Step 10:

[0642] The AI ​​module analyzes the user's progress data, determines whether the learning content is appropriate, adjusts the curriculum as necessary, and sends the adjusted curriculum to the server.

[0643] Step 11:

[0644] The server stores the adjusted curriculum in a database and notifies the user.

[0645] Step 12:

[0646] The server periodically aggregates the user's learning progress and generates a performance evaluation report, which includes the user's learning progress, performance evaluation, improvement points, and next steps.

[0647] Step 13:

[0648] The device displays the performance evaluation report to the user and provides advice, allowing the user to adjust their learning methods and goals based on the evaluation results.

[0649] The above is a concrete explanation of the processing steps of the program.

[0650] Example 1

[0651] 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."

[0652] Conventional learning support systems are unable to respond to the individual learning needs and progress of each user, and are limited to providing a uniform curriculum. In addition, it is difficult for users to manage their learning progress and receive appropriate feedback and advice, which hinders effective learning.

[0653] 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.

[0654] In this invention, the server includes means for receiving personal information entered by the user and storing it in a storage device, means for displaying a survey form for entering the user's interests and learning goals and collecting the results, and means for transmitting the collected data to an AI module to generate a curriculum based on the data. This allows for the provision of a curriculum that meets the individual learning needs of each user, enabling effective learning.

[0655] "Personal information" refers to information necessary to identify an individual, such as a user's name, age, country of residence, and email address.

[0656] A "memory device" is a device that electronically stores and manages information, such as a database or storage.

[0657] A "survey" is a questionnaire or form used to gather information about a user's interests, learning goals, etc.

[0658] An "AI module" is a component that uses artificial intelligence to perform processes such as curriculum generation and learning progress analysis.

[0659] A "curriculum" is a collection of learning plans and materials organized around a user's learning goals.

[0660] "Study reminders" are messages and alerts that inform users of their daily learning content and progress.

[0661] "Study progress" is data on the progress status that indicates how far the user has progressed toward the learning goal set by the user.

[0662] A "performance evaluation report" is a document that evaluates a user's learning progress and lists their grades, areas for improvement, and next steps.

[0663] "Advice" is specific advice or instruction provided to support the user's learning.

[0664] "Generative AI" is an artificial intelligence technology that generates optimal curriculum and advice based on data entered by the user.

[0665] This invention relates to an AI tutoring system that supports daily learning by providing users with individually customized learning curricula based on their specific interests and goals. The program processing of this system is explained below in natural language.

[0666] System Overview

[0667] This system mainly consists of the following elements:

[0668] server

[0669] Terminal

[0670] User

[0671] Generative AI Models

[0672] storage device

[0673] Registering users and saving basic information

[0674] When a user accesses the system, an account creation page is displayed. The user enters personal information such as name, age, country of residence, and email address. This information is sent to the server via the terminal, and the server stores it in a storage device. The terminal then displays a survey form about the user's interests and learning goals, which the user answers. The survey results are again sent to the server via the terminal and stored in a storage device.

[0675] Curriculum generation

[0676] The server sends a curriculum generation request to the generative AI model based on the user's basic information and the survey results. Specifically, the following prompt sentence is used:

[0677] "Please create a curriculum for elementary school students to learn about space. Specifically, please include the basics of space, planets in the solar system, and simple space experiments."

[0678] "Please create a curriculum for working professionals seeking an MBA. Specifically, please include business strategy, financial analysis, and marketing."

[0679] The generative AI model generates a curriculum based on these prompts and sends it to the server. The server stores the received curriculum in a storage device and notifies the user. The device then informs the user that "a curriculum has been generated."

[0680] Daily learning support

[0681] During daily learning, the server sends the day's learning content and reminders to the device. For example, the device displays a reminder such as "Today's learning content: Planets of the solar system." This allows the user to start learning with the specified learning material. Once the learning is complete, the user enters progress information into the device, which then sends it to the server. The progress information is stored in a storage device.

[0682] Learning progress management and curriculum adjustment

[0683] The server periodically sends the user's learning progress data to the generative AI model for analysis. The generative AI model adjusts the curriculum based on the user's progress and suggests new learning paces and materials. The adjusted curriculum is saved in a storage device from the server and notified to the user.

[0684] Grading and Advice

[0685] The server periodically collects the user's learning progress data and generates a performance evaluation report, which includes a performance evaluation, areas for improvement, and next steps. The terminal displays the performance evaluation report to the user and provides specific advice, such as "Next time, focus on the topic of XX."

[0686] Specific examples

[0687] When elementary school students learn about space

[0688] The user (elementary school student) enters basic information and answers "space" to a questionnaire about interests.

[0689] The terminal sends the survey results to the server and requests the AI ​​module to generate a curriculum.

[0690] The generative AI model generates a curriculum including "Space Basics," "Planets of the Solar System," and "Simple Space Experiments."

[0691] Each day, the device displays reminders and educational materials, such as "Today's learning: Planets in the solar system."

[0692] Users study and report their progress, and the server records the progress data and adjusts the curriculum as needed.

[0693] The above is a specific embodiment for carrying out the invention. This system allows users to continue learning in a way that is optimal for them.

[0694] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0695] Step 1: Enter and save basic user information

[0696] When a user accesses the system, they are presented with an account creation page.

[0697] The user enters personal information such as name, age, country of residence, email address, etc. This input data is sent to the terminal.

[0698] The terminal transmits the entered personal information to the server.

[0699] The server stores the received personal information in a storage device.

[0700] Output: The registered user's personal information is saved to the storage device.

[0701] Step 2: View the survey and save the results

[0702] The terminal presents the user with a survey of interests and learning goals.

[0703] The user answers the survey and the results are sent to the terminal.

[0704] The terminal transmits the results of the survey to the server.

[0705] The server stores the results of the investigation in a storage device.

[0706] Output: Data about the user's interests and learning goals is saved to a storage device.

[0707] Step 3: Submit a curriculum generation request

[0708] The server creates prompts for curriculum generation based on the user's basic information and survey results.

[0709] Input: User basic information and survey results

[0710] Output: Curriculum-generated prompt

[0711] The server sends the generated prompt sentence as a request to the generative AI model.

[0712] Example: "Generate a curriculum for elementary school students to learn about space. Specifically, include the basics of space, planets in the solar system, and simple space experiments."

[0713] Step 4: Generate and save the curriculum

[0714] The generative AI model generates a learning curriculum based on the prompt sentence.

[0715] Input: Curriculum generation prompt

[0716] Output: Generated learning curriculum

[0717] The server receives the generated curriculum and stores it in a storage device.

[0718] The terminal notifies the user that "The curriculum has been generated."

[0719] Step 5: View study reminders and materials

[0720] The server sends the day's learning content and reminders to the device.

[0721] The device displays reminders and educational materials to the user, such as "Today's learning: Planets in the solar system."

[0722] Input: Today's learning content and reminders

[0723] Output: Reminders and educational materials displayed to the user

[0724] Step 6: Enter and save your learning progress

[0725] The user checks the reminder and continues studying.

[0726] When the user has completed the learning, the terminal displays a "Learning Completed" button.

[0727] When the user clicks the button, progress information is sent to the terminal.

[0728] The terminal sends progress information to the server.

[0729] The server stores the progress information in a storage device.

[0730] Input: Learning progress information

[0731] Output: Learning progress information stored in memory.

[0732] Step 7: Analyze learning progress data and adjust curriculum

[0733] The server periodically sends progress data to the generative AI model.

[0734] The generative AI model analyzes the user's progress data to ensure that the learning content is appropriate.

[0735] Input: Learning progress data

[0736] Output: Analysis results and adjustment suggestions

[0737] If necessary, the generative AI model will adjust the curriculum.

[0738] The server receives the tailored curriculum and stores it in a storage device.

[0739] The terminal notifies the user of the adjusted curriculum.

[0740] Step 8: Generate and view the grading report

[0741] The server periodically compiles the user's learning progress data and generates a performance evaluation report.

[0742] Input: Learning progress data

[0743] Output: Grade evaluation report

[0744] The terminal displays the performance evaluation report to the user and provides specific advice.

[0745] For example, advice such as "Next time, let's focus on the topic of XX."

[0746] The above are the specific processing steps of this system's program. This makes it possible to provide an optimal curriculum for each user, manage learning progress, and provide appropriate feedback.

[0747] (Application example 1)

[0748] 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."

[0749] Conventional tutoring systems lack the ability to customize to meet the individual learning needs and goals of users, resulting in a decline in learning effectiveness. Furthermore, the lack of interactive learning content utilizing smart devices has led to issues such as difficulty in maintaining motivation to learn.

[0750] 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.

[0751] In this invention, the server includes means for receiving basic information input by a user and storing it in a data management device, means for displaying a survey for inputting the user's interests and learning goals and collecting the results, means for transmitting the collected data to an intelligence module for generating an educational plan based on the collected data, means for storing the educational plan generated by the intelligence module in the data management device and notifying the user, means for displaying daily learning notifications and educational materials to the user, means for tracking the user's learning progress and storing it in the data management device, means for the intelligence module to adjust the educational plan based on the learning progress data, means for periodically compiling the user's learning progress and generating a performance evaluation report, means for displaying the performance evaluation report to the user and providing advice, and means for delivering interactive learning content on devices such as smart glasses and mobile terminals, thereby enabling a highly customized learning experience tailored to the user's individual needs.

[0752] "User" refers to any individual or entity that uses the System.

[0753] "Basic information" refers to personal information such as the user's name, age, place of residence, and email address.

[0754] "Data Management Device" refers to a system or device for storing and managing information collected from users.

[0755] "Survey" refers to a questionnaire-style interface that includes questions about the user's interests and learning goals.

[0756] "Intelligence Module" refers to a program containing artificial intelligence algorithms for generating an optimal training plan based on user input data.

[0757] "Educational Plan" means a plan including curriculum, materials, and learning pace designed to achieve a user's learning goals.

[0758] "Notification" refers to the action of sending important information or reminders from the system to the user.

[0759] "Educational materials" refers to teaching materials and content used for learning, such as texts, videos, and quizzes.

[0760] "Study progress" refers to data indicating how much of the learning content a user has completed.

[0761] "Performance evaluation report" refers to a report that compiles and evaluates a user's learning outcomes and progress.

[0762] "Advice" refers to advice on the user's learning and suggestions for next steps.

[0763] "Smart glasses" refers to a glasses-type device equipped with augmented reality and information display functions.

[0764] "Mobile device" refers to a portable electronic device such as a smartphone or tablet.

[0765] "Interactive learning content" refers to educational content that allows users to actively participate and learn while receiving feedback.

[0766] This invention relates to an AI tutoring system that supports daily learning by providing a personalized learning curriculum based on a user's specific interests and goals. The system can deliver interactive learning content on devices such as smart glasses and mobile terminals.

[0767] System Configuration

[0768] 1. User registration and initial settings

[0769] The user navigates to an account creation page on the device. First, the user enters basic information such as their name, age, place of residence, and email address. This information is sent to the server via the device, and the server stores the received information in a data management device. The device then displays a survey asking the user about their interests and learning goals. After the user completes the survey, the results are sent from the device to the server and stored in the data management device.

[0770] 2. Curriculum Generation

[0771] The server sends a request to the intelligent module to generate a learning plan based on the user's basic information and survey results. The intelligent module uses the generative AI model to design an optimal learning plan for the user. This learning plan includes learning topics, materials, and learning pace. The generated learning plan is sent to the server, stored in the data management device, and notified to the user.

[0772] 3. Daily learning support

[0773] During daily learning, the device displays daily learning notifications and the day's educational materials to the user. For example, a notification such as "Today's learning content: Planets in the solar system" is displayed. The user confirms this and begins learning. When the user completes their learning, the device sends progress information to the server. The server stores this information in the data management device and transmits it to the intelligent module in a timely manner.

[0774] 4. Managing learning progress and adjusting educational plans

[0775] The intelligent module analyzes the user's progress data to determine whether the learning content is appropriate. If necessary, it adjusts the learning plan and suggests new learning materials and a learning pace. The adjusted learning plan is then stored in the data management device from the server and notified to the user.

[0776] 5. Grading and Advice

[0777] The server periodically compiles the user's learning progress and generates a performance evaluation report. This report includes the user's learning progress, performance evaluation, areas for improvement, and next steps. The device displays this performance evaluation report to the user and provides advice. For example, specific advice such as "Next time, focus on topic XX" may be included.

[0778] Detailed processing

[0779] The basic information and survey results entered by the user are sent to the server via the device. The server stores this data in a data management device and sends it to an intelligence module (a generative AI model such as GPT-3). The intelligence module generates an optimal educational plan for the user based on the prompt sentence. For example, the following prompt sentences can be used:

[0780] Prompt Sentence Examples

[0781] User information: Name = Taro Tanaka, Age = 25, Interests = Programming, Level = Beginner

[0782] Survey results: Learning goal = Web development, Hobby = Game development, Study time = 1 hour / day

[0783] Generated curriculum:

[0784] Week 1: HTML / CSS Basics

[0785] Week 2: JavaScript Basics

[0786] Week 3: Simple web application development

[0787] Week 4: Game Development Fundamentals

[0788] The generated educational plan is stored in a data management device and sent to the user's device. The user receives daily learning notifications and begins studying. Learning progress is sent to the server in real time, and an intelligent module analyzes it and periodically adjusts the educational plan. Overall, this system provides users with a customized learning experience, enabling them to continue learning while maintaining their motivation.

[0789] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0790] Step 1:

[0791] The user accesses the account creation page using a terminal and enters basic information (name, age, place of residence, email address, etc.). The terminal sends the entered basic information to the server, which then stores the information in the data management device.

[0792] Input: Basic information such as name, age, place of residence, and email address

[0793] Output: Basic information of the user stored in the data management device

[0794] Step 2:

[0795] The device displays a survey to the user asking about their interests and learning goals. After the user completes the survey, the device transmits the results to a server, which stores the survey results in a data management device.

[0796] Input: Survey results about user interests and learning goals

[0797] Output: Survey results stored in the data management device

[0798] Step 3:

[0799] The server sends a request for generating an educational plan to the intelligence module based on the user's basic information and the survey results. The intelligence module uses the generative AI model to generate the optimal educational plan for the user. This process is based on the prompt text.

[0800] Input: User basic information and survey results stored in the data management device

[0801] Output: The training plan generated by the intelligence module

[0802] Step 4:

[0803] The intelligent module sends the generated training plan to the server, which stores it in the data management device and notifies the user, who then displays the notification to the terminal, allowing the user to confirm the training plan.

[0804] Input: Educational plan generated by the intelligence module

[0805] Output: Education plan stored in the data management device and notification displayed to the user

[0806] Step 5:

[0807] Every day, the device displays a learning notification and the day's educational material to the user. The user checks the notification and begins learning.

[0808] Input: Educational materials for the day stored in the data management device

[0809] Output: Learning notifications and educational materials displayed on the device

[0810] Step 6:

[0811] When the user completes the learning, the terminal transmits the progress information to the server, which stores the progress information in the data management device.

[0812] Input: User learning progress information

[0813] Output: Learning progress information stored in the data management device

[0814] Step 7:

[0815] The server periodically transmits the learning progress data to the intelligent module, which analyzes the data and adjusts the educational plan, which is then stored in the data management device by the server and notified to the user.

[0816] Input: Learning progress data stored in the data management device

[0817] Output: Coordinated educational plan

[0818] Step 8:

[0819] The server periodically compiles the user's learning progress and generates a performance evaluation report, which includes the user's learning progress, performance evaluation, areas for improvement, and next steps. The terminal displays the performance evaluation report to the user and provides advice.

[0820] Input: Aggregated data based on learning progress stored in the data management device

[0821] Output: A grading report and advice displayed to the user

[0822] The above are the specific processing steps of this system.

[0823] 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.

[0824] This invention relates to an AI tutoring system that supports daily learning by providing a personalized learning curriculum based on the user's specific interests and goals. Furthermore, this system combines an emotion engine that recognizes the user's emotions, enabling more flexible and personalized instruction.

[0825] System Configuration

[0826] 1. User registration and initial settings

[0827] A user accesses the system and proceeds to the account creation page. First, the user enters basic information such as their name, age, country of residence, email address, etc. The device sends the entered information to the server, which stores it in a database.

[0828] Next, the device displays a questionnaire to the user asking about their interests and learning goals. After the user answers the questionnaire, the results are sent to the server and stored in a database.

[0829] 2. Curriculum Generation

[0830] The server sends a curriculum generation request to the AI ​​module based on the user's basic information and survey results. The AI ​​module uses generative AI to design a curriculum that is optimal for the user. This curriculum includes learning topics, materials, and learning pace.

[0831] The generated curriculum is sent to the server and stored in a database, and the server notifies the user.

[0832] 3. Emotion engine integration

[0833] The device is equipped with an emotion engine that analyzes the user's emotions from their facial expressions and voice. The emotion engine collects emotional data as the user progresses through the learning process and analyzes it in real time.

[0834] Emotion analysis data is sent from the device to a server. The server stores the emotional data in a database and sends it to an AI module. The AI ​​module adjusts the curriculum and learning content according to the user's emotions.

[0835] 4. Daily study support

[0836] For daily study, the device displays study reminders and the day's study materials to the user. For example, a reminder such as "Today's study topic: Planets in the solar system" is displayed. The user confirms this and begins studying.

[0837] The device analyzes the user's facial expressions and voice and sends emotional data to the server, which stores it in a database and sends it to the AI ​​module, which then adjusts its learning content accordingly.

[0838] 5. Learning progress management and curriculum adjustment

[0839] When a user completes their study, they input their progress into the device and send it. The device then sends the progress data to the server and stores it in a database. Based on the emotional data and learning progress data, the AI ​​module adjusts the curriculum and learning pace.

[0840] 6. Grading and Advice

[0841] The server periodically collects the user's learning progress and emotion data and generates a performance evaluation report, which includes the user's learning progress, performance evaluation, improvement points, and next steps. The terminal displays the performance evaluation report to the user and provides advice.

[0842] Specific examples

[0843] Example 1: Elementary school students learning about space

[0844] A user (elementary school student) wants to learn about space. He enters basic information and answers "space" in a questionnaire about his interests.

[0845] The server requests the AI ​​module to generate a curriculum, and the AI ​​module generates a curriculum including "Basics of the Universe," "Planets in the Solar System," and "Simple Experiments."

[0846] Every day, the device displays "Today's learning content: Planets of the solar system," and as the user progresses, the emotion engine analyzes the user's facial expressions and voice. If it determines that the user has lost interest, the AI ​​module adjusts the curriculum and suggests new topics.

[0847] When the user completes the study, the study progress and emotional data are input into the terminal and transmitted to the server.

[0848] The server generates a performance evaluation report based on progress data and emotion data, and suggests next learning steps and areas for improvement.

[0849] Example 2: Working adults seeking an MBA

[0850] The user (a working adult) aims to obtain an MBA, enters basic information, and answers "business administration" to a questionnaire about interests.

[0851] The server requests the AI ​​module to generate a curriculum, and the AI ​​module generates a curriculum including "business strategy," "financial analysis," and "marketing."

[0852] Every day, the device displays "Today's learning content: Financial analysis," and as the user progresses through the learning process, the emotion engine analyzes the user's facial expressions and voice. If the AI ​​module determines that the user's concentration is declining, it adjusts the learning content and encourages them to take a break at the appropriate time.

[0853] The user inputs learning progress and emotional data into the terminal and transmits it to the server.

[0854] The server generates a performance evaluation report based on progress data and emotion data, and suggests next learning steps and areas for improvement.

[0855] This system provides a personalized learning curriculum based on the user's interests and goals, and responds flexibly through real-time emotion analysis, enabling lifelong learning support. This invention improves the quality of education and allows users to continue learning in a way that is best suited to them.

[0856] The above is the "Mode for Carrying Out the Invention."

[0857] The processing flow will be explained below.

[0858] Step 1:

[0859] A user accesses the system and proceeds to the account creation page. The terminal displays a form for entering basic information such as name, age, country of residence, email address, etc. The user enters the information and clicks the submit button.

[0860] Step 2:

[0861] The device sends the entered basic information to the server, which stores the received information in a database and notifies the user via the device that account creation has been completed.

[0862] Step 3:

[0863] The terminal displays a questionnaire to the new user asking about their interests and learning goals. The user answers the questionnaire and submits the results.

[0864] Step 4:

[0865] The device sends the survey results to the server, which stores them in a database and sends the data to the AI ​​module.

[0866] Step 5:

[0867] The server sends a curriculum generation request to the AI ​​module based on the user's basic information and the survey results. The AI ​​module uses the generation AI to design the optimal curriculum for the user.

[0868] Step 6:

[0869] The AI ​​module sends the generated curriculum to the server, which stores it in a database and notifies the user.

[0870] Step 7:

[0871] The device displays daily study reminders and the day's learning materials to the user. For example, a reminder might say, "Today's learning content: Planets in the solar system." The user then begins studying the materials provided.

[0872] Step 8:

[0873] While the user is learning, the device's built-in emotion engine analyzes the user's facial expressions and voice to collect emotional data, including facial expression analysis and voice tone analysis.

[0874] Step 9:

[0875] The device sends the collected emotional data to a server, which stores the data in a database and sends it to an AI module.

[0876] Step 10:

[0877] The AI ​​module analyzes emotional and learning progress data and adjusts learning content and methods based on the user's current emotional state. For example, if the user is tired, it will suggest a break or switch to a less difficult problem.

[0878] Step 11:

[0879] The server stores the adjusted curriculum in a database and notifies the user.

[0880] Step 12:

[0881] When the user completes the study, they input their study progress into the device and click the send button. The device then sends the study progress data and emotion data to the server.

[0882] Step 13:

[0883] The server stores the learning progress data and emotion data in a database and periodically aggregates them to generate a performance evaluation report, which includes the user's learning progress, performance evaluation, improvement points, and next steps.

[0884] Step 14:

[0885] The device displays a performance evaluation report to the user and offers advice, such as "Next time, try taking breaks to improve your concentration."

[0886] Step 15:

[0887] The server collects user feedback and sends it to the AI ​​module for further curriculum optimization.

[0888] The above is a concrete explanation of the processing steps of the system that integrates the emotion engine.

[0889] Example 2

[0890] 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."

[0891] In recent years, there has been a demand for individually customized learning support systems, but existing systems lack the flexibility to respond sufficiently to users' interests and goals. Furthermore, they lack the ability to analyze users' emotions in real time and adjust the curriculum accordingly, resulting in the problem of only being able to provide uniform instruction. Furthermore, the management of learning progress and grade evaluation are still done manually, which is inefficient and affects users' ability to continue learning. There is a need for a comprehensive learning support system that can solve these issues.

[0892] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving basic information entered by a user and storing it in a database, means for displaying a questionnaire for entering the user's interests and learning goals and collecting the results, means for transmitting data to an artificial intelligence module to generate a curriculum based on the collected data, means for storing the curriculum generated by the artificial intelligence module in a database and notifying the user, means for displaying daily learning reminders and learning materials to the user, means for tracking the user's learning progress and storing it in a database, means for the artificial intelligence module to adjust the curriculum based on learning progress data, means for analyzing emotions from the user's facial expressions and voice, sending the analyzed data to the server and storing it in a database, means for adjusting the curriculum and learning content based on the emotion data, means for periodically compiling the user's learning progress and emotion data and generating a performance evaluation report, and means for displaying the performance evaluation report to the user and providing advice. This enables the provision of a customized learning curriculum tailored to the user's interests and goals and flexible learning support based on emotion analysis.

[0893] "Basic information" refers to personal information such as name, age, country of residence, and email address that a user enters when registering with the system.

[0894] A "survey" is a collection of questions displayed to gather information about a user's interests and learning goals.

[0895] An "artificial intelligence module" is a program that includes artificial intelligence capabilities to generate a curriculum based on collected data and tailor it to the user's individual needs.

[0896] A "curriculum" is a set of learning plans, including learning content, learning materials, and learning pace, designed based on a user's learning goals.

[0897] "Reminder" is a system function that notifies users of the day's study content and schedule.

[0898] "Study progress" is information indicating the results achieved by the user in the course of studying and the current progress status.

[0899] "Emotion data" is data that indicates the emotional state of the user analyzed from facial expressions, voice, etc.

[0900] The "performance evaluation report" is a report that compiles the user's learning progress and emotional data, and includes an evaluation of the learning content and suggestions for the next learning step.

[0901] "Generative AI" is AI that has the ability to generate new information or content based on instructions such as prompts.

[0902] The present invention is a system that supports daily learning by providing an individually customized learning curriculum based on the user's specific interests and goals. Furthermore, this system combines an emotion engine that recognizes the user's emotions, enabling more flexible and personalized instruction.

[0903] System Configuration

[0904] 1. User registration and initial settings

[0905] A user accesses the system and proceeds to the account creation page. Here, the user enters basic information such as name, age, country of residence, and email address. The device sends this information to the server, which stores the data in a database. The device then displays a survey asking about the user's interests and learning goals. After the user answers the survey, the results are sent to the server and stored in the database.

[0906] 2. Curriculum Generation

[0907] The server sends a curriculum generation request to the artificial intelligence module based on the user's basic information and the survey results. The artificial intelligence module uses the generative AI model to design the optimal curriculum for the user. The generated curriculum is sent to the server and stored in the database. The server then notifies the user.

[0908] 3. Emotion engine integration

[0909] The device is equipped with an emotion engine that analyzes emotions from the user's facial expressions and voice. The emotion engine collects emotional data as the user progresses through the study and analyzes it in real time. The analyzed emotional data is sent from the device to a server and stored in a database. This data is then sent to an artificial intelligence module, which adjusts the curriculum and learning content according to the user's emotions.

[0910] 4. Daily study support

[0911] During daily learning, the device displays learning reminders and the day's learning materials to the user. For example, a reminder such as "Today's learning content: Planets in the solar system" may be displayed. The user confirms this and begins learning. The device analyzes the user's facial expressions and voice and sends emotional data to the server. The server stores this data in a database and sends it to the artificial intelligence module. The artificial intelligence module adjusts the learning content accordingly based on the emotional data.

[0912] 5. Learning progress management and curriculum adjustment

[0913] When a user completes their learning, they input their progress data into the device and send it to the server, which then sends it to the server and stores it in a database. The server then sends this progress data and emotion data to an AI module, which then adjusts the curriculum and learning pace based on the month.

[0914] 6. Grading and Advice

[0915] The server periodically collects the user's learning progress and emotional data and generates a performance evaluation report, which includes the user's learning progress, performance evaluation, improvement points, and next steps. The device displays this report to the user and provides advice.

[0916] Specific examples

[0917] Example 1: Elementary school students learning about space

[0918] A user (elementary school student) wishes to learn about space, enters basic information, and answers "space" to a questionnaire about their interests.

[0919] The server requests the artificial intelligence module to generate a curriculum, and the artificial intelligence module generates the curriculum using the prompt "Please generate a space-related learning curriculum for 10-year-old elementary school students."

[0920] The device displays "Today's lesson: Planets of the solar system" and uses an emotion engine to analyze the user's emotions while they are learning. The emotion data is sent to a server, and the curriculum is adjusted as needed.

[0921] The user completes the study and enters the progress data into the terminal and transmits it to the server.

[0922] The server generates a performance evaluation report based on progress data and emotional data, and displays advice such as "Next learning step: The basics of the universe" on the device.

[0923] Example 2: Working adults seeking an MBA

[0924] The user (a working adult) enters basic information and a questionnaire, and answers that they are interested in "business management."

[0925] The server requests the artificial intelligence module to generate a curriculum, and the artificial intelligence module generates a curriculum including content such as "business strategy" and "financial analysis."

[0926] The device displays "Today's Study Topic: Financial Analysis," and the emotion engine analyzes the user's concentration while they are studying. If it determines that their concentration is declining, the AI ​​module will suggest new study topics or a break.

[0927] The user inputs the learning progress into the terminal and sends it to the server.

[0928] The server generates a performance evaluation report based on progress and emotion data and provides advice such as "Next step: Marketing."

[0929] In this way, the system provides an individually customized learning curriculum based on the user's interests and goals, and responds flexibly through real-time emotion analysis, thereby realizing lifelong learning support.

[0930] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0931] Specific processing of the system program

[0932] User registration and initial settings

[0933] Step 1:

[0934] A user accesses the system and proceeds to the account creation page. Input: Basic information such as name, age, country of residence, email address, etc. Output: An input form displayed on the terminal.

[0935] What happens: The user enters basic information such as name, age, country of residence, and email address.

[0936] Step 2:

[0937] The terminal sends the entered basic information to the server. Input: User's basic information. Output: User data sent to the server.

[0938] Specific operation: The device sends data to the server via the API.

[0939] Step 3:

[0940] The server stores the received basic information in a database. Input: User data sent to the server. Output: Basic information stored in the database.

[0941] Specific operation: The server calls the database save function and saves the basic information.

[0942] Step 4:

[0943] The device displays a questionnaire asking about the user's interests and learning goals. Input: Information accessed by the user. Output: Display of the questionnaire screen.

[0944] Specific operation: The terminal displays a predefined questionnaire form to the user.

[0945] Step 5:

[0946] The user answers the survey. Input: User's survey answers. Output: Survey data entered into the terminal.

[0947] What happens: The user answers questions about their interests and learning goals and submits the survey form.

[0948] Step 6:

[0949] The terminal sends the survey results to the server. Input: User's survey response data. Output: Survey data sent to the server.

[0950] Specific operation: The device sends the survey results to the server's API.

[0951] Step 7:

[0952] The server stores the survey results in a database. Input: Survey data sent to the server. Output: Survey results stored in a database.

[0953] Specific operation: The server calls the save function and saves the survey results in the database.

[0954] Curriculum Generation

[0955] Step 8:

[0956] The server sends a curriculum generation request to the AI ​​module based on the user's basic information and survey results. Input: Basic information, survey result data. Output: Request to the AI ​​module.

[0957] Specific operation: The server sends an API request for curriculum generation to the artificial intelligence module.

[0958] Step 9:

[0959] The artificial intelligence module uses a generative AI model to design a curriculum. Input: A prompt for curriculum generation (e.g., "Please generate a space-related curriculum for 10-year-old elementary school students."). Output: The generated curriculum.

[0960] Specific operation: The artificial intelligence module inputs prompt sentences into the generation AI and generates an appropriate curriculum.

[0961] Step 10:

[0962] The generated curriculum is sent to the server and stored in the database. Input: Generated curriculum data. Output: Curriculum stored in the database.

[0963] Specific operation: The artificial intelligence module sends the generated curriculum data to the server, which stores it in a database.

[0964] Step 11:

[0965] The server notifies the user of the curriculum generation. Input: Notification data of the generated curriculum. Output: Notification sent to the user.

[0966] Specific behavior: The server uses the notification system to notify the user of the curriculum creation.

[0967] Emotion engine integration

[0968] Step 12:

[0969] The device uses an emotion engine to analyze the user's emotions. Input: User's facial and voice data. Output: Analyzed emotion data.

[0970] Specific operation: The device uses a camera and microphone to collect facial expressions and voice, and performs real-time analysis using an emotion engine.

[0971] Step 13:

[0972] The device sends emotion data to the server. Input: Analyzed emotion data. Output: Emotion data sent to the server.

[0973] Specific operation: The device sends emotion data to the server's API.

[0974] Step 14:

[0975] The server stores the emotion data in a database. Input: Emotion data sent to the server. Output: Emotion data stored in the database.

[0976] Specific operation: The server calls the save function and saves the emotion data in the database.

[0977] Step 15:

[0978] The server sends the emotion data to the AI ​​module. Input: Emotion data stored in the database. Output: Data sent to the AI ​​module.

[0979] Specific operation: The server calls an API that sends emotion data to the artificial intelligence module.

[0980] Step 16:

[0981] The AI ​​module adjusts the curriculum and learning content based on the emotional data. Input: Emotional data. Output: Adjusted curriculum.

[0982] How it works: The AI ​​module analyzes emotional data and adjusts the user's learning content and pace.

[0983] Daily learning support

[0984] Step 17:

[0985] The device displays the study reminder to the user. Input: Study reminder data. Output: Display of reminder screen.

[0986] What it does: The device displays a reminder to the user, such as "Today's lesson: Planets in the solar system."

[0987] Step 18:

[0988] User starts learning. Input: Show reminder. Output: Start learning.

[0989] Specific Action: The user engages in the assigned learning content.

[0990] Step 19:

[0991] The device analyzes the emotion data being learned and sends it to the server. Input: Facial expression and voice data of the user being learned. Output: Emotion data sent to the server.

[0992] Specific operation: The device continuously analyzes the user's facial expressions and voice during training and sends emotional data to the server.

[0993] Step 20:

[0994] The server stores the emotion data in a database and sends it to the AI ​​module. Input: Emotion data sent during training. Output: Emotion data stored in the database.

[0995] Specific operation: The server saves the emotion data in a database and calls an API to send it to the artificial intelligence module.

[0996] Step 21:

[0997] The AI ​​module adjusts the learning content based on the emotional data. Input: Emotional data sent during learning. Output: Adjusted learning content.

[0998] Specific operation: The AI ​​module adjusts its learning content appropriately based on emotional data.

[0999] Learning progress management and curriculum adjustment

[1000] Step 22:

[1001] The user completes the study and inputs the progress data into the terminal. Input: Study progress data. Output: Progress data input into the terminal.

[1002] Specific operation: After completing the study, the user enters their progress into the terminal.

[1003] Step 23:

[1004] The device sends progress data to the server. Input: Progress data entered by the user. Output: Progress data sent to the server.

[1005] Specific operation: The device sends progress data to the server's API.

[1006] Step 24:

[1007] The server stores the progress data in a database. Input: Progress data sent to the server. Output: Progress data stored in the database.

[1008] Specific behavior: The server calls the save function to save the progress data to the database.

[1009] Step 25:

[1010] The server sends the progress data to the AI ​​module. Input: Progress data stored in the database. Output: Data sent to the AI ​​module.

[1011] Specific operation: The server calls an API that sends progress data to the artificial intelligence module.

[1012] Step 26:

[1013] The AI ​​module adjusts the curriculum based on progress data and emotion data. Input: progress data, emotion data. Output: adjusted curriculum.

[1014] Specific operation: The AI ​​module adjusts the curriculum based on progress data and emotional data.

[1015] Grading and Advice

[1016] Step 27:

[1017] The server aggregates the progress data and emotion data and generates a performance evaluation report. Input: Progress data, emotion data. Output: Performance evaluation report.

[1018] Specific operation: The server aggregates the progress data and emotion data and generates a performance evaluation report.

[1019] Step 28:

[1020] The server sends the grading report to the terminal. Input: grading report. Output: Report sent to the user.

[1021] Specific operation: The server calls an API to send the grade evaluation report to the terminal.

[1022] Step 29:

[1023] The terminal displays the performance evaluation report to the user and provides advice. Input: Performance evaluation report sent from the server. Output: Report and advice displayed to the user.

[1024] Specific operation: The device displays the performance evaluation report and advice to the user.

[1025] The above are the specific processing steps of the program for this system. This system responds to the individual needs of users and flexibly adjusts the curriculum to provide effective learning support.

[1026] (Application example 2)

[1027] 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."

[1028] Conventional learning support systems can generate a curriculum based on a user's learning progress and interests. However, they are unable to flexibly respond to the user's emotional and concentration states, making it difficult to maximize learning effectiveness. The present invention aims to provide more effective learning support by monitoring the user's emotional state in real time and adjusting the learning curriculum as needed.

[1029] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1030] In this invention, the server includes means for receiving basic information entered by a user and storing it in a database, means for displaying a questionnaire for entering the user's interests and learning goals and collecting the results, means for transmitting the collected data to an AI module for generating a curriculum based on the collected data, means for storing the curriculum generated by the AI ​​module in a database and notifying the user, means for displaying daily learning reminders and learning materials to the user, means for tracking the user's learning progress and storing it in a database, means for the AI ​​module to adjust the curriculum based on the learning progress data, means for periodically compiling the user's learning progress and generating a performance evaluation report, means for displaying the performance evaluation report to the user and providing advice, means for analyzing the user's emotions from facial expressions or voice, and means for transmitting data to the AI ​​module for adjusting the curriculum based on the analyzed emotional data. This enables more personalized and effective learning support by analyzing the user's emotional state in real time and adjusting the learning curriculum in a timely manner.

[1031] "Basic information" refers to data such as name, age, country of residence, and email address that a user enters into the system.

[1032] A "database" is a storage device that stores basic information about users, survey results, learning progress data, curriculum, and so on.

[1033] A "survey" is a question-based survey used to understand a user's interests and learning goals.

[1034] A "curriculum" is a plan of learning content and teaching materials generated by an AI module based on the user's interests and learning goals.

[1035] An "AI module" is an artificial intelligence component that analyzes user data and generates the optimal curriculum.

[1036] "Study reminders" are notifications and messages that encourage users to study every day.

[1037] "Study progress" is data indicating how far the user has progressed in their studies.

[1038] The "grade evaluation report" is a report on the evaluation of learning grades that is created based on the user's learning progress and emotional data.

[1039] "Emotion analysis" is the process of analyzing a user's emotional state from their facial expressions and voice.

[1040] A "generative AI model" is an artificial intelligence model used by an AI module to generate a curriculum.

[1041] To implement this invention, the following system configuration and program implementation are required: In particular, a database for managing basic user information and learning progress, an AI module for generating a curriculum, and an emotion engine for analyzing emotions are combined.

[1042] System Configuration

[1043] 1. Terminals and Servers

[1044] Users access the system using a smartphone, tablet, or PC (hereinafter referred to as the "terminal"). The terminal receives input from the user and transmits the data to the server. The server is the core of the system, including the database, AI module, and emotion engine.

[1045] 2. User registration and initial settings

[1046] Users enter basic information such as their name, age, country of residence, and email address, and send it to the server via their device. The server stores this information in a database. Users also answer a questionnaire to enter their interests and learning goals, and the results are also sent to the server and stored in the database.

[1047] 3. Curriculum Generation

[1048] The server sends a curriculum generation request to the AI ​​module based on the user's basic information and survey results. The AI ​​module uses the generative AI model to design an optimal curriculum for the user. This curriculum includes learning topics, materials, and learning pace. The generated curriculum is stored in a database via the server and notified to the user.

[1049] 4. Emotion engine integration

[1050] The device is equipped with an emotion engine that analyzes emotions from the user's facial expressions and voice. The emotion engine collects and analyzes the user's emotional data in real time while they are learning. The analysis results are sent to a server and stored in a database. The server then sends the emotional data to an AI module, which then adjusts the curriculum and learning content.

[1051] 5. Daily study support

[1052] During daily study, the device displays study reminders and the day's study materials to the user. The user confirms this and begins studying. The device analyzes the user's facial expressions and voice while studying and sends emotional data to the server. The server stores the emotional data in a database and sends it to the AI ​​module. The AI ​​module adjusts the study content as needed based on the emotional data.

[1053] 6. Learning progress management and curriculum adjustment

[1054] When a user completes their study, they input their progress into the device and send it. The device then sends the progress data to the server and stores it in a database. Based on the emotional data and learning progress data, the AI ​​module adjusts the curriculum and learning pace.

[1055] 7. Grading and Advice

[1056] The server periodically collects the user's learning progress and emotion data and generates a performance evaluation report, which includes the user's learning progress, performance evaluation, improvement points, and next steps. The terminal displays the performance evaluation report to the user and provides advice.

[1057] Specific examples

[1058] Example 1: Elementary school students learning about space

[1059] A user (elementary school student) wishes to learn about space, so he enters his basic information and answers "space" in the questionnaire.

[1060] The server requests the AI ​​module to generate a curriculum, and the AI ​​module generates a curriculum including "Basics of the Universe," "Planets in the Solar System," and "Simple Experiments."

[1061] The device displays daily study reminders, and an emotional engine analyzes the user's facial expressions and voice as they study. If it determines they have lost interest, the AI ​​module will adjust the curriculum and suggest new topics.

[1062] When the user completes the study, the study progress and emotional data are input into the terminal and transmitted to the server.

[1063] The server generates a performance evaluation report based on progress data and emotion data, and suggests next learning steps and areas for improvement.

[1064] Example 2: When a working adult studies business administration

[1065] A user (working adult) wishes to study business administration, enters basic information, and answers "business administration" in the questionnaire.

[1066] The server requests the AI ​​module to generate a curriculum, and the AI ​​module generates a curriculum including "business strategy," "financial analysis," and "marketing."

[1067] The device displays daily study reminders, and while the user is studying, the emotion engine analyzes the user's facial expressions and voice. If it determines that the user's concentration is declining, the AI ​​module will adjust the study content and encourage appropriate breaks.

[1068] When the user completes the study, the study progress and emotional data are input into the terminal and transmitted to the server.

[1069] The server generates a performance evaluation report based on progress data and emotion data, and suggests next learning steps and areas for improvement.

[1070] In this way, the system of the present invention provides a learning curriculum that is individually customized based on the user's interests and goals, and responds flexibly through real-time emotion analysis, thereby realizing lifelong learning support.

[1071] Examples of prompt statements

[1072] "Use generative AI models for curriculum generation."

[1073] "Please suggest the next learning step based on the sentiment analysis data."

[1074] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1075] Step 1:

[1076] The user uses the device to enter basic information (name, age, country of residence, email address) and submits it.

[1077] Input: Basic information entered by the user

[1078] Output: Basic information is sent to the server and stored in the database

[1079] Specific operation: The basic information entered on the terminal is sent to the server, which then stores it in a database.

[1080] Step 2:

[1081] The user answers and submits a survey on the device, entering their interests and learning goals.

[1082] Input: Survey results of interests and learning goals entered by users

[1083] Output: Survey results are sent to the server and stored in the database.

[1084] Specific operation: The user answers a questionnaire displayed on the terminal, and the data is sent to the server, which stores it in a database.

[1085] Step 3:

[1086] The server sends a curriculum generation request to the AI ​​module based on the user's basic information and survey results.

[1087] Input: User's basic information and survey results

[1088] Output: Send a curriculum generation request to the AI ​​module

[1089] Specific operation: The server references the user's basic information and survey results from the database and sends a request to the AI ​​module to design the optimal curriculum using a generative AI model.

[1090] Step 4:

[1091] The AI ​​module uses the generative AI model to design an optimal curriculum for the user and transmits the curriculum to the server.

[1092] Input: Curriculum generation request, user basic information and survey results

[1093] Output: Generated curriculum

[1094] Specific operation: The AI ​​module uses the generative AI model to analyze the data, generate a curriculum including learning topics, materials, and learning pace, and send it to the server.

[1095] Step 5:

[1096] The server stores the generated curriculum in a database and notifies the user.

[1097] Input: Generated curriculum

[1098] Output: Save the curriculum in the database and notify the user

[1099] Specific operation: The server saves the generated curriculum in a database and sends a notification to the terminal to inform the user of the new curriculum.

[1100] Step 6:

[1101] The device displays study reminders and the day's study materials to the user.

[1102] Input: Generated curriculum

[1103] Output: Display of study reminders and learning materials

[1104] Specific operation: The terminal displays daily study reminders and the day's learning materials to the user based on the curriculum received from the server.

[1105] Step 7:

[1106] The terminal uses an emotion engine to analyze emotions from the user's facial expressions and voice, and transmits the emotion data to the server.

[1107] Input: Facial expressions and voice of the user during training

[1108] Output: Parsed emotion data

[1109] Specific operation: The device uses a camera and microphone to capture the user's facial expressions and voice, and the emotion engine analyzes the data to recognize the user's emotional state and sends it to the server.

[1110] Step 8:

[1111] The server stores the emotional data in a database and sends it to an AI module to adjust the curriculum.

[1112] Input: Parsed emotion data

[1113] Output: Curriculum adjustment

[1114] How it works: The server stores the emotional data in a database and sends it to the AI ​​module, which then adjusts the content and pace of the curriculum based on the emotional data.

[1115] Step 9:

[1116] When the user completes the study, he / she inputs the study progress into the terminal and transmits it.

[1117] Input: Learning progress data

[1118] Output: Study progress data sent to server and saved in database

[1119] Specific operation: When the user completes learning, he / she inputs the progress data into the terminal, which then sends it to the server, which stores it in the database.

[1120] Step 10:

[1121] The server generates a performance evaluation report based on the learning progress data and emotion data and notifies the user.

[1122] Input: learning progress data, emotion data

[1123] Output: Generate and notify grade evaluation report

[1124] Specific operation: The server analyzes the progress data and emotion data, generates a performance evaluation report, and notifies the user via the terminal.

[1125] Examples of prompt statements

[1126] "Use generative AI models for curriculum generation."

[1127] "Please suggest the next learning step based on the sentiment analysis data."

[1128] 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.

[1129] 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.

[1130] 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.

[1131] [Third embodiment]

[1132] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1133] 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.

[1134] 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).

[1135] 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.

[1136] 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.

[1137] 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).

[1138] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for 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.

[1139] 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.

[1140] 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.

[1141] 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.

[1142] 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.

[1143] 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."

[1144] This invention relates to an AI tutoring system that supports daily learning by providing users with individually customized learning curricula based on their specific interests and goals. Below, we will explain the program processing of this system in natural language and provide specific examples.

[1145] System Configuration

[1146] 1. User registration and initial settings

[1147] A user accesses the system and proceeds to the account creation page. First, the user enters basic information such as their name, age, country of residence, email address, etc. This information is sent to the server via the terminal, and the server stores the received information in a database.

[1148] The device then displays a questionnaire to the user asking about their interests and learning goals. When the user answers the questionnaire, the results are sent from the device to the server and stored in a database.

[1149] 2. Curriculum Generation

[1150] The server sends a curriculum generation request to the AI ​​module based on the user's basic information and survey results. The AI ​​module uses generative AI to design a curriculum that is optimal for the user. This curriculum includes learning topics, materials, and learning pace.

[1151] The generated curriculum is sent to the server, which stores it in a database and notifies the user.

[1152] 3. Daily learning support

[1153] For daily learning, the device displays daily learning reminders and the day's study materials to the user. For example, a reminder such as "Today's learning content: Planets of the solar system" is displayed. The user confirms this and begins studying.

[1154] Once the user has completed their learning, the device will send progress information to the server, which will store it in a database and send it to the AI ​​module in a timely manner.

[1155] 4. Learning progress management and curriculum adjustment

[1156] The AI ​​module analyzes the user's progress data to check whether the learning content is appropriate. If necessary, it adjusts the curriculum and suggests new materials and a learning pace. The adjusted curriculum is saved in a database on the server and notified to the user.

[1157] 5. Grading and Advice

[1158] The server periodically aggregates the user's learning progress and generates a performance evaluation report, which includes the user's learning progress, performance evaluation, improvement points, and next steps.

[1159] The device displays this performance evaluation report to the user and provides advice, such as "Next time, focus on the topic of XX."

[1160] Specific examples

[1161] Example 1: Elementary school students learning about space

[1162] A user (elementary school student) wants to learn about space. He enters basic information and answers "space" in a questionnaire about his interests.

[1163] The terminal sends the survey results to the server, and the server requests the AI ​​module to generate a curriculum.

[1164] The AI ​​module generates a curriculum including "Space Basics," "Planets of the Solar System," and "Simple Space Experiments."

[1165] Each day, the device displays reminders and educational materials, such as "Today's learning: Planets in the solar system."

[1166] Users study and report their progress, and the server records the progress data and adjusts the curriculum as needed.

[1167] Example 2: Working adults seeking an MBA

[1168] The user (a working adult) aims to obtain an MBA, enters basic information, and answers "business administration" to a questionnaire about interests.

[1169] The server requests the AI ​​module to generate a curriculum, and the AI ​​module generates a curriculum including "business strategy," "financial analysis," and "marketing."

[1170] Each day, the device displays reminders and learning materials such as "Today's learning topic: Financial analysis."

[1171] Users study and report their progress. The server records the progress data and generates a performance report that includes next steps and areas for improvement.

[1172] In this way, this system provides a learning curriculum that is individually customized based on the user's interests and goals, thereby supporting lifelong learning. This invention improves the quality of education and allows users to continue learning in a way that is best suited to them.

[1173] The above is the "Mode for Carrying Out the Invention."

[1174] The processing flow will be explained below.

[1175] Step 1:

[1176] A user accesses the system and proceeds to the account creation page. The terminal displays a form for entering basic information such as name, age, country of residence, email address, etc. The user enters the information and clicks the submit button.

[1177] Step 2:

[1178] The device sends the entered basic information to the server, which stores the received information in a database and notifies the user via the device that account creation has been completed.

[1179] Step 3:

[1180] The terminal displays a questionnaire to the new user asking about their interests and learning goals. The user answers the questionnaire and submits the results.

[1181] Step 4:

[1182] The device sends the survey results to the server, which stores them in a database and sends the data to the AI ​​module.

[1183] Step 5:

[1184] The server sends a curriculum generation request to the AI ​​module based on the user's basic information and the survey results. The AI ​​module uses the generation AI to design the optimal curriculum for the user.

[1185] Step 6:

[1186] The AI ​​module sends the generated curriculum to the server, which stores it in a database and notifies the user.

[1187] Step 7:

[1188] The device displays daily study reminders and the day's study materials to the user, who then begins studying with the materials presented.

[1189] Step 8:

[1190] When the user completes the study, he / she enters the study progress into the terminal and clicks the send button.

[1191] Step 9:

[1192] The device sends learning progress data to the server, which stores this data in a database and sends it to the AI ​​module as needed.

[1193] Step 10:

[1194] The AI ​​module analyzes the user's progress data, determines whether the learning content is appropriate, adjusts the curriculum as necessary, and sends the adjusted curriculum to the server.

[1195] Step 11:

[1196] The server stores the adjusted curriculum in a database and notifies the user.

[1197] Step 12:

[1198] The server periodically aggregates the user's learning progress and generates a performance evaluation report, which includes the user's learning progress, performance evaluation, improvement points, and next steps.

[1199] Step 13:

[1200] The device displays the performance evaluation report to the user and provides advice, allowing the user to adjust their learning methods and goals based on the evaluation results.

[1201] The above is a concrete explanation of the processing steps of the program.

[1202] Example 1

[1203] 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."

[1204] Conventional learning support systems are unable to respond to the individual learning needs and progress of each user, and are limited to providing a uniform curriculum. In addition, it is difficult for users to manage their learning progress and receive appropriate feedback and advice, which hinders effective learning.

[1205] 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.

[1206] In this invention, the server includes means for receiving personal information entered by the user and storing it in a storage device, means for displaying a survey form for entering the user's interests and learning goals and collecting the results, and means for transmitting the collected data to an AI module to generate a curriculum based on the data. This allows for the provision of a curriculum that meets the individual learning needs of each user, enabling effective learning.

[1207] "Personal information" refers to information necessary to identify an individual, such as a user's name, age, country of residence, and email address.

[1208] A "memory device" is a device that electronically stores and manages information, such as a database or storage.

[1209] A "survey" is a questionnaire or form used to gather information about a user's interests, learning goals, etc.

[1210] An "AI module" is a component that uses artificial intelligence to perform processes such as curriculum generation and learning progress analysis.

[1211] A "curriculum" is a collection of learning plans and materials organized around a user's learning goals.

[1212] "Study reminders" are messages and alerts that inform users of their daily learning content and progress.

[1213] "Study progress" is data on the progress status that indicates how far the user has progressed toward the learning goal set by the user.

[1214] A "performance evaluation report" is a document that evaluates a user's learning progress and lists their grades, areas for improvement, and next steps.

[1215] "Advice" is specific advice or instruction provided to support the user's learning.

[1216] "Generative AI" is an artificial intelligence technology that generates optimal curriculum and advice based on data entered by the user.

[1217] This invention relates to an AI tutoring system that supports daily learning by providing users with individually customized learning curricula based on their specific interests and goals. The program processing of this system is explained below in natural language.

[1218] System Overview

[1219] This system mainly consists of the following elements:

[1220] server

[1221] Terminal

[1222] User

[1223] Generative AI Models

[1224] storage device

[1225] Registering users and saving basic information

[1226] When a user accesses the system, an account creation page is displayed. The user enters personal information such as name, age, country of residence, and email address. This information is sent to the server via the terminal, and the server stores it in a storage device. The terminal then displays a survey form about the user's interests and learning goals, which the user answers. The survey results are again sent to the server via the terminal and stored in a storage device.

[1227] Curriculum generation

[1228] The server sends a curriculum generation request to the generative AI model based on the user's basic information and the survey results. Specifically, the following prompt sentence is used:

[1229] "Please create a curriculum for elementary school students to learn about space. Specifically, please include the basics of space, planets in the solar system, and simple space experiments."

[1230] "Please create a curriculum for working professionals seeking an MBA. Specifically, please include business strategy, financial analysis, and marketing."

[1231] The generative AI model generates a curriculum based on these prompts and sends it to the server. The server stores the received curriculum in a storage device and notifies the user. The device then informs the user that "a curriculum has been generated."

[1232] Daily learning support

[1233] During daily learning, the server sends the day's learning content and reminders to the device. For example, the device displays a reminder such as "Today's learning content: Planets of the solar system." This allows the user to start learning with the specified learning material. Once the learning is complete, the user enters progress information into the device, which then sends it to the server. The progress information is stored in a storage device.

[1234] Learning progress management and curriculum adjustment

[1235] The server periodically sends the user's learning progress data to the generative AI model for analysis. The generative AI model adjusts the curriculum based on the user's progress and suggests new learning paces and materials. The adjusted curriculum is saved in a storage device from the server and notified to the user.

[1236] Grading and Advice

[1237] The server periodically collects the user's learning progress data and generates a performance evaluation report, which includes a performance evaluation, areas for improvement, and next steps. The terminal displays the performance evaluation report to the user and provides specific advice, such as "Next time, focus on the topic of XX."

[1238] Specific examples

[1239] When elementary school students learn about space

[1240] The user (elementary school student) enters basic information and answers "space" to a questionnaire about interests.

[1241] The terminal sends the survey results to the server and requests the AI ​​module to generate a curriculum.

[1242] The generative AI model generates a curriculum including "Space Basics," "Planets of the Solar System," and "Simple Space Experiments."

[1243] Each day, the device displays reminders and educational materials, such as "Today's learning: Planets in the solar system."

[1244] Users study and report their progress, and the server records the progress data and adjusts the curriculum as needed.

[1245] The above is a specific embodiment for carrying out the invention. This system allows users to continue learning in a way that is optimal for them.

[1246] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1247] Step 1: Enter and save basic user information

[1248] When a user accesses the system, they are presented with an account creation page.

[1249] The user enters personal information such as name, age, country of residence, email address, etc. This input data is sent to the terminal.

[1250] The terminal transmits the entered personal information to the server.

[1251] The server stores the received personal information in a storage device.

[1252] Output: The registered user's personal information is saved to the storage device.

[1253] Step 2: View the survey and save the results

[1254] The terminal presents the user with a survey of interests and learning goals.

[1255] The user answers the survey and the results are sent to the terminal.

[1256] The terminal transmits the results of the survey to the server.

[1257] The server stores the results of the investigation in a storage device.

[1258] Output: Data about the user's interests and learning goals is saved to a storage device.

[1259] Step 3: Submit a curriculum generation request

[1260] The server creates prompts for curriculum generation based on the user's basic information and survey results.

[1261] Input: User basic information and survey results

[1262] Output: Curriculum-generated prompt

[1263] The server sends the generated prompt sentence as a request to the generative AI model.

[1264] Example: "Generate a curriculum for elementary school students to learn about space. Specifically, include the basics of space, planets in the solar system, and simple space experiments."

[1265] Step 4: Generate and save the curriculum

[1266] The generative AI model generates a learning curriculum based on the prompt sentence.

[1267] Input: Curriculum generation prompt

[1268] Output: Generated learning curriculum

[1269] The server receives the generated curriculum and stores it in a storage device.

[1270] The terminal notifies the user that "The curriculum has been generated."

[1271] Step 5: View study reminders and materials

[1272] The server sends the day's learning content and reminders to the device.

[1273] The device displays reminders and educational materials to the user, such as "Today's learning: Planets in the solar system."

[1274] Input: Today's learning content and reminders

[1275] Output: Reminders and educational materials displayed to the user

[1276] Step 6: Enter and save your learning progress

[1277] The user checks the reminder and continues studying.

[1278] When the user has completed the learning, the terminal displays a "Learning Completed" button.

[1279] When the user clicks the button, progress information is sent to the terminal.

[1280] The terminal sends progress information to the server.

[1281] The server stores the progress information in a storage device.

[1282] Input: Learning progress information

[1283] Output: Learning progress information stored in memory.

[1284] Step 7: Analyze learning progress data and adjust curriculum

[1285] The server periodically sends progress data to the generative AI model.

[1286] The generative AI model analyzes the user's progress data to ensure that the learning content is appropriate.

[1287] Input: Learning progress data

[1288] Output: Analysis results and adjustment suggestions

[1289] If necessary, the generative AI model will adjust the curriculum.

[1290] The server receives the tailored curriculum and stores it in a storage device.

[1291] The terminal notifies the user of the adjusted curriculum.

[1292] Step 8: Generate and view the grading report

[1293] The server periodically compiles the user's learning progress data and generates a performance evaluation report.

[1294] Input: Learning progress data

[1295] Output: Grade evaluation report

[1296] The terminal displays the performance evaluation report to the user and provides specific advice.

[1297] For example, advice such as "Next time, let's focus on the topic of XX."

[1298] The above are the specific processing steps of this system's program. This makes it possible to provide an optimal curriculum for each user, manage learning progress, and provide appropriate feedback.

[1299] (Application example 1)

[1300] 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."

[1301] Conventional tutoring systems lack the ability to customize to meet the individual learning needs and goals of users, resulting in a decline in learning effectiveness. Furthermore, the lack of interactive learning content utilizing smart devices has led to issues such as difficulty in maintaining motivation to learn.

[1302] 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.

[1303] In this invention, the server includes means for receiving basic information input by a user and storing it in a data management device, means for displaying a survey for inputting the user's interests and learning goals and collecting the results, means for transmitting the collected data to an intelligence module for generating an educational plan based on the collected data, means for storing the educational plan generated by the intelligence module in the data management device and notifying the user, means for displaying daily learning notifications and educational materials to the user, means for tracking the user's learning progress and storing it in the data management device, means for the intelligence module to adjust the educational plan based on the learning progress data, means for periodically compiling the user's learning progress and generating a performance evaluation report, means for displaying the performance evaluation report to the user and providing advice, and means for delivering interactive learning content on devices such as smart glasses and mobile terminals, thereby enabling a highly customized learning experience tailored to the user's individual needs.

[1304] "User" refers to any individual or entity that uses the System.

[1305] "Basic information" refers to personal information such as the user's name, age, place of residence, and email address.

[1306] "Data Management Device" refers to a system or device for storing and managing information collected from users.

[1307] "Survey" refers to a questionnaire-style interface that includes questions about the user's interests and learning goals.

[1308] "Intelligence Module" refers to a program containing artificial intelligence algorithms for generating an optimal training plan based on user input data.

[1309] "Educational Plan" means a plan including curriculum, materials, and learning pace designed to achieve a user's learning goals.

[1310] "Notification" refers to the action of sending important information or reminders from the system to the user.

[1311] "Educational materials" refers to teaching materials and content used for learning, such as texts, videos, and quizzes.

[1312] "Study progress" refers to data indicating how much of the learning content a user has completed.

[1313] "Performance evaluation report" refers to a report that compiles and evaluates a user's learning outcomes and progress.

[1314] "Advice" refers to advice on the user's learning and suggestions for next steps.

[1315] "Smart glasses" refers to a glasses-type device equipped with augmented reality and information display functions.

[1316] "Mobile device" refers to a portable electronic device such as a smartphone or tablet.

[1317] "Interactive learning content" refers to educational content that allows users to actively participate and learn while receiving feedback.

[1318] This invention relates to an AI tutoring system that supports daily learning by providing a personalized learning curriculum based on a user's specific interests and goals. The system can deliver interactive learning content on devices such as smart glasses and mobile terminals.

[1319] System Configuration

[1320] 1. User registration and initial settings

[1321] The user navigates to an account creation page on the device. First, the user enters basic information such as their name, age, place of residence, and email address. This information is sent to the server via the device, and the server stores the received information in a data management device. The device then displays a survey asking the user about their interests and learning goals. After the user completes the survey, the results are sent from the device to the server and stored in the data management device.

[1322] 2. Curriculum Generation

[1323] The server sends a request to the intelligent module to generate a learning plan based on the user's basic information and survey results. The intelligent module uses the generative AI model to design an optimal learning plan for the user. This learning plan includes learning topics, materials, and learning pace. The generated learning plan is sent to the server, stored in the data management device, and notified to the user.

[1324] 3. Daily learning support

[1325] During daily learning, the device displays daily learning notifications and the day's educational materials to the user. For example, a notification such as "Today's learning content: Planets in the solar system" is displayed. The user confirms this and begins learning. When the user completes their learning, the device sends progress information to the server. The server stores this information in the data management device and transmits it to the intelligent module in a timely manner.

[1326] 4. Managing learning progress and adjusting educational plans

[1327] The intelligent module analyzes the user's progress data to determine whether the learning content is appropriate. If necessary, it adjusts the learning plan and suggests new learning materials and a learning pace. The adjusted learning plan is then stored in the data management device from the server and notified to the user.

[1328] 5. Grading and Advice

[1329] The server periodically compiles the user's learning progress and generates a performance evaluation report. This report includes the user's learning progress, performance evaluation, areas for improvement, and next steps. The device displays this performance evaluation report to the user and provides advice. For example, specific advice such as "Next time, focus on topic XX" may be included.

[1330] Detailed processing

[1331] The basic information and survey results entered by the user are sent to the server via the device. The server stores this data in a data management device and sends it to an intelligence module (a generative AI model such as GPT-3). The intelligence module generates an optimal educational plan for the user based on the prompt sentence. For example, the following prompt sentences can be used:

[1332] Prompt Sentence Examples

[1333] User information: Name = Taro Tanaka, Age = 25, Interests = Programming, Level = Beginner

[1334] Survey results: Learning goal = Web development, Hobby = Game development, Study time = 1 hour / day

[1335] Generated curriculum:

[1336] Week 1: HTML / CSS Basics

[1337] Week 2: JavaScript Basics

[1338] Week 3: Simple web application development

[1339] Week 4: Game Development Fundamentals

[1340] The generated educational plan is stored in a data management device and sent to the user's device. The user receives daily learning notifications and begins studying. Learning progress is sent to the server in real time, and an intelligent module analyzes it and periodically adjusts the educational plan. Overall, this system provides users with a customized learning experience, enabling them to continue learning while maintaining their motivation.

[1341] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1342] Step 1:

[1343] The user accesses the account creation page using a terminal and enters basic information (name, age, place of residence, email address, etc.). The terminal sends the entered basic information to the server, which then stores the information in the data management device.

[1344] Input: Basic information such as name, age, place of residence, and email address

[1345] Output: Basic information of the user stored in the data management device

[1346] Step 2:

[1347] The device displays a survey to the user asking about their interests and learning goals. After the user completes the survey, the device transmits the results to a server, which stores the survey results in a data management device.

[1348] Input: Survey results about user interests and learning goals

[1349] Output: Survey results stored in the data management device

[1350] Step 3:

[1351] The server sends a request for generating an educational plan to the intelligence module based on the user's basic information and the survey results. The intelligence module uses the generative AI model to generate the optimal educational plan for the user. This process is based on the prompt text.

[1352] Input: User basic information and survey results stored in the data management device

[1353] Output: The training plan generated by the intelligence module

[1354] Step 4:

[1355] The intelligent module sends the generated training plan to the server, which stores it in the data management device and notifies the user, who then displays the notification to the terminal, allowing the user to confirm the training plan.

[1356] Input: Educational plan generated by the intelligence module

[1357] Output: Education plan stored in the data management device and notification displayed to the user

[1358] Step 5:

[1359] Every day, the device displays a learning notification and the day's educational material to the user. The user checks the notification and begins learning.

[1360] Input: Educational materials for the day stored in the data management device

[1361] Output: Learning notifications and educational materials displayed on the device

[1362] Step 6:

[1363] When the user completes the learning, the terminal transmits the progress information to the server, which stores the progress information in the data management device.

[1364] Input: User learning progress information

[1365] Output: Learning progress information stored in the data management device

[1366] Step 7:

[1367] The server periodically transmits the learning progress data to the intelligent module, which analyzes the data and adjusts the educational plan, which is then stored in the data management device by the server and notified to the user.

[1368] Input: Learning progress data stored in the data management device

[1369] Output: Coordinated educational plan

[1370] Step 8:

[1371] The server periodically compiles the user's learning progress and generates a performance evaluation report, which includes the user's learning progress, performance evaluation, areas for improvement, and next steps. The terminal displays the performance evaluation report to the user and provides advice.

[1372] Input: Aggregated data based on learning progress stored in the data management device

[1373] Output: A grading report and advice displayed to the user

[1374] The above are the specific processing steps of this system.

[1375] 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.

[1376] This invention relates to an AI tutoring system that supports daily learning by providing a personalized learning curriculum based on the user's specific interests and goals. Furthermore, this system combines an emotion engine that recognizes the user's emotions, enabling more flexible and personalized instruction.

[1377] System Configuration

[1378] 1. User registration and initial settings

[1379] A user accesses the system and proceeds to the account creation page. First, the user enters basic information such as their name, age, country of residence, email address, etc. The device sends the entered information to the server, which stores it in a database.

[1380] Next, the device displays a questionnaire to the user asking about their interests and learning goals. After the user answers the questionnaire, the results are sent to the server and stored in a database.

[1381] 2. Curriculum Generation

[1382] The server sends a curriculum generation request to the AI ​​module based on the user's basic information and survey results. The AI ​​module uses generative AI to design a curriculum that is optimal for the user. This curriculum includes learning topics, materials, and learning pace.

[1383] The generated curriculum is sent to the server and stored in a database, and the server notifies the user.

[1384] 3. Emotion engine integration

[1385] The device is equipped with an emotion engine that analyzes the user's emotions from their facial expressions and voice. The emotion engine collects emotional data as the user progresses through the learning process and analyzes it in real time.

[1386] Emotion analysis data is sent from the device to a server. The server stores the emotional data in a database and sends it to an AI module. The AI ​​module adjusts the curriculum and learning content according to the user's emotions.

[1387] 4. Daily study support

[1388] For daily study, the device displays study reminders and the day's study materials to the user. For example, a reminder such as "Today's study topic: Planets in the solar system" is displayed. The user confirms this and begins studying.

[1389] The device analyzes the user's facial expressions and voice and sends emotional data to the server, which stores it in a database and sends it to the AI ​​module, which then adjusts its learning content accordingly.

[1390] 5. Learning progress management and curriculum adjustment

[1391] When a user completes their study, they input their progress into the device and send it. The device then sends the progress data to the server and stores it in a database. Based on the emotional data and learning progress data, the AI ​​module adjusts the curriculum and learning pace.

[1392] 6. Grading and Advice

[1393] The server periodically collects the user's learning progress and emotion data and generates a performance evaluation report, which includes the user's learning progress, performance evaluation, improvement points, and next steps. The terminal displays the performance evaluation report to the user and provides advice.

[1394] Specific examples

[1395] Example 1: Elementary school students learning about space

[1396] A user (elementary school student) wants to learn about space. He enters basic information and answers "space" in a questionnaire about his interests.

[1397] The server requests the AI ​​module to generate a curriculum, and the AI ​​module generates a curriculum including "Basics of the Universe," "Planets in the Solar System," and "Simple Experiments."

[1398] Every day, the device displays "Today's learning content: Planets of the solar system," and as the user progresses, the emotion engine analyzes the user's facial expressions and voice. If it determines that the user has lost interest, the AI ​​module adjusts the curriculum and suggests new topics.

[1399] When the user completes the study, the study progress and emotional data are input into the terminal and transmitted to the server.

[1400] The server generates a performance evaluation report based on progress data and emotion data, and suggests next learning steps and areas for improvement.

[1401] Example 2: Working adults seeking an MBA

[1402] The user (a working adult) aims to obtain an MBA, enters basic information, and answers "business administration" to a questionnaire about interests.

[1403] The server requests the AI ​​module to generate a curriculum, and the AI ​​module generates a curriculum including "business strategy," "financial analysis," and "marketing."

[1404] Every day, the device displays "Today's learning content: Financial analysis," and as the user progresses through the learning process, the emotion engine analyzes the user's facial expressions and voice. If the AI ​​module determines that the user's concentration is declining, it adjusts the learning content and encourages them to take a break at the appropriate time.

[1405] The user inputs learning progress and emotional data into the terminal and transmits it to the server.

[1406] The server generates a performance evaluation report based on progress data and emotion data, and suggests next learning steps and areas for improvement.

[1407] This system provides a personalized learning curriculum based on the user's interests and goals, and responds flexibly through real-time emotion analysis, enabling lifelong learning support. This invention improves the quality of education and allows users to continue learning in a way that is best suited to them.

[1408] The above is the "Mode for Carrying Out the Invention."

[1409] The processing flow will be explained below.

[1410] Step 1:

[1411] A user accesses the system and proceeds to the account creation page. The terminal displays a form for entering basic information such as name, age, country of residence, email address, etc. The user enters the information and clicks the submit button.

[1412] Step 2:

[1413] The device sends the entered basic information to the server, which stores the received information in a database and notifies the user via the device that account creation has been completed.

[1414] Step 3:

[1415] The terminal displays a questionnaire to the new user asking about their interests and learning goals. The user answers the questionnaire and submits the results.

[1416] Step 4:

[1417] The device sends the survey results to the server, which stores them in a database and sends the data to the AI ​​module.

[1418] Step 5:

[1419] The server sends a curriculum generation request to the AI ​​module based on the user's basic information and the survey results. The AI ​​module uses the generation AI to design the optimal curriculum for the user.

[1420] Step 6:

[1421] The AI ​​module sends the generated curriculum to the server, which stores it in a database and notifies the user.

[1422] Step 7:

[1423] The device displays daily study reminders and the day's learning materials to the user. For example, a reminder might say, "Today's learning content: Planets in the solar system." The user then begins studying the materials provided.

[1424] Step 8:

[1425] While the user is learning, the device's built-in emotion engine analyzes the user's facial expressions and voice to collect emotional data, including facial expression analysis and voice tone analysis.

[1426] Step 9:

[1427] The device sends the collected emotional data to a server, which stores the data in a database and sends it to an AI module.

[1428] Step 10:

[1429] The AI ​​module analyzes emotional and learning progress data and adjusts learning content and methods based on the user's current emotional state. For example, if the user is tired, it will suggest a break or switch to a less difficult problem.

[1430] Step 11:

[1431] The server stores the adjusted curriculum in a database and notifies the user.

[1432] Step 12:

[1433] When the user completes the study, they input their study progress into the device and click the send button. The device then sends the study progress data and emotion data to the server.

[1434] Step 13:

[1435] The server stores the learning progress data and emotion data in a database and periodically aggregates them to generate a performance evaluation report, which includes the user's learning progress, performance evaluation, improvement points, and next steps.

[1436] Step 14:

[1437] The device displays a performance evaluation report to the user and offers advice, such as "Next time, try taking breaks to improve your concentration."

[1438] Step 15:

[1439] The server collects user feedback and sends it to the AI ​​module for further curriculum optimization.

[1440] The above is a concrete explanation of the processing steps of the system that integrates the emotion engine.

[1441] Example 2

[1442] 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."

[1443] In recent years, there has been a demand for individually customized learning support systems, but existing systems lack the flexibility to respond sufficiently to users' interests and goals. Furthermore, they lack the ability to analyze users' emotions in real time and adjust the curriculum accordingly, resulting in the problem of only being able to provide uniform instruction. Furthermore, the management of learning progress and grade evaluation are still done manually, which is inefficient and affects users' ability to continue learning. There is a need for a comprehensive learning support system that can solve these issues.

[1444] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving basic information entered by a user and storing it in a database, means for displaying a questionnaire for entering the user's interests and learning goals and collecting the results, means for transmitting data to an artificial intelligence module to generate a curriculum based on the collected data, means for storing the curriculum generated by the artificial intelligence module in a database and notifying the user, means for displaying daily learning reminders and learning materials to the user, means for tracking the user's learning progress and storing it in a database, means for the artificial intelligence module to adjust the curriculum based on learning progress data, means for analyzing emotions from the user's facial expressions and voice, sending the analyzed data to the server and storing it in a database, means for adjusting the curriculum and learning content based on the emotion data, means for periodically compiling the user's learning progress and emotion data and generating a performance evaluation report, and means for displaying the performance evaluation report to the user and providing advice. This enables the provision of a customized learning curriculum tailored to the user's interests and goals and flexible learning support based on emotion analysis.

[1445] "Basic information" refers to personal information such as name, age, country of residence, and email address that a user enters when registering with the system.

[1446] A "survey" is a collection of questions displayed to gather information about a user's interests and learning goals.

[1447] An "artificial intelligence module" is a program that includes artificial intelligence capabilities to generate a curriculum based on collected data and tailor it to the user's individual needs.

[1448] A "curriculum" is a set of learning plans, including learning content, learning materials, and learning pace, designed based on a user's learning goals.

[1449] "Reminder" is a system function that notifies users of the day's study content and schedule.

[1450] "Study progress" is information indicating the results achieved by the user in the course of studying and the current progress status.

[1451] "Emotion data" is data that indicates the emotional state of the user analyzed from facial expressions, voice, etc.

[1452] The "performance evaluation report" is a report that compiles the user's learning progress and emotional data, and includes an evaluation of the learning content and suggestions for the next learning step.

[1453] "Generative AI" is AI that has the ability to generate new information or content based on instructions such as prompts.

[1454] The present invention is a system that supports daily learning by providing an individually customized learning curriculum based on the user's specific interests and goals. Furthermore, this system combines an emotion engine that recognizes the user's emotions, enabling more flexible and personalized instruction.

[1455] System Configuration

[1456] 1. User registration and initial settings

[1457] A user accesses the system and proceeds to the account creation page. Here, the user enters basic information such as name, age, country of residence, and email address. The device sends this information to the server, which stores the data in a database. The device then displays a survey asking about the user's interests and learning goals. After the user answers the survey, the results are sent to the server and stored in the database.

[1458] 2. Curriculum Generation

[1459] The server sends a curriculum generation request to the artificial intelligence module based on the user's basic information and the survey results. The artificial intelligence module uses the generative AI model to design the optimal curriculum for the user. The generated curriculum is sent to the server and stored in the database. The server then notifies the user.

[1460] 3. Emotion engine integration

[1461] The device is equipped with an emotion engine that analyzes emotions from the user's facial expressions and voice. The emotion engine collects emotional data as the user progresses through the study and analyzes it in real time. The analyzed emotional data is sent from the device to a server and stored in a database. This data is then sent to an artificial intelligence module, which adjusts the curriculum and learning content according to the user's emotions.

[1462] 4. Daily study support

[1463] During daily learning, the device displays learning reminders and the day's learning materials to the user. For example, a reminder such as "Today's learning content: Planets in the solar system" may be displayed. The user confirms this and begins learning. The device analyzes the user's facial expressions and voice and sends emotional data to the server. The server stores this data in a database and sends it to the artificial intelligence module. The artificial intelligence module adjusts the learning content accordingly based on the emotional data.

[1464] 5. Learning progress management and curriculum adjustment

[1465] When a user completes their learning, they input their progress data into the device and send it to the server, which then sends it to the server and stores it in a database. The server then sends this progress data and emotion data to an AI module, which then adjusts the curriculum and learning pace based on the month.

[1466] 6. Grading and Advice

[1467] The server periodically collects the user's learning progress and emotional data and generates a performance evaluation report, which includes the user's learning progress, performance evaluation, improvement points, and next steps. The device displays this report to the user and provides advice.

[1468] Specific examples

[1469] Example 1: Elementary school students learning about space

[1470] A user (elementary school student) wishes to learn about space, enters basic information, and answers "space" to a questionnaire about their interests.

[1471] The server requests the artificial intelligence module to generate a curriculum, and the artificial intelligence module generates the curriculum using the prompt "Please generate a space-related learning curriculum for 10-year-old elementary school students."

[1472] The device displays "Today's lesson: Planets of the solar system" and uses an emotion engine to analyze the user's emotions while they are learning. The emotion data is sent to a server, and the curriculum is adjusted as needed.

[1473] The user completes the study and enters the progress data into the terminal and transmits it to the server.

[1474] The server generates a performance evaluation report based on progress data and emotional data, and displays advice such as "Next learning step: The basics of the universe" on the device.

[1475] Example 2: Working adults seeking an MBA

[1476] The user (a working adult) enters basic information and a questionnaire, and answers that they are interested in "business management."

[1477] The server requests the artificial intelligence module to generate a curriculum, and the artificial intelligence module generates a curriculum including content such as "business strategy" and "financial analysis."

[1478] The device displays "Today's Study Topic: Financial Analysis," and the emotion engine analyzes the user's concentration while they are studying. If it determines that their concentration is declining, the AI ​​module will suggest new study topics or a break.

[1479] The user inputs the learning progress into the terminal and sends it to the server.

[1480] The server generates a performance evaluation report based on progress and emotion data and provides advice such as "Next step: Marketing."

[1481] In this way, the system provides an individually customized learning curriculum based on the user's interests and goals, and responds flexibly through real-time emotion analysis, thereby realizing lifelong learning support.

[1482] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1483] Specific processing of the system program

[1484] User registration and initial settings

[1485] Step 1:

[1486] A user accesses the system and proceeds to the account creation page. Input: Basic information such as name, age, country of residence, email address, etc. Output: An input form displayed on the terminal.

[1487] What happens: The user enters basic information such as name, age, country of residence, and email address.

[1488] Step 2:

[1489] The terminal sends the entered basic information to the server. Input: User's basic information. Output: User data sent to the server.

[1490] Specific operation: The device sends data to the server via the API.

[1491] Step 3:

[1492] The server stores the received basic information in a database. Input: User data sent to the server. Output: Basic information stored in the database.

[1493] Specific operation: The server calls the database save function and saves the basic information.

[1494] Step 4:

[1495] The device displays a questionnaire asking about the user's interests and learning goals. Input: Information accessed by the user. Output: Display of the questionnaire screen.

[1496] Specific operation: The terminal displays a predefined questionnaire form to the user.

[1497] Step 5:

[1498] The user answers the survey. Input: User's survey answers. Output: Survey data entered into the terminal.

[1499] What happens: The user answers questions about their interests and learning goals and submits the survey form.

[1500] Step 6:

[1501] The terminal sends the survey results to the server. Input: User's survey response data. Output: Survey data sent to the server.

[1502] Specific operation: The device sends the survey results to the server's API.

[1503] Step 7:

[1504] The server stores the survey results in a database. Input: Survey data sent to the server. Output: Survey results stored in a database.

[1505] Specific operation: The server calls the save function and saves the survey results in the database.

[1506] Curriculum Generation

[1507] Step 8:

[1508] The server sends a curriculum generation request to the AI ​​module based on the user's basic information and survey results. Input: Basic information, survey result data. Output: Request to the AI ​​module.

[1509] Specific operation: The server sends an API request for curriculum generation to the artificial intelligence module.

[1510] Step 9:

[1511] The artificial intelligence module uses a generative AI model to design a curriculum. Input: A prompt for curriculum generation (e.g., "Please generate a space-related curriculum for 10-year-old elementary school students."). Output: The generated curriculum.

[1512] Specific operation: The artificial intelligence module inputs prompt sentences into the generation AI and generates an appropriate curriculum.

[1513] Step 10:

[1514] The generated curriculum is sent to the server and stored in the database. Input: Generated curriculum data. Output: Curriculum stored in the database.

[1515] Specific operation: The artificial intelligence module sends the generated curriculum data to the server, which stores it in a database.

[1516] Step 11:

[1517] The server notifies the user of the curriculum generation. Input: Notification data of the generated curriculum. Output: Notification sent to the user.

[1518] Specific behavior: The server uses the notification system to notify the user of the curriculum creation.

[1519] Emotion engine integration

[1520] Step 12:

[1521] The device uses an emotion engine to analyze the user's emotions. Input: User's facial and voice data. Output: Analyzed emotion data.

[1522] Specific operation: The device uses a camera and microphone to collect facial expressions and voice, and performs real-time analysis using an emotion engine.

[1523] Step 13:

[1524] The device sends emotion data to the server. Input: Analyzed emotion data. Output: Emotion data sent to the server.

[1525] Specific operation: The device sends emotion data to the server's API.

[1526] Step 14:

[1527] The server stores the emotion data in a database. Input: Emotion data sent to the server. Output: Emotion data stored in the database.

[1528] Specific operation: The server calls the save function and saves the emotion data in the database.

[1529] Step 15:

[1530] The server sends the emotion data to the AI ​​module. Input: Emotion data stored in the database. Output: Data sent to the AI ​​module.

[1531] Specific operation: The server calls an API that sends emotion data to the artificial intelligence module.

[1532] Step 16:

[1533] The AI ​​module adjusts the curriculum and learning content based on the emotional data. Input: Emotional data. Output: Adjusted curriculum.

[1534] How it works: The AI ​​module analyzes emotional data and adjusts the user's learning content and pace.

[1535] Daily learning support

[1536] Step 17:

[1537] The device displays the study reminder to the user. Input: Study reminder data. Output: Display of reminder screen.

[1538] What it does: The device displays a reminder to the user, such as "Today's lesson: Planets in the solar system."

[1539] Step 18:

[1540] User starts learning. Input: Show reminder. Output: Start learning.

[1541] Specific Action: The user engages in the assigned learning content.

[1542] Step 19:

[1543] The device analyzes the emotion data being learned and sends it to the server. Input: Facial expression and voice data of the user being learned. Output: Emotion data sent to the server.

[1544] Specific operation: The device continuously analyzes the user's facial expressions and voice during training and sends emotional data to the server.

[1545] Step 20:

[1546] The server stores the emotion data in a database and sends it to the AI ​​module. Input: Emotion data sent during training. Output: Emotion data stored in the database.

[1547] Specific operation: The server saves the emotion data in a database and calls an API to send it to the artificial intelligence module.

[1548] Step 21:

[1549] The AI ​​module adjusts the learning content based on the emotional data. Input: Emotional data sent during learning. Output: Adjusted learning content.

[1550] Specific operation: The AI ​​module adjusts its learning content appropriately based on emotional data.

[1551] Learning progress management and curriculum adjustment

[1552] Step 22:

[1553] The user completes the study and inputs the progress data into the terminal. Input: Study progress data. Output: Progress data input into the terminal.

[1554] Specific operation: After completing the study, the user enters their progress into the terminal.

[1555] Step 23:

[1556] The device sends progress data to the server. Input: Progress data entered by the user. Output: Progress data sent to the server.

[1557] Specific operation: The device sends progress data to the server's API.

[1558] Step 24:

[1559] The server stores the progress data in a database. Input: Progress data sent to the server. Output: Progress data stored in the database.

[1560] Specific behavior: The server calls the save function to save the progress data to the database.

[1561] Step 25:

[1562] The server sends the progress data to the AI ​​module. Input: Progress data stored in the database. Output: Data sent to the AI ​​module.

[1563] Specific operation: The server calls an API that sends progress data to the artificial intelligence module.

[1564] Step 26:

[1565] The AI ​​module adjusts the curriculum based on progress data and emotion data. Input: progress data, emotion data. Output: adjusted curriculum.

[1566] Specific operation: The AI ​​module adjusts the curriculum based on progress data and emotional data.

[1567] Grading and Advice

[1568] Step 27:

[1569] The server aggregates the progress data and emotion data and generates a performance evaluation report. Input: Progress data, emotion data. Output: Performance evaluation report.

[1570] Specific operation: The server aggregates the progress data and emotion data and generates a performance evaluation report.

[1571] Step 28:

[1572] The server sends the grading report to the terminal. Input: grading report. Output: Report sent to the user.

[1573] Specific operation: The server calls an API to send the grade evaluation report to the terminal.

[1574] Step 29:

[1575] The terminal displays the performance evaluation report to the user and provides advice. Input: Performance evaluation report sent from the server. Output: Report and advice displayed to the user.

[1576] Specific operation: The device displays the performance evaluation report and advice to the user.

[1577] The above are the specific processing steps of the program for this system. This system responds to the individual needs of users and flexibly adjusts the curriculum to provide effective learning support.

[1578] (Application example 2)

[1579] 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."

[1580] Conventional learning support systems can generate a curriculum based on a user's learning progress and interests. However, they are unable to flexibly respond to the user's emotional and concentration states, making it difficult to maximize learning effectiveness. The present invention aims to provide more effective learning support by monitoring the user's emotional state in real time and adjusting the learning curriculum as needed.

[1581] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1582] In this invention, the server includes means for receiving basic information entered by a user and storing it in a database, means for displaying a questionnaire for entering the user's interests and learning goals and collecting the results, means for transmitting the collected data to an AI module for generating a curriculum based on the collected data, means for storing the curriculum generated by the AI ​​module in a database and notifying the user, means for displaying daily learning reminders and learning materials to the user, means for tracking the user's learning progress and storing it in a database, means for the AI ​​module to adjust the curriculum based on the learning progress data, means for periodically compiling the user's learning progress and generating a performance evaluation report, means for displaying the performance evaluation report to the user and providing advice, means for analyzing the user's emotions from facial expressions or voice, and means for transmitting data to the AI ​​module for adjusting the curriculum based on the analyzed emotional data. This enables more personalized and effective learning support by analyzing the user's emotional state in real time and adjusting the learning curriculum in a timely manner.

[1583] "Basic information" refers to data such as name, age, country of residence, and email address that a user enters into the system.

[1584] A "database" is a storage device that stores basic information about users, survey results, learning progress data, curriculum, and so on.

[1585] A "survey" is a question-based survey used to understand a user's interests and learning goals.

[1586] A "curriculum" is a plan of learning content and teaching materials generated by an AI module based on the user's interests and learning goals.

[1587] An "AI module" is an artificial intelligence component that analyzes user data and generates the optimal curriculum.

[1588] "Study reminders" are notifications and messages that encourage users to study every day.

[1589] "Study progress" is data indicating how far the user has progressed in their studies.

[1590] The "grade evaluation report" is a report on the evaluation of learning grades that is created based on the user's learning progress and emotional data.

[1591] "Emotion analysis" is the process of analyzing a user's emotional state from their facial expressions and voice.

[1592] A "generative AI model" is an artificial intelligence model used by an AI module to generate a curriculum.

[1593] To implement this invention, the following system configuration and program implementation are required: In particular, a database for managing basic user information and learning progress, an AI module for generating a curriculum, and an emotion engine for analyzing emotions are combined.

[1594] System Configuration

[1595] 1. Terminals and Servers

[1596] Users access the system using a smartphone, tablet, or PC (hereinafter referred to as the "terminal"). The terminal receives input from the user and transmits the data to the server. The server is the core of the system, including the database, AI module, and emotion engine.

[1597] 2. User registration and initial settings

[1598] Users enter basic information such as their name, age, country of residence, and email address, and send it to the server via their device. The server stores this information in a database. Users also answer a questionnaire to enter their interests and learning goals, and the results are also sent to the server and stored in the database.

[1599] 3. Curriculum Generation

[1600] The server sends a curriculum generation request to the AI ​​module based on the user's basic information and survey results. The AI ​​module uses the generative AI model to design an optimal curriculum for the user. This curriculum includes learning topics, materials, and learning pace. The generated curriculum is stored in a database via the server and notified to the user.

[1601] 4. Emotion engine integration

[1602] The device is equipped with an emotion engine that analyzes emotions from the user's facial expressions and voice. The emotion engine collects and analyzes the user's emotional data in real time while they are learning. The analysis results are sent to a server and stored in a database. The server then sends the emotional data to an AI module, which then adjusts the curriculum and learning content.

[1603] 5. Daily study support

[1604] During daily study, the device displays study reminders and the day's study materials to the user. The user confirms this and begins studying. The device analyzes the user's facial expressions and voice while studying and sends emotional data to the server. The server stores the emotional data in a database and sends it to the AI ​​module. The AI ​​module adjusts the study content as needed based on the emotional data.

[1605] 6. Learning progress management and curriculum adjustment

[1606] When a user completes their study, they input their progress into the device and send it. The device then sends the progress data to the server and stores it in a database. Based on the emotional data and learning progress data, the AI ​​module adjusts the curriculum and learning pace.

[1607] 7. Grading and Advice

[1608] The server periodically collects the user's learning progress and emotion data and generates a performance evaluation report, which includes the user's learning progress, performance evaluation, improvement points, and next steps. The terminal displays the performance evaluation report to the user and provides advice.

[1609] Specific examples

[1610] Example 1: Elementary school students learning about space

[1611] A user (elementary school student) wishes to learn about space, so he enters his basic information and answers "space" in the questionnaire.

[1612] The server requests the AI ​​module to generate a curriculum, and the AI ​​module generates a curriculum including "Basics of the Universe," "Planets in the Solar System," and "Simple Experiments."

[1613] The device displays daily study reminders, and an emotional engine analyzes the user's facial expressions and voice as they study. If it determines they have lost interest, the AI ​​module will adjust the curriculum and suggest new topics.

[1614] When the user completes the study, the study progress and emotional data are input into the terminal and transmitted to the server.

[1615] The server generates a performance evaluation report based on progress data and emotion data, and suggests next learning steps and areas for improvement.

[1616] Example 2: When a working adult studies business administration

[1617] A user (working adult) wishes to study business administration, enters basic information, and answers "business administration" in the questionnaire.

[1618] The server requests the AI ​​module to generate a curriculum, and the AI ​​module generates a curriculum including "business strategy," "financial analysis," and "marketing."

[1619] The device displays daily study reminders, and while the user is studying, the emotion engine analyzes the user's facial expressions and voice. If it determines that the user's concentration is declining, the AI ​​module will adjust the study content and encourage appropriate breaks.

[1620] When the user completes the study, the study progress and emotional data are input into the terminal and transmitted to the server.

[1621] The server generates a performance evaluation report based on progress data and emotion data, and suggests next learning steps and areas for improvement.

[1622] In this way, the system of the present invention provides a learning curriculum that is individually customized based on the user's interests and goals, and responds flexibly through real-time emotion analysis, thereby realizing lifelong learning support.

[1623] Examples of prompt statements

[1624] "Use generative AI models for curriculum generation."

[1625] "Please suggest the next learning step based on the sentiment analysis data."

[1626] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1627] Step 1:

[1628] The user uses the device to enter basic information (name, age, country of residence, email address) and submits it.

[1629] Input: Basic information entered by the user

[1630] Output: Basic information is sent to the server and stored in the database

[1631] Specific operation: The basic information entered on the terminal is sent to the server, which then stores it in a database.

[1632] Step 2:

[1633] The user answers and submits a survey on the device, entering their interests and learning goals.

[1634] Input: Survey results of interests and learning goals entered by users

[1635] Output: Survey results are sent to the server and stored in the database.

[1636] Specific operation: The user answers a questionnaire displayed on the terminal, and the data is sent to the server, which stores it in a database.

[1637] Step 3:

[1638] The server sends a curriculum generation request to the AI ​​module based on the user's basic information and survey results.

[1639] Input: User's basic information and survey results

[1640] Output: Send a curriculum generation request to the AI ​​module

[1641] Specific operation: The server references the user's basic information and survey results from the database and sends a request to the AI ​​module to design the optimal curriculum using a generative AI model.

[1642] Step 4:

[1643] The AI ​​module uses the generative AI model to design an optimal curriculum for the user and transmits the curriculum to the server.

[1644] Input: Curriculum generation request, user basic information and survey results

[1645] Output: Generated curriculum

[1646] Specific operation: The AI ​​module uses the generative AI model to analyze the data, generate a curriculum including learning topics, materials, and learning pace, and send it to the server.

[1647] Step 5:

[1648] The server stores the generated curriculum in a database and notifies the user.

[1649] Input: Generated curriculum

[1650] Output: Save the curriculum in the database and notify the user

[1651] Specific operation: The server saves the generated curriculum in a database and sends a notification to the terminal to inform the user of the new curriculum.

[1652] Step 6:

[1653] The device displays study reminders and the day's study materials to the user.

[1654] Input: Generated curriculum

[1655] Output: Display of study reminders and learning materials

[1656] Specific operation: The terminal displays daily study reminders and the day's learning materials to the user based on the curriculum received from the server.

[1657] Step 7:

[1658] The terminal uses an emotion engine to analyze emotions from the user's facial expressions and voice, and transmits the emotion data to the server.

[1659] Input: Facial expressions and voice of the user during training

[1660] Output: Parsed emotion data

[1661] Specific operation: The device uses a camera and microphone to capture the user's facial expressions and voice, and the emotion engine analyzes the data to recognize the user's emotional state and sends it to the server.

[1662] Step 8:

[1663] The server stores the emotional data in a database and sends it to an AI module to adjust the curriculum.

[1664] Input: Parsed emotion data

[1665] Output: Curriculum adjustment

[1666] How it works: The server stores the emotional data in a database and sends it to the AI ​​module, which then adjusts the content and pace of the curriculum based on the emotional data.

[1667] Step 9:

[1668] When the user completes the study, he / she inputs the study progress into the terminal and transmits it.

[1669] Input: Learning progress data

[1670] Output: Study progress data sent to server and saved in database

[1671] Specific operation: When the user completes learning, he / she inputs the progress data into the terminal, which then sends it to the server, which stores it in the database.

[1672] Step 10:

[1673] The server generates a performance evaluation report based on the learning progress data and emotion data and notifies the user.

[1674] Input: learning progress data, emotion data

[1675] Output: Generate and notify grade evaluation report

[1676] Specific operation: The server analyzes the progress data and emotion data, generates a performance evaluation report, and notifies the user via the terminal.

[1677] Examples of prompt statements

[1678] "Use generative AI models for curriculum generation."

[1679] "Please suggest the next learning step based on the sentiment analysis data."

[1680] 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.

[1681] 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.

[1682] 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.

[1683] [Fourth embodiment]

[1684] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1685] 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.

[1686] 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).

[1687] 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.

[1688] 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.

[1689] 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).

[1690] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for 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.

[1691] 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.

[1692] 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.

[1693] 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.

[1694] 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.

[1695] 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.

[1696] 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."

[1697] This invention relates to an AI tutoring system that supports daily learning by providing users with individually customized learning curricula based on their specific interests and goals. Below, we will explain the program processing of this system in natural language and provide specific examples.

[1698] System Configuration

[1699] 1. User registration and initial settings

[1700] A user accesses the system and proceeds to the account creation page. First, the user enters basic information such as their name, age, country of residence, email address, etc. This information is sent to the server via the terminal, and the server stores the received information in a database.

[1701] The device then displays a questionnaire to the user asking about their interests and learning goals. When the user answers the questionnaire, the results are sent from the device to the server and stored in a database.

[1702] 2. Curriculum Generation

[1703] The server sends a curriculum generation request to the AI ​​module based on the user's basic information and survey results. The AI ​​module uses generative AI to design a curriculum that is optimal for the user. This curriculum includes learning topics, materials, and learning pace.

[1704] The generated curriculum is sent to the server, which stores it in a database and notifies the user.

[1705] 3. Daily learning support

[1706] For daily learning, the device displays daily learning reminders and the day's study materials to the user. For example, a reminder such as "Today's learning content: Planets of the solar system" is displayed. The user confirms this and begins studying.

[1707] Once the user has completed their learning, the device will send progress information to the server, which will store it in a database and send it to the AI ​​module in a timely manner.

[1708] 4. Learning progress management and curriculum adjustment

[1709] The AI ​​module analyzes the user's progress data to check whether the learning content is appropriate. If necessary, it adjusts the curriculum and suggests new materials and a learning pace. The adjusted curriculum is saved in a database on the server and notified to the user.

[1710] 5. Grading and Advice

[1711] The server periodically aggregates the user's learning progress and generates a performance evaluation report, which includes the user's learning progress, performance evaluation, improvement points, and next steps.

[1712] The device displays this performance evaluation report to the user and provides advice, such as "Next time, focus on the topic of XX."

[1713] Specific examples

[1714] Example 1: Elementary school students learning about space

[1715] A user (elementary school student) wants to learn about space. He enters basic information and answers "space" in a questionnaire about his interests.

[1716] The terminal sends the survey results to the server, and the server requests the AI ​​module to generate a curriculum.

[1717] The AI ​​module generates a curriculum including "Space Basics," "Planets of the Solar System," and "Simple Space Experiments."

[1718] Each day, the device displays reminders and educational materials, such as "Today's learning: Planets in the solar system."

[1719] Users study and report their progress, and the server records the progress data and adjusts the curriculum as needed.

[1720] Example 2: Working adults seeking an MBA

[1721] The user (a working adult) aims to obtain an MBA, enters basic information, and answers "business administration" to a questionnaire about interests.

[1722] The server requests the AI ​​module to generate a curriculum, and the AI ​​module generates a curriculum including "business strategy," "financial analysis," and "marketing."

[1723] Each day, the device displays reminders and learning materials such as "Today's learning topic: Financial analysis."

[1724] Users study and report their progress. The server records the progress data and generates a performance report that includes next steps and areas for improvement.

[1725] In this way, this system provides a learning curriculum that is individually customized based on the user's interests and goals, thereby supporting lifelong learning. This invention improves the quality of education and allows users to continue learning in a way that is best suited to them.

[1726] The above is the "Mode for Carrying Out the Invention."

[1727] The processing flow will be explained below.

[1728] Step 1:

[1729] A user accesses the system and proceeds to the account creation page. The terminal displays a form for entering basic information such as name, age, country of residence, email address, etc. The user enters the information and clicks the submit button.

[1730] Step 2:

[1731] The device sends the entered basic information to the server, which stores the received information in a database and notifies the user via the device that account creation has been completed.

[1732] Step 3:

[1733] The terminal displays a questionnaire to the new user asking about their interests and learning goals. The user answers the questionnaire and submits the results.

[1734] Step 4:

[1735] The device sends the survey results to the server, which stores them in a database and sends the data to the AI ​​module.

[1736] Step 5:

[1737] The server sends a curriculum generation request to the AI ​​module based on the user's basic information and the survey results. The AI ​​module uses the generation AI to design the optimal curriculum for the user.

[1738] Step 6:

[1739] The AI ​​module sends the generated curriculum to the server, which stores it in a database and notifies the user.

[1740] Step 7:

[1741] The device displays daily study reminders and the day's study materials to the user, who then begins studying with the materials presented.

[1742] Step 8:

[1743] When the user completes the study, he / she enters the study progress into the terminal and clicks the send button.

[1744] Step 9:

[1745] The device sends learning progress data to the server, which stores this data in a database and sends it to the AI ​​module as needed.

[1746] Step 10:

[1747] The AI ​​module analyzes the user's progress data, determines whether the learning content is appropriate, adjusts the curriculum as necessary, and sends the adjusted curriculum to the server.

[1748] Step 11:

[1749] The server stores the adjusted curriculum in a database and notifies the user.

[1750] Step 12:

[1751] The server periodically aggregates the user's learning progress and generates a performance evaluation report, which includes the user's learning progress, performance evaluation, improvement points, and next steps.

[1752] Step 13:

[1753] The device displays the performance evaluation report to the user and provides advice, allowing the user to adjust their learning methods and goals based on the evaluation results.

[1754] The above is a concrete explanation of the processing steps of the program.

[1755] Example 1

[1756] 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."

[1757] Conventional learning support systems are unable to respond to the individual learning needs and progress of each user, and are limited to providing a uniform curriculum. In addition, it is difficult for users to manage their learning progress and receive appropriate feedback and advice, which hinders effective learning.

[1758] 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.

[1759] In this invention, the server includes means for receiving personal information entered by the user and storing it in a storage device, means for displaying a survey form for entering the user's interests and learning goals and collecting the results, and means for transmitting the collected data to an AI module to generate a curriculum based on the data. This allows for the provision of a curriculum that meets the individual learning needs of each user, enabling effective learning.

[1760] "Personal information" refers to information necessary to identify an individual, such as a user's name, age, country of residence, and email address.

[1761] A "memory device" is a device that electronically stores and manages information, such as a database or storage.

[1762] A "survey" is a questionnaire or form used to gather information about a user's interests, learning goals, etc.

[1763] An "AI module" is a component that uses artificial intelligence to perform processes such as curriculum generation and learning progress analysis.

[1764] A "curriculum" is a collection of learning plans and materials organized around a user's learning goals.

[1765] "Study reminders" are messages and alerts that inform users of their daily learning content and progress.

[1766] "Study progress" is data on the progress status that indicates how far the user has progressed toward the learning goal set by the user.

[1767] A "performance evaluation report" is a document that evaluates a user's learning progress and lists their grades, areas for improvement, and next steps.

[1768] "Advice" is specific advice or instruction provided to support the user's learning.

[1769] "Generative AI" is an artificial intelligence technology that generates optimal curriculum and advice based on data entered by the user.

[1770] This invention relates to an AI tutoring system that supports daily learning by providing users with individually customized learning curricula based on their specific interests and goals. The program processing of this system is explained below in natural language.

[1771] System Overview

[1772] This system mainly consists of the following elements:

[1773] server

[1774] Terminal

[1775] User

[1776] Generative AI Models

[1777] storage device

[1778] Registering users and saving basic information

[1779] When a user accesses the system, an account creation page is displayed. The user enters personal information such as name, age, country of residence, and email address. This information is sent to the server via the terminal, and the server stores it in a storage device. The terminal then displays a survey form about the user's interests and learning goals, which the user answers. The survey results are again sent to the server via the terminal and stored in a storage device.

[1780] Curriculum generation

[1781] The server sends a curriculum generation request to the generative AI model based on the user's basic information and the survey results. Specifically, the following prompt sentence is used:

[1782] "Please create a curriculum for elementary school students to learn about space. Specifically, please include the basics of space, planets in the solar system, and simple space experiments."

[1783] "Please create a curriculum for working professionals seeking an MBA. Specifically, please include business strategy, financial analysis, and marketing."

[1784] The generative AI model generates a curriculum based on these prompts and sends it to the server. The server stores the received curriculum in a storage device and notifies the user. The device then informs the user that "a curriculum has been generated."

[1785] Daily learning support

[1786] During daily learning, the server sends the day's learning content and reminders to the device. For example, the device displays a reminder such as "Today's learning content: Planets of the solar system." This allows the user to start learning with the specified learning material. Once the learning is complete, the user enters progress information into the device, which then sends it to the server. The progress information is stored in a storage device.

[1787] Learning progress management and curriculum adjustment

[1788] The server periodically sends the user's learning progress data to the generative AI model for analysis. The generative AI model adjusts the curriculum based on the user's progress and suggests new learning paces and materials. The adjusted curriculum is saved in a storage device from the server and notified to the user.

[1789] Grading and Advice

[1790] The server periodically collects the user's learning progress data and generates a performance evaluation report, which includes a performance evaluation, areas for improvement, and next steps. The terminal displays the performance evaluation report to the user and provides specific advice, such as "Next time, focus on the topic of XX."

[1791] Specific examples

[1792] When elementary school students learn about space

[1793] The user (elementary school student) enters basic information and answers "space" to a questionnaire about interests.

[1794] The terminal sends the survey results to the server and requests the AI ​​module to generate a curriculum.

[1795] The generative AI model generates a curriculum including "Space Basics," "Planets of the Solar System," and "Simple Space Experiments."

[1796] Each day, the device displays reminders and educational materials, such as "Today's learning: Planets in the solar system."

[1797] Users study and report their progress, and the server records the progress data and adjusts the curriculum as needed.

[1798] The above is a specific embodiment for carrying out the invention. This system allows users to continue learning in a way that is optimal for them.

[1799] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1800] Step 1: Enter and save basic user information

[1801] When a user accesses the system, they are presented with an account creation page.

[1802] The user enters personal information such as name, age, country of residence, email address, etc. This input data is sent to the terminal.

[1803] The terminal transmits the entered personal information to the server.

[1804] The server stores the received personal information in a storage device.

[1805] Output: The registered user's personal information is saved to the storage device.

[1806] Step 2: View the survey and save the results

[1807] The terminal presents the user with a survey of interests and learning goals.

[1808] The user answers the survey and the results are sent to the terminal.

[1809] The terminal transmits the results of the survey to the server.

[1810] The server stores the results of the investigation in a storage device.

[1811] Output: Data about the user's interests and learning goals is saved to a storage device.

[1812] Step 3: Submit a curriculum generation request

[1813] The server creates prompts for curriculum generation based on the user's basic information and survey results.

[1814] Input: User basic information and survey results

[1815] Output: Curriculum-generated prompt

[1816] The server sends the generated prompt sentence as a request to the generative AI model.

[1817] Example: "Generate a curriculum for elementary school students to learn about space. Specifically, include the basics of space, planets in the solar system, and simple space experiments."

[1818] Step 4: Generate and save the curriculum

[1819] The generative AI model generates a learning curriculum based on the prompt sentence.

[1820] Input: Curriculum generation prompt

[1821] Output: Generated learning curriculum

[1822] The server receives the generated curriculum and stores it in a storage device.

[1823] The terminal notifies the user that "The curriculum has been generated."

[1824] Step 5: View study reminders and materials

[1825] The server sends the day's learning content and reminders to the device.

[1826] The device displays reminders and educational materials to the user, such as "Today's learning: Planets in the solar system."

[1827] Input: Today's learning content and reminders

[1828] Output: Reminders and educational materials displayed to the user

[1829] Step 6: Enter and save your learning progress

[1830] The user checks the reminder and continues studying.

[1831] When the user has completed the learning, the terminal displays a "Learning Completed" button.

[1832] When the user clicks the button, progress information is sent to the terminal.

[1833] The terminal sends progress information to the server.

[1834] The server stores the progress information in a storage device.

[1835] Input: Learning progress information

[1836] Output: Learning progress information stored in memory.

[1837] Step 7: Analyze learning progress data and adjust curriculum

[1838] The server periodically sends progress data to the generative AI model.

[1839] The generative AI model analyzes the user's progress data to ensure that the learning content is appropriate.

[1840] Input: Learning progress data

[1841] Output: Analysis results and adjustment suggestions

[1842] If necessary, the generative AI model will adjust the curriculum.

[1843] The server receives the tailored curriculum and stores it in a storage device.

[1844] The terminal notifies the user of the adjusted curriculum.

[1845] Step 8: Generate and view the grading report

[1846] The server periodically compiles the user's learning progress data and generates a performance evaluation report.

[1847] Input: Learning progress data

[1848] Output: Grade evaluation report

[1849] The terminal displays the performance evaluation report to the user and provides specific advice.

[1850] For example, advice such as "Next time, let's focus on the topic of XX."

[1851] The above are the specific processing steps of this system's program. This makes it possible to provide an optimal curriculum for each user, manage learning progress, and provide appropriate feedback.

[1852] (Application example 1)

[1853] 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."

[1854] Conventional tutoring systems lack the ability to customize to meet the individual learning needs and goals of users, resulting in a decline in learning effectiveness. Furthermore, the lack of interactive learning content utilizing smart devices has led to issues such as difficulty in maintaining motivation to learn.

[1855] 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.

[1856] In this invention, the server includes means for receiving basic information input by a user and storing it in a data management device, means for displaying a survey for inputting the user's interests and learning goals and collecting the results, means for transmitting the collected data to an intelligence module for generating an educational plan based on the collected data, means for storing the educational plan generated by the intelligence module in the data management device and notifying the user, means for displaying daily learning notifications and educational materials to the user, means for tracking the user's learning progress and storing it in the data management device, means for the intelligence module to adjust the educational plan based on the learning progress data, means for periodically compiling the user's learning progress and generating a performance evaluation report, means for displaying the performance evaluation report to the user and providing advice, and means for delivering interactive learning content on devices such as smart glasses and mobile terminals, thereby enabling a highly customized learning experience tailored to the user's individual needs.

[1857] "User" refers to any individual or entity that uses the System.

[1858] "Basic information" refers to personal information such as the user's name, age, place of residence, and email address.

[1859] "Data Management Device" refers to a system or device for storing and managing information collected from users.

[1860] "Survey" refers to a questionnaire-style interface that includes questions about the user's interests and learning goals.

[1861] "Intelligence Module" refers to a program containing artificial intelligence algorithms for generating an optimal training plan based on user input data.

[1862] "Educational Plan" means a plan including curriculum, materials, and learning pace designed to achieve a user's learning goals.

[1863] "Notification" refers to the action of sending important information or reminders from the system to the user.

[1864] "Educational materials" refers to teaching materials and content used for learning, such as texts, videos, and quizzes.

[1865] "Study progress" refers to data indicating how much of the learning content a user has completed.

[1866] "Performance evaluation report" refers to a report that compiles and evaluates a user's learning outcomes and progress.

[1867] "Advice" refers to advice on the user's learning and suggestions for next steps.

[1868] "Smart glasses" refers to a glasses-type device equipped with augmented reality and information display functions.

[1869] "Mobile device" refers to a portable electronic device such as a smartphone or tablet.

[1870] "Interactive learning content" refers to educational content that allows users to actively participate and learn while receiving feedback.

[1871] This invention relates to an AI tutoring system that supports daily learning by providing a personalized learning curriculum based on a user's specific interests and goals. The system can deliver interactive learning content on devices such as smart glasses and mobile terminals.

[1872] System Configuration

[1873] 1. User registration and initial settings

[1874] The user navigates to an account creation page on the device. First, the user enters basic information such as their name, age, place of residence, and email address. This information is sent to the server via the device, and the server stores the received information in a data management device. The device then displays a survey asking the user about their interests and learning goals. After the user completes the survey, the results are sent from the device to the server and stored in the data management device.

[1875] 2. Curriculum Generation

[1876] The server sends a request to the intelligent module to generate a learning plan based on the user's basic information and survey results. The intelligent module uses the generative AI model to design an optimal learning plan for the user. This learning plan includes learning topics, materials, and learning pace. The generated learning plan is sent to the server, stored in the data management device, and notified to the user.

[1877] 3. Daily learning support

[1878] During daily learning, the device displays daily learning notifications and the day's educational materials to the user. For example, a notification such as "Today's learning content: Planets in the solar system" is displayed. The user confirms this and begins learning. When the user completes their learning, the device sends progress information to the server. The server stores this information in the data management device and transmits it to the intelligent module in a timely manner.

[1879] 4. Managing learning progress and adjusting educational plans

[1880] The intelligent module analyzes the user's progress data to determine whether the learning content is appropriate. If necessary, it adjusts the learning plan and suggests new learning materials and a learning pace. The adjusted learning plan is then stored in the data management device from the server and notified to the user.

[1881] 5. Grading and Advice

[1882] The server periodically compiles the user's learning progress and generates a performance evaluation report. This report includes the user's learning progress, performance evaluation, areas for improvement, and next steps. The device displays this performance evaluation report to the user and provides advice. For example, specific advice such as "Next time, focus on topic XX" may be included.

[1883] Detailed processing

[1884] The basic information and survey results entered by the user are sent to the server via the device. The server stores this data in a data management device and sends it to an intelligence module (a generative AI model such as GPT-3). The intelligence module generates an optimal educational plan for the user based on the prompt sentence. For example, the following prompt sentences can be used:

[1885] Prompt Sentence Examples

[1886] User information: Name = Taro Tanaka, Age = 25, Interests = Programming, Level = Beginner

[1887] Survey results: Learning goal = Web development, Hobby = Game development, Study time = 1 hour / day

[1888] Generated curriculum:

[1889] Week 1: HTML / CSS Basics

[1890] Week 2: JavaScript Basics

[1891] Week 3: Simple web application development

[1892] Week 4: Game Development Fundamentals

[1893] The generated educational plan is stored in a data management device and sent to the user's device. The user receives daily learning notifications and begins studying. Learning progress is sent to the server in real time, and an intelligent module analyzes it and periodically adjusts the educational plan. Overall, this system provides users with a customized learning experience, enabling them to continue learning while maintaining their motivation.

[1894] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1895] Step 1:

[1896] The user accesses the account creation page using a terminal and enters basic information (name, age, place of residence, email address, etc.). The terminal sends the entered basic information to the server, which then stores the information in the data management device.

[1897] Input: Basic information such as name, age, place of residence, and email address

[1898] Output: Basic information of the user stored in the data management device

[1899] Step 2:

[1900] The device displays a survey to the user asking about their interests and learning goals. After the user completes the survey, the device transmits the results to a server, which stores the survey results in a data management device.

[1901] Input: Survey results about user interests and learning goals

[1902] Output: Survey results stored in the data management device

[1903] Step 3:

[1904] The server sends a request for generating an educational plan to the intelligence module based on the user's basic information and the survey results. The intelligence module uses the generative AI model to generate the optimal educational plan for the user. This process is based on the prompt text.

[1905] Input: User basic information and survey results stored in the data management device

[1906] Output: The training plan generated by the intelligence module

[1907] Step 4:

[1908] The intelligent module sends the generated training plan to the server, which stores it in the data management device and notifies the user, who then displays the notification to the terminal, allowing the user to confirm the training plan.

[1909] Input: Educational plan generated by the intelligence module

[1910] Output: Education plan stored in the data management device and notification displayed to the user

[1911] Step 5:

[1912] Every day, the device displays a learning notification and the day's educational material to the user. The user checks the notification and begins learning.

[1913] Input: Educational materials for the day stored in the data management device

[1914] Output: Learning notifications and educational materials displayed on the device

[1915] Step 6:

[1916] When the user completes the learning, the terminal transmits the progress information to the server, which stores the progress information in the data management device.

[1917] Input: User learning progress information

[1918] Output: Learning progress information stored in the data management device

[1919] Step 7:

[1920] The server periodically transmits the learning progress data to the intelligent module, which analyzes the data and adjusts the educational plan, which is then stored in the data management device by the server and notified to the user.

[1921] Input: Learning progress data stored in the data management device

[1922] Output: Coordinated educational plan

[1923] Step 8:

[1924] The server periodically compiles the user's learning progress and generates a performance evaluation report, which includes the user's learning progress, performance evaluation, areas for improvement, and next steps. The terminal displays the performance evaluation report to the user and provides advice.

[1925] Input: Aggregated data based on learning progress stored in the data management device

[1926] Output: A grading report and advice displayed to the user

[1927] The above are the specific processing steps of this system.

[1928] 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.

[1929] This invention relates to an AI tutoring system that supports daily learning by providing a personalized learning curriculum based on the user's specific interests and goals. Furthermore, this system combines an emotion engine that recognizes the user's emotions, enabling more flexible and personalized instruction.

[1930] System Configuration

[1931] 1. User registration and initial settings

[1932] A user accesses the system and proceeds to the account creation page. First, the user enters basic information such as their name, age, country of residence, email address, etc. The device sends the entered information to the server, which stores it in a database.

[1933] Next, the device displays a questionnaire to the user asking about their interests and learning goals. After the user answers the questionnaire, the results are sent to the server and stored in a database.

[1934] 2. Curriculum Generation

[1935] The server sends a curriculum generation request to the AI ​​module based on the user's basic information and survey results. The AI ​​module uses generative AI to design a curriculum that is optimal for the user. This curriculum includes learning topics, materials, and learning pace.

[1936] The generated curriculum is sent to the server and stored in a database, and the server notifies the user.

[1937] 3. Emotion engine integration

[1938] The device is equipped with an emotion engine that analyzes the user's emotions from their facial expressions and voice. The emotion engine collects emotional data as the user progresses through the learning process and analyzes it in real time.

[1939] Emotion analysis data is sent from the device to a server. The server stores the emotional data in a database and sends it to an AI module. The AI ​​module adjusts the curriculum and learning content according to the user's emotions.

[1940] 4. Daily study support

[1941] For daily study, the device displays study reminders and the day's study materials to the user. For example, a reminder such as "Today's study topic: Planets in the solar system" is displayed. The user confirms this and begins studying.

[1942] The device analyzes the user's facial expressions and voice and sends emotional data to the server, which stores it in a database and sends it to the AI ​​module, which then adjusts its learning content accordingly.

[1943] 5. Learning progress management and curriculum adjustment

[1944] When a user completes their study, they input their progress into the device and send it. The device then sends the progress data to the server and stores it in a database. Based on the emotional data and learning progress data, the AI ​​module adjusts the curriculum and learning pace.

[1945] 6. Grading and Advice

[1946] The server periodically collects the user's learning progress and emotion data and generates a performance evaluation report, which includes the user's learning progress, performance evaluation, improvement points, and next steps. The terminal displays the performance evaluation report to the user and provides advice.

[1947] Specific examples

[1948] Example 1: Elementary school students learning about space

[1949] A user (elementary school student) wants to learn about space. He enters basic information and answers "space" in a questionnaire about his interests.

[1950] The server requests the AI ​​module to generate a curriculum, and the AI ​​module generates a curriculum including "Basics of the Universe," "Planets in the Solar System," and "Simple Experiments."

[1951] Every day, the device displays "Today's learning content: Planets of the solar system," and as the user progresses, the emotion engine analyzes the user's facial expressions and voice. If it determines that the user has lost interest, the AI ​​module adjusts the curriculum and suggests new topics.

[1952] When the user completes the study, the study progress and emotional data are input into the terminal and transmitted to the server.

[1953] The server generates a performance evaluation report based on progress data and emotion data, and suggests next learning steps and areas for improvement.

[1954] Example 2: Working adults seeking an MBA

[1955] The user (a working adult) aims to obtain an MBA, enters basic information, and answers "business administration" to a questionnaire about interests.

[1956] The server requests the AI ​​module to generate a curriculum, and the AI ​​module generates a curriculum including "business strategy," "financial analysis," and "marketing."

[1957] Every day, the device displays "Today's learning content: Financial analysis," and as the user progresses through the learning process, the emotion engine analyzes the user's facial expressions and voice. If the AI ​​module determines that the user's concentration is declining, it adjusts the learning content and encourages them to take a break at the appropriate time.

[1958] The user inputs learning progress and emotional data into the terminal and transmits it to the server.

[1959] The server generates a performance evaluation report based on progress data and emotion data, and suggests next learning steps and areas for improvement.

[1960] This system provides a personalized learning curriculum based on the user's interests and goals, and responds flexibly through real-time emotion analysis, enabling lifelong learning support. This invention improves the quality of education and allows users to continue learning in a way that is best suited to them.

[1961] The above is the "Mode for Carrying Out the Invention."

[1962] The processing flow will be explained below.

[1963] Step 1:

[1964] A user accesses the system and proceeds to the account creation page. The terminal displays a form for entering basic information such as name, age, country of residence, email address, etc. The user enters the information and clicks the submit button.

[1965] Step 2:

[1966] The device sends the entered basic information to the server, which stores the received information in a database and notifies the user via the device that account creation has been completed.

[1967] Step 3:

[1968] The terminal displays a questionnaire to the new user asking about their interests and learning goals. The user answers the questionnaire and submits the results.

[1969] Step 4:

[1970] The device sends the survey results to the server, which stores them in a database and sends the data to the AI ​​module.

[1971] Step 5:

[1972] The server sends a curriculum generation request to the AI ​​module based on the user's basic information and the survey results. The AI ​​module uses the generation AI to design the optimal curriculum for the user.

[1973] Step 6:

[1974] The AI ​​module sends the generated curriculum to the server, which stores it in a database and notifies the user.

[1975] Step 7:

[1976] The device displays daily study reminders and the day's learning materials to the user. For example, a reminder might say, "Today's learning content: Planets in the solar system." The user then begins studying the materials provided.

[1977] Step 8:

[1978] While the user is learning, the device's built-in emotion engine analyzes the user's facial expressions and voice to collect emotional data, including facial expression analysis and voice tone analysis.

[1979] Step 9:

[1980] The device sends the collected emotional data to a server, which stores the data in a database and sends it to an AI module.

[1981] Step 10:

[1982] The AI ​​module analyzes emotional and learning progress data and adjusts learning content and methods based on the user's current emotional state. For example, if the user is tired, it will suggest a break or switch to a less difficult problem.

[1983] Step 11:

[1984] The server stores the adjusted curriculum in a database and notifies the user.

[1985] Step 12:

[1986] When the user completes the study, they input their study progress into the device and click the send button. The device then sends the study progress data and emotion data to the server.

[1987] Step 13:

[1988] The server stores the learning progress data and emotion data in a database and periodically aggregates them to generate a performance evaluation report, which includes the user's learning progress, performance evaluation, improvement points, and next steps.

[1989] Step 14:

[1990] The device displays a performance evaluation report to the user and offers advice, such as "Next time, try taking breaks to improve your concentration."

[1991] Step 15:

[1992] The server collects user feedback and sends it to the AI ​​module for further curriculum optimization.

[1993] The above is a concrete explanation of the processing steps of the system that integrates the emotion engine.

[1994] Example 2

[1995] 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."

[1996] In recent years, there has been a demand for individually customized learning support systems, but existing systems lack the flexibility to respond sufficiently to users' interests and goals. Furthermore, they lack the ability to analyze users' emotions in real time and adjust the curriculum accordingly, resulting in the problem of only being able to provide uniform instruction. Furthermore, the management of learning progress and grade evaluation are still done manually, which is inefficient and affects users' ability to continue learning. There is a need for a comprehensive learning support system that can solve these issues.

[1997] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving basic information entered by a user and storing it in a database, means for displaying a questionnaire for entering the user's interests and learning goals and collecting the results, means for transmitting data to an artificial intelligence module to generate a curriculum based on the collected data, means for storing the curriculum generated by the artificial intelligence module in a database and notifying the user, means for displaying daily learning reminders and learning materials to the user, means for tracking the user's learning progress and storing it in a database, means for the artificial intelligence module to adjust the curriculum based on learning progress data, means for analyzing emotions from the user's facial expressions and voice, sending the analyzed data to the server and storing it in a database, means for adjusting the curriculum and learning content based on the emotion data, means for periodically compiling the user's learning progress and emotion data and generating a performance evaluation report, and means for displaying the performance evaluation report to the user and providing advice. This enables the provision of a customized learning curriculum tailored to the user's interests and goals and flexible learning support based on emotion analysis.

[1998] "Basic information" refers to personal information such as name, age, country of residence, and email address that a user enters when registering with the system.

[1999] A "survey" is a collection of questions displayed to gather information about a user's interests and learning goals.

[2000] An "artificial intelligence module" is a program that includes artificial intelligence capabilities to generate a curriculum based on collected data and tailor it to the user's individual needs.

[2001] A "curriculum" is a set of learning plans, including learning content, learning materials, and learning pace, designed based on a user's learning goals.

[2002] "Reminder" is a system function that notifies users of the day's study content and schedule.

[2003] "Study progress" is information indicating the results achieved by the user in the course of studying and the current progress status.

[2004] "Emotion data" is data that indicates the emotional state of the user analyzed from facial expressions, voice, etc.

[2005] The "performance evaluation report" is a report that compiles the user's learning progress and emotional data, and includes an evaluation of the learning content and suggestions for the next learning step.

[2006] "Generative AI" is AI that has the ability to generate new information or content based on instructions such as prompts.

[2007] The present invention is a system that supports daily learning by providing an individually customized learning curriculum based on the user's specific interests and goals. Furthermore, this system combines an emotion engine that recognizes the user's emotions, enabling more flexible and personalized instruction.

[2008] System Configuration

[2009] 1. User registration and initial settings

[2010] A user accesses the system and proceeds to the account creation page. Here, the user enters basic information such as name, age, country of residence, and email address. The device sends this information to the server, which stores the data in a database. The device then displays a survey asking about the user's interests and learning goals. After the user answers the survey, the results are sent to the server and stored in the database.

[2011] 2. Curriculum Generation

[2012] The server sends a curriculum generation request to the artificial intelligence module based on the user's basic information and the survey results. The artificial intelligence module uses the generative AI model to design the optimal curriculum for the user. The generated curriculum is sent to the server and stored in the database. The server then notifies the user.

[2013] 3. Emotion engine integration

[2014] The device is equipped with an emotion engine that analyzes emotions from the user's facial expressions and voice. The emotion engine collects emotional data as the user progresses through the study and analyzes it in real time. The analyzed emotional data is sent from the device to a server and stored in a database. This data is then sent to an artificial intelligence module, which adjusts the curriculum and learning content according to the user's emotions.

[2015] 4. Daily study support

[2016] During daily learning, the device displays learning reminders and the day's learning materials to the user. For example, a reminder such as "Today's learning content: Planets in the solar system" may be displayed. The user confirms this and begins learning. The device analyzes the user's facial expressions and voice and sends emotional data to the server. The server stores this data in a database and sends it to the artificial intelligence module. The artificial intelligence module adjusts the learning content accordingly based on the emotional data.

[2017] 5. Learning progress management and curriculum adjustment

[2018] When a user completes their learning, they input their progress data into the device and send it to the server, which then sends it to the server and stores it in a database. The server then sends this progress data and emotion data to an AI module, which then adjusts the curriculum and learning pace based on the month.

[2019] 6. Grading and Advice

[2020] The server periodically collects the user's learning progress and emotional data and generates a performance evaluation report, which includes the user's learning progress, performance evaluation, improvement points, and next steps. The device displays this report to the user and provides advice.

[2021] Specific examples

[2022] Example 1: Elementary school students learning about space

[2023] A user (elementary school student) wishes to learn about space, enters basic information, and answers "space" to a questionnaire about their interests.

[2024] The server requests the artificial intelligence module to generate a curriculum, and the artificial intelligence module generates the curriculum using the prompt "Please generate a space-related learning curriculum for 10-year-old elementary school students."

[2025] The device displays "Today's lesson: Planets of the solar system" and uses an emotion engine to analyze the user's emotions while they are learning. The emotion data is sent to a server, and the curriculum is adjusted as needed.

[2026] The user completes the study and enters the progress data into the terminal and transmits it to the server.

[2027] The server generates a performance evaluation report based on progress data and emotional data, and displays advice such as "Next learning step: The basics of the universe" on the device.

[2028] Example 2: Working adults seeking an MBA

[2029] The user (a working adult) enters basic information and a questionnaire, and answers that they are interested in "business management."

[2030] The server requests the artificial intelligence module to generate a curriculum, and the artificial intelligence module generates a curriculum including content such as "business strategy" and "financial analysis."

[2031] The device displays "Today's Study Topic: Financial Analysis," and the emotion engine analyzes the user's concentration while they are studying. If it determines that their concentration is declining, the AI ​​module will suggest new study topics or a break.

[2032] The user inputs the learning progress into the terminal and sends it to the server.

[2033] The server generates a performance evaluation report based on progress and emotion data and provides advice such as "Next step: Marketing."

[2034] In this way, the system provides an individually customized learning curriculum based on the user's interests and goals, and responds flexibly through real-time emotion analysis, thereby realizing lifelong learning support.

[2035] The flow of the identification process in the second embodiment will be describe...

Claims

1. A means of receiving basic information entered by the user and storing it in a database; a means for displaying a survey for inputting user interests and learning goals and collecting the results; a means for transmitting the collected data to an AI module for generating a curriculum based on the collected data; A means for storing the curriculum generated by the AI ​​module in a database and notifying the user; a means for displaying daily study reminders and learning materials to the user; a means for tracking and storing in a database the user's learning progress; A means for the AI ​​module to adjust the curriculum based on learning progress data; a means for periodically compiling the user's learning progress and generating a performance evaluation report; a means for displaying the performance evaluation report to the user and providing advice; A system including:

2. The system of claim 1 , wherein the AI ​​module used for generating the curriculum includes a generative AI.

3. The system according to claim 1, further comprising an AI module that flexibly adjusts the curriculum based on learning progress data input by the user.

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