System

Abstract

A system is provided.SOLUTION: A system comprising: means for collecting initial data from a learner; means for generating a learning curriculum optimized for each learner using artificial intelligence; means for transmitting the learning curriculum to a terminal of the learner; means for generating data of a virtual instructor; means for transmitting the generated virtual instructor to the terminal of the learner; means for monitoring a learning progress status; and means for generating feedback based on the learning progress data.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Many learners who attend cram schools or private tutoring classes often drop out midway or experience no benefit. While excellent instructors can provide effective learning instruction tailored to each learner, there are few such instructors, making it difficult to provide consistently high-quality instruction to all learners. It is also difficult to maintain motivation for continued learning, preventing effective improvement in academic ability. The goal is to solve this situation and provide an effective learning environment optimized for each learner. [Means for solving the problem]

[0005] The present invention provides individually optimized learning guidance to learners using a system including a means for collecting initial data from learners, a means for generating a learning curriculum optimized for each learner using artificial intelligence, a means for transmitting the learning curriculum to the learner's terminal, a means for generating virtual tutor data, a means for transmitting the generated virtual tutor to the learner's terminal, a means for monitoring learning progress, and a means for generating feedback based on the learning progress data. This maximizes the learner's learning efficiency and effectively improves their academic ability. Furthermore, customizing the virtual tutor based on the learner's preferences makes it easier to maintain learning motivation. Furthermore, the feedback includes adjusting the curriculum based on learning progress, making it possible to always provide an optimal learning environment.

[0006] "Initial data" refers to individual information such as the learner's basic information, academic test results, learning objectives, and preferred learning methods.

[0007] "Artificial intelligence" refers to technology that allows computers to mimic human intelligence and perform data analysis and decision-making.

[0008] A "learning curriculum" refers to a plan that defines the learning content and schedule that learners should undertake.

[0009] "Devices" refer to electronic devices such as computers, smartphones, and tablets that learners can operate.

[0010] A "virtual instructor" refers to a character or person who explains lesson content to learners in a virtual environment.

[0011] "Learning progress" refers to data that shows the results and progress of a learner's efforts in learning content.

[0012] "Feedback" refers to information that evaluates a learner's performance and communicates areas for improvement.

[0013] "Customization" refers to adjusting the appearance and functionality based on individual preferences and desires.

[0014] "Monitoring" refers to the real-time observation and recording of learners' learning behavior and progress.

[0015] "Optimization" refers to adjusting methods and conditions to maximize learner efficiency and effectiveness. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

[0024] [First embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0037] This invention is a system that utilizes AI and VR technology to provide individually optimized learning guidance to learners. This system operates in cooperation with three parties: a server, a terminal, and a user.

[0038] Server processing explanation

[0039] 1. Data Collection and Initial Setup:

[0040] The server collects initial data from the learner, including name, age, grade, achievement test results, learning goals, and preferred learning methods.

[0041] Example: The server receives the data entered by the user in the registration form (e.g., name "Yamada Taro", age "12 years old").

[0042] 2. Generating an individually optimized curriculum:

[0043] The server uses artificial intelligence to generate an optimized learning curriculum for each learner, including the learning content for each subject, progress schedule, and evaluation method.

[0044] Example: A server-generated curriculum specifies weekly math practice problems and monthly practice tests.

[0045] 3. Virtual Instructor Setup:

[0046] The server generates data on a virtual teacher based on the learner's preferences, and this teacher appears in the VR environment with the appearance and speaking style of a specific character or person.

[0047] Example: When a learner selects a virtual teacher who resembles Doraemon, the server generates a 3D model and voice data that resembles Doraemon.

[0048] 4. Progress monitoring and feedback:

[0049] The server monitors learning progress in real time, adjusts the curriculum as needed, and provides feedback based on the learner's performance data.

[0050] Example: The server generates and sends a message saying "Well done!" based on the learner's test results (e.g., 90 points in mathematics).

[0051] Terminal processing explanation

[0052] 1. Data Entry:

[0053] The terminal accepts data input from the learner, including initial data and learning progress data.

[0054] Example: The device displays a popup to start an academic ability test, and the user starts the test.

[0055] 2. View Virtual Instructor:

[0056] The device receives data from the server and displays the virtual instructor in a VR environment, providing interactive lessons.

[0057] Example: Using a VR headset, a video is displayed in which a virtual instructor dressed like Doraemon explains the content of the preparatory lesson.

[0058] 3. View and progress your learning:

[0059] The device displays learning content (text, videos, exercises) to the learner based on the learning curriculum.

[0060] Example: A device displays math exercises and the user answers them.

[0061] 4. Sending progress data:

[0062] The device sends learning progress and test results to the server, allowing the server to track progress in real time and provide appropriate feedback.

[0063] Example: The device sends the learner's test results (e.g., 90 points in mathematics) to the server.

[0064] User behavior description

[0065] 1. Enter the initial data:

[0066] Users enter their information into a registration form, including their name, age, grade level, learning goals, and preferred learning method.

[0067] Example: A user fills out a registration form with the name "Yamada Taro" and age "12 years old."

[0068] 2. Participating in a VR environment:

[0069] Users wear a VR device and participate in lessons taught by a virtual instructor. If they have any questions during the lesson, they can ask them using voice input or a dedicated interface.

[0070] Example: A user uses a VR headset to take a lesson from a Doraemon-style virtual instructor.

[0071] 3. Engage in learning content:

[0072] Users work through the learning content displayed on their device, solving problems and taking tests.

[0073] Example: A user works through a math exercise displayed on a terminal and enters the answers.

[0074] 4. Receiving and incorporating feedback:

[0075] Users receive feedback from the server and incorporate it into their learning. They also receive messages and rewards to keep them motivated.

[0076] Example: The user receives a "Good job!" message from the server and proceeds to the next learning step.

[0077] This system allows learners to continue studying in a learning environment that is optimized for them, and aims to effectively improve their academic ability.

[0078] The processing flow will be explained below.

[0079] Server processing explanation

[0080] Step 1:

[0081] The server receives the user registration information.

[0082] Specific operation: The user enters the name, age, and grade in the registration form and presses the submit button, which sends the entered data to the server and saves it in the database.

[0083] Step 2:

[0084] The server provides the user with a link to the achievement test.

[0085] Specific operation: The server automatically generates an email containing the URL of the academic ability test and sends it to the user, or displays the link of the academic ability test on the dashboard.

[0086] Step 3:

[0087] The server receives and stores the results of the academic achievement test.

[0088] Specific operation: When a user completes an academic ability test, the results are sent from the device to the server and stored in a database.

[0089] Step 4:

[0090] The server uses artificial intelligence to generate an individually optimized curriculum.

[0091] Specific operation: Analyze the received academic ability test results and initial data, and generate the learning content and progress schedule required for the user.

[0092] Step 5:

[0093] The server transmits the generated curriculum to the terminal.

[0094] Specific operation: Send data to the terminal so that the generated learning curriculum is displayed on the user's dashboard.

[0095] Step 6:

[0096] The server generates the data of the virtual instructor.

[0097] Specific operation: Generates a 3D model and audio data based on the user's preferences and stores it in a database.

[0098] Step 7:

[0099] The server transmits the generated virtual instructor data to the terminal.

[0100] Specific operation: The generated virtual instructor data is sent to the terminal so that it is displayed in the user's VR environment.

[0101] Step 8:

[0102] The server monitors the learning progress.

[0103] Specific operation: Receives user progress data (e.g., exercise completion status, test results) sent from the device in real time and stores it in a database.

[0104] Step 9:

[0105] The server generates feedback and adjusts the curriculum as needed.

[0106] Specific behavior: Analyzes progress data, generates feedback messages with praise and suggestions for improvement, and sends them to the device, updating the learning curriculum as needed.

[0107] Terminal processing explanation

[0108] Step 1:

[0109] The terminal displays an initial data entry form to the user.

[0110] What it does: Displays a registration form on a web page or app, allowing users to enter their name, age, grade, etc.

[0111] Step 2:

[0112] The terminal transmits the user's input data to the server.

[0113] Specific operation: When the user presses the submit button to send the data entered in the registration form to the server, the data is sent to the backend.

[0114] Step 3:

[0115] The device displays the academic achievement test link and allows the user to access it.

[0116] Specific behavior: A link to the academic achievement test is displayed on the dashboard or in an email, and the user clicks it to begin the test.

[0117] Step 4:

[0118] The terminal inputs the user's academic achievement test results and sends them to the server.

[0119] What it does: The user completes the test and the results are automatically sent to the server.

[0120] Step 5:

[0121] The terminal displays the curriculum received from the server.

[0122] Specific operation: The curriculum data received from the server is displayed on the dashboard so that the user can check it.

[0123] Step 6:

[0124] The device displays the virtual instructor data received from the server in a VR environment.

[0125] Specific operation: Using a VR device, the 3D model and audio data received from the server are rendered to provide interactive lessons.

[0126] Step 7:

[0127] The device displays the learning content and the user works on it.

[0128] Specific operation: Learning content such as text, videos, and exercises are displayed to the user, and the user works on it.

[0129] Step 8:

[0130] The terminal transmits learning progress data to the server.

[0131] Specific operation: The results of the user's work on the learning content are recorded in real time and periodically sent to the server.

[0132] User behavior description

[0133] Step 1:

[0134] The user enters the initial data.

[0135] Specific actions: Enter your name, age, grade, learning goals, and preferred learning method in the registration form and press the submit button.

[0136] Step 2:

[0137] The user accesses the test link and begins the test.

[0138] Specific actions: Click on the academic achievement test link displayed in email or on the dashboard to begin the test.

[0139] Step 3:

[0140] A user completes a quiz.

[0141] Specific actions: Answer the test questions and enter the results into the terminal.

[0142] Step 4:

[0143] Users wear VR devices and participate in classes taught by virtual instructors.

[0144] Specific actions: Put on a VR headset and watch a lesson from a virtual instructor.

[0145] Step 5:

[0146] The user engages with the learning content.

[0147] Specific actions: Work through the text, videos, and practice problems displayed on the device.

[0148] Step 6:

[0149] The user receives feedback and moves on to the next learning step.

[0150] Specific behavior: Receive the feedback message sent from the server and work on the next learning content.

[0151] In this way, the server, terminal, and user work together to provide effective learning guidance.

[0152] Example 1

[0153] 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."

[0154] In recent years, there has been a demand for a learning environment that is optimized for each learner's academic ability and learning style, but conventional systems have difficulty fully meeting this demand. In particular, they lack the functionality to integrate multiple elements, such as generating individually optimized learning curricula, providing virtual instructors that match the learner's preferences, and monitoring learning progress in real time and providing feedback.

[0155] 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.

[0156] In this invention, the server includes means for inputting personal information from the learner, means for generating an education plan optimized for each learner using artificial intelligence, means for transmitting the education plan to the learner's device, means for generating virtual instructor data, means for transmitting the generated virtual instructor to the learner's device, means for displaying the virtual instructor in a virtual reality environment, means for monitoring learning progress in real time, and means for generating and transmitting feedback based on the learning progress data. This makes it possible to provide an individually optimized learning curriculum, effective learning support by a virtual instructor that suits the learner's preferences, and real-time understanding of progress and appropriate feedback.

[0157] "Means for learner input of personal information" refers to an interface designed to allow learners to input personal information such as their name, age, grade, and learning goals.

[0158] "Means for generating educational plans optimized for each learner using artificial intelligence" refers to algorithms or software that take a learner's personal information and learning data as input and automatically generate appropriate learning content and schedules.

[0159] The "means for transmitting the educational plan to the learner's device" refers to a system including communication means and protocols for transferring the generated educational plan to the learner's terminal.

[0160] "Means for generating virtual instructor data" refers to software or tools for creating data that resembles the appearance and speaking style of a specific character or person based on learner preferences.

[0161] The "means for transmitting the generated virtual instructor to the learner's device" refers to a system including communication means and protocols for transmitting data of the generated virtual instructor to the learner's terminal.

[0162] The "means for displaying the virtual instructor in a virtual reality environment" refers to a device or software that displays the virtual instructor in a virtual reality environment and allows learners to take lessons interactively.

[0163] "Means for monitoring learning progress in real time" refers to a system that collects, records, and analyzes information in real time, such as the learner's current stage and how well they have completed tasks.

[0164] The "means for generating and transmitting feedback based on the learning progress data" refers to an algorithm or system that automatically generates appropriate feedback (e.g., words of encouragement, suggestions for correction, etc.) based on the collected learning progress data and transmits it to the learner's device.

[0165] This invention is a system that utilizes AI and VR technology to provide individually optimized learning guidance to learners. This system operates in cooperation with three parties: a server, a terminal, and a user.

[0166] Server processing explanation

[0167] The server collects initial data:

[0168] To collect the initial data, the server receives the user's name, age, grade, academic test results, learning goals, and preferred learning methods entered through the terminal. This data is sent via HTTP protocol and in JSON format to the server. The server then stores this data using a database management system (e.g., MySQL).

[0169] Generate a personalized optimization curriculum:

[0170] The server sends prompts to a generative AI model (e.g., OpenAI GPT-4) based on the collected initial data to generate an educational plan optimized for each individual learner. An example of a prompt is, "Please create the optimal learning curriculum based on Taro Yamada's academic ability data." The server receives the generated curriculum data and stores it in a database.

[0171] Generate the virtual instructor data:

[0172] The server generates virtual teacher data based on the learner's preferences. Specifically, it creates the character's appearance using 3D modeling software (e.g., Blender) and generates voice data using a voice generation tool (e.g., Google Text-to-Speech). An example of a prompt is "Please generate a virtual teacher in the style of Doraemon."

[0173] Generate and send feedback:

[0174] Learning progress is monitored in real time, and the server generates feedback based on the performance data, for example, a message such as "You got 90 points on the math test! Well done!" and sends it to the device.

[0175] Terminal processing explanation

[0176] Accept user data input:

[0177] The terminal accepts data input from the user, specifically providing a registration form where the user enters their name, age, etc., and transmits the collected data to the server.

[0178] View Virtual Instructors:

[0179] The device receives data from the server and displays it in a VR environment, allowing users to enjoy interactive lessons with virtual instructors using VR headsets such as Oculus Quest and HTC Vive.

[0180] View learning content:

[0181] The device displays learning content (text, videos, exercises) based on the learning curriculum, and users solve problems and watch videos through the device.

[0182] Send the learning progress to the server:

[0183] The device records the questions and test results the user has answered and sends them to a server, which receives them in real time and monitors the user's progress.

[0184] User behavior description

[0185] Enter the initial data:

[0186] The user enters their information into the registration form, for example, their name "Yamada Taro" and age "12 years old" into the terminal.

[0187] Participating in a VR environment:

[0188] Users wear VR devices and participate in lessons taught by virtual instructors. For example, users can take lessons from Doraemon-style virtual instructors.

[0189] Engage in learning content:

[0190] The user engages in learning content displayed on the device, for example, answering math exercises.

[0191] Receiving and implementing feedback:

[0192] The user receives feedback from the server and reflects it in their learning, for example, receiving a message like "Good job!" and proceeding to the next learning step.

[0193] The system provides an effective learning environment by combining an individually optimized learning curriculum, virtual instructors tailored to the user's preferences, and real-time monitoring and feedback.

[0194] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0195] Step 1: Data collection

[0196] ---

[0197] server:

[0198] The server collects personal information entered by the user on the device, including name, age, grade, achievement test results, learning goals, and preferred learning methods.

[0199] Input: Personal information entered by the user into the device.

[0200] Data processing: The server receives the data using the HTTP protocol and parses it in JSON format.

[0201] Output: Save the parsed data in a database management system (e.g., MySQL).

[0202] Device:

[0203] The terminal displays an input form to the user and prompts the user to input the required data.

[0204] Input: Personal information entered by the user.

[0205] Data calculation: Convert the input data into JSON format and send it to the server.

[0206] Output: User data sent to the server.

[0207] User:

[0208] The user enters his / her information into the input form displayed on the terminal.

[0209] Input: Name, age, grade, achievement test results, learning goals, preferred learning method.

[0210] Output: Sends data entered into the terminal to the server.

[0211] Step 2: Generate an individually optimized curriculum

[0212] ---

[0213] server:

[0214] The server sends a prompt to the generative AI model (e.g., OpenAI GPT-4) based on the collected initial data.

[0215] Example prompt: "Create the optimal learning curriculum based on Yamada Taro's academic achievement data."

[0216] Input: Initial user data read from the database, prompt statement.

[0217] Data calculation: Send a prompt to the generative AI model and generate an optimized curriculum in response.

[0218] Output: Save the generated curriculum data in a database.

[0219] Device:

[0220] There is no special processing.

[0221] User:

[0222] There is no special processing.

[0223] Step 3: Generate virtual instructor data

[0224] ---

[0225] server:

[0226] The server generates virtual instructor data based on the learner's preferences, creates the character's appearance using 3D modeling software (e.g., Blender), and generates voice data using a voice generation tool (e.g., Google Text-to-Speech).

[0227] Example prompt: "Create a Doraemon-style virtual teacher."

[0228] Input: User preference data, prompt text.

[0229] Data calculation: Using 3D modeling software and voice generation tools, a model and voice of the virtual teacher are generated.

[0230] Output: Save the generated virtual instructor data in a database.

[0231] Device:

[0232] There is no special processing.

[0233] User:

[0234] The user selects virtual instructor preferences at the terminal.

[0235] Step 4: Deliver learning content

[0236] ---

[0237] server:

[0238] The server prepares learning content (text, videos, exercises) based on the learning curriculum.

[0239] Input: Appropriate learning curriculum.

[0240] Data calculation: Retrieve learning content from the database and combine the necessary data.

[0241] Output: Creates an endpoint to send prepared learning content to the device.

[0242] Device:

[0243] The terminal receives the learning content from the server and displays it to the user.

[0244] Input: The learning content sent from the server.

[0245] Data calculation: Analyzes received data and displays it as learning content.

[0246] Output: The learning content displayed to the user.

[0247] User:

[0248] Users engage with the learning content displayed on their device, solving math exercises and watching videos.

[0249] Input: The learning content displayed on the device.

[0250] Output: Question answer results and viewing history.

[0251] Step 5: Monitoring your learning progress

[0252] ---

[0253] server:

[0254] The server monitors the learning progress in real time.

[0255] Input: Learning progress data sent from the device.

[0256] Data calculation: Save learning progress data in a database and analyze and monitor progress.

[0257] Output: Detailed statistics of your learning progress.

[0258] Device:

[0259] The device records the user's learning content and test results and sends them to the server.

[0260] Input: User's learning progress data.

[0261] Data Computation: Formatting the collected data for sending to the server.

[0262] Output: Learning progress data sent to the server.

[0263] User:

[0264] The user continues to work on the learning content.

[0265] Input: Question answers and test results.

[0266] Output: Your learning progress data.

[0267] Step 6: Provide feedback

[0268] ---

[0269] server:

[0270] The server generates feedback based on the learning progress data and transmits it to the terminal.

[0271] Input: Learning progress data.

[0272] Data computation: Uses feedback generation algorithms to create appropriate messages.

[0273] Output: Sends feedback messages to the terminal.

[0274] Device:

[0275] The terminal displays the feedback message received from the server to the user.

[0276] Input: The feedback message sent by the server.

[0277] Data processing: Converting feedback messages into a display format.

[0278] Output: The feedback displayed to the user.

[0279] User:

[0280] The user receives feedback from the server and reflects it in their learning.

[0281] Input: The feedback message displayed on the terminal.

[0282] Output: Reflected learning behavior.

[0283] The above are the specific processing steps and operations of the server, terminal, and user.

[0284] (Application example 1)

[0285] 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."

[0286] Conventional learning support systems often provide a uniform learning curriculum, which means they are unable to adequately address the individual needs of each learner. Furthermore, creating an environment that maximizes learning effectiveness is difficult, due to the lack of real-time feedback that is common in face-to-face classes and the difficulty of maintaining motivation. Furthermore, the limited customization of virtual instructors can prevent effective instruction tailored to learners' interests and preferences. A system that can solve these issues and provide personalized instruction optimized for each learner is needed.

[0287] 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.

[0288] In this invention, the server includes means for collecting initial data from learners, means for generating a learning curriculum optimized for each learner using artificial intelligence, means for generating virtual instructor data, means for displaying the generated virtual instructor in a virtual reality environment, means for monitoring learning progress, means for generating feedback based on the learning progress data, and means for providing feedback in real time, thereby providing personalized learning guidance optimized for each learner and maximizing the learning effect.

[0289] "Initial data" is basic information about the learner, such as the learner's name, age, grade, learning goals, and preferred learning methods.

[0290] "Artificial intelligence" is a technology that allows computer systems to perform highly complex tasks and analyze learner data to generate optimal learning curricula.

[0291] A "learning curriculum" is a plan that includes learning content, progress schedule, and evaluation methods optimized for each learner.

[0292] A "virtual instructor" is an interactive instructor that is customized based on the learner's preferences and displayed in a virtual reality environment.

[0293] A "virtual reality environment" is a simulated environment that feels real using computer technology.

[0294] "Study progress" is data that indicates how far a learner has progressed in their studies according to the learning curriculum.

[0295] "Feedback" refers to evaluations, advice, and messages to maintain motivation that are generated based on the learner's learning progress.

[0296] "Real-time" means that data is sent, received, and processed immediately, without delay.

[0297] The present invention is a system for providing individually optimized learning guidance to learners, and involves cooperation between a server, a terminal, and a user. A method for realizing this system will be described in detail below.

[0298] Server processing explanation

[0299] 1. Data Collection and Initial Setup:

[0300] The server collects initial data from the learner, including the learner's name, age, grade, achievement test results, learning goals, and preferred learning methods, thereby obtaining basic information about the learner and using it to generate an individually optimized learning curriculum.

[0301] 2. Generating an individually optimized curriculum:

[0302] The server uses a generative AI model to generate an optimized learning curriculum for each learner, including the learning content, progress schedule, and assessment method for each subject.

[0303] 3. Virtual Instructor Setup:

[0304] The server generates data on a virtual tutor based on the learner's preferences, and the tutor appears in a virtual reality environment, looking and speaking like a specific character or person.

[0305] 4. Progress monitoring and feedback:

[0306] The server monitors learning progress in real time, adjusts the curriculum as needed, and provides feedback based on learners' performance data.

[0307] Terminal processing explanation

[0308] 1. Data Entry:

[0309] The device accepts data input from the learner, including initial data and learning progress data, for example, displaying a popup to allow the user to start an achievement test on the device and collecting the achievement test results.

[0310] 2. View Virtual Instructor:

[0311] The device receives data from the server and displays it in a virtual reality environment, allowing learners to take interactive lessons.

[0312] 3. View and progress your learning:

[0313] The device displays learning content (text, videos, exercises) to the learner based on the curriculum, allowing the learner to progress through their studies efficiently.

[0314] 4. Sending progress data:

[0315] The device sends learning progress and test results to the server, allowing the server to track progress in real time and provide appropriate feedback.

[0316] User behavior description

[0317] 1. Enter the initial data:

[0318] Users enter their information into a registration form on the device, including their name, age, grade level, learning goals, and preferred learning method.

[0319] 2. Participating in a VR environment:

[0320] Users wear a VR device and participate in lessons taught by a virtual instructor. If they have any questions during the lesson, they can ask them using voice input or a dedicated interface.

[0321] 3. Engage in learning content:

[0322] Users work through the learning content displayed on their devices, solve problems, and take tests, for example, by working through math exercises and entering their answers.

[0323] 4. Receiving and incorporating feedback:

[0324] The user receives feedback from the server and incorporates it into their learning. They also receive messages and rewards to maintain motivation. For example, the user receives a message from the server saying "Good job!" and moves on to the next learning step.

[0325] In one example, a 12-year-old student can improve their math grades by donning a VR headset and being taught how to solve quadratic equations by a virtual teacher who resembles a specific character. The teacher explains easy-to-understand examples and provides real-time feedback immediately after the student solves the problem.

[0326] An example of a prompt for the generative AI model is as follows:

[0327] "Generate a 3D model of a virtual teacher resembling a specific character explaining to a 12-year-old student how to solve quadratic equations. The teacher should use a friendly voice and easy-to-understand language, providing step-by-step instructions that the student can understand. Explain examples and provide immediate feedback when the student solves."

[0328] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0329] Step 1:

[0330] The server collects initial data from the learner. When the user enters their name, age, grade, learning goals, and preferred learning method into the registration form on their device, this data is sent to the server. The server stores the received initial data in a database. The input data is the learner's basic information, and the output is the initial data stored in the database.

[0331] Step 2:

[0332] The server uses a generative AI model based on the collected initial data to generate an optimized learning curriculum for each learner. The initial data is input into the AI ​​model, and the data output as a learning curriculum includes the learning content, progress schedule, and evaluation method for each subject. This learning curriculum is created individually according to the learner's needs.

[0333] Step 3:

[0334] The server sends the generated learning curriculum to the learner's terminal. The input is the learning curriculum data generated on the server side, and the output is the learning curriculum data sent to the terminal. The terminal receives this data and stores it so that the learner can access it.

[0335] Step 4:

[0336] The server generates virtual teacher data based on the learner's preferences. For example, if a learner likes a particular character, it generates a 3D model and voice data of a virtual teacher that resembles that character. The input is the learner's preference data, and the output is the generated virtual teacher data.

[0337] Step 5:

[0338] The server sends the generated virtual instructor data to the terminal. The terminal receives this data and prepares to display the virtual instructor in a virtual reality environment. The input is the virtual instructor data from the server, and the output is a 3D model of the virtual instructor and audio data stored in the terminal.

[0339] Step 6:

[0340] The learner puts on the VR device and starts the lesson with the virtual instructor on the terminal. The terminal uses the virtual instructor data sent from the server to display the virtual instructor in a virtual reality environment. The input is the virtual instructor data stored on the terminal, and the output is the virtual instructor displayed on the VR device.

[0341] Step 7:

[0342] Learners follow the guidance of a virtual instructor and work on learning content based on the learning curriculum. The device records the learner's progress and collects test results and answer data for practice questions. The input is the learner's answer data, and the output is the learning progress data stored on the device.

[0343] Step 8:

[0344] The terminal sends the collected learning progress data to the server. The input is the learner's progress data, and the output is the learning progress data sent to the server. The server uses this data to monitor the learner's progress.

[0345] Step 9:

[0346] The server generates feedback based on the learning progress data. It uses a generative AI model to analyze the learner's progress and test results and create appropriate feedback messages. The input is the learning progress data, and the output is the feedback message.

[0347] Step 10:

[0348] The server sends the generated feedback message to the terminal. The terminal receives this message and displays it to the learner. The input is the server-side feedback message, and the output is the feedback message displayed on the terminal. For example, the message "Good job!" is displayed.

[0349] As described above, by these specific processing steps, a system can be realized that provides individually optimized learning guidance to learners.

[0350] 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.

[0351] This invention is a system that utilizes AI, VR technology, and an emotion engine to provide individually optimized learning guidance to learners. This system operates in cooperation with three parties: a server, a terminal, and a user.

[0352] Server processing explanation

[0353] 1. Data Collection and Initial Setup:

[0354] The server collects initial data from the learner, including name, age, grade, achievement test results, learning goals, and preferred learning methods.

[0355] Example: The server receives the data entered by the user in the registration form (e.g., name "Yamada Taro", age "12 years old").

[0356] 2. Generating an individually optimized curriculum:

[0357] The server uses artificial intelligence to generate an optimized learning curriculum for each learner, including the learning content for each subject, progress schedule, and evaluation method.

[0358] Example: A server-generated curriculum specifies weekly math practice problems and monthly practice tests.

[0359] 3. Virtual Instructor Setup:

[0360] The server generates data on a virtual teacher based on the learner's preferences, and this teacher appears in the VR environment with the appearance and speaking style of a specific character or person.

[0361] Example: When a learner selects a virtual teacher who resembles Doraemon, the server generates a 3D model and voice data that resembles Doraemon.

[0362] 4. Progress monitoring and feedback:

[0363] The server monitors learning progress in real time, adjusts the curriculum as needed, and provides feedback based on the learner's performance data.

[0364] Example: The server generates and sends a message saying "Well done!" based on the learner's test results (e.g., 90 points in mathematics).

[0365] 5. Emotion Recognition with Emotion Engine:

[0366] The server analyzes the learner's emotional data using an emotion engine to appropriately adjust instructional content and feedback. This engine recognizes emotions by analyzing the learner's facial expressions and voice.

[0367] Example: The server detects the learner's stress level from facial expression data and provides relaxation content.

[0368] Terminal processing explanation

[0369] 1. Data Entry:

[0370] The terminal accepts data input from the learner, including initial data and learning progress data.

[0371] Specific operation: The device displays a pop-up to start the academic ability test, and the user starts the test.

[0372] 2. View Virtual Instructor:

[0373] The device receives data from the server and displays the virtual instructor in a VR environment, providing interactive lessons.

[0374] Specific operation: Using a VR headset, a video is displayed in which a Doraemon-style virtual instructor explains the preparatory content.

[0375] 3. View and progress your learning:

[0376] The device displays learning content (text, videos, exercises) to the learner based on the learning curriculum.

[0377] Example: A device displays math exercises and the user answers them.

[0378] 4. Sending progress data:

[0379] The device sends learning progress and test results to the server, allowing the server to track progress in real time and provide appropriate feedback.

[0380] Example: The device sends the learner's test results (e.g., 90 points in mathematics) to the server.

[0381] 5. Emotional Data Collection and Transmission:

[0382] The device collects the learner's facial expressions and voice data and sends it to a server, where it is analyzed by an emotion engine.

[0383] Example: The device collects the learner's facial expression data (e.g., images captured from a camera) and voice data and sends them to a server.

[0384] User behavior description

[0385] 1. Enter the initial data:

[0386] Users enter their information into a registration form, including their name, age, grade level, learning goals, and preferred learning method.

[0387] Example: A user fills out a registration form with the name "Yamada Taro" and age "12 years old."

[0388] 2. Participating in a VR environment:

[0389] Users wear a VR device and participate in lessons taught by a virtual instructor. If they have any questions during the lesson, they can ask them using voice input or a dedicated interface.

[0390] Example: A user uses a VR headset to take a lesson from a Doraemon-style virtual instructor.

[0391] 3. Engage in learning content:

[0392] Users work through the learning content displayed on their device, solving problems and taking tests.

[0393] Example: A user works through a math exercise displayed on a terminal and enters the answers.

[0394] 4. Providing Emotion Data:

[0395] During the learning process, users provide emotional data through their facial expressions and the sounds they hear.

[0396] Example: When a user is learning in front of a camera and has a tired expression, the facial expression data is sent from the device to the server.

[0397] 5. Receiving and incorporating feedback:

[0398] Users receive feedback from the server and incorporate it into their learning. They also receive messages and rewards to keep them motivated.

[0399] Example: The user receives a "Good job!" message from the server and proceeds to the next learning step.

[0400] 6. Use of relaxation content:

[0401] The user utilizes relaxation content provided by the emotion engine.

[0402] Example: When a user experiences high stress levels, they listen to relaxation music sent from a server.

[0403] This system allows learners to continue studying in a self-optimized learning environment and effectively improve their academic ability. In addition, the introduction of an emotion engine allows for detailed guidance and support that responds to the learner's emotions.

[0404] The processing flow will be explained below.

[0405] Server processing explanation

[0406] Step 1:

[0407] The server receives the user registration information.

[0408] Specific operation: The user enters the name, age, and grade in the registration form and presses the submit button, which sends the entered data to the server and saves it in the database.

[0409] Step 2:

[0410] The server provides the user with a link to the achievement test.

[0411] Specific operation: The server automatically generates an email containing the URL of the academic achievement test and sends it to the user, or displays the link of the academic achievement test on the dashboard.

[0412] Step 3:

[0413] The server receives and stores the results of the academic achievement test.

[0414] Specific operation: When a user completes an academic ability test, the results are sent from the device to the server and stored in a database.

[0415] Step 4:

[0416] The server uses artificial intelligence to generate an individually optimized curriculum.

[0417] Specific operation: Analyze the received academic ability test results and initial data, and generate the learning content and progress schedule required for the user.

[0418] Step 5:

[0419] The server transmits the generated curriculum to the terminal.

[0420] Specific operation: Send data to the terminal so that the generated learning curriculum is displayed on the user's dashboard.

[0421] Step 6:

[0422] The server generates the data of the virtual instructor.

[0423] Specific operation: Generates a 3D model and audio data based on the user's preferences and stores it in a database.

[0424] Step 7:

[0425] The server transmits the generated virtual instructor data to the terminal.

[0426] Specific operation: The generated virtual instructor data is sent to the terminal so that it is displayed in the user's VR environment.

[0427] Step 8:

[0428] The server monitors the learning progress.

[0429] Specific operation: Receives user progress data (e.g., exercise completion status, test results) sent from the device in real time and stores it in a database.

[0430] Step 9:

[0431] The server uses an emotion engine to analyze the learner's emotion data and generate feedback.

[0432] Specific actions: Analyze the learner's facial expressions and voice data to assess their stress level and motivation.

[0433] Step 10:

[0434] The server adjusts the instruction content and feedback based on the user's emotional data and updates the curriculum as needed.

[0435] Specific behavior: When stress levels are high, a message is generated recommending a break. When motivation levels are low, a message of encouragement is generated.

[0436] Step 11:

[0437] The server generates feedback and sends it to the device.

[0438] Specific behavior: Send data to the device to display a feedback message on the user's dashboard.

[0439] Terminal processing explanation

[0440] Step 1:

[0441] The terminal displays an initial data entry form to the user.

[0442] What it does: Displays a registration form on a web page or app, allowing users to enter their name, age, grade, etc.

[0443] Step 2:

[0444] The terminal transmits the user's input data to the server.

[0445] Specific operation: When the user presses the submit button to send the data entered in the registration form to the server, the data is sent to the backend.

[0446] Step 3:

[0447] The device displays the academic achievement test link and allows the user to access it.

[0448] Specific behavior: A link to the academic achievement test is displayed on the dashboard or in an email, and the user clicks it to begin the test.

[0449] Step 4:

[0450] The terminal transmits the user's academic achievement test results to the server.

[0451] What it does: The user completes the test and the results are automatically sent to the server.

[0452] Step 5:

[0453] The terminal displays the curriculum received from the server.

[0454] Specific operation: The curriculum data received from the server is displayed on the dashboard so that the user can check it.

[0455] Step 6:

[0456] The device displays the virtual instructor data received from the server in a VR environment.

[0457] Specific operation: Using a VR device, the 3D model and audio data received from the server are rendered to provide interactive lessons.

[0458] Step 7:

[0459] The device displays the learning content and the user works on it.

[0460] Specific operation: Learning content such as text, videos, and exercises are displayed to the user, and the user works on it.

[0461] Step 8:

[0462] The terminal transmits learning progress data to the server.

[0463] Specific operation: The results of the user's work on the learning content are recorded in real time and periodically sent to the server.

[0464] Step 9:

[0465] The device collects the user's facial expressions and voice data and sends it to the server.

[0466] Specific operation: The device uses a camera and microphone to collect facial expression and voice data and sends it to a server.

[0467] User behavior description

[0468] Step 1:

[0469] The user enters the initial data.

[0470] Specific actions: Enter your name, age, grade, learning goals, and preferred learning method in the registration form and press the submit button.

[0471] Step 2:

[0472] The user accesses the test link and begins the test.

[0473] Specific actions: Click on the academic achievement test link displayed in email or on the dashboard to begin the test.

[0474] Step 3:

[0475] A user completes a quiz.

[0476] Specific actions: Answer the test questions and enter the results into the terminal.

[0477] Step 4:

[0478] Users wear VR devices and participate in classes taught by virtual instructors.

[0479] Specific actions: Put on a VR headset and watch a lesson from a virtual instructor.

[0480] Step 5:

[0481] The user engages with the learning content.

[0482] Specific actions: Work through the text, videos, and practice problems displayed on the device.

[0483] Step 6:

[0484] The user records facial expressions and voice to provide emotional data.

[0485] Specific operation: During learning, the device uses a camera and microphone to record facial expressions and voice, and then sends the data from the device to the server.

[0486] Step 7:

[0487] The user receives feedback and moves on to the next learning step.

[0488] Specific operation: Receive the feedback message sent from the server and proceed to the next learning step.

[0489] Step 8:

[0490] When a user feels stressed, they can use relaxation content.

[0491] Specific operation: Reduce stress by listening to relaxation music and watching videos sent from the server.

[0492] In this way, the server, device, and user work together to enable individually optimized learning instruction that takes emotions into consideration. This system allows learners to continue studying and aim for effective improvement of their academic ability.

[0493] Example 2

[0494] 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."

[0495] In today's educational environment, there is a demand for individually optimized learning guidance tailored to the needs of each learner. However, conventional systems have difficulty providing learning guidance and feedback that fully reflects the learner's progress and emotional state. In particular, there is a lack of emotional support, making it difficult to address learners' stress and loss of motivation.

[0496] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0497] In this invention, the server includes means for collecting initial data from a learner, means for generating a learning curriculum optimized for each learner using artificial intelligence, means for transmitting the learning curriculum to the learner's terminal, means for generating virtual instructor data, means for transmitting the generated virtual instructor to the learner's terminal, means for monitoring learning progress, means for generating feedback based on the learning progress data, means for analyzing the learner's emotional data using an emotion engine, and means for adjusting instruction content and feedback based on the analysis results. This makes it possible to grasp the learner's learning progress and emotional state in real time and provide individually optimized and effective learning instruction.

[0498] "Initial learner data" is information collected at the beginning of a study, such as the learner's name, age, grade, achievement test results, learning goals, and preferred learning methods.

[0499] "Artificial intelligence" is a computer technology that includes machine learning and data analysis techniques and is used to create learning curricula that are optimized for each learner.

[0500] A "learning curriculum" is an educational plan that includes learning content, progress schedule, and evaluation methods that are optimized for each learner.

[0501] A "virtual teacher" is a teacher character that appears in a digital environment (especially a VR environment) and has the appearance and speaking style of a specific character or person.

[0502] "Learning progress" refers to progress data and results as a learner progresses through the learning curriculum.

[0503] "Feedback" refers to comments and advice for guidance and improvement that are generated based on the learner's learning progress.

[0504] The "emotion engine" is a technology that analyzes a learner's facial expressions and voice data to recognize their emotional state.

[0505] "Emotion data" is data that indicates the emotional state of a learner, recognized based on the learner's facial expressions and voice.

[0506] "Analysis results" refers to the conclusions or conditions obtained after analyzing collected data.

[0507] "Instructional content" refers to the specific learning or educational content provided to learners.

[0508] This invention is a system that utilizes artificial intelligence (AI), virtual reality (VR) technology, and an emotion engine to provide individually optimized learning guidance to learners. This system operates in cooperation with a server, a terminal, and a user.

[0509] Server processing explanation

[0510] The server first collects initial data from the learner, including the learner's name, age, grade, academic achievement test results, learning goals, and preferred learning methods. For example, if a learner enters the name "Yamada Taro" and age "12 years old," the data is sent to the server and stored in a database.

[0511] Based on the initial data, the server uses artificial intelligence (e.g., TensorFlow or PyTorch) to generate a learning curriculum optimized for each learner. The curriculum includes the learning content, progress schedule, and evaluation method for each subject. For example, the curriculum includes weekly math practice problems and monthly mock tests.

[0512] Next, the server generates data on a virtual tutor based on the learner's preferences. This tutor will have the appearance and speaking style of a specific character or person and will be displayed in the VR environment. For example, if a learner selects a virtual tutor resembling Doraemon, the server will generate a 3D model and voice data that resembles Doraemon.

[0513] The server also monitors the learner's progress in real time, adjusts the curriculum as needed, and generates feedback based on the progress data. For example, if a learner gets 90 points on a test, the server generates a message saying "Well done!" and sends it to the learner's device.

[0514] The emotion engine is used to analyze the learner's facial expression and voice data to recognize their emotional state. This allows the server to adjust instruction content and feedback based on the emotional data. For example, if the server detects a high stress level from the learner's facial expression data, it can provide relaxation content (e.g., relaxation music).

[0515] Terminal processing explanation

[0516] The device first accepts initial data from the learner, including the results of an achievement test and data on the learner's progress. As a specific example, the device displays a pop-up to start the achievement test, and the user starts the test.

[0517] The virtual instructor data received from the server is displayed in a VR environment. By using a VR headset, a video of a Doraemon-style virtual instructor explaining the content of the preparation is displayed.

[0518] The device displays learning content such as textbooks, videos, and exercises to the learner based on the learning curriculum. For example, the device may display mathematics exercises for the user to answer.

[0519] The device sends learning progress and test results to the server, allowing the server to understand progress in real time and provide appropriate feedback. For example, the device sends the learner's test results (e.g., 90 points in mathematics) to the server.

[0520] The device also collects the learner's facial expression and voice data and transmits it to the server. For example, the device can collect the learner's facial expression data (e.g., images captured by a camera) and voice data and transmit them to the server.

[0521] User behavior description

[0522] A user first enters their information into a registration form, including their name, age, grade, learning goals, and preferred learning method. For example, a user enters their name "Yamada Taro" and age "12 years old" into the registration form.

[0523] Next, the user puts on the VR device and participates in a lesson taught by a virtual instructor. If the user has a question during the lesson, they can ask it using voice input or a dedicated interface. For example, a user can take a lesson from a Doraemon-style virtual instructor using a VR headset.

[0524] The user works on the learning content displayed on the terminal, solves problems, takes tests, etc. For example, the user works on math exercises displayed on the terminal and inputs the answers.

[0525] During learning, users provide emotional data through their facial expressions and voice. For example, if a user looks tired while learning in front of the camera, that facial data is sent from the device to the server.

[0526] The user receives feedback from the server and reflects it in their learning. For example, the user receives a message saying "Good job!" and proceeds to the next learning step.

[0527] Users also use relaxation content provided by the emotion engine. For example, when their stress level is high, they listen to relaxation music sent from the server.

[0528] This system allows learners to continue studying in a self-optimized learning environment and effectively improve their academic ability. In addition, the introduction of an emotion engine allows for detailed guidance and support that responds to the learner's emotions.

[0529] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0530] Step 1:

[0531] Data collection and initial setup

[0532] Input: The initial data that the user enters in the registration form (name, age, grade, academic test results, learning goals, preferred learning methods)

[0533] How it works: The server receives an HTTP POST request and stores the initial data in a database.

[0534] Output: Initial data stored in the database

[0535] Example: A user enters "Yamada Taro" and "12 years old", and the server saves this in the database.

[0536] Step 2:

[0537] Generation of individually optimized curriculum

[0538] Input: Initial data of the student obtained from the server database

[0539] How it works: The server runs an AI model (e.g., TensorFlow, PyTorch) to generate an optimized learning curriculum for each learner. The AI ​​model receives learner data as input and calculates the learning content, progress schedule, and assessment method for each subject.

[0540] Output: Generated individualized optimized curriculum

[0541] Example: A server generates a curriculum that includes weekly math practice questions and monthly practice tests.

[0542] Step 3:

[0543] Virtual Instructor Setup

[0544] Input: Information based on the user's preferences (e.g., favorite character)

[0545] Operation: The server generates corresponding 3D model data and audio data based on the preference information. These data are used in the VR environment as a virtual teacher.

[0546] Output: Generated virtual instructor data (3D model and audio data)

[0547] Example: A learner selects a virtual teacher who looks like Doraemon, and the server generates a 3D model of Doraemon and audio data.

[0548] Step 4:

[0549] Sending learning curriculum and instructor data

[0550] Input: Generated learning curriculum and virtual instructor data

[0551] Operation: The server sends these data to the user's terminal.

[0552] Output: The learning curriculum and virtual instructor data are sent to the terminal.

[0553] Example: The server sends the created learning curriculum and Doraemon-style instructor data to the user's device.

[0554] Step 5:

[0555] Display in VR environment

[0556] Input: Virtual instructor data sent from the server

[0557] How it works: The device displays the received virtual instructor data in a VR environment. Specifically, it uses Unity or Unreal Engine to render a 3D model and play audio data.

[0558] Output: VR environment with virtual instructor displayed

[0559] Example: A Doraemon-style virtual teacher begins a lesson on a VR headset.

[0560] Step 6:

[0561] View and progress your learning

[0562] Input: Learning curriculum received from the server

[0563] How it works: The device displays curriculum-based text, videos, and exercises to the learner, and also provides an interface where the user can enter their answers.

[0564] Output: What the user sees

[0565] Example: A device displays math exercises and the user answers them.

[0566] Step 7:

[0567] Sending progress data

[0568] Input: User-entered learning progress and test results

[0569] How it works: The device sends this data to the server using an HTTP POST request.

[0570] Output: Progress data sent to the server

[0571] Example: The device sends the learner's test results (e.g., 90 points in mathematics) to the server.

[0572] Step 8:

[0573] Collecting and transmitting emotional data

[0574] Input: User's facial expressions and voice data

[0575] How it works: The device uses its camera and microphone to collect this data and sends it to a server.

[0576] Output: Emotion data sent to the server

[0577] Example: The device sends the learner's facial expression data and voice data to the server.

[0578] Step 9:

[0579] Emotional Data Analysis

[0580] Input: Emotion data sent from the device

[0581] How it works: The server uses the emotion engine to analyze the emotion data. The analysis results indicate the learner's emotional state.

[0582] Output: Parsed emotion data

[0583] Example: The server analyzes the learner's stress level from facial expression data.

[0584] Step 10:

[0585] Generate feedback

[0586] Input: Learning progress data and emotion data analysis results

[0587] Operation: The server generates feedback based on this data and adjusts the curriculum. The generated feedback is sent to the device.

[0588] Output: Generated feedback and adjusted curriculum

[0589] Example: The server generates a message saying "Good job!" and sends it to the device. Also, if the learner shows signs of fatigue, the curriculum is adjusted to add breaks.

[0590] (Application example 2)

[0591] 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."

[0592] In recent years, there has been a demand for providing educational content that is optimized for each individual learner. However, conventional systems often fail to adequately grasp learners' progress or analyze their emotional data, resulting in a uniform curriculum and teaching methods, resulting in low learning effectiveness. Furthermore, a lack of appropriate feedback and content to alleviate stress during learning has also led to a decline in learners' motivation.

[0593] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting initial data from the learner, means for generating a learning curriculum optimized for each learner using artificial intelligence, means for transmitting the learning curriculum to the learner's terminal, means for generating virtual instructor data, means for transmitting the generated virtual instructor to the learner's terminal, means for monitoring the learning progress, means for generating feedback based on the learning progress data, means for providing additional learning content based on the feedback, means for providing lessons by the virtual instructor in a VR environment, means for collecting and analyzing emotional data, and means for providing relaxation content based on the learner's emotional data. This makes it possible to provide individually optimized learning guidance and feedback for each learner, as well as content tailored to their emotions.

[0594] "Student" refers to an individual receiving education or training, and in particular, to a person who uses the System to carry out learning activities.

[0595] "Initial data" refers to basic information about the learner, including name, age, grade, achievement test results, learning goals, preferred learning methods, etc.

[0596] "Artificial intelligence" is a technology that gives intelligence to computer systems, and in this system it is a technology used to optimize learning curricula, etc.

[0597] "Learning curriculum" refers to the educational content and learning plan provided to learners, including specific subject content, progress schedule, and evaluation methods.

[0598] "Device" refers to the computer device used by the learner, including smartphones, tablets, and PCs.

[0599] A "virtual instructor" refers to a virtual educator generated by a computer program who provides educational content to learners.

[0600] "Means for generating data" refers to the programs or algorithms used to create or generate the required data.

[0601] "Means for transmitting data" refers to the technology for transmitting and receiving the generated data between terminals and servers, including network communication technology.

[0602] "Study progress" refers to information that indicates how far a learner has progressed in the learning content, and includes test results, progress status, and the like.

[0603] "Feedback" refers to reactions and advice provided based on a learner's learning status, and is used to improve learning outcomes.

[0604] "Additional learning content" refers to supplementary educational content provided in addition to an existing learning curriculum, including content to fill learning gaps.

[0605] A "VR environment" refers to an environment in which a virtual learning space is created and provided to learners using virtual reality technology.

[0606] "Emotional data" refers to information that indicates the learner's emotional state, and is obtained through facial expressions, voice data, and other biometric data.

[0607] "Relaxation content" refers to content provided to reduce learners' stress and promote relaxation, and includes music, videos, guidance, etc.

[0608] This invention provides a system that provides individually optimized learning guidance to learners. This invention utilizes AI, VR technology, and an emotion engine, and operates in cooperation with a server, a terminal, and a user.

[0609] Server Processing

[0610] 1. Data Collection and Initial Setup:

[0611] The server collects initial data from the learner, including name, age, grade, achievement test results, learning goals, and preferred learning methods. For example, a learner enters his name "Yamada Taro" and age "12 years old" into a registration form.

[0612] 2. Generating an individually optimized curriculum:

[0613] The server uses artificial intelligence to generate a learning curriculum optimized for each learner. This curriculum includes the learning content, progress schedule, and evaluation method for each subject. For example, the server-generated curriculum specifies weekly math practice problems and monthly mock tests.

[0614] 3. Virtual Instructor Setup:

[0615] The server generates data on a virtual teacher based on the learner's preferences. This teacher will have the appearance and speaking style of a specific character or person and will be displayed in the VR environment. For example, if a learner selects a virtual teacher who resembles a virtual character, the server generates a 3D model and voice data that resembles that character.

[0616] 4. Progress monitoring and feedback:

[0617] The server monitors the learner's progress in real time and adjusts the curriculum as needed. It also provides feedback based on the learner's performance data. For example, the server generates and sends a message saying "Well done!" based on the learner's test results (e.g., 90 points in mathematics).

[0618] 5. Emotion Recognition with Emotion Engine:

[0619] The server uses an emotion engine to analyze the learner's emotional data and adjust the instruction content and feedback appropriately. This engine recognizes emotions by analyzing the learner's facial expressions and voice. As a specific example, the server detects the learner's stress level from their facial expression data and provides relaxation content.

[0620] Terminal handling

[0621] 1. Data Entry:

[0622] The device accepts data input from the learner, including initial data and learning progress data. Specifically, the device displays a popup to start the academic ability test, and the user begins the test.

[0623] 2. View Virtual Instructor:

[0624] The device receives data from the server and displays it in a VR environment, providing an interactive lesson. Specifically, a VR headset is used to display a video of the virtual instructor explaining the content of the lesson.

[0625] 3. View and progress your learning:

[0626] The device displays learning content (text, videos, exercises) to the learner based on the learning curriculum. For example, the device displays mathematics exercises, and the user answers them.

[0627] 4. Sending progress data:

[0628] The device sends learning progress and test results to the server, allowing the server to understand progress in real time and provide appropriate feedback. For example, the device sends the learner's test results (e.g., 90 points in mathematics) to the server.

[0629] 5. Emotional Data Collection and Transmission:

[0630] The device collects the learner's facial expression and voice data and sends it to the server. This data is analyzed by the emotion engine. For example, the device collects the learner's facial expression data (e.g., images captured from a camera) and voice data and sends it to the server.

[0631] User behavior

[0632] 1. Enter the initial data:

[0633] A user enters their information into a registration form, including their name, age, grade, learning goals, preferred learning method, etc. For example, a user enters their name "Yamada Taro" and age "12 years old" into a registration form.

[0634] 2. Participating in a VR environment:

[0635] Users wear a VR device and participate in lessons taught by a virtual instructor. If they have questions during the lesson, they can ask using voice input or a dedicated interface. For example, a user can take a lesson taught by a virtual instructor using a VR headset.

[0636] 3. Engage in learning content:

[0637] The user works on the learning content displayed on the device, solves problems, takes tests, etc. For example, the user works on a math exercise displayed on the device and enters the answers.

[0638] 4. Providing Emotion Data:

[0639] During the learning process, users provide emotional data through their facial expressions and voice. For example, if a user looks tired while learning in front of the camera, that facial expression data is sent from the device to the server.

[0640] 5. Receiving and incorporating feedback:

[0641] The user receives feedback from the server and reflects it in their learning. They also receive messages and rewards to maintain their motivation. For example, the user receives a message from the server saying "Good job!" and moves on to the next learning step.

[0642] 6. Use of relaxation content:

[0643] The user uses relaxation content provided by the emotion engine. For example, when the user is under high stress, they listen to relaxation music sent from the server.

[0644] Prompt Sentence Examples

[0645] Generate an appropriate learning curriculum based on the user: {Name: "Yamada Taro", Age: 12, Grade: "1st year of junior high school", Academic achievement test results: {Math: 80, English: 75}, Learning goal: "Math reinforcement", Preferred learning method: "Visual"}.

[0646] In this way, the present invention realizes individually optimized learning guidance and feedback for each learner, as well as the provision of content according to their emotions.

[0647] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0648] Step 1:

[0649] The server collects initial data from the learner, such as name, age, grade, achievement test results, learning goals, preferred learning methods, etc., entered by the user in the registration form. Based on the input data, the server creates a learner profile.

[0650] Step 2:

[0651] The server uses artificial intelligence to generate an optimized learning curriculum for each learner. To do this, the learner's initial data is input, and the AI ​​model processes and analyzes the data to output an individually optimized curriculum (educational content, progress schedule, evaluation method, etc.). Specifically, the curriculum is generated using OpenAI's AI model.

[0652] Step 3:

[0653] The server sends the generated optimized curriculum to the learner's device. The curriculum data is input and sent to the device via the network, where the curriculum is displayed. Specifically, data is sent using an API.

[0654] Step 4:

[0655] The server generates the virtual teacher's data and customizes it based on the learner's preferences. It uses the learner's initial data as input to generate the virtual teacher's appearance and speaking style. Specifically, it uses an AI model to generate the virtual teacher's character data.

[0656] Step 5:

[0657] The server sends the generated virtual instructor data to the learner's device. The virtual instructor data is used as input and sent to the device via the network, where the virtual instructor is displayed on the device. Specifically, data is sent using an API.

[0658] Step 6:

[0659] The device receives the virtual instructor's data and displays it in the VR environment. Based on the received data, an interactive lesson is provided using a VR headset. For example, a video of a Doraemon-style virtual instructor explaining the content of the lesson is displayed.

[0660] Step 7:

[0661] The device sends the learner's progress and academic test results to the server. By collecting the learner's progress data and sending it to the server, real-time progress management is performed. As a concrete example, a math test result of 90 points is sent to the server.

[0662] Step 8:

[0663] The server monitors the learning progress and generates feedback. It analyzes the learning progress data as input, generates appropriate feedback (e.g., "Good job!"), and sends it to the learner's device.

[0664] Step 9:

[0665] The device collects the learner's facial expressions and voice data and sends it to the server. Emotional data is collected using a camera and microphone and sent to the server. As a specific example, image data of a tired facial expression is sent to the server.

[0666] Step 10:

[0667] The server uses an emotion engine to analyze the learner's emotional data and provide appropriate content based on their emotions.The server analyzes the emotional data as input, generates relaxation content (e.g., relaxation music), and sends it to the device.

[0668] 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.

[0669] 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.

[0670] 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.

[0671] [Second embodiment]

[0672] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0673] 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.

[0674] 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).

[0675] 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.

[0676] 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.

[0677] 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).

[0678] 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.

[0679] 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.

[0680] 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.

[0681] 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.

[0682] 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.

[0683] 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."

[0684] This invention is a system that utilizes AI and VR technology to provide individually optimized learning guidance to learners. This system operates in cooperation with three parties: a server, a terminal, and a user.

[0685] Server processing explanation

[0686] 1. Data Collection and Initial Setup:

[0687] The server collects initial data from the learner, including name, age, grade, achievement test results, learning goals, and preferred learning methods.

[0688] Example: The server receives the data entered by the user in the registration form (e.g., name "Yamada Taro", age "12 years old").

[0689] 2. Generating an individually optimized curriculum:

[0690] The server uses artificial intelligence to generate an optimized learning curriculum for each learner, including the learning content for each subject, progress schedule, and evaluation method.

[0691] Example: A server-generated curriculum specifies weekly math practice problems and monthly practice tests.

[0692] 3. Virtual Instructor Setup:

[0693] The server generates data on a virtual teacher based on the learner's preferences, and this teacher appears in the VR environment with the appearance and speaking style of a specific character or person.

[0694] Example: When a learner selects a virtual teacher who resembles Doraemon, the server generates a 3D model and voice data that resembles Doraemon.

[0695] 4. Progress monitoring and feedback:

[0696] The server monitors learning progress in real time, adjusts the curriculum as needed, and provides feedback based on the learner's performance data.

[0697] Example: The server generates and sends a message saying "Well done!" based on the learner's test results (e.g., 90 points in mathematics).

[0698] Terminal processing explanation

[0699] 1. Data Entry:

[0700] The terminal accepts data input from the learner, including initial data and learning progress data.

[0701] Example: The device displays a popup to start an academic ability test, and the user starts the test.

[0702] 2. View Virtual Instructor:

[0703] The device receives data from the server and displays the virtual instructor in a VR environment, providing interactive lessons.

[0704] Example: Using a VR headset, a video is displayed in which a virtual instructor dressed like Doraemon explains the content of the preparatory lesson.

[0705] 3. View and progress your learning:

[0706] The device displays learning content (text, videos, exercises) to the learner based on the learning curriculum.

[0707] Example: A device displays math exercises and the user answers them.

[0708] 4. Sending progress data:

[0709] The device sends learning progress and test results to the server, allowing the server to track progress in real time and provide appropriate feedback.

[0710] Example: The device sends the learner's test results (e.g., 90 points in mathematics) to the server.

[0711] User behavior description

[0712] 1. Enter the initial data:

[0713] Users enter their information into a registration form, including their name, age, grade level, learning goals, and preferred learning method.

[0714] Example: A user fills out a registration form with the name "Yamada Taro" and age "12 years old."

[0715] 2. Participating in a VR environment:

[0716] Users wear a VR device and participate in lessons taught by a virtual instructor. If they have any questions during the lesson, they can ask them using voice input or a dedicated interface.

[0717] Example: A user uses a VR headset to take a lesson from a Doraemon-style virtual instructor.

[0718] 3. Engage in learning content:

[0719] Users work through the learning content displayed on their device, solving problems and taking tests.

[0720] Example: A user works through a math exercise displayed on a terminal and enters the answers.

[0721] 4. Receiving and incorporating feedback:

[0722] Users receive feedback from the server and incorporate it into their learning. They also receive messages and rewards to keep them motivated.

[0723] Example: The user receives a "Good job!" message from the server and proceeds to the next learning step.

[0724] This system allows learners to continue studying in a learning environment that is optimized for them, and aims to effectively improve their academic ability.

[0725] The processing flow will be explained below.

[0726] Server processing explanation

[0727] Step 1:

[0728] The server receives the user registration information.

[0729] Specific operation: The user enters the name, age, and grade in the registration form and presses the submit button, which sends the entered data to the server and saves it in the database.

[0730] Step 2:

[0731] The server provides the user with a link to the achievement test.

[0732] Specific operation: The server automatically generates an email containing the URL of the academic ability test and sends it to the user, or displays the link of the academic ability test on the dashboard.

[0733] Step 3:

[0734] The server receives and stores the results of the academic achievement test.

[0735] Specific operation: When a user completes an academic ability test, the results are sent from the device to the server and stored in a database.

[0736] Step 4:

[0737] The server uses artificial intelligence to generate an individually optimized curriculum.

[0738] Specific operation: Analyze the received academic ability test results and initial data, and generate the learning content and progress schedule required for the user.

[0739] Step 5:

[0740] The server transmits the generated curriculum to the terminal.

[0741] Specific operation: Send data to the terminal so that the generated learning curriculum is displayed on the user's dashboard.

[0742] Step 6:

[0743] The server generates the data of the virtual instructor.

[0744] Specific operation: Generates a 3D model and audio data based on the user's preferences and stores it in a database.

[0745] Step 7:

[0746] The server transmits the generated virtual instructor data to the terminal.

[0747] Specific operation: The generated virtual instructor data is sent to the terminal so that it is displayed in the user's VR environment.

[0748] Step 8:

[0749] The server monitors the learning progress.

[0750] Specific operation: Receives user progress data (e.g., exercise completion status, test results) sent from the device in real time and stores it in a database.

[0751] Step 9:

[0752] The server generates feedback and adjusts the curriculum as needed.

[0753] Specific behavior: Analyzes progress data, generates feedback messages with praise and suggestions for improvement, and sends them to the device, updating the learning curriculum as needed.

[0754] Terminal processing explanation

[0755] Step 1:

[0756] The terminal displays an initial data entry form to the user.

[0757] What it does: Displays a registration form on a web page or app, allowing users to enter their name, age, grade, etc.

[0758] Step 2:

[0759] The terminal transmits the user's input data to the server.

[0760] Specific operation: When the user presses the submit button to send the data entered in the registration form to the server, the data is sent to the backend.

[0761] Step 3:

[0762] The device displays the academic achievement test link and allows the user to access it.

[0763] Specific behavior: A link to the academic achievement test is displayed on the dashboard or in an email, and the user clicks it to begin the test.

[0764] Step 4:

[0765] The terminal inputs the user's academic achievement test results and sends them to the server.

[0766] What it does: The user completes the test and the results are automatically sent to the server.

[0767] Step 5:

[0768] The terminal displays the curriculum received from the server.

[0769] Specific operation: The curriculum data received from the server is displayed on the dashboard so that the user can check it.

[0770] Step 6:

[0771] The device displays the virtual instructor data received from the server in a VR environment.

[0772] Specific operation: Using a VR device, the 3D model and audio data received from the server are rendered to provide interactive lessons.

[0773] Step 7:

[0774] The device displays the learning content and the user works on it.

[0775] Specific operation: Learning content such as text, videos, and exercises are displayed to the user, and the user works on it.

[0776] Step 8:

[0777] The terminal transmits learning progress data to the server.

[0778] Specific operation: The results of the user's work on the learning content are recorded in real time and periodically sent to the server.

[0779] User behavior description

[0780] Step 1:

[0781] The user enters the initial data.

[0782] Specific actions: Enter your name, age, grade, learning goals, and preferred learning method in the registration form and press the submit button.

[0783] Step 2:

[0784] The user accesses the test link and begins the test.

[0785] Specific actions: Click on the academic achievement test link displayed in email or on the dashboard to begin the test.

[0786] Step 3:

[0787] A user completes a quiz.

[0788] Specific actions: Answer the test questions and enter the results into the terminal.

[0789] Step 4:

[0790] Users wear VR devices and participate in classes taught by virtual instructors.

[0791] Specific actions: Put on a VR headset and watch a lesson from a virtual instructor.

[0792] Step 5:

[0793] The user engages with the learning content.

[0794] Specific actions: Work through the text, videos, and practice problems displayed on the device.

[0795] Step 6:

[0796] The user receives feedback and moves on to the next learning step.

[0797] Specific behavior: Receive the feedback message sent from the server and work on the next learning content.

[0798] In this way, the server, terminal, and user work together to provide effective learning guidance.

[0799] Example 1

[0800] 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."

[0801] In recent years, there has been a demand for a learning environment that is optimized for each learner's academic ability and learning style, but conventional systems have difficulty fully meeting this demand. In particular, they lack the functionality to integrate multiple elements, such as generating individually optimized learning curricula, providing virtual instructors that match the learner's preferences, and monitoring learning progress in real time and providing feedback.

[0802] 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.

[0803] In this invention, the server includes means for inputting personal information from the learner, means for generating an education plan optimized for each learner using artificial intelligence, means for transmitting the education plan to the learner's device, means for generating virtual instructor data, means for transmitting the generated virtual instructor to the learner's device, means for displaying the virtual instructor in a virtual reality environment, means for monitoring learning progress in real time, and means for generating and transmitting feedback based on the learning progress data. This makes it possible to provide an individually optimized learning curriculum, effective learning support by a virtual instructor that suits the learner's preferences, and real-time understanding of progress and appropriate feedback.

[0804] "Means for learner input of personal information" refers to an interface designed to allow learners to input personal information such as their name, age, grade, and learning goals.

[0805] "Means for generating educational plans optimized for each learner using artificial intelligence" refers to algorithms or software that take a learner's personal information and learning data as input and automatically generate appropriate learning content and schedules.

[0806] The "means for transmitting the educational plan to the learner's device" refers to a system including communication means and protocols for transferring the generated educational plan to the learner's terminal.

[0807] "Means for generating virtual instructor data" refers to software or tools for creating data that resembles the appearance and speaking style of a specific character or person based on learner preferences.

[0808] The "means for transmitting the generated virtual instructor to the learner's device" refers to a system including communication means and protocols for transmitting data of the generated virtual instructor to the learner's terminal.

[0809] The "means for displaying the virtual instructor in a virtual reality environment" refers to a device or software that displays the virtual instructor in a virtual reality environment and allows learners to take lessons interactively.

[0810] "Means for monitoring learning progress in real time" refers to a system that collects, records, and analyzes information in real time, such as the learner's current stage and how well they have completed tasks.

[0811] The "means for generating and transmitting feedback based on the learning progress data" refers to an algorithm or system that automatically generates appropriate feedback (e.g., words of encouragement, suggestions for correction, etc.) based on the collected learning progress data and transmits it to the learner's device.

[0812] This invention is a system that utilizes AI and VR technology to provide individually optimized learning guidance to learners. This system operates in cooperation with three parties: a server, a terminal, and a user.

[0813] Server processing explanation

[0814] The server collects initial data:

[0815] To collect the initial data, the server receives the user's name, age, grade, academic test results, learning goals, and preferred learning methods entered through the terminal. This data is sent via HTTP protocol and in JSON format to the server. The server then stores this data using a database management system (e.g., MySQL).

[0816] Generate a personalized optimization curriculum:

[0817] The server sends prompts to a generative AI model (e.g., OpenAI GPT-4) based on the collected initial data to generate an educational plan optimized for each individual learner. An example of a prompt is, "Please create the optimal learning curriculum based on Taro Yamada's academic ability data." The server receives the generated curriculum data and stores it in a database.

[0818] Generate the virtual instructor data:

[0819] The server generates virtual teacher data based on the learner's preferences. Specifically, it creates the character's appearance using 3D modeling software (e.g., Blender) and generates voice data using a voice generation tool (e.g., Google Text-to-Speech). An example of a prompt is "Please generate a virtual teacher in the style of Doraemon."

[0820] Generate and send feedback:

[0821] Learning progress is monitored in real time, and the server generates feedback based on the performance data, for example, a message such as "You got 90 points on the math test! Well done!" and sends it to the device.

[0822] Terminal processing explanation

[0823] Accept user data input:

[0824] The terminal accepts data input from the user, specifically providing a registration form where the user enters their name, age, etc., and transmits the collected data to the server.

[0825] View Virtual Instructors:

[0826] The device receives data from the server and displays it in a VR environment, allowing users to enjoy interactive lessons with virtual instructors using VR headsets such as Oculus Quest and HTC Vive.

[0827] View learning content:

[0828] The device displays learning content (text, videos, exercises) based on the learning curriculum, and users solve problems and watch videos through the device.

[0829] Send the learning progress to the server:

[0830] The device records the questions and test results the user has answered and sends them to a server, which receives them in real time and monitors the user's progress.

[0831] User behavior description

[0832] Enter the initial data:

[0833] The user enters their information into the registration form, for example, their name "Yamada Taro" and age "12 years old" into the terminal.

[0834] Participating in a VR environment:

[0835] Users wear VR devices and participate in lessons taught by virtual instructors. For example, users can take lessons from Doraemon-style virtual instructors.

[0836] Engage in learning content:

[0837] The user engages in learning content displayed on the device, for example, answering math exercises.

[0838] Receiving and implementing feedback:

[0839] The user receives feedback from the server and reflects it in their learning, for example, receiving a message like "Good job!" and proceeding to the next learning step.

[0840] The system provides an effective learning environment by combining an individually optimized learning curriculum, virtual instructors tailored to the user's preferences, and real-time monitoring and feedback.

[0841] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0842] Step 1: Data collection

[0843] ---

[0844] server:

[0845] The server collects personal information entered by the user on the device, including name, age, grade, achievement test results, learning goals, and preferred learning methods.

[0846] Input: Personal information entered by the user into the device.

[0847] Data processing: The server receives the data using the HTTP protocol and parses it in JSON format.

[0848] Output: Save the parsed data in a database management system (e.g., MySQL).

[0849] Device:

[0850] The terminal displays an input form to the user and prompts the user to input the required data.

[0851] Input: Personal information entered by the user.

[0852] Data calculation: Convert the input data into JSON format and send it to the server.

[0853] Output: User data sent to the server.

[0854] User:

[0855] The user enters his / her information into the input form displayed on the terminal.

[0856] Input: Name, age, grade, achievement test results, learning goals, preferred learning method.

[0857] Output: Sends data entered into the terminal to the server.

[0858] Step 2: Generate an individually optimized curriculum

[0859] ---

[0860] server:

[0861] The server sends a prompt to the generative AI model (e.g., OpenAI GPT-4) based on the collected initial data.

[0862] Example prompt: "Create the optimal learning curriculum based on Yamada Taro's academic achievement data."

[0863] Input: Initial user data read from the database, prompt statement.

[0864] Data calculation: Send a prompt to the generative AI model and generate an optimized curriculum in response.

[0865] Output: Save the generated curriculum data in a database.

[0866] Device:

[0867] There is no special processing.

[0868] User:

[0869] There is no special processing.

[0870] Step 3: Generate virtual instructor data

[0871] ---

[0872] server:

[0873] The server generates virtual instructor data based on the learner's preferences, creates the character's appearance using 3D modeling software (e.g., Blender), and generates voice data using a voice generation tool (e.g., Google Text-to-Speech).

[0874] Example prompt: "Create a Doraemon-style virtual teacher."

[0875] Input: User preference data, prompt text.

[0876] Data calculation: Using 3D modeling software and voice generation tools, a model and voice of the virtual teacher are generated.

[0877] Output: Save the generated virtual instructor data in a database.

[0878] Device:

[0879] There is no special processing.

[0880] User:

[0881] The user selects virtual instructor preferences at the terminal.

[0882] Step 4: Deliver learning content

[0883] ---

[0884] server:

[0885] The server prepares learning content (text, videos, exercises) based on the learning curriculum.

[0886] Input: Appropriate learning curriculum.

[0887] Data calculation: Retrieve learning content from the database and combine the necessary data.

[0888] Output: Creates an endpoint to send prepared learning content to the device.

[0889] Device:

[0890] The terminal receives the learning content from the server and displays it to the user.

[0891] Input: The learning content sent from the server.

[0892] Data calculation: Analyzes received data and displays it as learning content.

[0893] Output: The learning content displayed to the user.

[0894] User:

[0895] Users engage with the learning content displayed on their device, solving math exercises and watching videos.

[0896] Input: The learning content displayed on the device.

[0897] Output: Question answer results and viewing history.

[0898] Step 5: Monitoring your learning progress

[0899] ---

[0900] server:

[0901] The server monitors the learning progress in real time.

[0902] Input: Learning progress data sent from the device.

[0903] Data calculation: Save learning progress data in a database and analyze and monitor progress.

[0904] Output: Detailed statistics of your learning progress.

[0905] Device:

[0906] The device records the user's learning content and test results and sends them to the server.

[0907] Input: User's learning progress data.

[0908] Data Computation: Formatting the collected data for sending to the server.

[0909] Output: Learning progress data sent to the server.

[0910] User:

[0911] The user continues to work on the learning content.

[0912] Input: Question answers and test results.

[0913] Output: Your learning progress data.

[0914] Step 6: Provide feedback

[0915] ---

[0916] server:

[0917] The server generates feedback based on the learning progress data and transmits it to the terminal.

[0918] Input: Learning progress data.

[0919] Data computation: Uses feedback generation algorithms to create appropriate messages.

[0920] Output: Sends feedback messages to the terminal.

[0921] Device:

[0922] The terminal displays the feedback message received from the server to the user.

[0923] Input: The feedback message sent by the server.

[0924] Data processing: Converting feedback messages into a display format.

[0925] Output: The feedback displayed to the user.

[0926] User:

[0927] The user receives feedback from the server and reflects it in their learning.

[0928] Input: The feedback message displayed on the terminal.

[0929] Output: Reflected learning behavior.

[0930] The above are the specific processing steps and operations of the server, terminal, and user.

[0931] (Application example 1)

[0932] 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."

[0933] Conventional learning support systems often provide a uniform learning curriculum, which means they are unable to adequately address the individual needs of each learner. Furthermore, creating an environment that maximizes learning effectiveness is difficult, due to the lack of real-time feedback that is common in face-to-face classes and the difficulty of maintaining motivation. Furthermore, the limited customization of virtual instructors can prevent effective instruction tailored to learners' interests and preferences. A system that can solve these issues and provide personalized instruction optimized for each learner is needed.

[0934] 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.

[0935] In this invention, the server includes means for collecting initial data from learners, means for generating a learning curriculum optimized for each learner using artificial intelligence, means for generating virtual instructor data, means for displaying the generated virtual instructor in a virtual reality environment, means for monitoring learning progress, means for generating feedback based on the learning progress data, and means for providing feedback in real time, thereby providing personalized learning guidance optimized for each learner and maximizing the learning effect.

[0936] "Initial data" is basic information about the learner, such as the learner's name, age, grade, learning goals, and preferred learning methods.

[0937] "Artificial intelligence" is a technology that allows computer systems to perform highly complex tasks and analyze learner data to generate optimal learning curricula.

[0938] A "learning curriculum" is a plan that includes learning content, progress schedule, and evaluation methods optimized for each learner.

[0939] A "virtual instructor" is an interactive instructor that is customized based on the learner's preferences and displayed in a virtual reality environment.

[0940] A "virtual reality environment" is a simulated environment that feels real using computer technology.

[0941] "Study progress" is data that indicates how far a learner has progressed in their studies according to the learning curriculum.

[0942] "Feedback" refers to evaluations, advice, and messages to maintain motivation that are generated based on the learner's learning progress.

[0943] "Real-time" means that data is sent, received, and processed immediately, without delay.

[0944] The present invention is a system for providing individually optimized learning guidance to learners, and involves cooperation between a server, a terminal, and a user. A method for realizing this system will be described in detail below.

[0945] Server processing explanation

[0946] 1. Data Collection and Initial Setup:

[0947] The server collects initial data from the learner, including the learner's name, age, grade, achievement test results, learning goals, and preferred learning methods, thereby obtaining basic information about the learner and using it to generate an individually optimized learning curriculum.

[0948] 2. Generating an individually optimized curriculum:

[0949] The server uses a generative AI model to generate an optimized learning curriculum for each learner, including the learning content, progress schedule, and assessment method for each subject.

[0950] 3. Virtual Instructor Setup:

[0951] The server generates data on a virtual tutor based on the learner's preferences, and the tutor appears in a virtual reality environment, looking and speaking like a specific character or person.

[0952] 4. Progress monitoring and feedback:

[0953] The server monitors learning progress in real time, adjusts the curriculum as needed, and provides feedback based on learners' performance data.

[0954] Terminal processing explanation

[0955] 1. Data Entry:

[0956] The device accepts data input from the learner, including initial data and learning progress data, for example, displaying a popup to allow the user to start an achievement test on the device and collecting the achievement test results.

[0957] 2. View Virtual Instructor:

[0958] The device receives data from the server and displays it in a virtual reality environment, allowing learners to take interactive lessons.

[0959] 3. View and progress your learning:

[0960] The device displays learning content (text, videos, exercises) to the learner based on the curriculum, allowing the learner to progress through their studies efficiently.

[0961] 4. Sending progress data:

[0962] The device sends learning progress and test results to the server, allowing the server to track progress in real time and provide appropriate feedback.

[0963] User behavior description

[0964] 1. Enter the initial data:

[0965] Users enter their information into a registration form on the device, including their name, age, grade level, learning goals, and preferred learning method.

[0966] 2. Participating in a VR environment:

[0967] Users wear a VR device and participate in lessons taught by a virtual instructor. If they have any questions during the lesson, they can ask them using voice input or a dedicated interface.

[0968] 3. Engage in learning content:

[0969] Users work through the learning content displayed on their devices, solve problems, and take tests, for example, by working through math exercises and entering their answers.

[0970] 4. Receiving and incorporating feedback:

[0971] The user receives feedback from the server and incorporates it into their learning. They also receive messages and rewards to maintain motivation. For example, the user receives a message from the server saying "Good job!" and moves on to the next learning step.

[0972] In one example, a 12-year-old student can improve their math grades by donning a VR headset and being taught how to solve quadratic equations by a virtual teacher who resembles a specific character. The teacher explains easy-to-understand examples and provides real-time feedback immediately after the student solves the problem.

[0973] An example of a prompt for the generative AI model is as follows:

[0974] "Generate a 3D model of a virtual teacher resembling a specific character explaining to a 12-year-old student how to solve quadratic equations. The teacher should use a friendly voice and easy-to-understand language, providing step-by-step instructions that the student can understand. Explain examples and provide immediate feedback when the student solves."

[0975] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0976] Step 1:

[0977] The server collects initial data from the learner. When the user enters their name, age, grade, learning goals, and preferred learning method into the registration form on their device, this data is sent to the server. The server stores the received initial data in a database. The input data is the learner's basic information, and the output is the initial data stored in the database.

[0978] Step 2:

[0979] The server uses a generative AI model based on the collected initial data to generate an optimized learning curriculum for each learner. The initial data is input into the AI ​​model, and the data output as a learning curriculum includes the learning content, progress schedule, and evaluation method for each subject. This learning curriculum is created individually according to the learner's needs.

[0980] Step 3:

[0981] The server sends the generated learning curriculum to the learner's terminal. The input is the learning curriculum data generated on the server side, and the output is the learning curriculum data sent to the terminal. The terminal receives this data and stores it so that the learner can access it.

[0982] Step 4:

[0983] The server generates virtual teacher data based on the learner's preferences. For example, if a learner likes a particular character, it generates a 3D model and voice data of a virtual teacher that resembles that character. The input is the learner's preference data, and the output is the generated virtual teacher data.

[0984] Step 5:

[0985] The server sends the generated virtual instructor data to the terminal. The terminal receives this data and prepares to display the virtual instructor in a virtual reality environment. The input is the virtual instructor data from the server, and the output is a 3D model of the virtual instructor and audio data stored in the terminal.

[0986] Step 6:

[0987] The learner puts on the VR device and starts the lesson with the virtual instructor on the terminal. The terminal uses the virtual instructor data sent from the server to display the virtual instructor in a virtual reality environment. The input is the virtual instructor data stored on the terminal, and the output is the virtual instructor displayed on the VR device.

[0988] Step 7:

[0989] Learners follow the guidance of a virtual instructor and work on learning content based on the learning curriculum. The device records the learner's progress and collects test results and answer data for practice questions. The input is the learner's answer data, and the output is the learning progress data stored on the device.

[0990] Step 8:

[0991] The terminal sends the collected learning progress data to the server. The input is the learner's progress data, and the output is the learning progress data sent to the server. The server uses this data to monitor the learner's progress.

[0992] Step 9:

[0993] The server generates feedback based on the learning progress data. It uses a generative AI model to analyze the learner's progress and test results and create appropriate feedback messages. The input is the learning progress data, and the output is the feedback message.

[0994] Step 10:

[0995] The server sends the generated feedback message to the terminal. The terminal receives this message and displays it to the learner. The input is the server-side feedback message, and the output is the feedback message displayed on the terminal. For example, the message "Good job!" is displayed.

[0996] As described above, by these specific processing steps, a system can be realized that provides individually optimized learning guidance to learners.

[0997] 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.

[0998] This invention is a system that utilizes AI, VR technology, and an emotion engine to provide individually optimized learning guidance to learners. This system operates in cooperation with three parties: a server, a terminal, and a user.

[0999] Server processing explanation

[1000] 1. Data Collection and Initial Setup:

[1001] The server collects initial data from the learner, including name, age, grade, achievement test results, learning goals, and preferred learning methods.

[1002] Example: The server receives the data entered by the user in the registration form (e.g., name "Yamada Taro", age "12 years old").

[1003] 2. Generating an individually optimized curriculum:

[1004] The server uses artificial intelligence to generate an optimized learning curriculum for each learner, including the learning content for each subject, progress schedule, and evaluation method.

[1005] Example: A server-generated curriculum specifies weekly math practice problems and monthly practice tests.

[1006] 3. Virtual Instructor Setup:

[1007] The server generates data on a virtual teacher based on the learner's preferences, and this teacher appears in the VR environment with the appearance and speaking style of a specific character or person.

[1008] Example: When a learner selects a virtual teacher who resembles Doraemon, the server generates a 3D model and voice data that resembles Doraemon.

[1009] 4. Progress monitoring and feedback:

[1010] The server monitors learning progress in real time, adjusts the curriculum as needed, and provides feedback based on the learner's performance data.

[1011] Example: The server generates and sends a message saying "Well done!" based on the learner's test results (e.g., 90 points in mathematics).

[1012] 5. Emotion Recognition with Emotion Engine:

[1013] The server analyzes the learner's emotional data using an emotion engine to appropriately adjust instructional content and feedback. This engine recognizes emotions by analyzing the learner's facial expressions and voice.

[1014] Example: The server detects the learner's stress level from facial expression data and provides relaxation content.

[1015] Terminal processing explanation

[1016] 1. Data Entry:

[1017] The terminal accepts data input from the learner, including initial data and learning progress data.

[1018] Specific operation: The device displays a pop-up to start the academic ability test, and the user starts the test.

[1019] 2. View Virtual Instructor:

[1020] The device receives data from the server and displays the virtual instructor in a VR environment, providing interactive lessons.

[1021] Specific operation: Using a VR headset, a video is displayed in which a Doraemon-style virtual instructor explains the preparatory content.

[1022] 3. View and progress your learning:

[1023] The device displays learning content (text, videos, exercises) to the learner based on the learning curriculum.

[1024] Example: A device displays math exercises and the user answers them.

[1025] 4. Sending progress data:

[1026] The device sends learning progress and test results to the server, allowing the server to track progress in real time and provide appropriate feedback.

[1027] Example: The device sends the learner's test results (e.g., 90 points in mathematics) to the server.

[1028] 5. Emotional Data Collection and Transmission:

[1029] The device collects the learner's facial expressions and voice data and sends it to a server, where it is analyzed by an emotion engine.

[1030] Example: The device collects the learner's facial expression data (e.g., images captured from a camera) and voice data and sends them to a server.

[1031] User behavior description

[1032] 1. Enter the initial data:

[1033] Users enter their information into a registration form, including their name, age, grade level, learning goals, and preferred learning method.

[1034] Example: A user fills out a registration form with the name "Yamada Taro" and age "12 years old."

[1035] 2. Participating in a VR environment:

[1036] Users wear a VR device and participate in lessons taught by a virtual instructor. If they have any questions during the lesson, they can ask them using voice input or a dedicated interface.

[1037] Example: A user uses a VR headset to take a lesson from a Doraemon-style virtual instructor.

[1038] 3. Engage in learning content:

[1039] Users work through the learning content displayed on their device, solving problems and taking tests.

[1040] Example: A user works through a math exercise displayed on a terminal and enters the answers.

[1041] 4. Providing Emotion Data:

[1042] During the learning process, users provide emotional data through their facial expressions and the sounds they hear.

[1043] Example: When a user is learning in front of a camera and has a tired expression, the facial expression data is sent from the device to the server.

[1044] 5. Receiving and incorporating feedback:

[1045] Users receive feedback from the server and incorporate it into their learning. They also receive messages and rewards to keep them motivated.

[1046] Example: The user receives a "Good job!" message from the server and proceeds to the next learning step.

[1047] 6. Use of relaxation content:

[1048] The user utilizes relaxation content provided by the emotion engine.

[1049] Example: When a user experiences high stress levels, they listen to relaxation music sent from a server.

[1050] This system allows learners to continue studying in a self-optimized learning environment and effectively improve their academic ability. In addition, the introduction of an emotion engine allows for detailed guidance and support that responds to the learner's emotions.

[1051] The processing flow will be explained below.

[1052] Server processing explanation

[1053] Step 1:

[1054] The server receives the user registration information.

[1055] Specific operation: The user enters the name, age, and grade in the registration form and presses the submit button, which sends the entered data to the server and saves it in the database.

[1056] Step 2:

[1057] The server provides the user with a link to the achievement test.

[1058] Specific operation: The server automatically generates an email containing the URL of the academic achievement test and sends it to the user, or displays the link of the academic achievement test on the dashboard.

[1059] Step 3:

[1060] The server receives and stores the results of the academic achievement test.

[1061] Specific operation: When a user completes an academic ability test, the results are sent from the device to the server and stored in a database.

[1062] Step 4:

[1063] The server uses artificial intelligence to generate an individually optimized curriculum.

[1064] Specific operation: Analyze the received academic ability test results and initial data, and generate the learning content and progress schedule required for the user.

[1065] Step 5:

[1066] The server transmits the generated curriculum to the terminal.

[1067] Specific operation: Send data to the terminal so that the generated learning curriculum is displayed on the user's dashboard.

[1068] Step 6:

[1069] The server generates the data of the virtual instructor.

[1070] Specific operation: Generates a 3D model and audio data based on the user's preferences and stores it in a database.

[1071] Step 7:

[1072] The server transmits the generated virtual instructor data to the terminal.

[1073] Specific operation: The generated virtual instructor data is sent to the terminal so that it is displayed in the user's VR environment.

[1074] Step 8:

[1075] The server monitors the learning progress.

[1076] Specific operation: Receives user progress data (e.g., exercise completion status, test results) sent from the device in real time and stores it in a database.

[1077] Step 9:

[1078] The server uses an emotion engine to analyze the learner's emotion data and generate feedback.

[1079] Specific actions: Analyze the learner's facial expressions and voice data to assess their stress level and motivation.

[1080] Step 10:

[1081] The server adjusts the instruction content and feedback based on the user's emotional data and updates the curriculum as needed.

[1082] Specific behavior: When stress levels are high, a message is generated recommending a break. When motivation levels are low, a message of encouragement is generated.

[1083] Step 11:

[1084] The server generates feedback and sends it to the device.

[1085] Specific behavior: Send data to the device to display a feedback message on the user's dashboard.

[1086] Terminal processing explanation

[1087] Step 1:

[1088] The terminal displays an initial data entry form to the user.

[1089] What it does: Displays a registration form on a web page or app, allowing users to enter their name, age, grade, etc.

[1090] Step 2:

[1091] The terminal transmits the user's input data to the server.

[1092] Specific operation: When the user presses the submit button to send the data entered in the registration form to the server, the data is sent to the backend.

[1093] Step 3:

[1094] The device displays the academic achievement test link and allows the user to access it.

[1095] Specific behavior: A link to the academic achievement test is displayed on the dashboard or in an email, and the user clicks it to begin the test.

[1096] Step 4:

[1097] The terminal transmits the user's academic achievement test results to the server.

[1098] What it does: The user completes the test and the results are automatically sent to the server.

[1099] Step 5:

[1100] The terminal displays the curriculum received from the server.

[1101] Specific operation: The curriculum data received from the server is displayed on the dashboard so that the user can check it.

[1102] Step 6:

[1103] The device displays the virtual instructor data received from the server in a VR environment.

[1104] Specific operation: Using a VR device, the 3D model and audio data received from the server are rendered to provide interactive lessons.

[1105] Step 7:

[1106] The device displays the learning content and the user works on it.

[1107] Specific operation: Learning content such as text, videos, and exercises are displayed to the user, and the user works on it.

[1108] Step 8:

[1109] The terminal transmits learning progress data to the server.

[1110] Specific operation: The results of the user's work on the learning content are recorded in real time and periodically sent to the server.

[1111] Step 9:

[1112] The device collects the user's facial expressions and voice data and sends it to the server.

[1113] Specific operation: The device uses a camera and microphone to collect facial expression and voice data and sends it to a server.

[1114] User behavior description

[1115] Step 1:

[1116] The user enters the initial data.

[1117] Specific actions: Enter your name, age, grade, learning goals, and preferred learning method in the registration form and press the submit button.

[1118] Step 2:

[1119] The user accesses the test link and begins the test.

[1120] Specific actions: Click on the academic achievement test link displayed in email or on the dashboard to begin the test.

[1121] Step 3:

[1122] A user completes a quiz.

[1123] Specific actions: Answer the test questions and enter the results into the terminal.

[1124] Step 4:

[1125] Users wear VR devices and participate in classes taught by virtual instructors.

[1126] Specific actions: Put on a VR headset and watch a lesson from a virtual instructor.

[1127] Step 5:

[1128] The user engages with the learning content.

[1129] Specific actions: Work through the text, videos, and practice problems displayed on the device.

[1130] Step 6:

[1131] The user records facial expressions and voice to provide emotional data.

[1132] Specific operation: During learning, the device uses a camera and microphone to record facial expressions and voice, and then sends the data from the device to the server.

[1133] Step 7:

[1134] The user receives feedback and moves on to the next learning step.

[1135] Specific operation: Receive the feedback message sent from the server and proceed to the next learning step.

[1136] Step 8:

[1137] When a user feels stressed, they can use relaxation content.

[1138] Specific operation: Reduce stress by listening to relaxation music and watching videos sent from the server.

[1139] In this way, the server, device, and user work together to enable individually optimized learning instruction that takes emotions into consideration. This system allows learners to continue studying and aim for effective improvement of their academic ability.

[1140] Example 2

[1141] 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."

[1142] In today's educational environment, there is a demand for individually optimized learning guidance tailored to the needs of each learner. However, conventional systems have difficulty providing learning guidance and feedback that fully reflects the learner's progress and emotional state. In particular, there is a lack of emotional support, making it difficult to address learners' stress and loss of motivation.

[1143] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1144] In this invention, the server includes means for collecting initial data from a learner, means for generating a learning curriculum optimized for each learner using artificial intelligence, means for transmitting the learning curriculum to the learner's terminal, means for generating virtual instructor data, means for transmitting the generated virtual instructor to the learner's terminal, means for monitoring learning progress, means for generating feedback based on the learning progress data, means for analyzing the learner's emotional data using an emotion engine, and means for adjusting instruction content and feedback based on the analysis results. This makes it possible to grasp the learner's learning progress and emotional state in real time and provide individually optimized and effective learning instruction.

[1145] "Initial learner data" is information collected at the beginning of a study, such as the learner's name, age, grade, achievement test results, learning goals, and preferred learning methods.

[1146] "Artificial intelligence" is a computer technology that includes machine learning and data analysis techniques and is used to create learning curricula that are optimized for each learner.

[1147] A "learning curriculum" is an educational plan that includes learning content, progress schedule, and evaluation methods that are optimized for each learner.

[1148] A "virtual teacher" is a teacher character that appears in a digital environment (especially a VR environment) and has the appearance and speaking style of a specific character or person.

[1149] "Learning progress" refers to progress data and results as a learner progresses through the learning curriculum.

[1150] "Feedback" refers to comments and advice for guidance and improvement that are generated based on the learner's learning progress.

[1151] The "emotion engine" is a technology that analyzes a learner's facial expressions and voice data to recognize their emotional state.

[1152] "Emotion data" is data that indicates the emotional state of a learner, recognized based on the learner's facial expressions and voice.

[1153] "Analysis results" refers to the conclusions or conditions obtained after analyzing collected data.

[1154] "Instructional content" refers to the specific learning or educational content provided to learners.

[1155] This invention is a system that utilizes artificial intelligence (AI), virtual reality (VR) technology, and an emotion engine to provide individually optimized learning guidance to learners. This system operates in cooperation with a server, a terminal, and a user.

[1156] Server processing explanation

[1157] The server first collects initial data from the learner, including the learner's name, age, grade, academic achievement test results, learning goals, and preferred learning methods. For example, if a learner enters the name "Yamada Taro" and age "12 years old," the data is sent to the server and stored in a database.

[1158] Based on the initial data, the server uses artificial intelligence (e.g., TensorFlow or PyTorch) to generate a learning curriculum optimized for each learner. The curriculum includes the learning content, progress schedule, and evaluation method for each subject. For example, the curriculum includes weekly math practice problems and monthly mock tests.

[1159] Next, the server generates data on a virtual tutor based on the learner's preferences. This tutor will have the appearance and speaking style of a specific character or person and will be displayed in the VR environment. For example, if a learner selects a virtual tutor resembling Doraemon, the server will generate a 3D model and voice data that resembles Doraemon.

[1160] The server also monitors the learner's progress in real time, adjusts the curriculum as needed, and generates feedback based on the progress data. For example, if a learner gets 90 points on a test, the server generates a message saying "Well done!" and sends it to the learner's device.

[1161] The emotion engine is used to analyze the learner's facial expression and voice data to recognize their emotional state. This allows the server to adjust instruction content and feedback based on the emotional data. For example, if the server detects a high stress level from the learner's facial expression data, it can provide relaxation content (e.g., relaxation music).

[1162] Terminal processing explanation

[1163] The device first accepts initial data from the learner, including the results of an achievement test and data on the learner's progress. As a specific example, the device displays a pop-up to start the achievement test, and the user starts the test.

[1164] The virtual instructor data received from the server is displayed in a VR environment. By using a VR headset, a video of a Doraemon-style virtual instructor explaining the content of the preparation is displayed.

[1165] The device displays learning content such as textbooks, videos, and exercises to the learner based on the learning curriculum. For example, the device may display mathematics exercises for the user to answer.

[1166] The device sends learning progress and test results to the server, allowing the server to understand progress in real time and provide appropriate feedback. For example, the device sends the learner's test results (e.g., 90 points in mathematics) to the server.

[1167] The device also collects the learner's facial expression and voice data and transmits it to the server. For example, the device can collect the learner's facial expression data (e.g., images captured by a camera) and voice data and transmit them to the server.

[1168] User behavior description

[1169] A user first enters their information into a registration form, including their name, age, grade, learning goals, and preferred learning method. For example, a user enters their name "Yamada Taro" and age "12 years old" into the registration form.

[1170] Next, the user puts on the VR device and participates in a lesson taught by a virtual instructor. If the user has a question during the lesson, they can ask it using voice input or a dedicated interface. For example, a user can take a lesson from a Doraemon-style virtual instructor using a VR headset.

[1171] The user works on the learning content displayed on the terminal, solves problems, takes tests, etc. For example, the user works on math exercises displayed on the terminal and inputs the answers.

[1172] During learning, users provide emotional data through their facial expressions and voice. For example, if a user looks tired while learning in front of the camera, that facial data is sent from the device to the server.

[1173] The user receives feedback from the server and reflects it in their learning. For example, the user receives a message saying "Good job!" and proceeds to the next learning step.

[1174] Users also use relaxation content provided by the emotion engine. For example, when their stress level is high, they listen to relaxation music sent from the server.

[1175] This system allows learners to continue studying in a self-optimized learning environment and effectively improve their academic ability. In addition, the introduction of an emotion engine allows for detailed guidance and support that responds to the learner's emotions.

[1176] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1177] Step 1:

[1178] Data collection and initial setup

[1179] Input: The initial data that the user enters in the registration form (name, age, grade, academic test results, learning goals, preferred learning methods)

[1180] How it works: The server receives an HTTP POST request and stores the initial data in a database.

[1181] Output: Initial data stored in the database

[1182] Example: A user enters "Yamada Taro" and "12 years old", and the server saves this in the database.

[1183] Step 2:

[1184] Generation of individually optimized curriculum

[1185] Input: Initial data of the student obtained from the server database

[1186] How it works: The server runs an AI model (e.g., TensorFlow, PyTorch) to generate an optimized learning curriculum for each learner. The AI ​​model receives learner data as input and calculates the learning content, progress schedule, and assessment method for each subject.

[1187] Output: Generated individualized optimized curriculum

[1188] Example: A server generates a curriculum that includes weekly math practice questions and monthly practice tests.

[1189] Step 3:

[1190] Virtual Instructor Setup

[1191] Input: Information based on the user's preferences (e.g., favorite character)

[1192] Operation: The server generates corresponding 3D model data and audio data based on the preference information. These data are used in the VR environment as a virtual teacher.

[1193] Output: Generated virtual instructor data (3D model and audio data)

[1194] Example: A learner selects a virtual teacher who looks like Doraemon, and the server generates a 3D model of Doraemon and audio data.

[1195] Step 4:

[1196] Sending learning curriculum and instructor data

[1197] Input: Generated learning curriculum and virtual instructor data

[1198] Operation: The server sends these data to the user's terminal.

[1199] Output: The learning curriculum and virtual instructor data are sent to the terminal.

[1200] Example: The server sends the created learning curriculum and Doraemon-style instructor data to the user's device.

[1201] Step 5:

[1202] Display in VR environment

[1203] Input: Virtual instructor data sent from the server

[1204] How it works: The device displays the received virtual instructor data in a VR environment. Specifically, it uses Unity or Unreal Engine to render a 3D model and play audio data.

[1205] Output: VR environment with virtual instructor displayed

[1206] Example: A Doraemon-style virtual teacher begins a lesson on a VR headset.

[1207] Step 6:

[1208] View and progress your learning

[1209] Input: Learning curriculum received from the server

[1210] How it works: The device displays curriculum-based text, videos, and exercises to the learner, and also provides an interface where the user can enter their answers.

[1211] Output: What the user sees

[1212] Example: A device displays math exercises and the user answers them.

[1213] Step 7:

[1214] Sending progress data

[1215] Input: User-entered learning progress and test results

[1216] How it works: The device sends this data to the server using an HTTP POST request.

[1217] Output: Progress data sent to the server

[1218] Example: The device sends the learner's test results (e.g., 90 points in mathematics) to the server.

[1219] Step 8:

[1220] Collecting and transmitting emotional data

[1221] Input: User's facial expressions and voice data

[1222] How it works: The device uses its camera and microphone to collect this data and sends it to a server.

[1223] Output: Emotion data sent to the server

[1224] Example: The device sends the learner's facial expression data and voice data to the server.

[1225] Step 9:

[1226] Emotional Data Analysis

[1227] Input: Emotion data sent from the device

[1228] How it works: The server uses the emotion engine to analyze the emotion data. The analysis results indicate the learner's emotional state.

[1229] Output: Parsed emotion data

[1230] Example: The server analyzes the learner's stress level from facial expression data.

[1231] Step 10:

[1232] Generate feedback

[1233] Input: Learning progress data and emotion data analysis results

[1234] Operation: The server generates feedback based on this data and adjusts the curriculum. The generated feedback is sent to the device.

[1235] Output: Generated feedback and adjusted curriculum

[1236] Example: The server generates a message saying "Good job!" and sends it to the device. Also, if the learner shows signs of fatigue, the curriculum is adjusted to add breaks.

[1237] (Application example 2)

[1238] 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."

[1239] In recent years, there has been a demand for providing educational content that is optimized for each individual learner. However, conventional systems often fail to adequately grasp learners' progress or analyze their emotional data, resulting in a uniform curriculum and teaching methods, resulting in low learning effectiveness. Furthermore, a lack of appropriate feedback and content to alleviate stress during learning has also led to a decline in learners' motivation.

[1240] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting initial data from the learner, means for generating a learning curriculum optimized for each learner using artificial intelligence, means for transmitting the learning curriculum to the learner's terminal, means for generating virtual instructor data, means for transmitting the generated virtual instructor to the learner's terminal, means for monitoring the learning progress, means for generating feedback based on the learning progress data, means for providing additional learning content based on the feedback, means for providing lessons by the virtual instructor in a VR environment, means for collecting and analyzing emotional data, and means for providing relaxation content based on the learner's emotional data. This makes it possible to provide individually optimized learning guidance and feedback for each learner, as well as content tailored to their emotions.

[1241] "Student" refers to an individual receiving education or training, and in particular, to a person who uses the System to carry out learning activities.

[1242] "Initial data" refers to basic information about the learner, including name, age, grade, achievement test results, learning goals, preferred learning methods, etc.

[1243] "Artificial intelligence" is a technology that gives intelligence to computer systems, and in this system it is a technology used to optimize learning curricula, etc.

[1244] "Learning curriculum" refers to the educational content and learning plan provided to learners, including specific subject content, progress schedule, and evaluation methods.

[1245] "Device" refers to the computer device used by the learner, including smartphones, tablets, and PCs.

[1246] A "virtual instructor" refers to a virtual educator generated by a computer program who provides educational content to learners.

[1247] "Means for generating data" refers to the programs or algorithms used to create or generate the required data.

[1248] "Means for transmitting data" refers to the technology for transmitting and receiving the generated data between terminals and servers, including network communication technology.

[1249] "Study progress" refers to information that indicates how far a learner has progressed in the learning content, and includes test results, progress status, and the like.

[1250] "Feedback" refers to reactions and advice provided based on a learner's learning status, and is used to improve learning outcomes.

[1251] "Additional learning content" refers to supplementary educational content provided in addition to an existing learning curriculum, including content to fill learning gaps.

[1252] A "VR environment" refers to an environment in which a virtual learning space is created and provided to learners using virtual reality technology.

[1253] "Emotional data" refers to information that indicates the learner's emotional state, and is obtained through facial expressions, voice data, and other biometric data.

[1254] "Relaxation content" refers to content provided to reduce learners' stress and promote relaxation, and includes music, videos, guidance, etc.

[1255] This invention provides a system that provides individually optimized learning guidance to learners. This invention utilizes AI, VR technology, and an emotion engine, and operates in cooperation with a server, a terminal, and a user.

[1256] Server Processing

[1257] 1. Data Collection and Initial Setup:

[1258] The server collects initial data from the learner, including name, age, grade, achievement test results, learning goals, and preferred learning methods. For example, a learner enters his name "Yamada Taro" and age "12 years old" into a registration form.

[1259] 2. Generating an individually optimized curriculum:

[1260] The server uses artificial intelligence to generate a learning curriculum optimized for each learner. This curriculum includes the learning content, progress schedule, and evaluation method for each subject. For example, the server-generated curriculum specifies weekly math practice problems and monthly mock tests.

[1261] 3. Virtual Instructor Setup:

[1262] The server generates data on a virtual teacher based on the learner's preferences. This teacher will have the appearance and speaking style of a specific character or person and will be displayed in the VR environment. For example, if a learner selects a virtual teacher who resembles a virtual character, the server generates a 3D model and voice data that resembles that character.

[1263] 4. Progress monitoring and feedback:

[1264] The server monitors the learner's progress in real time and adjusts the curriculum as needed. It also provides feedback based on the learner's performance data. For example, the server generates and sends a message saying "Well done!" based on the learner's test results (e.g., 90 points in mathematics).

[1265] 5. Emotion Recognition with Emotion Engine:

[1266] The server uses an emotion engine to analyze the learner's emotional data and adjust the instruction content and feedback appropriately. This engine recognizes emotions by analyzing the learner's facial expressions and voice. As a specific example, the server detects the learner's stress level from their facial expression data and provides relaxation content.

[1267] Terminal handling

[1268] 1. Data Entry:

[1269] The device accepts data input from the learner, including initial data and learning progress data. Specifically, the device displays a popup to start the academic ability test, and the user begins the test.

[1270] 2. View Virtual Instructor:

[1271] The device receives data from the server and displays it in a VR environment, providing an interactive lesson. Specifically, a VR headset is used to display a video of the virtual instructor explaining the content of the lesson.

[1272] 3. View and progress your learning:

[1273] The device displays learning content (text, videos, exercises) to the learner based on the learning curriculum. For example, the device displays mathematics exercises, and the user answers them.

[1274] 4. Sending progress data:

[1275] The device sends learning progress and test results to the server, allowing the server to understand progress in real time and provide appropriate feedback. For example, the device sends the learner's test results (e.g., 90 points in mathematics) to the server.

[1276] 5. Emotional Data Collection and Transmission:

[1277] The device collects the learner's facial expression and voice data and sends it to the server. This data is analyzed by the emotion engine. For example, the device collects the learner's facial expression data (e.g., images captured from a camera) and voice data and sends it to the server.

[1278] User behavior

[1279] 1. Enter the initial data:

[1280] A user enters their information into a registration form, including their name, age, grade, learning goals, preferred learning method, etc. For example, a user enters their name "Yamada Taro" and age "12 years old" into a registration form.

[1281] 2. Participating in a VR environment:

[1282] Users wear a VR device and participate in lessons taught by a virtual instructor. If they have questions during the lesson, they can ask using voice input or a dedicated interface. For example, a user can take a lesson taught by a virtual instructor using a VR headset.

[1283] 3. Engage in learning content:

[1284] The user works on the learning content displayed on the device, solves problems, takes tests, etc. For example, the user works on a math exercise displayed on the device and enters the answers.

[1285] 4. Providing Emotion Data:

[1286] During the learning process, users provide emotional data through their facial expressions and voice. For example, if a user looks tired while learning in front of the camera, that facial expression data is sent from the device to the server.

[1287] 5. Receiving and incorporating feedback:

[1288] The user receives feedback from the server and reflects it in their learning. They also receive messages and rewards to maintain their motivation. For example, the user receives a message from the server saying "Good job!" and moves on to the next learning step.

[1289] 6. Use of relaxation content:

[1290] The user uses relaxation content provided by the emotion engine. For example, when the user is under high stress, they listen to relaxation music sent from the server.

[1291] Prompt Sentence Examples

[1292] Generate an appropriate learning curriculum based on the user: {Name: "Yamada Taro", Age: 12, Grade: "1st year of junior high school", Academic achievement test results: {Math: 80, English: 75}, Learning goal: "Math reinforcement", Preferred learning method: "Visual"}.

[1293] In this way, the present invention realizes individually optimized learning guidance and feedback for each learner, as well as the provision of content according to their emotions.

[1294] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1295] Step 1:

[1296] The server collects initial data from the learner, such as name, age, grade, achievement test results, learning goals, preferred learning methods, etc., entered by the user in the registration form. Based on the input data, the server creates a learner profile.

[1297] Step 2:

[1298] The server uses artificial intelligence to generate an optimized learning curriculum for each learner. To do this, the learner's initial data is input, and the AI ​​model processes and analyzes the data to output an individually optimized curriculum (educational content, progress schedule, evaluation method, etc.). Specifically, the curriculum is generated using OpenAI's AI model.

[1299] Step 3:

[1300] The server sends the generated optimized curriculum to the learner's device. The curriculum data is input and sent to the device via the network, where the curriculum is displayed. Specifically, data is sent using an API.

[1301] Step 4:

[1302] The server generates the virtual teacher's data and customizes it based on the learner's preferences. It uses the learner's initial data as input to generate the virtual teacher's appearance and speaking style. Specifically, it uses an AI model to generate the virtual teacher's character data.

[1303] Step 5:

[1304] The server sends the generated virtual instructor data to the learner's device. The virtual instructor data is used as input and sent to the device via the network, where the virtual instructor is displayed on the device. Specifically, data is sent using an API.

[1305] Step 6:

[1306] The device receives the virtual instructor's data and displays it in the VR environment. Based on the received data, an interactive lesson is provided using a VR headset. For example, a video of a Doraemon-style virtual instructor explaining the content of the lesson is displayed.

[1307] Step 7:

[1308] The device sends the learner's progress and academic test results to the server. By collecting the learner's progress data and sending it to the server, real-time progress management is performed. As a concrete example, a math test result of 90 points is sent to the server.

[1309] Step 8:

[1310] The server monitors the learning progress and generates feedback. It analyzes the learning progress data as input, generates appropriate feedback (e.g., "Good job!"), and sends it to the learner's device.

[1311] Step 9:

[1312] The device collects the learner's facial expressions and voice data and sends it to the server. Emotional data is collected using a camera and microphone and sent to the server. As a specific example, image data of a tired facial expression is sent to the server.

[1313] Step 10:

[1314] The server uses an emotion engine to analyze the learner's emotional data and provide appropriate content based on their emotions.The server analyzes the emotional data as input, generates relaxation content (e.g., relaxation music), and sends it to the device.

[1315] 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.

[1316] 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.

[1317] 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.

[1318] [Third embodiment]

[1319] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1320] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1321] 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).

[1322] 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.

[1323] 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.

[1324] 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).

[1325] 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.

[1326] 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.

[1327] 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.

[1328] 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.

[1329] 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.

[1330] 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."

[1331] This invention is a system that utilizes AI and VR technology to provide individually optimized learning guidance to learners. This system operates in cooperation with three parties: a server, a terminal, and a user.

[1332] Server processing explanation

[1333] 1. Data Collection and Initial Setup:

[1334] The server collects initial data from the learner, including name, age, grade, achievement test results, learning goals, and preferred learning methods.

[1335] Example: The server receives the data entered by the user in the registration form (e.g., name "Yamada Taro", age "12 years old").

[1336] 2. Generating an individually optimized curriculum:

[1337] The server uses artificial intelligence to generate an optimized learning curriculum for each learner, including the learning content for each subject, progress schedule, and evaluation method.

[1338] Example: A server-generated curriculum specifies weekly math practice problems and monthly practice tests.

[1339] 3. Virtual Instructor Setup:

[1340] The server generates data on a virtual teacher based on the learner's preferences, and this teacher appears in the VR environment with the appearance and speaking style of a specific character or person.

[1341] Example: When a learner selects a virtual teacher who resembles Doraemon, the server generates a 3D model and voice data that resembles Doraemon.

[1342] 4. Progress monitoring and feedback:

[1343] The server monitors learning progress in real time, adjusts the curriculum as needed, and provides feedback based on the learner's performance data.

[1344] Example: The server generates and sends a message saying "Well done!" based on the learner's test results (e.g., 90 points in mathematics).

[1345] Terminal processing explanation

[1346] 1. Data Entry:

[1347] The terminal accepts data input from the learner, including initial data and learning progress data.

[1348] Example: The device displays a popup to start an academic ability test, and the user starts the test.

[1349] 2. View Virtual Instructor:

[1350] The device receives data from the server and displays the virtual instructor in a VR environment, providing interactive lessons.

[1351] Example: Using a VR headset, a video is displayed in which a virtual instructor dressed like Doraemon explains the content of the preparatory lesson.

[1352] 3. View and progress your learning:

[1353] The device displays learning content (text, videos, exercises) to the learner based on the learning curriculum.

[1354] Example: A device displays math exercises and the user answers them.

[1355] 4. Sending progress data:

[1356] The device sends learning progress and test results to the server, allowing the server to track progress in real time and provide appropriate feedback.

[1357] Example: The device sends the learner's test results (e.g., 90 points in mathematics) to the server.

[1358] User behavior description

[1359] 1. Enter the initial data:

[1360] Users enter their information into a registration form, including their name, age, grade level, learning goals, and preferred learning method.

[1361] Example: A user fills out a registration form with the name "Yamada Taro" and age "12 years old."

[1362] 2. Participating in a VR environment:

[1363] Users wear a VR device and participate in lessons taught by a virtual instructor. If they have any questions during the lesson, they can ask them using voice input or a dedicated interface.

[1364] Example: A user uses a VR headset to take a lesson from a Doraemon-style virtual instructor.

[1365] 3. Engage in learning content:

[1366] Users work through the learning content displayed on their device, solving problems and taking tests.

[1367] Example: A user works through a math exercise displayed on a terminal and enters the answers.

[1368] 4. Receiving and incorporating feedback:

[1369] Users receive feedback from the server and incorporate it into their learning. They also receive messages and rewards to keep them motivated.

[1370] Example: The user receives a "Good job!" message from the server and proceeds to the next learning step.

[1371] This system allows learners to continue studying in a learning environment that is optimized for them, and aims to effectively improve their academic ability.

[1372] The processing flow will be explained below.

[1373] Server processing explanation

[1374] Step 1:

[1375] The server receives the user registration information.

[1376] Specific operation: The user enters the name, age, and grade in the registration form and presses the submit button, which sends the entered data to the server and saves it in the database.

[1377] Step 2:

[1378] The server provides the user with a link to the achievement test.

[1379] Specific operation: The server automatically generates an email containing the URL of the academic ability test and sends it to the user, or displays the link of the academic ability test on the dashboard.

[1380] Step 3:

[1381] The server receives and stores the results of the academic achievement test.

[1382] Specific operation: When a user completes an academic ability test, the results are sent from the device to the server and stored in a database.

[1383] Step 4:

[1384] The server uses artificial intelligence to generate an individually optimized curriculum.

[1385] Specific operation: Analyze the received academic ability test results and initial data, and generate the learning content and progress schedule required for the user.

[1386] Step 5:

[1387] The server transmits the generated curriculum to the terminal.

[1388] Specific operation: Send data to the terminal so that the generated learning curriculum is displayed on the user's dashboard.

[1389] Step 6:

[1390] The server generates the data of the virtual instructor.

[1391] Specific operation: Generates a 3D model and audio data based on the user's preferences and stores it in a database.

[1392] Step 7:

[1393] The server transmits the generated virtual instructor data to the terminal.

[1394] Specific operation: The generated virtual instructor data is sent to the terminal so that it is displayed in the user's VR environment.

[1395] Step 8:

[1396] The server monitors the learning progress.

[1397] Specific operation: Receives user progress data (e.g., exercise completion status, test results) sent from the device in real time and stores it in a database.

[1398] Step 9:

[1399] The server generates feedback and adjusts the curriculum as needed.

[1400] Specific behavior: Analyzes progress data, generates feedback messages with praise and suggestions for improvement, and sends them to the device, updating the learning curriculum as needed.

[1401] Terminal processing explanation

[1402] Step 1:

[1403] The terminal displays an initial data entry form to the user.

[1404] What it does: Displays a registration form on a web page or app, allowing users to enter their name, age, grade, etc.

[1405] Step 2:

[1406] The terminal transmits the user's input data to the server.

[1407] Specific operation: When the user presses the submit button to send the data entered in the registration form to the server, the data is sent to the backend.

[1408] Step 3:

[1409] The device displays the academic achievement test link and allows the user to access it.

[1410] Specific behavior: A link to the academic achievement test is displayed on the dashboard or in an email, and the user clicks it to begin the test.

[1411] Step 4:

[1412] The terminal inputs the user's academic achievement test results and sends them to the server.

[1413] What it does: The user completes the test and the results are automatically sent to the server.

[1414] Step 5:

[1415] The terminal displays the curriculum received from the server.

[1416] Specific operation: The curriculum data received from the server is displayed on the dashboard so that the user can check it.

[1417] Step 6:

[1418] The device displays the virtual instructor data received from the server in a VR environment.

[1419] Specific operation: Using a VR device, the 3D model and audio data received from the server are rendered to provide interactive lessons.

[1420] Step 7:

[1421] The device displays the learning content and the user works on it.

[1422] Specific operation: Learning content such as text, videos, and exercises are displayed to the user, and the user works on it.

[1423] Step 8:

[1424] The terminal transmits learning progress data to the server.

[1425] Specific operation: The results of the user's work on the learning content are recorded in real time and periodically sent to the server.

[1426] User behavior description

[1427] Step 1:

[1428] The user enters the initial data.

[1429] Specific actions: Enter your name, age, grade, learning goals, and preferred learning method in the registration form and press the submit button.

[1430] Step 2:

[1431] The user accesses the test link and begins the test.

[1432] Specific actions: Click on the academic achievement test link displayed in email or on the dashboard to begin the test.

[1433] Step 3:

[1434] A user completes a quiz.

[1435] Specific actions: Answer the test questions and enter the results into the terminal.

[1436] Step 4:

[1437] Users wear VR devices and participate in classes taught by virtual instructors.

[1438] Specific actions: Put on a VR headset and watch a lesson from a virtual instructor.

[1439] Step 5:

[1440] The user engages with the learning content.

[1441] Specific actions: Work through the text, videos, and practice problems displayed on the device.

[1442] Step 6:

[1443] The user receives feedback and moves on to the next learning step.

[1444] Specific behavior: Receive the feedback message sent from the server and work on the next learning content.

[1445] In this way, the server, terminal, and user work together to provide effective learning guidance.

[1446] Example 1

[1447] 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."

[1448] In recent years, there has been a demand for a learning environment that is optimized for each learner's academic ability and learning style, but conventional systems have difficulty fully meeting this demand. In particular, they lack the functionality to integrate multiple elements, such as generating individually optimized learning curricula, providing virtual instructors that match the learner's preferences, and monitoring learning progress in real time and providing feedback.

[1449] 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.

[1450] In this invention, the server includes means for inputting personal information from the learner, means for generating an education plan optimized for each learner using artificial intelligence, means for transmitting the education plan to the learner's device, means for generating virtual instructor data, means for transmitting the generated virtual instructor to the learner's device, means for displaying the virtual instructor in a virtual reality environment, means for monitoring learning progress in real time, and means for generating and transmitting feedback based on the learning progress data. This makes it possible to provide an individually optimized learning curriculum, effective learning support by a virtual instructor that suits the learner's preferences, and real-time understanding of progress and appropriate feedback.

[1451] "Means for learner input of personal information" refers to an interface designed to allow learners to input personal information such as their name, age, grade, and learning goals.

[1452] "Means for generating educational plans optimized for each learner using artificial intelligence" refers to algorithms or software that take a learner's personal information and learning data as input and automatically generate appropriate learning content and schedules.

[1453] The "means for transmitting the educational plan to the learner's device" refers to a system including communication means and protocols for transferring the generated educational plan to the learner's terminal.

[1454] "Means for generating virtual instructor data" refers to software or tools for creating data that resembles the appearance and speaking style of a specific character or person based on learner preferences.

[1455] The "means for transmitting the generated virtual instructor to the learner's device" refers to a system including communication means and protocols for transmitting data of the generated virtual instructor to the learner's terminal.

[1456] The "means for displaying the virtual instructor in a virtual reality environment" refers to a device or software that displays the virtual instructor in a virtual reality environment and allows learners to take lessons interactively.

[1457] "Means for monitoring learning progress in real time" refers to a system that collects, records, and analyzes information in real time, such as the learner's current stage and how well they have completed tasks.

[1458] The "means for generating and transmitting feedback based on the learning progress data" refers to an algorithm or system that automatically generates appropriate feedback (e.g., words of encouragement, suggestions for correction, etc.) based on the collected learning progress data and transmits it to the learner's device.

[1459] This invention is a system that utilizes AI and VR technology to provide individually optimized learning guidance to learners. This system operates in cooperation with three parties: a server, a terminal, and a user.

[1460] Server processing explanation

[1461] The server collects initial data:

[1462] To collect the initial data, the server receives the user's name, age, grade, academic test results, learning goals, and preferred learning methods entered through the terminal. This data is sent via HTTP protocol and in JSON format to the server. The server then stores this data using a database management system (e.g., MySQL).

[1463] Generate a personalized optimization curriculum:

[1464] The server sends prompts to a generative AI model (e.g., OpenAI GPT-4) based on the collected initial data to generate an educational plan optimized for each individual learner. An example of a prompt is, "Please create the optimal learning curriculum based on Taro Yamada's academic ability data." The server receives the generated curriculum data and stores it in a database.

[1465] Generate the virtual instructor data:

[1466] The server generates virtual teacher data based on the learner's preferences. Specifically, it creates the character's appearance using 3D modeling software (e.g., Blender) and generates voice data using a voice generation tool (e.g., Google Text-to-Speech). An example of a prompt is "Please generate a virtual teacher in the style of Doraemon."

[1467] Generate and send feedback:

[1468] Learning progress is monitored in real time, and the server generates feedback based on the performance data, for example, a message such as "You got 90 points on the math test! Well done!" and sends it to the device.

[1469] Terminal processing explanation

[1470] Accept user data input:

[1471] The terminal accepts data input from the user, specifically providing a registration form where the user enters their name, age, etc., and transmits the collected data to the server.

[1472] View Virtual Instructors:

[1473] The device receives data from the server and displays it in a VR environment, allowing users to enjoy interactive lessons with virtual instructors using VR headsets such as Oculus Quest and HTC Vive.

[1474] View learning content:

[1475] The device displays learning content (text, videos, exercises) based on the learning curriculum, and users solve problems and watch videos through the device.

[1476] Send the learning progress to the server:

[1477] The device records the questions and test results the user has answered and sends them to a server, which receives them in real time and monitors the user's progress.

[1478] User behavior description

[1479] Enter the initial data:

[1480] The user enters their information into the registration form, for example, their name "Yamada Taro" and age "12 years old" into the terminal.

[1481] Participating in a VR environment:

[1482] Users wear VR devices and participate in lessons taught by virtual instructors. For example, users can take lessons from Doraemon-style virtual instructors.

[1483] Engage in learning content:

[1484] The user engages in learning content displayed on the device, for example, answering math exercises.

[1485] Receiving and implementing feedback:

[1486] The user receives feedback from the server and reflects it in their learning, for example, receiving a message like "Good job!" and proceeding to the next learning step.

[1487] The system provides an effective learning environment by combining an individually optimized learning curriculum, virtual instructors tailored to the user's preferences, and real-time monitoring and feedback.

[1488] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1489] Step 1: Data collection

[1490] ---

[1491] server:

[1492] The server collects personal information entered by the user on the device, including name, age, grade, achievement test results, learning goals, and preferred learning methods.

[1493] Input: Personal information entered by the user into the device.

[1494] Data processing: The server receives the data using the HTTP protocol and parses it in JSON format.

[1495] Output: Save the parsed data in a database management system (e.g., MySQL).

[1496] Device:

[1497] The terminal displays an input form to the user and prompts the user to input the required data.

[1498] Input: Personal information entered by the user.

[1499] Data calculation: Convert the input data into JSON format and send it to the server.

[1500] Output: User data sent to the server.

[1501] User:

[1502] The user enters his / her information into the input form displayed on the terminal.

[1503] Input: Name, age, grade, achievement test results, learning goals, preferred learning method.

[1504] Output: Sends data entered into the terminal to the server.

[1505] Step 2: Generate an individually optimized curriculum

[1506] ---

[1507] server:

[1508] The server sends a prompt to the generative AI model (e.g., OpenAI GPT-4) based on the collected initial data.

[1509] Example prompt: "Create the optimal learning curriculum based on Yamada Taro's academic achievement data."

[1510] Input: Initial user data read from the database, prompt statement.

[1511] Data calculation: Send a prompt to the generative AI model and generate an optimized curriculum in response.

[1512] Output: Save the generated curriculum data in a database.

[1513] Device:

[1514] There is no special processing.

[1515] User:

[1516] There is no special processing.

[1517] Step 3: Generate virtual instructor data

[1518] ---

[1519] server:

[1520] The server generates virtual instructor data based on the learner's preferences, creates the character's appearance using 3D modeling software (e.g., Blender), and generates voice data using a voice generation tool (e.g., Google Text-to-Speech).

[1521] Example prompt: "Create a Doraemon-style virtual teacher."

[1522] Input: User preference data, prompt text.

[1523] Data calculation: Using 3D modeling software and voice generation tools, a model and voice of the virtual teacher are generated.

[1524] Output: Save the generated virtual instructor data in a database.

[1525] Device:

[1526] There is no special processing.

[1527] User:

[1528] The user selects virtual instructor preferences at the terminal.

[1529] Step 4: Deliver learning content

[1530] ---

[1531] server:

[1532] The server prepares learning content (text, videos, exercises) based on the learning curriculum.

[1533] Input: Appropriate learning curriculum.

[1534] Data calculation: Retrieve learning content from the database and combine the necessary data.

[1535] Output: Creates an endpoint to send prepared learning content to the device.

[1536] Device:

[1537] The terminal receives the learning content from the server and displays it to the user.

[1538] Input: The learning content sent from the server.

[1539] Data calculation: Analyzes received data and displays it as learning content.

[1540] Output: The learning content displayed to the user.

[1541] User:

[1542] Users engage with the learning content displayed on their device, solving math exercises and watching videos.

[1543] Input: The learning content displayed on the device.

[1544] Output: Question answer results and viewing history.

[1545] Step 5: Monitoring your learning progress

[1546] ---

[1547] server:

[1548] The server monitors the learning progress in real time.

[1549] Input: Learning progress data sent from the device.

[1550] Data calculation: Save learning progress data in a database and analyze and monitor progress.

[1551] Output: Detailed statistics of your learning progress.

[1552] Device:

[1553] The device records the user's learning content and test results and sends them to the server.

[1554] Input: User's learning progress data.

[1555] Data Computation: Formatting the collected data for sending to the server.

[1556] Output: Learning progress data sent to the server.

[1557] User:

[1558] The user continues to work on the learning content.

[1559] Input: Question answers and test results.

[1560] Output: Your learning progress data.

[1561] Step 6: Provide feedback

[1562] ---

[1563] server:

[1564] The server generates feedback based on the learning progress data and transmits it to the terminal.

[1565] Input: Learning progress data.

[1566] Data computation: Uses feedback generation algorithms to create appropriate messages.

[1567] Output: Sends feedback messages to the terminal.

[1568] Device:

[1569] The terminal displays the feedback message received from the server to the user.

[1570] Input: The feedback message sent by the server.

[1571] Data processing: Converting feedback messages into a display format.

[1572] Output: The feedback displayed to the user.

[1573] User:

[1574] The user receives feedback from the server and reflects it in their learning.

[1575] Input: The feedback message displayed on the terminal.

[1576] Output: Reflected learning behavior.

[1577] The above are the specific processing steps and operations of the server, terminal, and user.

[1578] (Application example 1)

[1579] 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."

[1580] Conventional learning support systems often provide a uniform learning curriculum, which means they are unable to adequately address the individual needs of each learner. Furthermore, creating an environment that maximizes learning effectiveness is difficult, due to the lack of real-time feedback that is common in face-to-face classes and the difficulty of maintaining motivation. Furthermore, the limited customization of virtual instructors can prevent effective instruction tailored to learners' interests and preferences. A system that can solve these issues and provide personalized instruction optimized for each learner is needed.

[1581] 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.

[1582] In this invention, the server includes means for collecting initial data from learners, means for generating a learning curriculum optimized for each learner using artificial intelligence, means for generating virtual instructor data, means for displaying the generated virtual instructor in a virtual reality environment, means for monitoring learning progress, means for generating feedback based on the learning progress data, and means for providing feedback in real time, thereby providing personalized learning guidance optimized for each learner and maximizing the learning effect.

[1583] "Initial data" is basic information about the learner, such as the learner's name, age, grade, learning goals, and preferred learning methods.

[1584] "Artificial intelligence" is a technology that allows computer systems to perform highly complex tasks and analyze learner data to generate optimal learning curricula.

[1585] A "learning curriculum" is a plan that includes learning content, progress schedule, and evaluation methods optimized for each learner.

[1586] A "virtual instructor" is an interactive instructor that is customized based on the learner's preferences and displayed in a virtual reality environment.

[1587] A "virtual reality environment" is a simulated environment that feels real using computer technology.

[1588] "Study progress" is data that indicates how far a learner has progressed in their studies according to the learning curriculum.

[1589] "Feedback" refers to evaluations, advice, and messages to maintain motivation that are generated based on the learner's learning progress.

[1590] "Real-time" means that data is sent, received, and processed immediately, without delay.

[1591] The present invention is a system for providing individually optimized learning guidance to learners, and involves cooperation between a server, a terminal, and a user. A method for realizing this system will be described in detail below.

[1592] Server processing explanation

[1593] 1. Data Collection and Initial Setup:

[1594] The server collects initial data from the learner, including the learner's name, age, grade, achievement test results, learning goals, and preferred learning methods, thereby obtaining basic information about the learner and using it to generate an individually optimized learning curriculum.

[1595] 2. Generating an individually optimized curriculum:

[1596] The server uses a generative AI model to generate an optimized learning curriculum for each learner, including the learning content, progress schedule, and assessment method for each subject.

[1597] 3. Virtual Instructor Setup:

[1598] The server generates data on a virtual tutor based on the learner's preferences, and the tutor appears in a virtual reality environment, looking and speaking like a specific character or person.

[1599] 4. Progress monitoring and feedback:

[1600] The server monitors learning progress in real time, adjusts the curriculum as needed, and provides feedback based on learners' performance data.

[1601] Terminal processing explanation

[1602] 1. Data Entry:

[1603] The device accepts data input from the learner, including initial data and learning progress data, for example, displaying a popup to allow the user to start an achievement test on the device and collecting the achievement test results.

[1604] 2. View Virtual Instructor:

[1605] The device receives data from the server and displays it in a virtual reality environment, allowing learners to take interactive lessons.

[1606] 3. View and progress your learning:

[1607] The device displays learning content (text, videos, exercises) to the learner based on the curriculum, allowing the learner to progress through their studies efficiently.

[1608] 4. Sending progress data:

[1609] The device sends learning progress and test results to the server, allowing the server to track progress in real time and provide appropriate feedback.

[1610] User behavior description

[1611] 1. Enter the initial data:

[1612] Users enter their information into a registration form on the device, including their name, age, grade level, learning goals, and preferred learning method.

[1613] 2. Participating in a VR environment:

[1614] Users wear a VR device and participate in lessons taught by a virtual instructor. If they have any questions during the lesson, they can ask them using voice input or a dedicated interface.

[1615] 3. Engage in learning content:

[1616] Users work through the learning content displayed on their devices, solve problems, and take tests, for example, by working through math exercises and entering their answers.

[1617] 4. Receiving and incorporating feedback:

[1618] The user receives feedback from the server and incorporates it into their learning. They also receive messages and rewards to maintain motivation. For example, the user receives a message from the server saying "Good job!" and moves on to the next learning step.

[1619] In one example, a 12-year-old student can improve their math grades by donning a VR headset and being taught how to solve quadratic equations by a virtual teacher who resembles a specific character. The teacher explains easy-to-understand examples and provides real-time feedback immediately after the student solves the problem.

[1620] An example of a prompt for the generative AI model is as follows:

[1621] "Generate a 3D model of a virtual teacher resembling a specific character explaining to a 12-year-old student how to solve quadratic equations. The teacher should use a friendly voice and easy-to-understand language, providing step-by-step instructions that the student can understand. Explain examples and provide immediate feedback when the student solves."

[1622] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1623] Step 1:

[1624] The server collects initial data from the learner. When the user enters their name, age, grade, learning goals, and preferred learning method into the registration form on their device, this data is sent to the server. The server stores the received initial data in a database. The input data is the learner's basic information, and the output is the initial data stored in the database.

[1625] Step 2:

[1626] The server uses a generative AI model based on the collected initial data to generate an optimized learning curriculum for each learner. The initial data is input into the AI ​​model, and the data output as a learning curriculum includes the learning content, progress schedule, and evaluation method for each subject. This learning curriculum is created individually according to the learner's needs.

[1627] Step 3:

[1628] The server sends the generated learning curriculum to the learner's terminal. The input is the learning curriculum data generated on the server side, and the output is the learning curriculum data sent to the terminal. The terminal receives this data and stores it so that the learner can access it.

[1629] Step 4:

[1630] The server generates virtual teacher data based on the learner's preferences. For example, if a learner likes a particular character, it generates a 3D model and voice data of a virtual teacher that resembles that character. The input is the learner's preference data, and the output is the generated virtual teacher data.

[1631] Step 5:

[1632] The server sends the generated virtual instructor data to the terminal. The terminal receives this data and prepares to display the virtual instructor in a virtual reality environment. The input is the virtual instructor data from the server, and the output is a 3D model of the virtual instructor and audio data stored in the terminal.

[1633] Step 6:

[1634] The learner puts on the VR device and starts the lesson with the virtual instructor on the terminal. The terminal uses the virtual instructor data sent from the server to display the virtual instructor in a virtual reality environment. The input is the virtual instructor data stored on the terminal, and the output is the virtual instructor displayed on the VR device.

[1635] Step 7:

[1636] Learners follow the guidance of a virtual instructor and work on learning content based on the learning curriculum. The device records the learner's progress and collects test results and answer data for practice questions. The input is the learner's answer data, and the output is the learning progress data stored on the device.

[1637] Step 8:

[1638] The terminal sends the collected learning progress data to the server. The input is the learner's progress data, and the output is the learning progress data sent to the server. The server uses this data to monitor the learner's progress.

[1639] Step 9:

[1640] The server generates feedback based on the learning progress data. It uses a generative AI model to analyze the learner's progress and test results and create appropriate feedback messages. The input is the learning progress data, and the output is the feedback message.

[1641] Step 10:

[1642] The server sends the generated feedback message to the terminal. The terminal receives this message and displays it to the learner. The input is the server-side feedback message, and the output is the feedback message displayed on the terminal. For example, the message "Good job!" is displayed.

[1643] As described above, by these specific processing steps, a system can be realized that provides individually optimized learning guidance to learners.

[1644] 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.

[1645] This invention is a system that utilizes AI, VR technology, and an emotion engine to provide individually optimized learning guidance to learners. This system operates in cooperation with three parties: a server, a terminal, and a user.

[1646] Server processing explanation

[1647] 1. Data Collection and Initial Setup:

[1648] The server collects initial data from the learner, including name, age, grade, achievement test results, learning goals, and preferred learning methods.

[1649] Example: The server receives the data entered by the user in the registration form (e.g., name "Yamada Taro", age "12 years old").

[1650] 2. Generating an individually optimized curriculum:

[1651] The server uses artificial intelligence to generate an optimized learning curriculum for each learner, including the learning content for each subject, progress schedule, and evaluation method.

[1652] Example: A server-generated curriculum specifies weekly math practice problems and monthly practice tests.

[1653] 3. Virtual Instructor Setup:

[1654] The server generates data on a virtual teacher based on the learner's preferences, and this teacher appears in the VR environment with the appearance and speaking style of a specific character or person.

[1655] Example: When a learner selects a virtual teacher who resembles Doraemon, the server generates a 3D model and voice data that resembles Doraemon.

[1656] 4. Progress monitoring and feedback:

[1657] The server monitors learning progress in real time, adjusts the curriculum as needed, and provides feedback based on the learner's performance data.

[1658] Example: The server generates and sends a message saying "Well done!" based on the learner's test results (e.g., 90 points in mathematics).

[1659] 5. Emotion Recognition with Emotion Engine:

[1660] The server analyzes the learner's emotional data using an emotion engine to appropriately adjust instructional content and feedback. This engine recognizes emotions by analyzing the learner's facial expressions and voice.

[1661] Example: The server detects the learner's stress level from facial expression data and provides relaxation content.

[1662] Terminal processing explanation

[1663] 1. Data Entry:

[1664] The terminal accepts data input from the learner, including initial data and learning progress data.

[1665] Specific operation: The device displays a pop-up to start the academic ability test, and the user starts the test.

[1666] 2. View Virtual Instructor:

[1667] The device receives data from the server and displays the virtual instructor in a VR environment, providing interactive lessons.

[1668] Specific operation: Using a VR headset, a video is displayed in which a Doraemon-style virtual instructor explains the preparatory content.

[1669] 3. View and progress your learning:

[1670] The device displays learning content (text, videos, exercises) to the learner based on the learning curriculum.

[1671] Example: A device displays math exercises and the user answers them.

[1672] 4. Sending progress data:

[1673] The device sends learning progress and test results to the server, allowing the server to track progress in real time and provide appropriate feedback.

[1674] Example: The device sends the learner's test results (e.g., 90 points in mathematics) to the server.

[1675] 5. Emotional Data Collection and Transmission:

[1676] The device collects the learner's facial expressions and voice data and sends it to a server, where it is analyzed by an emotion engine.

[1677] Example: The device collects the learner's facial expression data (e.g., images captured from a camera) and voice data and sends them to a server.

[1678] User behavior description

[1679] 1. Enter the initial data:

[1680] Users enter their information into a registration form, including their name, age, grade level, learning goals, and preferred learning method.

[1681] Example: A user fills out a registration form with the name "Yamada Taro" and age "12 years old."

[1682] 2. Participating in a VR environment:

[1683] Users wear a VR device and participate in lessons taught by a virtual instructor. If they have any questions during the lesson, they can ask them using voice input or a dedicated interface.

[1684] Example: A user uses a VR headset to take a lesson from a Doraemon-style virtual instructor.

[1685] 3. Engage in learning content:

[1686] Users work through the learning content displayed on their device, solving problems and taking tests.

[1687] Example: A user works through a math exercise displayed on a terminal and enters the answers.

[1688] 4. Providing Emotion Data:

[1689] During the learning process, users provide emotional data through their facial expressions and the sounds they hear.

[1690] Example: When a user is learning in front of a camera and has a tired expression, the facial expression data is sent from the device to the server.

[1691] 5. Receiving and incorporating feedback:

[1692] Users receive feedback from the server and incorporate it into their learning. They also receive messages and rewards to keep them motivated.

[1693] Example: The user receives a "Good job!" message from the server and proceeds to the next learning step.

[1694] 6. Use of relaxation content:

[1695] The user utilizes relaxation content provided by the emotion engine.

[1696] Example: When a user experiences high stress levels, they listen to relaxation music sent from a server.

[1697] This system allows learners to continue studying in a self-optimized learning environment and effectively improve their academic ability. In addition, the introduction of an emotion engine allows for detailed guidance and support that responds to the learner's emotions.

[1698] The processing flow will be explained below.

[1699] Server processing explanation

[1700] Step 1:

[1701] The server receives the user registration information.

[1702] Specific operation: The user enters the name, age, and grade in the registration form and presses the submit button, which sends the entered data to the server and saves it in the database.

[1703] Step 2:

[1704] The server provides the user with a link to the achievement test.

[1705] Specific operation: The server automatically generates an email containing the URL of the academic achievement test and sends it to the user, or displays the link of the academic achievement test on the dashboard.

[1706] Step 3:

[1707] The server receives and stores the results of the academic achievement test.

[1708] Specific operation: When a user completes an academic ability test, the results are sent from the device to the server and stored in a database.

[1709] Step 4:

[1710] The server uses artificial intelligence to generate an individually optimized curriculum.

[1711] Specific operation: Analyze the received academic ability test results and initial data, and generate the learning content and progress schedule required for the user.

[1712] Step 5:

[1713] The server transmits the generated curriculum to the terminal.

[1714] Specific operation: Send data to the terminal so that the generated learning curriculum is displayed on the user's dashboard.

[1715] Step 6:

[1716] The server generates the data of the virtual instructor.

[1717] Specific operation: Generates a 3D model and audio data based on the user's preferences and stores it in a database.

[1718] Step 7:

[1719] The server transmits the generated virtual instructor data to the terminal.

[1720] Specific operation: The generated virtual instructor data is sent to the terminal so that it is displayed in the user's VR environment.

[1721] Step 8:

[1722] The server monitors the learning progress.

[1723] Specific operation: Receives user progress data (e.g., exercise completion status, test results) sent from the device in real time and stores it in a database.

[1724] Step 9:

[1725] The server uses an emotion engine to analyze the learner's emotion data and generate feedback.

[1726] Specific actions: Analyze the learner's facial expressions and voice data to assess their stress level and motivation.

[1727] Step 10:

[1728] The server adjusts the instruction content and feedback based on the user's emotional data and updates the curriculum as needed.

[1729] Specific behavior: When stress levels are high, a message is generated recommending a break. When motivation levels are low, a message of encouragement is generated.

[1730] Step 11:

[1731] The server generates feedback and sends it to the device.

[1732] Specific behavior: Send data to the device to display a feedback message on the user's dashboard.

[1733] Terminal processing explanation

[1734] Step 1:

[1735] The terminal displays an initial data entry form to the user.

[1736] What it does: Displays a registration form on a web page or app, allowing users to enter their name, age, grade, etc.

[1737] Step 2:

[1738] The terminal transmits the user's input data to the server.

[1739] Specific operation: When the user presses the submit button to send the data entered in the registration form to the server, the data is sent to the backend.

[1740] Step 3:

[1741] The device displays the academic achievement test link and allows the user to access it.

[1742] Specific behavior: A link to the academic achievement test is displayed on the dashboard or in an email, and the user clicks it to begin the test.

[1743] Step 4:

[1744] The terminal transmits the user's academic achievement test results to the server.

[1745] What it does: The user completes the test and the results are automatically sent to the server.

[1746] Step 5:

[1747] The terminal displays the curriculum received from the server.

[1748] Specific operation: The curriculum data received from the server is displayed on the dashboard so that the user can check it.

[1749] Step 6:

[1750] The device displays the virtual instructor data received from the server in a VR environment.

[1751] Specific operation: Using a VR device, the 3D model and audio data received from the server are rendered to provide interactive lessons.

[1752] Step 7:

[1753] The device displays the learning content and the user works on it.

[1754] Specific operation: Learning content such as text, videos, and exercises are displayed to the user, and the user works on it.

[1755] Step 8:

[1756] The terminal transmits learning progress data to the server.

[1757] Specific operation: The results of the user's work on the learning content are recorded in real time and periodically sent to the server.

[1758] Step 9:

[1759] The device collects the user's facial expressions and voice data and sends it to the server.

[1760] Specific operation: The device uses a camera and microphone to collect facial expression and voice data and sends it to a server.

[1761] User behavior description

[1762] Step 1:

[1763] The user enters the initial data.

[1764] Specific actions: Enter your name, age, grade, learning goals, and preferred learning method in the registration form and press the submit button.

[1765] Step 2:

[1766] The user accesses the test link and begins the test.

[1767] Specific actions: Click on the academic achievement test link displayed in email or on the dashboard to begin the test.

[1768] Step 3:

[1769] A user completes a quiz.

[1770] Specific actions: Answer the test questions and enter the results into the terminal.

[1771] Step 4:

[1772] Users wear VR devices and participate in classes taught by virtual instructors.

[1773] Specific actions: Put on a VR headset and watch a lesson from a virtual instructor.

[1774] Step 5:

[1775] The user engages with the learning content.

[1776] Specific actions: Work through the text, videos, and practice problems displayed on the device.

[1777] Step 6:

[1778] The user records facial expressions and voice to provide emotional data.

[1779] Specific operation: During learning, the device uses a camera and microphone to record facial expressions and voice, and then sends the data from the device to the server.

[1780] Step 7:

[1781] The user receives feedback and moves on to the next learning step.

[1782] Specific operation: Receive the feedback message sent from the server and proceed to the next learning step.

[1783] Step 8:

[1784] When a user feels stressed, they can use relaxation content.

[1785] Specific operation: Reduce stress by listening to relaxation music and watching videos sent from the server.

[1786] In this way, the server, device, and user work together to enable individually optimized learning instruction that takes emotions into consideration. This system allows learners to continue studying and aim for effective improvement of their academic ability.

[1787] Example 2

[1788] 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."

[1789] In today's educational environment, there is a demand for individually optimized learning guidance tailored to the needs of each learner. However, conventional systems have difficulty providing learning guidance and feedback that fully reflects the learner's progress and emotional state. In particular, there is a lack of emotional support, making it difficult to address learners' stress and loss of motivation.

[1790] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1791] In this invention, the server includes means for collecting initial data from a learner, means for generating a learning curriculum optimized for each learner using artificial intelligence, means for transmitting the learning curriculum to the learner's terminal, means for generating virtual instructor data, means for transmitting the generated virtual instructor to the learner's terminal, means for monitoring learning progress, means for generating feedback based on the learning progress data, means for analyzing the learner's emotional data using an emotion engine, and means for adjusting instruction content and feedback based on the analysis results. This makes it possible to grasp the learner's learning progress and emotional state in real time and provide individually optimized and effective learning instruction.

[1792] "Initial learner data" is information collected at the beginning of a study, such as the learner's name, age, grade, achievement test results, learning goals, and preferred learning methods.

[1793] "Artificial intelligence" is a computer technology that includes machine learning and data analysis techniques and is used to create learning curricula that are optimized for each learner.

[1794] A "learning curriculum" is an educational plan that includes learning content, progress schedule, and evaluation methods that are optimized for each learner.

[1795] A "virtual teacher" is a teacher character that appears in a digital environment (especially a VR environment) and has the appearance and speaking style of a specific character or person.

[1796] "Learning progress" refers to progress data and results as a learner progresses through the learning curriculum.

[1797] "Feedback" refers to comments and advice for guidance and improvement that are generated based on the learner's learning progress.

[1798] The "emotion engine" is a technology that analyzes a learner's facial expressions and voice data to recognize their emotional state.

[1799] "Emotion data" is data that indicates the emotional state of a learner, recognized based on the learner's facial expressions and voice.

[1800] "Analysis results" refers to the conclusions or conditions obtained after analyzing collected data.

[1801] "Instructional content" refers to the specific learning or educational content provided to learners.

[1802] This invention is a system that utilizes artificial intelligence (AI), virtual reality (VR) technology, and an emotion engine to provide individually optimized learning guidance to learners. This system operates in cooperation with a server, a terminal, and a user.

[1803] Server processing explanation

[1804] The server first collects initial data from the learner, including the learner's name, age, grade, academic achievement test results, learning goals, and preferred learning methods. For example, if a learner enters the name "Yamada Taro" and age "12 years old," the data is sent to the server and stored in a database.

[1805] Based on the initial data, the server uses artificial intelligence (e.g., TensorFlow or PyTorch) to generate a learning curriculum optimized for each learner. The curriculum includes the learning content, progress schedule, and evaluation method for each subject. For example, the curriculum includes weekly math practice problems and monthly mock tests.

[1806] Next, the server generates data on a virtual tutor based on the learner's preferences. This tutor will have the appearance and speaking style of a specific character or person and will be displayed in the VR environment. For example, if a learner selects a virtual tutor resembling Doraemon, the server will generate a 3D model and voice data that resembles Doraemon.

[1807] The server also monitors the learner's progress in real time, adjusts the curriculum as needed, and generates feedback based on the progress data. For example, if a learner gets 90 points on a test, the server generates a message saying "Well done!" and sends it to the learner's device.

[1808] The emotion engine is used to analyze the learner's facial expression and voice data to recognize their emotional state. This allows the server to adjust instruction content and feedback based on the emotional data. For example, if the server detects a high stress level from the learner's facial expression data, it can provide relaxation content (e.g., relaxation music).

[1809] Terminal processing explanation

[1810] The device first accepts initial data from the learner, including the results of an achievement test and data on the learner's progress. As a specific example, the device displays a pop-up to start the achievement test, and the user starts the test.

[1811] The virtual instructor data received from the server is displayed in a VR environment. By using a VR headset, a video of a Doraemon-style virtual instructor explaining the content of the preparation is displayed.

[1812] The device displays learning content such as textbooks, videos, and exercises to the learner based on the learning curriculum. For example, the device may display mathematics exercises for the user to answer.

[1813] The device sends learning progress and test results to the server, allowing the server to understand progress in real time and provide appropriate feedback. For example, the device sends the learner's test results (e.g., 90 points in mathematics) to the server.

[1814] The device also collects the learner's facial expression and voice data and transmits it to the server. For example, the device can collect the learner's facial expression data (e.g., images captured by a camera) and voice data and transmit them to the server.

[1815] User behavior description

[1816] A user first enters their information into a registration form, including their name, age, grade, learning goals, and preferred learning method. For example, a user enters their name "Yamada Taro" and age "12 years old" into the registration form.

[1817] Next, the user puts on the VR device and participates in a lesson taught by a virtual instructor. If the user has a question during the lesson, they can ask it using voice input or a dedicated interface. For example, a user can take a lesson from a Doraemon-style virtual instructor using a VR headset.

[1818] The user works on the learning content displayed on the terminal, solves problems, takes tests, etc. For example, the user works on math exercises displayed on the terminal and inputs the answers.

[1819] During learning, users provide emotional data through their facial expressions and voice. For example, if a user looks tired while learning in front of the camera, that facial data is sent from the device to the server.

[1820] The user receives feedback from the server and reflects it in their learning. For example, the user receives a message saying "Good job!" and proceeds to the next learning step.

[1821] Users also use relaxation content provided by the emotion engine. For example, when their stress level is high, they listen to relaxation music sent from the server.

[1822] This system allows learners to continue studying in a self-optimized learning environment and effectively improve their academic ability. In addition, the introduction of an emotion engine allows for detailed guidance and support that responds to the learner's emotions.

[1823] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1824] Step 1:

[1825] Data collection and initial setup

[1826] Input: The initial data that the user enters in the registration form (name, age, grade, academic test results, learning goals, preferred learning methods)

[1827] How it works: The server receives an HTTP POST request and stores the initial data in a database.

[1828] Output: Initial data stored in the database

[1829] Example: A user enters "Yamada Taro" and "12 years old", and the server saves this in the database.

[1830] Step 2:

[1831] Generation of individually optimized curriculum

[1832] Input: Initial data of the student obtained from the server database

[1833] How it works: The server runs an AI model (e.g., TensorFlow, PyTorch) to generate an optimized learning curriculum for each learner. The AI ​​model receives learner data as input and calculates the learning content, progress schedule, and assessment method for each subject.

[1834] Output: Generated individualized optimized curriculum

[1835] Example: A server generates a curriculum that includes weekly math practice questions and monthly practice tests.

[1836] Step 3:

[1837] Virtual Instructor Setup

[1838] Input: Information based on the user's preferences (e.g., favorite character)

[1839] Operation: The server generates corresponding 3D model data and audio data based on the preference information. These data are used in the VR environment as a virtual teacher.

[1840] Output: Generated virtual instructor data (3D model and audio data)

[1841] Example: A learner selects a virtual teacher who looks like Doraemon, and the server generates a 3D model of Doraemon and audio data.

[1842] Step 4:

[1843] Sending learning curriculum and instructor data

[1844] Input: Generated learning curriculum and virtual instructor data

[1845] Operation: The server sends these data to the user's terminal.

[1846] Output: The learning curriculum and virtual instructor data are sent to the terminal.

[1847] Example: The server sends the created learning curriculum and Doraemon-style instructor data to the user's device.

[1848] Step 5:

[1849] Display in VR environment

[1850] Input: Virtual instructor data sent from the server

[1851] How it works: The device displays the received virtual instructor data in a VR environment. Specifically, it uses Unity or Unreal Engine to render a 3D model and play audio data.

[1852] Output: VR environment with virtual instructor displayed

[1853] Example: A Doraemon-style virtual teacher begins a lesson on a VR headset.

[1854] Step 6:

[1855] View and progress your learning

[1856] Input: Learning curriculum received from the server

[1857] How it works: The device displays curriculum-based text, videos, and exercises to the learner, and also provides an interface where the user can enter their answers.

[1858] Output: What the user sees

[1859] Example: A device displays math exercises and the user answers them.

[1860] Step 7:

[1861] Sending progress data

[1862] Input: User-entered learning progress and test results

[1863] How it works: The device sends this data to the server using an HTTP POST request.

[1864] Output: Progress data sent to the server

[1865] Example: The device sends the learner's test results (e.g., 90 points in mathematics) to the server.

[1866] Step 8:

[1867] Collecting and transmitting emotional data

[1868] Input: User's facial expressions and voice data

[1869] How it works: The device uses its camera and microphone to collect this data and sends it to a server.

[1870] Output: Emotion data sent to the server

[1871] Example: The device sends the learner's facial expression data and voice data to the server.

[1872] Step 9:

[1873] Emotional Data Analysis

[1874] Input: Emotion data sent from the device

[1875] How it works: The server uses the emotion engine to analyze the emotion data. The analysis results indicate the learner's emotional state.

[1876] Output: Parsed emotion data

[1877] Example: The server analyzes the learner's stress level from facial expression data.

[1878] Step 10:

[1879] Generate feedback

[1880] Input: Learning progress data and emotion data analysis results

[1881] Operation: The server generates feedback based on this data and adjusts the curriculum. The generated feedback is sent to the device.

[1882] Output: Generated feedback and adjusted curriculum

[1883] Example: The server generates a message saying "Good job!" and sends it to the device. Also, if the learner shows signs of fatigue, the curriculum is adjusted to add breaks.

[1884] (Application example 2)

[1885] 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."

[1886] In recent years, there has been a demand for providing educational content that is optimized for each individual learner. However, conventional systems often fail to adequately grasp learners' progress or analyze their emotional data, resulting in a uniform curriculum and teaching methods, resulting in low learning effectiveness. Furthermore, a lack of appropriate feedback and content to alleviate stress during learning has also led to a decline in learners' motivation.

[1887] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting initial data from the learner, means for generating a learning curriculum optimized for each learner using artificial intelligence, means for transmitting the learning curriculum to the learner's terminal, means for generating virtual instructor data, means for transmitting the generated virtual instructor to the learner's terminal, means for monitoring the learning progress, means for generating feedback based on the learning progress data, means for providing additional learning content based on the feedback, means for providing lessons by the virtual instructor in a VR environment, means for collecting and analyzing emotional data, and means for providing relaxation content based on the learner's emotional data. This makes it possible to provide individually optimized learning guidance and feedback for each learner, as well as content tailored to their emotions.

[1888] "Student" refers to an individual receiving education or training, and in particular, to a person who uses the System to carry out learning activities.

[1889] "Initial data" refers to basic information about the learner, including name, age, grade, achievement test results, learning goals, preferred learning methods, etc.

[1890] "Artificial intelligence" is a technology that gives intelligence to computer systems, and in this system it is a technology used to optimize learning curricula, etc.

[1891] "Learning curriculum" refers to the educational content and learning plan provided to learners, including specific subject content, progress schedule, and evaluation methods.

[1892] "Device" refers to the computer device used by the learner, including smartphones, tablets, and PCs.

[1893] A "virtual instructor" refers to a virtual educator generated by a computer program who provides educational content to learners.

[1894] "Means for generating data" refers to the programs or algorithms used to create or generate the required data.

[1895] "Means for transmitting data" refers to the technology for transmitting and receiving the generated data between terminals and servers, including network communication technology.

[1896] "Study progress" refers to information that indicates how far a learner has progressed in the learning content, and includes test results, progress status, and the like.

[1897] "Feedback" refers to reactions and advice provided based on a learner's learning status, and is used to improve learning outcomes.

[1898] "Additional learning content" refers to supplementary educational content provided in addition to an existing learning curriculum, including content to fill learning gaps.

[1899] A "VR environment" refers to an environment in which a virtual learning space is created and provided to learners using virtual reality technology.

[1900] "Emotional data" refers to information that indicates the learner's emotional state, and is obtained through facial expressions, voice data, and other biometric data.

[1901] "Relaxation content" refers to content provided to reduce learners' stress and promote relaxation, and includes music, videos, guidance, etc.

[1902] This invention provides a system that provides individually optimized learning guidance to learners. This invention utilizes AI, VR technology, and an emotion engine, and operates in cooperation with a server, a terminal, and a user.

[1903] Server Processing

[1904] 1. Data Collection and Initial Setup:

[1905] The server collects initial data from the learner, including name, age, grade, achievement test results, learning goals, and preferred learning methods. For example, a learner enters his name "Yamada Taro" and age "12 years old" into a registration form.

[1906] 2. Generating an individually optimized curriculum:

[1907] The server uses artificial intelligence to generate a learning curriculum optimized for each learner. This curriculum includes the learning content, progress schedule, and evaluation method for each subject. For example, the server-generated curriculum specifies weekly math practice problems and monthly mock tests.

[1908] 3. Virtual Instructor Setup:

[1909] The server generates data on a virtual teacher based on the learner's preferences. This teacher will have the appearance and speaking style of a specific character or person and will be displayed in the VR environment. For example, if a learner selects a virtual teacher who resembles a virtual character, the server generates a 3D model and voice data that resembles that character.

[1910] 4. Progress monitoring and feedback:

[1911] The server monitors the learner's progress in real time and adjusts the curriculum as needed. It also provides feedback based on the learner's performance data. For example, the server generates and sends a message saying "Well done!" based on the learner's test results (e.g., 90 points in mathematics).

[1912] 5. Emotion Recognition with Emotion Engine:

[1913] The server uses an emotion engine to analyze the learner's emotional data and adjust the instruction content and feedback appropriately. This engine recognizes emotions by analyzing the learner's facial expressions and voice. As a specific example, the server detects the learner's stress level from their facial expression data and provides relaxation content.

[1914] Terminal handling

[1915] 1. Data Entry:

[1916] The device accepts data input from the learner, including initial data and learning progress data. Specifically, the device displays a popup to start the academic ability test, and the user begins the test.

[1917] 2. View Virtual Instructor:

[1918] The device receives data from the server and displays it in a VR environment, providing an interactive lesson. Specifically, a VR headset is used to display a video of the virtual instructor explaining the content of the lesson.

[1919] 3. View and progress your learning:

[1920] The device displays learning content (text, videos, exercises) to the learner based on the learning curriculum. For example, the device displays mathematics exercises, and the user answers them.

[1921] 4. Sending progress data:

[1922] The device sends learning progress and test results to the server, allowing the server to understand progress in real time and provide appropriate feedback. For example, the device sends the learner's test results (e.g., 90 points in mathematics) to the server.

[1923] 5. Emotional Data Collection and Transmission:

[1924] The device collects the learner's facial expression and voice data and sends it to the server. This data is analyzed by the emotion engine. For example, the device collects the learner's facial expression data (e.g., images captured from a camera) and voice data and sends it to the server.

[1925] User behavior

[1926] 1. Enter the initial data:

[1927] A user enters their information into a registration form, including their name, age, grade, learning goals, preferred learning method, etc. For example, a user enters their name "Yamada Taro" and age "12 years old" into a registration form.

[1928] 2. Participating in a VR environment:

[1929] Users wear a VR device and participate in lessons taught by a virtual instructor. If they have questions during the lesson, they can ask using voice input or a dedicated interface. For example, a user can take a lesson taught by a virtual instructor using a VR headset.

[1930] 3. Engage in learning content:

[1931] The user works on the learning content displayed on the device, solves problems, takes tests, etc. For example, the user works on a math exercise displayed on the device and enters the answers.

[1932] 4. Providing Emotion Data:

[1933] During the learning process, users provide emotional data through their facial expressions and voice. For example, if a user looks tired while learning in front of the camera, that facial expression data is sent from the device to the server.

[1934] 5. Receiving and incorporating feedback:

[1935] The user receives feedback from the server and reflects it in their learning. They also receive messages and rewards to maintain their motivation. For example, the user receives a message from the server saying "Good job!" and moves on to the next learning step.

[1936] 6. Use of relaxation content:

[1937] The user uses relaxation content provided by the emotion engine. For example, when the user is under high stress, they listen to relaxation music sent from the server.

[1938] Prompt Sentence Examples

[1939] Generate an appropriate learning curriculum based on the user: {Name: "Yamada Taro", Age: 12, Grade: "1st year of junior high school", Academic achievement test results: {Math: 80, English: 75}, Learning goal: "Math reinforcement", Preferred learning method: "Visual"}.

[1940] In this way, the present invention realizes individually optimized learning guidance and feedback for each learner, as well as the provision of content according to their emotions.

[1941] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1942] Step 1:

[1943] The server collects initial data from the learner, such as name, age, grade, achievement test results, learning goals, preferred learning methods, etc., entered by the user in the registration form. Based on the input data, the server creates a learner profile.

[1944] Step 2:

[1945] The server uses artificial intelligence to generate an optimized learning curriculum for each learner. To do this, the learner's initial data is input, and the AI ​​model processes and analyzes the data to output an individually optimized curriculum (educational content, progress schedule, evaluation method, etc.). Specifically, the curriculum is generated using OpenAI's AI model.

[1946] Step 3:

[1947] The server sends the generated optimized curriculum to the learner's device. The curriculum data is input and sent to the device via the network, where the curriculum is displayed. Specifically, data is sent using an API.

[1948] Step 4:

[1949] The server generates the virtual teacher's data and customizes it based on the learner's preferences. It uses the learner's initial data as input to generate the virtual teacher's appearance and speaking style. Specifically, it uses an AI model to generate the virtual teacher's character data.

[1950] Step 5:

[1951] The server sends the generated virtual instructor data to the learner's device. The virtual instructor data is used as input and sent to the device via the network, where the virtual instructor is displayed on the device. Specifically, data is sent using an API.

[1952] Step 6:

[1953] The device receives the virtual instructor's data and displays it in the VR environment. Based on the received data, an interactive lesson is provided using a VR headset. For example, a video of a Doraemon-style virtual instructor explaining the content of the lesson is displayed.

[1954] Step 7:

[1955] The device sends the learner's progress and academic test results to the server. By collecting the learner's progress data and sending it to the server, real-time progress management is performed. As a concrete example, a math test result of 90 points is sent to the server.

[1956] Step 8:

[1957] The server monitors the learning progress and generates feedback. It analyzes the learning progress data as input, generates appropriate feedback (e.g., "Good job!"), and sends it to the learner's device.

[1958] Step 9:

[1959] The device collects the learner's facial expressions and voice data and sends it to the server. Emotional data is collected using a camera and microphone and sent to the server. As a specific example, image data of a tired facial expression is sent to the server.

[1960] Step 10:

[1961] The server uses an emotion engine to analyze the learner's emotional data and provide appropriate content based on their emotions.The server analyzes the emotional data as input, generates relaxation content (e.g., relaxation music), and sends it to the device.

[1962] 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.

[1963] 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.

[1964] 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.

[1965] [Fourth embodiment]

[1966] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1967] 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.

[1968] 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).

[1969] 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.

[1970] 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.

[1971] 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).

[1972] 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.

[1973] 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.

[1974] 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.

[1975] 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.

[1976] 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.

[1977] 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.

[1978] 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."

[1979] This invention is a system that utilizes AI and VR technology to provide individually optimized learning guidance to learners. This system operates in cooperation with three parties: a server, a terminal, and a user.

[1980] Server processing explanation

[1981] 1. Data Collection and Initial Setup:

[1982] The server collects initial data from the learner, including name, age, grade, achievement test results, learning goals, and preferred learning methods.

[1983] Example: The server receives the data entered by the user in the registration form (e.g., name "Yamada Taro", age "12 years old").

[1984] 2. Generating an individually optimized curriculum:

[1985] The server uses artificial intelligence to generate an optimized learning curriculum for each learner, including the learning content for each subject, progress schedule, and evaluation method.

[1986] Example: A server-generated curriculum specifies weekly math practice problems and monthly practice tests.

[1987] 3. Virtual Instructor Setup:

[1988] The server generates data on a virtual teacher based on the learner's preferences, and this teacher appears in the VR environment with the appearance and speaking style of a specific character or person.

[1989] Example: When a learner selects a virtual teacher who resembles Doraemon, the server generates a 3D model and voice data that resembles Doraemon.

[1990] 4. Progress monitoring and feedback:

[1991] The server monitors learning progress in real time, adjusts the curriculum as needed, and provides feedback based on the learner's performance data.

[1992] Example: The server generates and sends a message saying "Well done!" based on the learner's test results (e.g., 90 points in mathematics).

[1993] Terminal processing explanation

[1994] 1. Data Entry:

[1995] The terminal accepts data input from the learner, including initial data and learning progress data.

[1996] Example: The device displays a popup to start an academic ability test, and the user starts the test.

[1997] 2. View Virtual Instructor:

[1998] The device receives data from the server and displays the virtual instructor in a VR environment, providing interactive lessons.

[1999] Example: Using a VR headset, a video is displayed in which a virtual instructor dressed like Doraemon explains the content of the preparatory lesson.

[2000] 3. View and progress your learning:

[2001] The device displays learning content (text, videos, exercises) to the learner based on the learning curriculum.

[2002] Example: A device displays math exercises and the user answers them.

[2003] 4. Sending progress data:

[2004] The device sends learning progress and test results to the server, allowing the server to track progress in real time and provide appropriate feedback.

[2005] Example: The device sends the learner's test results (e.g., 90 points in mathematics) to the server.

[2006] User behavior description

[2007] 1. Enter the initial data:

[2008] Users enter their information into a registration form, including their name, age, grade level, learning goals, and preferred learning method.

[2009] Example: A user fills out a registration form with the name "Yamada Taro" and age "12 years old."

[2010] 2. Participating in a VR environment:

[2011] Users wear a VR device and participate in lessons taught by a virtual instructor. If they have any questions during the lesson, they can ask them using voice input or a dedicated interface.

[2012] Example: A user uses a VR headset to take a lesson from a Doraemon-style virtual instructor.

[2013] 3. Engage in learning content:

[2014] Users work through the learning content displayed on their device, solving problems and taking tests.

[2015] Example: A user works through a math exercise displayed on a terminal and enters the answers.

[2016] 4. Receiving and incorporating feedback:

[2017] Users receive feedback from the server and incorporate it into their learning. They also receive messages and rewards to keep them motivated.

[2018] Example: The user receives a "Good job!" message from the server and proceeds to the next learning step.

[2019] This system allows learners to continue studying in a learning environment that is optimized for them, and aims to effectively improve their academic ability.

[2020] The processing flow will be explained below.

[2021] Server processing explanation

[2022] Step 1:

[2023] The server receives the user registration information.

[2024] Specific operation: The user enters the name, age, and grade in the registration form and presses the submit button, which sends the entered data to the server and saves it in the database.

[2025] Step 2:

[2026] The server provides the user with a link to the achievement test.

[2027] Specific operation: The server automatically generates an email containing the URL of the academic ability test and sends it to the user, or displays the link of the academic ability test on the dashboard.

[2028] Step 3:

[2029] The server receives and stores the results of the academic achievement test.

[2030] Specific operation: When a user completes an academic ability test, the results are sent from the device to the server and stored in a database.

[2031] Step 4:

[2032] The server uses artificial intelligence to generate an individually optimized curriculum.

[2033] Specific operation: Analyze the received academic ability test results and initial data, and generate the learning content and progress schedule required for the user.

[2034] Step 5:

[2035] The server transmits the generated curriculum to the terminal.

[2036] Specific operation: Send data to the terminal so that the generated learning curriculum is displayed on the user's dashboard.

[2037] Step 6:

[2038] The server generates the data of the virtual instructor.

[2039] Specific operation: Generates a 3D model and audio data based on the user's preferences and stores it in a database.

[2040] Step 7:

[2041] The server transmits the generated virtual instructor data to the terminal.

[2042] Specific operation: The generated virtual instructor data is sent to the terminal so that it is displayed in the user's VR environment.

[2043] Step 8:

[2044] The server monitors the learning progress.

[2045] Specific operation: Receives user progress data (e.g., exercise completion status, test results) sent from the device in real time and stores it in a database.

[2046] Step 9:

[2047] The server generates feedback and adjusts the curriculum as needed.

[2048] Specific behavior: Analyzes progress data, generates feedback messages with praise and suggestions for improvement, and sends them to the device, updating the learning curriculum as needed.

[2049] Terminal processing explanation

[2050] Step 1:

[2051] The terminal displays an initial data entry form to the user.

[2052] What it does: Displays a registration form on a web page or app, allowing users to enter their name, age, grade, etc.

[2053] Step 2:

[2054] The terminal transmits the user's input data to the server.

[2055] Specific operation: When the user presses the submit button to send the data entered in the registration form to the server, the data is sent to the backend.

[2056] Step 3:

[2057] The device displays the academic achievement test link and allows the user to access it.

[2058] Specific behavior: A link to the academic achievement test is displayed on the dashboard or in an email, and the user clicks it to begin the test.

[2059] Step 4:

[2060] The terminal inputs the user's academic achievement test results and sends them to the server.

[2061] What it does: The user completes the test and the results are automatically sent to the server.

[2062] Step 5:

[2063] The terminal displays the curriculum received from the server.

[2064] Specific operation: The curriculum data received from the server is displayed on the dashboard so that the user can check it.

[2065] Step 6:

[2066] The device displays the virtual instructor data received from the server in a VR environment.

[2067] Specific operation: Using a VR device, the 3D model and audio data received from the server are rendered to provide interactive lessons.

[2068] Step 7:

[2069] The device displays the learning content and the user works on it.

[2070] Specific operation: Learning content such as text, videos, and exercises are displayed to the user, and the user works on it.

[2071] Step 8:

[2072] The terminal transmits learning progress data to the server.

[2073] Specific operation: The results of the user's work on the learning content are recorded in real time and periodically sent to the server.

[2074] User behavior description

[2075] Step 1:

[2076] The user enters the initial data.

[2077] Specific actions: Enter your name, age, grade, learning goals, and preferred learning method in the registration form and press the submit button.

[2078] Step 2:

[2079] The user accesses the test link and begins the test.

[2080] Specific actions: Click on the academic achievement test link displayed in email or on the dashboard to begin the test.

[2081] Step 3:

[2082] A user completes a quiz.

[2083] Specific actions: Answer the test questions and enter the results into the terminal.

[2084] Step 4:

[2085] Users wear VR devices and participate in classes taught by virtual instructors.

[2086] Specific actions: Put on a VR headset and watch a lesson from a virtual instructor.

[2087] Step 5:

[2088] The user engages with the learning content.

[2089] Specific actions: Work through the text, videos, and practice problems displayed on the device.

[2090] Step 6:

[2091] The user receives feedback and moves on to the next learning step.

[2092] Specific behavior: Receive the feedback message sent from the server and work on the next learning content.

[2093] In this way, the server, terminal, and user work together to provide effective learning guidance.

[2094] Example 1

[2095] 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."

[2096] In recent years, there has been a demand for a learning environment that is optimized for each learner's academic ability and learning style, but conventional systems have difficulty fully meeting this demand. In particular, they lack the functionality to integrate multiple elements, such as generating individually optimized learning curricula, providing virtual instructors that match the learner's preferences, and monitoring learning progress in real time and providing feedback.

[2097] 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.

[2098] In this invention, the server includes means for inputting personal information from the learner, means for generating an education plan optimized for each learner using artificial intelligence, means for transmitting the education plan to the learner's device, means for generating virtual instructor data, means for transmitting the generated virtual instructor to the learner's device, means for displaying the virtual instructor in a virtual reality environment, means for monitoring learning progress in real time, and means for generating and transmitting feedback based on the learning progress data. This makes it possible to provide an individually optimized learning curriculum, effective learning support by a virtual instructor that suits the learner's preferences, and real-time understanding of progress and appropriate feedback.

[2099] "Means for learner input of personal information" refers to an interface designed to allow learners to input personal information such as their name, age, grade, and learning goals.

[2100] "Means for generating educational plans optimized for each learner using artificial intelligence" refers to algorithms or software that take a learner's personal information and learning data as input and automatically generate appropriate learning content and schedules.

[2101] The "means for transmitting the educational plan to the learner's device" refers to a system including communication means and protocols for transferring the generated educational plan to the learner's terminal.

[2102] "Means for generating virtual instructor data" refers to software or tools for creating data that resembles the appearance and speaking style of a specific character or person based on learner preferences.

[2103] The "means for transmitting the generated virtual instructor to the learner's device" refers to a system including communication means and protocols for transmitting data of the generated virtual instructor to the learner's terminal.

[2104] The "means for displaying the virtual instructor in a virtual reality environment" refers to a device or software that displays the virtual instructor in a virtual reality environment and allows learners to take lessons interactively.

[2105] "Means for monitoring learning progress in real time" refers to a system that collects, records, and analyzes information in real time, such as the learner's current stage and how well they have completed tasks.

[2106] The "means for generating and transmitting feedback based on the learning progress data" refers to an algorithm or system that automatically generates appropriate feedback (e.g., words of encouragement, suggestions for correction, etc.) based on the collected learning progress data and transmits it to the learner's device.

[2107] This invention is a system that utilizes AI and VR technology to provide individually optimized learning guidance to learners. This system operates in cooperation with three parties: a server, a terminal, and a user.

[2108] Server processing explanation

[2109] The server collects initial data:

[2110] To collect the initial data, the server receives the user's name, age, grade, academic test results, learning goals, and preferred learning methods entered through the terminal. This data is sent via HTTP protocol and in JSON format to the server. The server then stores this data using a database management system (e.g., MySQL).

[2111] Generate a personalized optimization curriculum:

[2112] The server sends prompts to a generative AI model (e.g., OpenAI GPT-4) based on the collected initial data to generate an educational plan optimized for each individual learner. An example of a prompt is, "Please create the optimal learning curriculum based on Taro Yamada's academic ability data." The server receives the generated curriculum data and stores it in a database.

[2113] Generate the virtual instructor data:

[2114] The server generates virtual teacher data based on the learner's preferences. Specifically, it creates the character's appearance using 3D modeling software (e.g., Blender) and generates voice data using a voice generation tool (e.g., Google Text-to-Speech). An example of a prompt is "Please generate a virtual teacher in the style of Doraemon."

[2115] Generate and send feedback:

[2116] Learning progress is monitored in real time, and the server generates feedback based on the performance data, for example, a message such as "You got 90 points on the math test! Well done!" and sends it to the device.

[2117] Terminal processing explanation

[2118] Accept user data input:

[2119] The terminal accepts data input from the user, specifically providing a registration form where the user enters their name, age, etc., and transmits the collected data to the server.

[2120] View Virtual Instructors:

[2121] The device receives data from the server and displays it in a VR environment, allowing users to enjoy interactive lessons with virtual instructors using VR headsets such as Oculus Quest and HTC Vive.

[2122] View learning content:

[2123] The device displays learning content (text, videos, exercises) based on the learning curriculum, and users solve problems and watch videos through the device.

[2124] Send the learning progress to the server:

[2125] The device records the questions and test results the user has answered and sends them to a server, which receives them in real time and monitors the user's progress.

[2126] User behavior description

[2127] Enter the initial data:

[2128] The user enters their information into the registration form, for example, their name "Yamada Taro" and age "12 years old" into the terminal.

[2129] Participating in a VR environment:

[2130] Users wear VR devices and participate in lessons taught by virtual instructors. For example, users can take lessons from Doraemon-style virtual instructors.

[2131] Engage in learning content:

[2132] The user engages in learning content displayed on the device, for example, answering math exercises.

[2133] Receiving and implementing feedback:

[2134] The user receives feedback from the server and reflects it in their learning, for example, receiving a message like "Good job!" and proceeding to the next learning step.

[2135] The system provides an effective learning environment by combining an individually optimized learning curriculum, virtual instructors tailored to the user's preferences, and real-time monitoring and feedback.

[2136] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2137] Step 1: Data collection

[2138] ---

[2139] server:

[2140] The server collects personal information entered by the user on the device, including name, age, grade, achievement test results, learning goals, and preferred learning methods.

[2141] Input: Personal information entered by the user into the device.

[2142] Data processing: The server receives the data using the HTTP protocol and parses it in JSON format.

[2143] Output: Save the parsed data in a database management system (e.g., MySQL).

[2144] Device:

[2145] The terminal displays an input form to the user and prompts the user to input the required data.

[2146] Input: Personal information entered by the user.

[2147] Data calculation: Convert the input data into JSON format and send it to the server.

[2148] Output: User data sent to the server.

[2149] User:

[2150] The user enters his / her information into the input form displayed on the terminal.

[2151] Input: Name, age, grade, achievement test results, learning goals, preferred learning method.

[2152] Output: Sends data entered into the terminal to the server.

[2153] Step 2: Generate an individually optimized curriculum

[2154] ---

[2155] server:

[2156] The server sends a prompt to the generative AI model (e.g., OpenAI GPT-4) based on the collected initial data.

[2157] Example prompt: "Create the optimal learning curriculum based on Yamada Taro's academic achievement data."

[2158] Input: Initial user data read from the database, prompt statement.

[2159] Data calculation: Send a prompt to the generative AI model and generate an optimized curriculum in response.

[2160] Output: Save the generated curriculum data in a database.

[2161] Device:

[2162] There is no special processing.

[2163] User:

[2164] There is no special processing.

[2165] Step 3: Generate virtual instructor data

[2166] ---

[2167] server:

[2168] The server generates virtual instructor data based on the learner's preferences, creates the character's appearance using 3D modeling software (e.g., Blender), and generates voice data using a voice generation tool (e.g., Google Text-to-Speech).

[2169] Example prompt: "Create a Doraemon-style virtual teacher."

[2170] Input: User preference data, prompt text.

[2171] Data calculation: Using 3D modeling software and voice generation tools, a model and voice of the virtual teacher are generated.

[2172] Output: Save the generated virtual instructor data in a database.

[2173] Device:

[2174] There is no special processing.

[2175] User:

[2176] The user selects virtual instructor preferences at the terminal.

[2177] Step 4: Deliver learning content

[2178] ---

[2179] server:

[2180] The server prepares learning content (text, videos, exercises) based on the learning curriculum.

[2181] Input: Appropriate learning curriculum.

[2182] Data calculation: Retrieve learning content from the database and combine the necessary data.

[2183] Output: Creates an endpoint to send prepared learning content to the device.

[2184] Device:

[2185] The terminal receives the learning content from the server and displays it to the user.

[2186] Input: The learning content sent from the server.

[2187] Data calculation: Analyzes received data and displays it as learning content.

[2188] Output: The learning content displayed to the user.

[2189] User:

[2190] Users engage with the learning content displayed on their device, solving math exercises and watching videos.

[2191] Input: The learning content displayed on the device.

[2192] Output: Question answer results and viewing history.

[2193] Step 5: Monitoring your learning progress

[2194] ---

[2195] server:

[2196] The server monitors the learning progress in real time.

[2197] Input: Learning progress data sent from the device.

[2198] Data calculation: Save learning progress data in a database and analyze and monitor progress.

[2199] Output: Detailed statistics of your learning progress.

[2200] Device:

[2201] The device records the user's learning content and test results and sends them to the server.

[2202] Input: User's learning progress data.

[2203] Data Computation: Formatting the collected data for sending to the server.

[2204] Output: Learning progress data sent to the server.

[2205] User:

[2206] The user continues to work on the learning content.

[2207] Input: Question answers and test results.

[2208] Output: Your learning progress data.

[2209] Step 6: Provide feedback

[2210] ---

[2211] server:

[2212] The server generates feedback based on the learning progress data and transmits it to the terminal.

[2213] Input: Learning progress data.

[2214] Data computation: Uses feedback generation algorithms to create appropriate messages.

[2215] Output: Sends feedback messages to the terminal.

[2216] Device:

[2217] The terminal displays the feedback message received from the server to the user.

[2218] Input: The feedback message sent by the server.

[2219] Data processing: Converting feedback messages into a display format.

[2220] Output: The feedback displayed to the user.

[2221] User:

[2222] The user receives feedback from the server and reflects it in their learning.

[2223] Input: The feedback message displayed on the terminal.

[2224] Output: Reflected learning behavior.

[2225] The above are the specific processing steps and operations of the server, terminal, and user.

[2226] (Application example 1)

[2227] 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."

[2228] Conventional learning support systems often provide a uniform learning curriculum, which means they are unable to adequately address the individual needs of each learner. Furthermore, creating an environment that maximizes learning effectiveness is difficult, due to the lack of real-time feedback that is common in face-to-face classes and the difficulty of maintaining motivation. Furthermore, the limited customization of virtual instructors can prevent effective instruction tailored to learners' interests and preferences. A system that can solve these issues and provide personalized instruction optimized for each learner is needed.

[2229] 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.

[2230] In this invention, the server includes means for collecting initial data from learners, means for generating a learning curriculum optimized for each learner using artificial intelligence, means for generating virtual instructor data, means for displaying the generated virtual instructor in a virtual reality environment, means for monitoring learning progress, means for generating feedback based on the learning progress data, and means for providing feedback in real time, thereby providing personalized learning guidance optimized for each learner and maximizing the learning effect.

[2231] "Initial data" is basic information about the learner, such as the learner's name, age, grade, learning goals, and preferred learning methods.

[2232] "Artificial intelligence" is a technology that allows computer systems to perform highly complex tasks and analyze learner data to generate optimal learning curricula.

[2233] A "learning curriculum" is a plan that includes learning content, progress schedule, and evaluation methods optimized for each learner.

[2234] A "virtual instructor" is an interactive instructor that is customized based on the learner's preferences and displayed in a virtual reality environment.

[2235] A "virtual reality environment" is a simulated environment that feels real using computer technology.

[2236] "Study progress" is data that indicates how far a learner has progressed in their studies according to the learning curriculum.

[2237] "Feedback" refers to evaluations, advice, and messages to maintain motivation that are generated based on the learner's learning progress.

[2238] "Real-time" means that data is sent, received, and processed immediately, without delay.

[2239] The present invention is a system for providing individually optimized learning guidance to learners, and involves cooperation between a server, a terminal, and a user. A method for realizing this system will be described in detail below.

[2240] Server processing explanation

[2241] 1. Data Collection and Initial Setup:

[2242] The server collects initial data from the learner, including the learner's name, age, grade, achievement test results, learning goals, and preferred learning methods, thereby obtaining basic information about the learner and using it to generate an individually optimized learning curriculum.

[2243] 2. Generating an individually optimized curriculum:

[2244] The server uses a generative AI model to generate an optimized learning curriculum for each learner, including the learning content, progress schedule, and assessment method for each subject.

[2245] 3. Virtual Instructor Setup:

[2246] The server generates data on a virtual tutor based on the learner's preferences, and the tutor appears in a virtual reality environment, looking and speaking like a specific character or person.

[2247] 4. Progress monitoring and feedback:

[2248] The server monitors learning progress in real time, adjusts the curriculum as needed, and provides feedback based on learners' performance data.

[2249] Terminal processing explanation

[2250] 1. Data Entry:

[2251] The device accepts data input from the learner, including initial data and learning progress data, for example, displaying a popup to allow the user to start an achievement test on the device and collecting the achievement test results.

[2252] 2. View Virtual Instructor:

[2253] The device receives data from the server and displays it in a virtual reality environment, allowing learners to take interactive lessons.

[2254] 3. View and progress your learning:

[2255] The device displays learning content (text, videos, exercises) to the learner based on the curriculum, allowing the learner to progress through their studies efficiently.

[2256] 4. Sending progress data:

[2257] The device sends learning progress and test results to the server, allowing the server to track progress in real time and provide appropriate feedback.

[2258] User behavior description

[2259] 1. Enter the initial data:

[2260] Users enter their information into a registration form on the device, including their name, age, grade level, learning goals, and preferred learning method.

[2261] 2. Participating in a VR environment:

[2262] Users wear a VR device and participate in lessons taught by a virtual instructor. If they have any questions during the lesson, they can ask them using voice input or a dedicated interface.

[2263] 3. Engage in learning content:

[2264] Users work through the learning content displayed on their devices, solve problems, and take tests, for example, by working through math exercises and entering their answers.

[2265] 4. Receiving and incorporating feedback:

[2266] The user receives feedback from the server and incorporates it into their learning. They also receive messages and rewards to maintain motivation. For example, the user receives a message from the server saying "Good job!" and moves on to the next learning step.

[2267] In one example, a 12-year-old student can improve their math grades by donning a VR headset and being taught how to solve quadratic equations by a virtual teacher who resembles a specific character. The teacher explains easy-to-understand examples and provides real-time feedback immediately after the student solves the problem.

[2268] An example of a prompt for the generative AI model is as follows:

[2269] "Generate a 3D model of a virtual teacher resembling a specific character explaining to a 12-year-old student how to solve quadratic equations. The teacher should use a friendly voice and easy-to-understand language, providing step-by-step instructions that the student can understand. Explain examples and provide immediate feedback when the student solves."

[2270] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2271] Step 1:

[2272] The server collects initial data from the learner. When the user enters their name, age, grade, learning goals, and preferred learning method into the registration form on their device, this data is sent to the server. The server stores the received initial data in a database. The input data is the learner's basic information, and the output is the initial data stored in the database.

[2273] Step 2:

[2274] The server uses a generative AI model based on the collected initial data to generate an optimized learning curriculum for each learner. The initial data is input into the AI ​​model, and the data output as a learning curriculum includes the learning content, progress schedule, and evaluation method for each subject. This learning curriculum is created individually according to the learner's needs.

[2275] Step 3:

[2276] The server sends the generated learning curriculum to the learner's terminal. The input is the learning curriculum data generated on the server side, and the output is the learning curriculum data sent to the terminal. The terminal receives this data and stores it so that the learner can access it.

[2277] Step 4:

[2278] The server generates virtual teacher data based on the learner's preferences. For example, if a learner likes a particular character, it generates a 3D model and voice data of a virtual teacher that resembles that character. The input is the learner's preference data, and the output is the generated virtual teacher data.

[2279] Step 5:

[2280] The server sends the generated virtual instructor data to the terminal. The terminal receives this data and prepares to display the virtual instructor in a virtual reality environment. The input is the virtual instructor data from the server, and the output is a 3D model of the virtual instructor and audio data stored in the terminal.

[2281] Step 6:

[2282] The learner puts on the VR device and starts the lesson with the virtual instructor on the terminal. The terminal uses the virtual instructor data sent from the server to display the virtual instructor in a virtual reality environment. The input is the virtual instructor data stored on the terminal, and the output is the virtual instructor displayed on the VR device.

[2283] Step 7:

[2284] Learners follow the guidance of a virtual instructor and work on learning content based on the learning curriculum. The device records the learner's progress and collects test results and answer data for practice questions. The input is the learner's answer data, and the output is the learning progress data stored on the device.

[2285] Step 8:

[2286] The terminal sends the collected learning progress data to the server. The input is the learner's progress data, and the output is the learning progress data sent to the server. The server uses this data to monitor the learner's progress.

[2287] Step 9:

[2288] The server generates feedback based on the learning progress data. It uses a generative AI model to analyze the learner's progress and test results and create appropriate feedback messages. The input is the learning progress data, and the output is the feedback message.

[2289] Step 10:

[2290] The server sends the generated feedback message to the terminal. The terminal receives this message and displays it to the learner. The input is the server-side feedback message, and the output is the feedback message displayed on the terminal. For example, the message "Good job!" is displayed.

[2291] As described above, by these specific processing steps, a system can be realized that provides individually optimized learning guidance to learners.

[2292] 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.

[2293] This invention is a system that utilizes AI, VR technology, and an emotion engine to provide individually optimized learning guidance to learners. This system operates in cooperation with three parties: a server, a terminal, and a user.

[2294] Server processing explanation

[2295] 1. Data Collection and Initial Setup:

[2296] The server collects initial data from the learner, including name, age, grade, achievement test results, learning goals, and preferred learning methods.

[2297] Example: The server receives the data entered by the user in the registration form (e.g., name "Yamada Taro", age "12 years old").

[2298] 2. Generating an individually optimized curriculum:

[2299] The server uses artificial intelligence to generate an optimized learning curriculum for each learner, including the learning content for each subject, progress schedule, and evaluation method.

[2300] Example: A server-generated curriculum specifies weekly math practice problems and monthly practice tests.

[2301] 3. Virtual Instructor Setup:

[2302] The server generates data on a virtual teacher based on the learner's preferences, and this teacher appears in the VR environment with the appearance and speaking style of a specific character or person.

[2303] Example: When a learner selects a virtual teacher who resembles Doraemon, the server generates a 3D model and voice data that resembles Doraemon.

[2304] 4. Progress monitoring and feedback:

[2305] The server monitors learning progress in real time, adjusts the curriculum as needed, and provides feedback based on the learner's performance data.

[2306] Example: The server generates and sends a message saying "Well done!" based on the learner's test results (e.g., 90 points in mathematics).

[2307] 5. Emotion Recognition with Emotion Engine:

[2308] The server analyzes the learner's emotional data using an emotion engine to appropriately adjust instructional content and feedback. This engine recognizes emotions by analyzing the learner's facial expressions and voice.

[2309] Example: The server detects the learner's stress level from facial expression data and provides relaxation content.

[2310] Terminal processing explanation

[2311] 1. Data Entry:

[2312] The terminal accepts data input from the learner, including initial data and learning progress data.

[2313] Specific operation: The device displays a pop-up to start the academic ability test, and the user starts the test.

[2314] 2. View Virtual Instructor:

[2315] The device receives data from the server and displays the virtual instructor in a VR environment, providing interactive lessons.

[2316] Specific operation: Using a VR headset, a video is displayed in which a Doraemon-style virtual instructor explains the preparatory content.

[2317] 3. View and progress your learning:

[2318] The device displays learning content (text, videos, exercises) to the learner based on the learning curriculum.

[2319] Example: A device displays math exercises and the user answers them.

[2320] 4. Sending progress data:

[2321] The device sends learning progress and test results to the server, allowing the server to track progress in real time and provide appropriate feedback.

[2322] Example: The device sends the learner's test results (e.g., 90 points in mathematics) to the server.

[2323] 5. Emotional Data Collection and Transmission:

[2324] The device collects the learner's facial expressions and voice data and sends it to a server, where it is analyzed by an emotion engine.

[2325] Example: The device collects the learner's facial expression data (e.g., images captured from a camera) and voice data and sends them to a server.

[2326] User behavior description

[2327] 1. Enter the initial data:

[2328] Users enter their information into a registration form, including their name, age, grade level, learning goals, and preferred learning method.

[2329] Example: A user fills out a registration form with the name "Yamada Taro" and age "12 years old."

[2330] 2. Participating in a VR environment:

[2331] Users wear a VR device and participate in lessons taught by a virtual instructor. If they have any questions during the lesson, they can ask them using voice input or a dedicated interface.

[2332] Example: A user uses a VR headset to take a lesson from a Doraemon-style virtual instructor.

[2333] 3. Engage in learning content:

[2334] Users work through the learning content displayed on their device, solving problems and taking tests.

[2335] Example: A user works through a math exercise displayed on a terminal and enters the answers.

[2336] 4. Providing Emotion Data:

[2337] During the learning process, users provide emotional data through their facial expressions and the sounds they hear.

[2338] Example: When a user is learning in front of a camera and has a tired expression, the facial expression data is sent from the device to the server.

[2339] 5. Receiving and incorporating feedback:

[2340] Users receive feedback from the server and incorporate it into their learning. They also receive messages and rewards to keep them motivated.

[2341] Example: Th...

Claims

1. a means of collecting initial data from learners; A means for generating a learning curriculum optimized for each learner using artificial intelligence; means for transmitting the learning curriculum to a learner's terminal; a means for generating virtual instructor data; means for transmitting the generated virtual instructor to a learner's terminal; a means of monitoring learning progress; means for generating feedback based on the learning progress data; A system including:

2. The virtual instructor is customized based on the learner's preferences. The system of claim 1 .

3. The feedback includes adjusting the curriculum based on the learner's learning progress. The system of claim 1 .

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