System

Abstract

A system is provided.SOLUTION: The system includes a means for inputting and storing individual information and interest information of learners, a means for generating a learning plan by using a generation AI for acquiring and analyzing the stored individual information and interest information, a means for providing a learning experience in virtual reality environments on the basis of the generated learning plan, and a means for providing an online community in which a plurality of learners can communicate with each other online.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] Traditionally, children who do not attend school have had difficulty finding a learning environment and have often been isolated from society. As a result, they have had issues with lowering their self-esteem and losing motivation to learn. Another problem is that they are not provided with optimal learning plans for each individual child and are not given enough opportunities to interact with other students. [Means for solving the problem]

[0005] To solve this problem, the present invention provides the following means. First, it provides a means for inputting and saving a learner's personal information and interests. It provides a means for a generation AI to generate an optimal learning plan for the learner based on this information. Next, it provides a means for providing a learning experience in a virtual reality environment based on the generated learning plan. Furthermore, it provides a means for providing an online community where multiple learners can interact online, thereby realizing a system that allows learners to connect with each other and improve their self-esteem.

[0006] "Learner" refers to an individual who intends to use the system to learn.

[0007] "Personal information" refers to information that identifies a learner, such as the learner's name, age, subjects of interest, and learning level.

[0008] "Interest information" refers to information about subjects or fields in which a learner is particularly interested.

[0009] "Generative AI" refers to artificial intelligence with algorithms that generate optimal learning plans based on the data it receives.

[0010] A "learning plan" refers to a plan of learning content and methods created based on the learner's interests and level.

[0011] "Virtual reality environment" refers to a three-dimensional virtual space created using computer technology.

[0012] An "online community" refers to a platform where multiple learners can interact and share information via the Internet. [Brief explanation of the drawings]

[0013] [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

[0014] 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.

[0015] First, the terms used in the following description will be explained.

[0016] 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).

[0017] 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.

[0018] 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.

[0019] 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.

[0020] 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."

[0021] [First embodiment]

[0022] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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."

[0034] The present invention is a system that provides an optimal learning experience for children who are not attending school, and the following means are used to realize this.

[0035] First, a learner accesses the system and enters personal information and interest information. Through this process, data such as the learner's name, age, academic level, and areas of interest are collected. This data is sent from the user's device to the server. This information is stored on the server and used to generate a learning plan.

[0036] The server then uses generative AI to analyze the collected data and generate an optimal learning plan for each individual. The generative AI automatically selects and plans relevant learning content based on the learner's interests and learning history. For example, a learner interested in history would be provided with a detailed learning plan on ancient Egyptian civilization.

[0037] The generated lesson plan is sent from the server to the user's device. The user can proceed with their studies based on this plan. The lesson plan includes experiential learning in a virtual reality environment, such as a virtual tour of the construction site of an Egyptian pyramid or a three-dimensional observation of the molecular structure of DNA. These VR experiences are realized by connecting the device to a VR headset or related devices.

[0038] Furthermore, learners can participate in online communities and interact with other learners. The server manages community data in real time and provides an environment that is easy to use even when multiple learners access the site simultaneously. Learners can share their learning progress and experiences, and exchange questions and advice.

[0039] Additionally, learners can use the counseling service if necessary. When a user accesses the counseling page and enters the details of their consultation, the server sends the data to an AI counselor. The AI ​​counselor analyzes the received information and provides appropriate advice and feedback. This helps to alleviate any anxieties or worries the learner may have.

[0040] Specific examples

[0041] For example, consider the case where Learner A is using an application for the first time. Learner A creates an account on their device and enters their name, age, subjects of interest (such as history), and current learning level. This information is sent to the server and stored. The server then uses generative AI to generate a detailed history lesson plan. This plan focuses on the ancient Egyptian civilization and includes content that allows the learner to experience the pyramid construction process in virtual reality.

[0042] Learner A follows the lesson plan generated on the device, puts on a VR headset, and takes a virtual tour of a construction site in Egypt. Interactive quizzes are provided during the tour, and Learner A can progress by answering them. This experience allows Learner A to deepen his understanding of ancient civilizations.

[0043] Furthermore, Learner A can access the online community and exchange opinions about Egyptian civilization with other learners. Finally, if Learner A wants to use counseling services, he or she can access the counseling page and enter his or her concerns about learning. The server will provide appropriate advice through an AI counselor to ease Learner A's anxiety.

[0044] As described above, this system can improve self-esteem and provide effective learning support to children who are not attending school by providing them with individually optimized learning experiences and opportunities for interaction.

[0045] The processing flow will be explained below.

[0046] Step 1:

[0047] A user launches the application and accesses the account creation page, where they enter information such as their name, age, subjects of interest, and learning level.

[0048] Step 2:

[0049] The device stores the input information in temporary memory and sends it to the server as JSON format data.

[0050] Step 3:

[0051] The server parses the received JSON data, stores the learner's personal information and interests in a database, and sends the user a confirmation message to create an account.

[0052] Step 4:

[0053] The server retrieves the user's learning history and interest information from the database and prepares to pass it on to the generation AI.

[0054] Step 5:

[0055] The generative AI analyzes the acquired data and generates an optimal learning plan for the user, which includes highly relevant learning content and experiences in a virtual reality environment.

[0056] Step 6:

[0057] The server stores the generated learning plan in a database and sends it to the user's device.

[0058] Step 7:

[0059] The user can view the lesson plan on the device and begin learning in a virtual reality environment. For example, the user can select the construction process of the Egyptian pyramids.

[0060] Step 8:

[0061] The device launches a VR module based on the selected learning content, and the user experiences learning in a virtual environment using a VR headset.

[0062] Step 9:

[0063] After the user has completed the VR learning experience, their learning progress is recorded on the device and sent to the server.

[0064] Step 10:

[0065] The learning progress received by the server is stored in a database and used to generate the next learning plan.

[0066] Step 11:

[0067] Users can access online communities to connect with other learners and post their learning experiences and questions.

[0068] Step 12:

[0069] The server manages community posting data in real time and notifies other users. The device receives the updated information and updates the community screen.

[0070] Step 13:

[0071] The user accesses the counseling page and enters the details of the consultation. The device sends the input data to the server.

[0072] Step 14:

[0073] The server passes the received counseling data to the AI ​​counselor, who then analyzes the input and generates appropriate advice and feedback.

[0074] Step 15:

[0075] The server sends the generated advice to the user's device, which displays the advice, and the user receives feedback.

[0076] Example 1

[0077] 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."

[0078] In modern society, it is becoming increasingly important for children who are not attending school to continue learning effectively and to improve their self-esteem. In particular, there is a need for individually optimized learning experiences and opportunities for interaction to reduce feelings of isolation. However, the traditional education system has not been able to adequately meet these needs.

[0079] 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.

[0080] In this invention, the server includes means for inputting and saving personal information and interest information of learners, means for generating a learning plan using a generation AI that acquires and analyzes the saved personal information and interest information, means for providing a learning experience in a virtual reality environment based on the generated learning plan, means for providing an online community where multiple learners can interact online, and means for transmitting the consultation details input by the learner to an AI counselor and providing appropriate advice and feedback. This provides individually optimized learning experiences and a place for interaction for children who are not attending school, improves their self-esteem, and enables effective learning support.

[0081] "Student" means an individual who uses the system and studies according to a study plan.

[0082] "Personal information" refers to information that can be used to identify a specific individual, such as a learner's name, age, academic level, and areas of interest.

[0083] "Interest information" refers to information that indicates a learner's interest or curiosity in a particular field or subject.

[0084] "Generative AI" refers to artificial intelligence that analyzes input data and generates individually optimized learning plans.

[0085] A "learning plan" is a learning plan or content generated by generative AI that is optimized for each individual learner.

[0086] A "virtual reality environment" is a computer-generated virtual learning environment that a user experiences using a device such as a VR headset.

[0087] An "online community" is a platform where multiple learners can interact and share information over the Internet.

[0088] An "AI counselor" is an artificial intelligence that analyzes the content of learners' consultations and provides appropriate advice and feedback.

[0089] An "interactive experience" is a two-way learning experience that progresses through learner participation and response.

[0090] "Feedback" refers to evaluation and advice provided to learners regarding their learning progress and behavior.

[0091] The present invention is a system that provides optimal learning experiences for children who are not attending school. This system is composed of users, terminals, and a server.

[0092] First, a user accesses the system using a device (such as a PC or smartphone). The user enters personal information and interest information such as name, age, academic level, and areas of interest. This information is sent from the user's device to the server and stored on the server.

[0093] The server analyzes the stored data and generates a learning plan using a generative AI model, which generates an individually optimized learning plan based on the input data. The software used for this includes machine learning libraries such as Python and TensorFlow.

[0094] The generated learning plan is sent from the server to the user's device and displayed on the device. The learning plan includes experiential learning in a virtual reality (VR) environment. Using a device such as a VR headset, users can experience a virtual tour of, for example, the ancient civilization of Egypt. This allows learners to deepen their understanding through interactive experiences.

[0095] Learners can also join online communities and interact with other learners. The server also manages the data of these online communities and updates it in real time, providing a comfortable environment for multiple learners to access the system simultaneously.

[0096] Furthermore, if users have any concerns about their studies, they can use the counseling service. When users input their concerns, the data is sent to a server, which then sends it to an AI counselor. The AI ​​counselor analyzes the concerns and provides appropriate advice and feedback.

[0097] Specific examples

[0098] For example, consider the case of Learner A using the system for the first time. Learner A creates an account on a device and enters his or her name, age, subjects of interest (such as history), and current academic level. This information is sent to and stored on the server. The server then uses a generative AI model to generate a detailed history lesson plan. This plan focuses on the ancient Egyptian civilization and includes content that allows the learner to experience the pyramid construction process in virtual reality.

[0099] Learner A follows the lesson plan generated on the device, puts on a VR headset, and takes a virtual tour of a construction site in Egypt. Interactive quizzes are provided during the tour, and Learner A can progress by answering them. This experience allows Learner A to deepen his understanding of ancient civilizations.

[0100] Furthermore, Learner A can access the online community and exchange opinions about Egyptian civilization with other learners. Finally, if Learner A wants to use counseling services, he or she can access the counseling page and enter his or her concerns about learning. The server will provide appropriate advice through an AI counselor to ease Learner A's anxiety.

[0101] Prompt Sentence Examples

[0102] "Student A is interested in history. Based on his current academic level and ongoing learning, generate a lesson plan on the ancient Egyptian civilization."

[0103] In this way, this system can provide children who are not attending school with individually optimized learning experiences and opportunities for interaction, thereby improving their self-esteem and providing effective learning support.

[0104] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0105] Program processing steps

[0106] Step 1: Enter and submit user information

[0107] Specific behavior:

[0108] A user accesses the system using a terminal and logs in by entering authentication information such as a username and password.

[0109] After logging in, users access a form where they can enter personal information and interests (such as name, age, academic level, and subjects of interest).

[0110] The input information is sent from the terminal to the server by pressing the send button.

[0111] input:

[0112] User personal information and interest information

[0113] output:

[0114] User information sent to the server

[0115] Step 2: Save your data

[0116] Specific behavior:

[0117] The server receives the user's personal information and interest information sent from the terminal.

[0118] Stores the received data in an internal database (e.g., MySQL or PostgreSQL).

[0119] input:

[0120] User information sent

[0121] output:

[0122] User information stored in a database

[0123] Step 3: Analyze the data and generate a learning plan

[0124] Specific behavior:

[0125] The server retrieves the user's personal information and interest information from the database.

[0126] The acquired data is then fed into a generative AI model, using a machine learning library such as TensorFlow or PyTorch.

[0127] A generative AI model analyzes the data and generates an individually optimized learning plan.

[0128] input:

[0129] User information retrieved from the database

[0130] output:

[0131] Generated Learning Plan

[0132] Step 4: Submit your study plan

[0133] Specific behavior:

[0134] The server transmits the generated study plan to the user's terminal.

[0135] The device receives the study plan and displays it to the user.

[0136] input:

[0137] Generated Learning Plan

[0138] output:

[0139] Study plans sent to the user's device

[0140] Step 5: Virtual reality learning experience

[0141] Specific behavior:

[0142] The user uses the device to set up a virtual reality (VR) learning environment by putting on a VR headset and launching a corresponding VR application.

[0143] The VR application creates a virtual reality environment based on the learning plan received from the server, providing the user with experiential learning.

[0144] input:

[0145] Learning plans sent to users

[0146] output:

[0147] Virtual reality learning experiences provided to users

[0148] Step 6: Access the online community

[0149] Specific behavior:

[0150] Users use terminals to access online communities within the system.

[0151] The server manages access from multiple users and updates data in real time.

[0152] Users can exchange opinions, ask questions, and post with other learners within the community.

[0153] input:

[0154] User information for community participation

[0155] output:

[0156] Real-time updated community data

[0157] Step 7: Access counseling services

[0158] Specific behavior:

[0159] The user accesses the counseling page using a terminal and inputs the concerns and questions about their studies.

[0160] The server sends the input data to the AI ​​counselor, who then analyzes the data using natural language processing technology and generates appropriate advice.

[0161] The advice is sent back to the user's terminal via the server and displayed on the screen.

[0162] input:

[0163] User consultation details

[0164] output:

[0165] Advice from an AI counselor

[0166] Through these steps, we can provide individually optimized learning experiences and opportunities for interaction for children who are not attending school, thereby improving their self-esteem.

[0167] (Application example 1)

[0168] 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."

[0169] The challenge is how to provide an individually optimized learning environment to improve technical skills and learning outcomes for children who are not attending school or for employee training. Traditional learning programs and training have made it difficult to provide optimal learning plans tailored to individual interests and skill levels. Furthermore, there has been a lack of methods to provide effective learning experiences, which has made it easy for learners to become isolated and difficult for them to continue learning.

[0170] 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.

[0171] In this invention, the server includes means for inputting and storing personal information and interest information of learners, means for generating a learning plan using a generation AI that acquires and analyzes the stored personal information and interest information, means for providing a learning experience in a virtual reality environment based on the generated learning plan, means for providing an online community where multiple learners can interact online, and means for providing an operation simulation in a virtual reality environment based on the generated learning plan to improve technical skills. This makes it possible to provide an optimal learning experience for individual learners and engineers, and to improve their technical skills and learning outcomes.

[0172] "Personal information and interest information of learners" refers to information that indicates the characteristics and interests of individual learners, such as the learner's name, age, academic ability / skill level, and areas of interest.

[0173] A "learning plan" is a plan that includes learning content and schedules that are optimal for a learner, created by a generative AI based on the learner's personal information and interests.

[0174] "Generative AI" is an artificial intelligence technology that analyzes a large amount of collected information and generates the optimal learning plan for each learner.

[0175] A "virtual reality environment" is a virtual space where learners can use a VR headset or similar device to experience real places and things in a highly realistic way.

[0176] An "online community" is a virtual communication platform where multiple learners can interact via the Internet.

[0177] An "operation simulation" is a virtual simulation that allows you to simulate the experience of specific operations or tasks in a virtual reality environment.

[0178] The present invention relates to a system for providing an optimal learning experience to a learner, and more particularly to a method for generating a learning program using a VR environment and an online community. The embodiment of the present invention is configured as follows.

[0179] Program Generation and Explanation

[0180] The server collects and stores personal information and interest information from the learner's device, including the learner's name, age, academic and technical level, and areas of interest. It also uses a generative AI to analyze this information. The generative AI uses a machine learning algorithm to generate an optimal learning plan based on the collected information.

[0181] The generated learning plans include simulated operations in a virtual reality environment. Learners can use a VR headset to experience real-world environments and operations in a virtual space. For example, in the case of automation technology training, robot operation and troubleshooting scenarios are simulated.

[0182] The server also provides an online community, creating an environment where multiple learners can interact in real time, allowing them to share their knowledge and experiences and maintain their motivation to learn.

[0183] Additionally, the generative AI tracks learners' progress and provides feedback, helping them to continually improve their learning.

[0184] Hardware and Software Use

[0185] Hardware: VR headset (e.g., Oculus Rift), user device (e.g., tablet, PC)

[0186] Software: Flask (Python web framework), generative AI model (for generating learning plans), VR simulation software, community platform, AI counseling system

[0187] Specific examples

[0188] When an engineer wants to learn how to operate a new robot, they access a terminal and enter their name, age, areas of interest, and level of automation technology skill. This information is stored on a server and analyzed by the generating AI. The generated learning plan includes simulations of operating the robot and troubleshooting.

[0189] Engineers put on a VR headset and begin practicing in a virtual environment, where they can actually operate the robot and answer interactive quizzes.

[0190] Engineers can also join online communities to deepen their learning while interacting with other like-minded engineers. Finally, they can consult with an AI counselor about their technical concerns and questions and receive appropriate advice.

[0191] Prompt Sentence Examples

[0192] Technician Information:

[0193] Name: Yamada

[0194] Age: 35

[0195] Area of ​​interest: Automation technology

[0196] Current Skill Level: Intermediate

[0197] Generate a personalized learning plan for this technician, including virtual reality simulations and interactive training modules.

[0198] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0199] Step 1:

[0200] A user creates an account by entering personal information and interests using a device. Specifically, the user enters their name, age, academic and technical level, and areas of interest. The entered information is sent from the device to a server and stored.

[0201] Input: User's personal information and interests

[0202] Output: User information stored on the server

[0203] Step 2:

[0204] The server retrieves the stored personal information and interest information and passes it to the generation AI, which analyzes this information and generates an optimal learning plan for the user. The learning plan includes specific learning content and operation simulations in a virtual reality environment.

[0205] Input: Stored Personal Information and Interests

[0206] Data processing: Information analysis using generative AI

[0207] Output: Optimal study plan

[0208] Step 3:

[0209] The server sends the generated learning plan to the user's device. The user then checks the learning plan and sets up the device to begin the learning experience in the virtual reality environment. Specifically, the user prepares a VR headset and enters the virtual environment.

[0210] Input: Optimal Study Plan

[0211] Output: The lesson plan displayed on the user's device

[0212] Step 4:

[0213] The user puts on a VR headset and begins simulating operations in a virtual reality environment. The server tracks the user's movements within the virtual environment and provides interactive quizzes and feedback. For example, a simulated robot operation or troubleshooting scenario is performed.

[0214] Input: User operation data, virtual reality environment

[0215] Output: Interactive quiz, feedback

[0216] Step 5:

[0217] The server tracks the user's learning progress and provides feedback based on the learning plan. The progress data is analyzed to present the user with additional learning content and advice.

[0218] Input: User progress data

[0219] Data processing: Analysis of progress data

[0220] Output: Feedback, additional learning content

[0221] Step 6:

[0222] Users access online communities and interact with other learners. The server manages data within the communities and supports smooth communication in real time. Users share their knowledge in forums and Q&A sessions.

[0223] Input: User's community participation information

[0224] Output: Interaction data within the online community

[0225] Step 7:

[0226] Users consult an AI counselor about their worries and questions about their studies. The server passes the user's question to the AI ​​counselor, who then responds with appropriate advice. The AI ​​counselor uses natural language processing to analyze the user's question and generate the most appropriate answer.

[0227] Input: User question data

[0228] Data processing: Question analysis using natural language processing

[0229] Output: Advice from an AI counselor

[0230] 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.

[0231] This invention is a system that provides an optimal learning experience for children who are not attending school, and aims to improve the effectiveness of learning and the quality of counseling by combining an emotion engine. The system includes a learning plan generated based on the learner's personal information and interests, a learning experience in a virtual reality environment, an online community, and emotion analysis using an emotion engine.

[0232] Specific operations and processing flow

[0233] First, a learner accesses the system and enters their personal information and interests. The data collected during this process is sent from the user's device to a server and stored in a database.

[0234] The server then uses generative AI to analyze the learner's data and generate a personalized learning plan that includes learning content selected based on the learner's interests and learning history. For example, if a user is interested in biology, a detailed learning plan on the molecular structure of DNA will be generated.

[0235] The generated learning plan is sent from the server to the user's device, and the user proceeds with their learning based on this plan. Specifically, the user can observe the molecular structure of DNA in 3D in a virtual reality environment, which deepens their understanding.

[0236] The emotion engine analyzes the user's facial expressions, voice, and text data to determine the user's emotional state in real time. For example, if the user shows a confused expression while studying, the emotion engine will recognize this and notify the server.

[0237] Based on this, the server dynamically adjusts the learning plan, for example by providing additional, clearer explanations or recommending counseling services.

[0238] Furthermore, users can participate in online communities and interact with other learners. The server manages community data in real time, ensuring that each user's posts and comments are updated immediately.

[0239] Emotion engines are also used in online communities to provide appropriate feedback and support by determining the emotional state of users as they interact with each other.

[0240] Specific examples

[0241] For example, consider the case where Learner B is using the system for the first time. Learner B creates an account and enters personal information and "history" as his or her subject of interest. The data is sent to the server and saved. The server then uses generative AI to generate a lesson plan on history. The plan includes content about the ancient Egyptian civilization, allowing the learner to experience the pyramid construction process in a virtual reality environment.

[0242] Learner B follows the lesson plan generated using the device, puts on a VR headset, and takes a virtual tour of a construction site in Egypt. Interactive quizzes are provided during the tour, and Learner B progresses by answering them. This experience allows Learner B to deepen his understanding of ancient civilizations.

[0243] Furthermore, Learner B's emotional state is monitored using an emotion engine. For example, if Learner B shows a confused expression, the server collects this information and immediately adjusts the learning content. Learner B also participates in an online community where he or she exchanges opinions about Egyptian civilization with other learners.

[0244] If Learner B enters their learning concerns on the counseling page, the AI ​​counselor will analyze them and provide appropriate advice. If the emotion engine recognizes stress or anxiety from the user's facial expressions or voice, the server will provide more specific and useful feedback.

[0245] As described above, the present invention realizes a system that achieves both learning effectiveness and psychological support by providing each learner with an individually optimized learning experience and emotional support.

[0246] The processing flow will be explained below.

[0247] Step 1:

[0248] A user launches the application and accesses the account creation page, where they enter information such as their name, age, subjects of interest, and learning level.

[0249] Step 2:

[0250] The device stores the input information in temporary memory and sends it to the server as JSON format data.

[0251] Step 3:

[0252] The server parses the received JSON data, stores the learner's personal information and interests in a database, and sends the user a confirmation message to create an account.

[0253] Step 4:

[0254] The server retrieves the user's learning history and interest information from the database and prepares to pass it on to the generation AI.

[0255] Step 5:

[0256] The AI ​​analyzes the acquired data and generates a learning plan that is optimal for the user. For example, if a user is interested in "history," it generates a plan that includes learning content such as "ancient Egyptian civilization."

[0257] Step 6:

[0258] The server stores the generated learning plan in a database and sends it to the user's device.

[0259] Step 7:

[0260] The user can view the lesson plan on the device and begin learning in a virtual reality environment. For example, the user can select the construction process of the Egyptian pyramids.

[0261] Step 8:

[0262] The device launches a VR module based on the selected learning content, and the user experiences learning in a virtual environment using a VR headset.

[0263] Step 9:

[0264] After the user has completed the VR learning experience, their learning progress is recorded on the device and sent to the server.

[0265] Step 10:

[0266] The learning progress received by the server is stored in a database and used to generate the next learning plan.

[0267] Step 11:

[0268] Users can access online communities to connect with other learners and post their learning experiences and questions.

[0269] Step 12:

[0270] The server manages community posting data in real time and notifies other users. The device receives the updated information and updates the community screen.

[0271] Step 13:

[0272] The user uses the emotion engine to recognize their emotional state during training by collecting facial and voice data using a camera and microphone, which is then sent from the device to a server.

[0273] Step 14:

[0274] The server passes the received emotional data to the emotion engine, which analyzes the user's emotional state in real time, for example, recognizing if the user is confused.

[0275] Step 15:

[0276] It provides a way for the server to dynamically adjust the learning plan based on the analysis results from the emotion engine. For example, if the user is confused, the server can provide additional explanations or hints.

[0277] Step 16:

[0278] As users continue to learn, they receive feedback based on their emotional changes. The emotion engine continuously monitors the user's emotional state and provides support as needed.

[0279] Step 17:

[0280] The user accesses the counseling page and enters the details of the consultation. The device sends the input data to the server.

[0281] Step 18:

[0282] The server passes the received counseling data to the AI ​​counselor, who then analyzes the input and generates appropriate advice and feedback.

[0283] Step 19:

[0284] The server sends the generated advice to the user's device, which displays the advice. The user receives feedback. The emotion engine monitors the user's emotional state during counseling and provides additional support.

[0285] The above steps will create a system that provides individually optimized learning experiences and emotional support, achieving both learning effectiveness and psychological support.

[0286] Example 2

[0287] 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."

[0288] Current learning systems are unable to provide learning plans that are adapted to each learner's emotional state and interests, limiting their effectiveness. Another issue is that it is difficult to provide optimal learning experiences and psychological support for children who are not attending school. Therefore, there is a need for a system that can simultaneously provide individually optimized learning experiences and psychological support by analyzing a learner's emotional state and dynamically adjusting learning plans in real time.

[0289] 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.

[0290] In this invention, the server includes means for inputting and saving personal information and interest information of a learner, means for generating a learning plan using a generation AI that acquires and analyzes the saved personal information and interest information, means for providing a learning experience in a virtual reality environment based on the generated learning plan, means for providing an online community where multiple learners can interact online, an emotion engine for analyzing the emotional state of the learner, and means for dynamically adjusting the learning plan based on information obtained from the emotion engine. This makes it possible to provide individually optimized learning plans and adjust the learning plan in accordance with the emotional state in real time.

[0291] "Learners" refers to individuals participating in educational activities, and in this system, the focus is primarily on out-of-school children.

[0292] "Personal information" refers to information that can identify a specific individual, including name, age, email address, etc.

[0293] "Interest information" refers to information about subjects or topics in which a learner is particularly interested.

[0294] "Generative AI" is artificial intelligence that performs specific tasks based on stored data, and in this case refers to an AI model that generates a learning plan.

[0295] "Study Plan" means an educational instruction plan optimized for an individual learner, including targeted content and activities.

[0296] "Virtual reality environment" refers to a virtual three-dimensional space generated using computer technology and used as a means to provide a learning experience.

[0297] An "online community" refers to a platform where multiple learners can interact over the Internet.

[0298] "Emotion engine" refers to technology that analyzes a learner's facial expressions, voice, and text data to determine their emotional state.

[0299] "Dynamic adjustment" refers to the process by which the system automatically modifies the learning plan in response to changing conditions in real time.

[0300] "Feedback" refers to assessment and advice provided based on learners' activities and progress.

[0301] This invention is a system that provides an optimal learning experience for children who are not attending school, and aims to improve the effectiveness of learning and the quality of counseling by combining an emotion engine. The system includes a learning plan generated based on the learner's personal information and interests, a learning experience in a virtual reality environment, an online community, and emotion analysis using an emotion engine.

[0302] First, the user accesses the system using their own device (PC, tablet, smartphone, etc.). The user accesses a form to enter personal information and interest information, and enters the required information. This data is temporarily stored on the device and then sent to the server. The server contains a database, and the received data is stored using a database management system (e.g., MySQL or PostgreSQL).

[0303] The server then uses a generative AI model (such as OpenAI's GPT-3) to analyze the stored data. The server takes into account the user's interests and past learning history to generate a personalized, optimized learning plan. This plan includes learning materials and activities that address the learner's interests. For example, if a user indicates an interest in "biology," the AI ​​will generate a detailed learning plan on the molecular structure of DNA.

[0304] The generated learning plan is sent from the server to the user's device. To progress through the learning process, the user wears a VR headset (e.g., Oculus Rift) and experiences the learning content in a virtual reality environment. Specifically, learners can observe the molecular structure of DNA in 3D and deepen their understanding by answering interactive quizzes in the VR environment.

[0305] This system incorporates an emotion engine that analyzes the learner's emotional state in real time. The emotion engine analyzes the user's facial expressions, voice, and text data to determine their emotional state. For example, if the user shows a confused expression, the emotion engine recognizes this and notifies the server. The server dynamically adjusts the learning plan based on feedback from the emotion engine. Specifically, it may provide additional explanations or recommend counseling.

[0306] Furthermore, users can join online communities and interact with other learners. The server manages community data in real time, ensuring that posts and comments are updated immediately. An emotion engine is also used within the online community to analyze the emotional state of users during interactions and provide appropriate feedback and support.

[0307] As a concrete example, consider the case where Learner B is using the system for the first time. Learner B creates an account and enters personal information and "history" as a subject of interest. The data is sent to the server and saved. The server then uses generative AI to generate a lesson plan on history. The plan includes content about the ancient Egyptian civilization and allows the learner to experience the pyramid construction process in a virtual reality environment.

[0308] Learner B follows the plan generated using the device, puts on a VR headset, and takes a virtual tour of a construction site in Egypt. Interactive quizzes are provided during the tour, and Learner B deepens his or her understanding of the ancient civilization by answering them as the tour progresses. In addition, an emotion engine monitors Learner B's emotional state while learning, and if Learner B shows a confused expression, the server immediately adjusts the learning content. Learner B can also participate in an online community and exchange opinions with other learners.

[0309] For generative AI models, use prompts like the following:

[0310] Prompt: "Student B is interested in the ancient Egyptian civilization. Generate a detailed lesson plan for Student B to use in a virtual reality environment using a VR headset."

[0311] In this way, the present invention provides learners with individually optimized learning experiences and emotional support, thereby improving learning effectiveness and psychological support at the same time.

[0312] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0313] Step 1: The user accesses the system and enters personal information and interest information.

[0314] Users access the system using their own devices (PC, tablet, smartphone). A form is displayed in which the user can enter personal information (such as name, age, and email address) and interest information (interesting subjects and topics). This data is temporarily stored on the device.

[0315] Input: Personal information and interests from the user.

[0316] Output: Input data that is temporarily stored on the device.

[0317] Step 2: The terminal sends the input data to the server.

[0318] The personal information and interest information temporarily stored on the device is sent to a server, where it is received and stored in a database.

[0319] Input: Input data temporarily stored on the device.

[0320] Output: The data sent to the server.

[0321] Step 3: The server saves the data in the database.

[0322] The server will store the received personal information and interest information permanently using a database management system (e.g., MySQL or PostgreSQL). This data will be used for subsequent analysis.

[0323] Input: The data sent to the server.

[0324] Output: Data stored in the database.

[0325] Step 4: The server generates a learning plan using the generative AI model.

[0326] The server generates a learning plan using a generative AI model (e.g., OpenAI's GPT-3) based on the user's personal information and interests stored in the database. The generative AI model analyzes the user's interests and past learning history and outputs an individually optimized learning plan.

[0327] Input: User data stored in the database.

[0328] Output: The generated lesson plan.

[0329] Step 5: The server sends the generated learning plan to the user's device.

[0330] The server then sends the generated learning plan to the user's device, which includes links to learning content and learning experiences in a virtual reality environment.

[0331] Input: The generated lesson plan.

[0332] Output: The study plan sent to the user's device.

[0333] Step 6: The user begins studying according to the study plan.

[0334] The user begins learning based on the received learning plan. Specifically, they put on a VR headset (e.g., Oculus Rift) and experience the learning content in a virtual reality environment. The user deepens their learning through interactive quizzes and activities.

[0335] Input: The study plan sent to the user's device.

[0336] Output: A learning experience in a VR environment.

[0337] Step 7: The emotion engine analyzes the user's emotional state during the learning process.

[0338] The emotion engine analyzes the user's facial expressions, voice, and text data in real time during learning to determine their emotional state (e.g., confusion, excitement, etc.). The analysis results of the emotion engine are sent to the server.

[0339] Input: User's facial expressions, voice, and text data.

[0340] Output: Parsed emotional state.

[0341] Step 8: The server dynamically adjusts the learning plan based on the emotional state.

[0342] The server dynamically adjusts the learning plan based on feedback from the emotion engine, for example, providing additional explanations or recommending counseling if the user is confused.

[0343] Input: Parsed emotional state.

[0344] Output: A tailored study plan.

[0345] Step 9: Users join the online community.

[0346] Users can join online communities within the system and interact with other learners. The server manages community posts and comments in real time and updates them instantly. An emotion engine is also used within the community to analyze the emotional state of users during interactions and provide appropriate feedback and support.

[0347] Input: User posts and comments.

[0348] Output: Online community interaction data.

[0349] (Application example 2)

[0350] 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."

[0351] In modern society, there is a need for appropriate learning support for children who are not attending school. However, there are not enough systems that provide individually optimized learning experiences or that can grasp children's emotional states in real time and respond appropriately. Furthermore, there are no established methods for students to interact with other students and deepen their understanding of their studies without feeling isolated.

[0352] 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 inputting and saving personal information and interest information of a learner, a learning plan generation device means for acquiring and analyzing the saved personal information and interest information, means for providing a learning experience in a virtual reality environment based on the generated learning plan, an emotion analysis engine means for analyzing the emotional state of the learner in real time, means for dynamically adjusting the learning plan based on the analyzed emotional state, and means for providing an online community in which multiple learners can interact online. This makes it possible to provide individually optimized learning experiences and emotional support for children who are not attending school, and to improve their learning effectiveness through interactions with other learners.

[0353] A "learning plan generation device" is a device that generates an optimal learning plan based on a learner's personal information and interest information.

[0354] A "virtual reality environment" is a computer-generated virtual environment that allows learners to have a realistic experience.

[0355] An "emotion analysis engine" is a device that analyzes a learner's facial expressions, voice, and text data to determine their emotional state in real time.

[0356] An "online community" is a virtual space where multiple learners can interact with each other and share information via the Internet.

[0357] A "learning plan" is a plan of learning content and activities that is structured based on the learner's interests and learning history.

[0358] An "interactive experience" is one in which learners actively participate and deepen their learning through two-way interaction.

[0359] "Feedback" is advice or corrective instruction provided based on a learner's learning progress or emotional state.

[0360] "Learning content" refers to the teaching materials and resources provided to learners, including text, images, video, audio, etc.

[0361] This invention is a system that provides optimal learning experiences for children who are not attending school, and aims to improve the effectiveness of learning and the quality of counseling by combining an emotion engine. The system consists of a learning plan generator, a virtual reality environment, an emotion analysis engine, and an online community.

[0362] First, a learner accesses the system from a terminal and enters personal information and information about their interests. This input data is sent to the server and stored in the server's database. The server then uses a learning plan generation device to analyze this data and generate an optimal learning plan for each learner. For example, if a learner is interested in history, a learning plan about ancient civilizations will be generated.

[0363] The generated learning plan is sent from the server to the learner's device and presented to them through the device. The learner then wears smart glasses or a head-mounted display and experiences the learning content in a virtual reality environment. For example, they can deepen their understanding by observing the construction process of the ancient Egyptian pyramids in 3D.

[0364] The emotion analysis engine analyzes the learner's facial expressions, voice, and text data in real time to determine their emotional state. If the learner feels confused or stressed, the emotion analysis engine sends that information to the server, which then dynamically adjusts the learning plan, for example by adding detailed explanations of difficult parts.

[0365] Learners can also participate in online communities and interact with other learners. The server manages the data from these online communities in real time and uses an emotion analysis engine to determine the emotional state of learners during their interactions. This allows appropriate feedback and support to be provided.

[0366] As a concrete example, consider the case where Learner B uses the system for the first time. Learner B creates an account and enters personal information and "history" as his or her subject of interest. The data is sent to the server and saved. The server uses generative AI to generate a history lesson plan and provides a learning experience in a virtual reality environment. If Learner B shows a confused expression, the emotion analysis engine detects this and the server adjusts the learning content.

[0367] An example of a prompt for a generative AI model is:

[0368] "A student shows a confused expression during a history lesson. Based on this, we provide additional explanations and generate advice from an AI counselor."

[0369] This allows the invention to realize an effective system that provides individually optimized learning experiences and emotional support to children who are not attending school.

[0370] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0371] Step 1:

[0372] This is the process where a user accesses the system from a terminal and inputs personal information and interest information. The input data is sent to the server and stored in the server's database. This is used as the basis for building a user profile. The input here is name, age, subjects of interest, etc., and the output is the profile data stored on the server.

[0373] Step 2:

[0374] The server retrieves the stored personal information and interest information, analyzes it using a learning plan generator, and generates an individually optimized learning plan. A generative AI model is used to create a plan containing detailed learning content based on past learning history and interest information. The input is profile data and past learning history, and the output is an individually customized learning plan.

[0375] Step 3:

[0376] The generated learning plan is sent from the server to the device. The user wears smart glasses or a head-mounted display and experiences the learning content in a virtual reality environment. Specifically, 3D models and interactive quizzes are used to provide visually realistic learning. The input here is the learning plan, and the output is the display of the learning content in a VR environment.

[0377] Step 4:

[0378] The emotion analysis engine analyzes the user's facial expression, voice, and text data in real time to determine their emotional state. For example, if a learner shows a confused expression, the facial expression data is sent to the server. The input here is real-time emotional data, and the output is the analyzed emotional state.

[0379] Step 5:

[0380] The server dynamically adjusts the learning plan based on the analyzed emotional state. For example, if the user is confused, the server receives that information and provides additional explanations or supplementary learning materials. The input is the analyzed emotional data, and the output is an adjusted learning plan.

[0381] Step 6:

[0382] Users can participate in online communities and interact with other learners. The server manages online community data in real time and uses an emotion analysis engine to determine the emotional state of learners during interactions. The input is real-time community data, and the output is appropriate feedback and support.

[0383] Through these steps, the system delivers an individually optimized learning experience and dynamically adjusts learning plans based on emotional state.

[0384] 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.

[0385] 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.

[0386] 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.

[0387] [Second embodiment]

[0388] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0389] 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.

[0390] 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).

[0391] 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.

[0392] 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.

[0393] 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).

[0394] 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.

[0395] 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.

[0396] 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.

[0397] 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.

[0398] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0399] 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."

[0400] The present invention is a system that provides an optimal learning experience for children who are not attending school, and the following means are used to realize this.

[0401] First, a learner accesses the system and enters personal information and interest information. Through this process, data such as the learner's name, age, academic level, and areas of interest are collected. This data is sent from the user's device to the server. This information is stored on the server and used to generate a learning plan.

[0402] The server then uses generative AI to analyze the collected data and generate an optimal learning plan for each individual. The generative AI automatically selects and plans relevant learning content based on the learner's interests and learning history. For example, a learner interested in history would be provided with a detailed learning plan on ancient Egyptian civilization.

[0403] The generated lesson plan is sent from the server to the user's device. The user can proceed with their studies based on this plan. The lesson plan includes experiential learning in a virtual reality environment, such as a virtual tour of the construction site of an Egyptian pyramid or a three-dimensional observation of the molecular structure of DNA. These VR experiences are realized by connecting the device to a VR headset or related devices.

[0404] Furthermore, learners can participate in online communities and interact with other learners. The server manages community data in real time and provides an environment that is easy to use even when multiple learners access the site simultaneously. Learners can share their learning progress and experiences, and exchange questions and advice.

[0405] Additionally, learners can use the counseling service if necessary. When a user accesses the counseling page and enters the details of their consultation, the server sends the data to an AI counselor. The AI ​​counselor analyzes the received information and provides appropriate advice and feedback. This helps to alleviate any anxieties or worries the learner may have.

[0406] Specific examples

[0407] For example, consider the case where Learner A is using an application for the first time. Learner A creates an account on their device and enters their name, age, subjects of interest (such as history), and current learning level. This information is sent to the server and stored. The server then uses generative AI to generate a detailed history lesson plan. This plan focuses on the ancient Egyptian civilization and includes content that allows the learner to experience the pyramid construction process in virtual reality.

[0408] Learner A follows the lesson plan generated on the device, puts on a VR headset, and takes a virtual tour of a construction site in Egypt. Interactive quizzes are provided during the tour, and Learner A can progress by answering them. This experience allows Learner A to deepen his understanding of ancient civilizations.

[0409] Furthermore, Learner A can access the online community and exchange opinions about Egyptian civilization with other learners. Finally, if Learner A wants to use counseling services, he or she can access the counseling page and enter his or her concerns about learning. The server will provide appropriate advice through an AI counselor to ease Learner A's anxiety.

[0410] As described above, this system can improve self-esteem and provide effective learning support to children who are not attending school by providing them with individually optimized learning experiences and opportunities for interaction.

[0411] The processing flow will be explained below.

[0412] Step 1:

[0413] A user launches the application and accesses the account creation page, where they enter information such as their name, age, subjects of interest, and learning level.

[0414] Step 2:

[0415] The device stores the input information in temporary memory and sends it to the server as JSON format data.

[0416] Step 3:

[0417] The server parses the received JSON data, stores the learner's personal information and interests in a database, and sends the user a confirmation message to create an account.

[0418] Step 4:

[0419] The server retrieves the user's learning history and interest information from the database and prepares to pass it on to the generation AI.

[0420] Step 5:

[0421] The generative AI analyzes the acquired data and generates an optimal learning plan for the user, which includes highly relevant learning content and experiences in a virtual reality environment.

[0422] Step 6:

[0423] The server stores the generated learning plan in a database and sends it to the user's device.

[0424] Step 7:

[0425] The user can view the lesson plan on the device and begin learning in a virtual reality environment. For example, the user can select the construction process of the Egyptian pyramids.

[0426] Step 8:

[0427] The device launches a VR module based on the selected learning content, and the user experiences learning in a virtual environment using a VR headset.

[0428] Step 9:

[0429] After the user has completed the VR learning experience, their learning progress is recorded on the device and sent to the server.

[0430] Step 10:

[0431] The learning progress received by the server is stored in a database and used to generate the next learning plan.

[0432] Step 11:

[0433] Users can access online communities to connect with other learners and post their learning experiences and questions.

[0434] Step 12:

[0435] The server manages community posting data in real time and notifies other users. The device receives the updated information and updates the community screen.

[0436] Step 13:

[0437] The user accesses the counseling page and enters the details of the consultation. The device sends the input data to the server.

[0438] Step 14:

[0439] The server passes the received counseling data to the AI ​​counselor, who then analyzes the input and generates appropriate advice and feedback.

[0440] Step 15:

[0441] The server sends the generated advice to the user's device, which displays the advice, and the user receives feedback.

[0442] Example 1

[0443] 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."

[0444] In modern society, it is becoming increasingly important for children who are not attending school to continue learning effectively and to improve their self-esteem. In particular, there is a need for individually optimized learning experiences and opportunities for interaction to reduce feelings of isolation. However, the traditional education system has not been able to adequately meet these needs.

[0445] 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.

[0446] In this invention, the server includes means for inputting and saving personal information and interest information of learners, means for generating a learning plan using a generation AI that acquires and analyzes the saved personal information and interest information, means for providing a learning experience in a virtual reality environment based on the generated learning plan, means for providing an online community where multiple learners can interact online, and means for transmitting the consultation details input by the learner to an AI counselor and providing appropriate advice and feedback. This provides individually optimized learning experiences and a place for interaction for children who are not attending school, improves their self-esteem, and enables effective learning support.

[0447] "Student" means an individual who uses the system and studies according to a study plan.

[0448] "Personal information" refers to information that can be used to identify a specific individual, such as a learner's name, age, academic level, and areas of interest.

[0449] "Interest information" refers to information that indicates a learner's interest or curiosity in a particular field or subject.

[0450] "Generative AI" refers to artificial intelligence that analyzes input data and generates individually optimized learning plans.

[0451] A "learning plan" is a learning plan or content generated by generative AI that is optimized for each individual learner.

[0452] A "virtual reality environment" is a computer-generated virtual learning environment that a user experiences using a device such as a VR headset.

[0453] An "online community" is a platform where multiple learners can interact and share information over the Internet.

[0454] An "AI counselor" is an artificial intelligence that analyzes the content of learners' consultations and provides appropriate advice and feedback.

[0455] An "interactive experience" is a two-way learning experience that progresses through learner participation and response.

[0456] "Feedback" refers to evaluation and advice provided to learners regarding their learning progress and behavior.

[0457] The present invention is a system that provides optimal learning experiences for children who are not attending school. This system is composed of users, terminals, and a server.

[0458] First, a user accesses the system using a device (such as a PC or smartphone). The user enters personal information and interest information such as name, age, academic level, and areas of interest. This information is sent from the user's device to the server and stored on the server.

[0459] The server analyzes the stored data and generates a learning plan using a generative AI model, which generates an individually optimized learning plan based on the input data. The software used for this includes machine learning libraries such as Python and TensorFlow.

[0460] The generated learning plan is sent from the server to the user's device and displayed on the device. The learning plan includes experiential learning in a virtual reality (VR) environment. Using a device such as a VR headset, users can experience a virtual tour of, for example, the ancient civilization of Egypt. This allows learners to deepen their understanding through interactive experiences.

[0461] Learners can also join online communities and interact with other learners. The server also manages the data of these online communities and updates it in real time, providing a comfortable environment for multiple learners to access the system simultaneously.

[0462] Furthermore, if users have any concerns about their studies, they can use the counseling service. When users input their concerns, the data is sent to a server, which then sends it to an AI counselor. The AI ​​counselor analyzes the concerns and provides appropriate advice and feedback.

[0463] Specific examples

[0464] For example, consider the case of Learner A using the system for the first time. Learner A creates an account on a device and enters his or her name, age, subjects of interest (such as history), and current academic level. This information is sent to and stored on the server. The server then uses a generative AI model to generate a detailed history lesson plan. This plan focuses on the ancient Egyptian civilization and includes content that allows the learner to experience the pyramid construction process in virtual reality.

[0465] Learner A follows the lesson plan generated on the device, puts on a VR headset, and takes a virtual tour of a construction site in Egypt. Interactive quizzes are provided during the tour, and Learner A can progress by answering them. This experience allows Learner A to deepen his understanding of ancient civilizations.

[0466] Furthermore, Learner A can access the online community and exchange opinions about Egyptian civilization with other learners. Finally, if Learner A wants to use counseling services, he or she can access the counseling page and enter his or her concerns about learning. The server will provide appropriate advice through an AI counselor to ease Learner A's anxiety.

[0467] Prompt Sentence Examples

[0468] "Student A is interested in history. Based on his current academic level and ongoing learning, generate a lesson plan on the ancient Egyptian civilization."

[0469] In this way, this system can provide children who are not attending school with individually optimized learning experiences and opportunities for interaction, thereby improving their self-esteem and providing effective learning support.

[0470] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0471] Program processing steps

[0472] Step 1: Enter and submit user information

[0473] Specific behavior:

[0474] A user accesses the system using a terminal and logs in by entering authentication information such as a username and password.

[0475] After logging in, users access a form where they can enter personal information and interests (such as name, age, academic level, and subjects of interest).

[0476] The input information is sent from the terminal to the server by pressing the send button.

[0477] input:

[0478] User personal information and interest information

[0479] output:

[0480] User information sent to the server

[0481] Step 2: Save your data

[0482] Specific behavior:

[0483] The server receives the user's personal information and interest information sent from the terminal.

[0484] Stores the received data in an internal database (e.g., MySQL or PostgreSQL).

[0485] input:

[0486] User information sent

[0487] output:

[0488] User information stored in a database

[0489] Step 3: Analyze the data and generate a learning plan

[0490] Specific behavior:

[0491] The server retrieves the user's personal information and interest information from the database.

[0492] The acquired data is then fed into a generative AI model, using a machine learning library such as TensorFlow or PyTorch.

[0493] A generative AI model analyzes the data and generates an individually optimized learning plan.

[0494] input:

[0495] User information retrieved from the database

[0496] output:

[0497] Generated Learning Plan

[0498] Step 4: Submit your study plan

[0499] Specific behavior:

[0500] The server transmits the generated study plan to the user's terminal.

[0501] The device receives the study plan and displays it to the user.

[0502] input:

[0503] Generated Learning Plan

[0504] output:

[0505] Study plans sent to the user's device

[0506] Step 5: Virtual reality learning experience

[0507] Specific behavior:

[0508] The user uses the device to set up a virtual reality (VR) learning environment by putting on a VR headset and launching a corresponding VR application.

[0509] The VR application creates a virtual reality environment based on the learning plan received from the server, providing the user with experiential learning.

[0510] input:

[0511] Learning plans sent to users

[0512] output:

[0513] Virtual reality learning experiences provided to users

[0514] Step 6: Access the online community

[0515] Specific behavior:

[0516] Users use terminals to access online communities within the system.

[0517] The server manages access from multiple users and updates data in real time.

[0518] Users can exchange opinions, ask questions, and post with other learners within the community.

[0519] input:

[0520] User information for community participation

[0521] output:

[0522] Real-time updated community data

[0523] Step 7: Access counseling services

[0524] Specific behavior:

[0525] The user accesses the counseling page using a terminal and inputs the concerns and questions about their studies.

[0526] The server sends the input data to the AI ​​counselor, who then analyzes the data using natural language processing technology and generates appropriate advice.

[0527] The advice is sent back to the user's terminal via the server and displayed on the screen.

[0528] input:

[0529] User consultation details

[0530] output:

[0531] Advice from an AI counselor

[0532] Through these steps, we can provide individually optimized learning experiences and opportunities for interaction for children who are not attending school, thereby improving their self-esteem.

[0533] (Application example 1)

[0534] 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."

[0535] The challenge is how to provide an individually optimized learning environment to improve technical skills and learning outcomes for children who are not attending school or for employee training. Traditional learning programs and training have made it difficult to provide optimal learning plans tailored to individual interests and skill levels. Furthermore, there has been a lack of methods to provide effective learning experiences, which has made it easy for learners to become isolated and difficult for them to continue learning.

[0536] 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.

[0537] In this invention, the server includes means for inputting and storing personal information and interest information of learners, means for generating a learning plan using a generation AI that acquires and analyzes the stored personal information and interest information, means for providing a learning experience in a virtual reality environment based on the generated learning plan, means for providing an online community where multiple learners can interact online, and means for providing an operation simulation in a virtual reality environment based on the generated learning plan to improve technical skills. This makes it possible to provide an optimal learning experience for individual learners and engineers, and to improve their technical skills and learning outcomes.

[0538] "Personal information and interest information of learners" refers to information that indicates the characteristics and interests of individual learners, such as the learner's name, age, academic ability / skill level, and areas of interest.

[0539] A "learning plan" is a plan that includes learning content and schedules that are optimal for a learner, created by a generative AI based on the learner's personal information and interests.

[0540] "Generative AI" is an artificial intelligence technology that analyzes a large amount of collected information and generates the optimal learning plan for each learner.

[0541] A "virtual reality environment" is a virtual space where learners can use a VR headset or similar device to experience real places and things in a highly realistic way.

[0542] An "online community" is a virtual communication platform where multiple learners can interact via the Internet.

[0543] An "operation simulation" is a virtual simulation that allows you to simulate the experience of specific operations or tasks in a virtual reality environment.

[0544] The present invention relates to a system for providing an optimal learning experience to a learner, and more particularly to a method for generating a learning program using a VR environment and an online community. The embodiment of the present invention is configured as follows.

[0545] Program Generation and Explanation

[0546] The server collects and stores personal information and interest information from the learner's device, including the learner's name, age, academic and technical level, and areas of interest. It also uses a generative AI to analyze this information. The generative AI uses a machine learning algorithm to generate an optimal learning plan based on the collected information.

[0547] The generated learning plans include simulated operations in a virtual reality environment. Learners can use a VR headset to experience real-world environments and operations in a virtual space. For example, in the case of automation technology training, robot operation and troubleshooting scenarios are simulated.

[0548] The server also provides an online community, creating an environment where multiple learners can interact in real time, allowing them to share their knowledge and experiences and maintain their motivation to learn.

[0549] Additionally, the generative AI tracks learners' progress and provides feedback, helping them to continually improve their learning.

[0550] Hardware and Software Use

[0551] Hardware: VR headset (e.g., Oculus Rift), user device (e.g., tablet, PC)

[0552] Software: Flask (Python web framework), generative AI model (for generating learning plans), VR simulation software, community platform, AI counseling system

[0553] Specific examples

[0554] When an engineer wants to learn how to operate a new robot, they access a terminal and enter their name, age, areas of interest, and level of automation technology skill. This information is stored on a server and analyzed by the generating AI. The generated learning plan includes simulations of operating the robot and troubleshooting.

[0555] Engineers put on a VR headset and begin practicing in a virtual environment, where they can actually operate the robot and answer interactive quizzes.

[0556] Engineers can also join online communities to deepen their learning while interacting with other like-minded engineers. Finally, they can consult with an AI counselor about their technical concerns and questions and receive appropriate advice.

[0557] Prompt Sentence Examples

[0558] Technician Information:

[0559] Name: Yamada

[0560] Age: 35

[0561] Area of ​​interest: Automation technology

[0562] Current Skill Level: Intermediate

[0563] Generate a personalized learning plan for this technician, including virtual reality simulations and interactive training modules.

[0564] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0565] Step 1:

[0566] A user creates an account by entering personal information and interests using a device. Specifically, the user enters their name, age, academic and technical level, and areas of interest. The entered information is sent from the device to a server and stored.

[0567] Input: User's personal information and interests

[0568] Output: User information stored on the server

[0569] Step 2:

[0570] The server retrieves the stored personal information and interest information and passes it to the generation AI, which analyzes this information and generates an optimal learning plan for the user. The learning plan includes specific learning content and operation simulations in a virtual reality environment.

[0571] Input: Stored Personal Information and Interests

[0572] Data processing: Information analysis using generative AI

[0573] Output: Optimal study plan

[0574] Step 3:

[0575] The server sends the generated learning plan to the user's device. The user then checks the learning plan and sets up the device to begin the learning experience in the virtual reality environment. Specifically, the user prepares a VR headset and enters the virtual environment.

[0576] Input: Optimal Study Plan

[0577] Output: The lesson plan displayed on the user's device

[0578] Step 4:

[0579] The user puts on a VR headset and begins simulating operations in a virtual reality environment. The server tracks the user's movements within the virtual environment and provides interactive quizzes and feedback. For example, a simulated robot operation or troubleshooting scenario is performed.

[0580] Input: User operation data, virtual reality environment

[0581] Output: Interactive quiz, feedback

[0582] Step 5:

[0583] The server tracks the user's learning progress and provides feedback based on the learning plan. The progress data is analyzed to present the user with additional learning content and advice.

[0584] Input: User progress data

[0585] Data processing: Analysis of progress data

[0586] Output: Feedback, additional learning content

[0587] Step 6:

[0588] Users access online communities and interact with other learners. The server manages data within the communities and supports smooth communication in real time. Users share their knowledge in forums and Q&A sessions.

[0589] Input: User's community participation information

[0590] Output: Interaction data within the online community

[0591] Step 7:

[0592] Users consult an AI counselor about their worries and questions about their studies. The server passes the user's question to the AI ​​counselor, who then responds with appropriate advice. The AI ​​counselor uses natural language processing to analyze the user's question and generate the most appropriate answer.

[0593] Input: User question data

[0594] Data processing: Question analysis using natural language processing

[0595] Output: Advice from an AI counselor

[0596] 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.

[0597] This invention is a system that provides an optimal learning experience for children who are not attending school, and aims to improve the effectiveness of learning and the quality of counseling by combining an emotion engine. The system includes a learning plan generated based on the learner's personal information and interests, a learning experience in a virtual reality environment, an online community, and emotion analysis using an emotion engine.

[0598] Specific operations and processing flow

[0599] First, a learner accesses the system and enters their personal information and interests. The data collected during this process is sent from the user's device to a server and stored in a database.

[0600] The server then uses generative AI to analyze the learner's data and generate a personalized learning plan that includes learning content selected based on the learner's interests and learning history. For example, if a user is interested in biology, a detailed learning plan on the molecular structure of DNA will be generated.

[0601] The generated learning plan is sent from the server to the user's device, and the user proceeds with their learning based on this plan. Specifically, the user can observe the molecular structure of DNA in 3D in a virtual reality environment, which deepens their understanding.

[0602] The emotion engine analyzes the user's facial expressions, voice, and text data to determine the user's emotional state in real time. For example, if the user shows a confused expression while studying, the emotion engine will recognize this and notify the server.

[0603] Based on this, the server dynamically adjusts the learning plan, for example by providing additional, clearer explanations or recommending counseling services.

[0604] Furthermore, users can participate in online communities and interact with other learners. The server manages community data in real time, ensuring that each user's posts and comments are updated immediately.

[0605] Emotion engines are also used in online communities to provide appropriate feedback and support by determining the emotional state of users as they interact with each other.

[0606] Specific examples

[0607] For example, consider the case where Learner B is using the system for the first time. Learner B creates an account and enters personal information and "history" as his or her subject of interest. The data is sent to the server and saved. The server then uses generative AI to generate a lesson plan on history. The plan includes content about the ancient Egyptian civilization, allowing the learner to experience the pyramid construction process in a virtual reality environment.

[0608] Learner B follows the lesson plan generated using the device, puts on a VR headset, and takes a virtual tour of a construction site in Egypt. Interactive quizzes are provided during the tour, and Learner B progresses by answering them. This experience allows Learner B to deepen his understanding of ancient civilizations.

[0609] Furthermore, Learner B's emotional state is monitored using an emotion engine. For example, if Learner B shows a confused expression, the server collects this information and immediately adjusts the learning content. Learner B also participates in an online community where he or she exchanges opinions about Egyptian civilization with other learners.

[0610] If Learner B enters their learning concerns on the counseling page, the AI ​​counselor will analyze them and provide appropriate advice. If the emotion engine recognizes stress or anxiety from the user's facial expressions or voice, the server will provide more specific and useful feedback.

[0611] As described above, the present invention realizes a system that achieves both learning effectiveness and psychological support by providing each learner with an individually optimized learning experience and emotional support.

[0612] The processing flow will be explained below.

[0613] Step 1:

[0614] A user launches the application and accesses the account creation page, where they enter information such as their name, age, subjects of interest, and learning level.

[0615] Step 2:

[0616] The device stores the input information in temporary memory and sends it to the server as JSON format data.

[0617] Step 3:

[0618] The server parses the received JSON data, stores the learner's personal information and interests in a database, and sends the user a confirmation message to create an account.

[0619] Step 4:

[0620] The server retrieves the user's learning history and interest information from the database and prepares to pass it on to the generation AI.

[0621] Step 5:

[0622] The AI ​​analyzes the acquired data and generates a learning plan that is optimal for the user. For example, if a user is interested in "history," it generates a plan that includes learning content such as "ancient Egyptian civilization."

[0623] Step 6:

[0624] The server stores the generated learning plan in a database and sends it to the user's device.

[0625] Step 7:

[0626] The user can view the lesson plan on the device and begin learning in a virtual reality environment. For example, the user can select the construction process of the Egyptian pyramids.

[0627] Step 8:

[0628] The device launches a VR module based on the selected learning content, and the user experiences learning in a virtual environment using a VR headset.

[0629] Step 9:

[0630] After the user has completed the VR learning experience, their learning progress is recorded on the device and sent to the server.

[0631] Step 10:

[0632] The learning progress received by the server is stored in a database and used to generate the next learning plan.

[0633] Step 11:

[0634] Users can access online communities to connect with other learners and post their learning experiences and questions.

[0635] Step 12:

[0636] The server manages community posting data in real time and notifies other users. The device receives the updated information and updates the community screen.

[0637] Step 13:

[0638] The user uses the emotion engine to recognize their emotional state during training by collecting facial and voice data using a camera and microphone, which is then sent from the device to a server.

[0639] Step 14:

[0640] The server passes the received emotional data to the emotion engine, which analyzes the user's emotional state in real time, for example, recognizing if the user is confused.

[0641] Step 15:

[0642] It provides a way for the server to dynamically adjust the learning plan based on the analysis results from the emotion engine. For example, if the user is confused, the server can provide additional explanations or hints.

[0643] Step 16:

[0644] As users continue to learn, they receive feedback based on their emotional changes. The emotion engine continuously monitors the user's emotional state and provides support as needed.

[0645] Step 17:

[0646] The user accesses the counseling page and enters the details of the consultation. The device sends the input data to the server.

[0647] Step 18:

[0648] The server passes the received counseling data to the AI ​​counselor, who then analyzes the input and generates appropriate advice and feedback.

[0649] Step 19:

[0650] The server sends the generated advice to the user's device, which displays the advice. The user receives feedback. The emotion engine monitors the user's emotional state during counseling and provides additional support.

[0651] The above steps will create a system that provides individually optimized learning experiences and emotional support, achieving both learning effectiveness and psychological support.

[0652] Example 2

[0653] 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."

[0654] Current learning systems are unable to provide learning plans that are adapted to each learner's emotional state and interests, limiting their effectiveness. Another issue is that it is difficult to provide optimal learning experiences and psychological support for children who are not attending school. Therefore, there is a need for a system that can simultaneously provide individually optimized learning experiences and psychological support by analyzing a learner's emotional state and dynamically adjusting learning plans in real time.

[0655] 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.

[0656] In this invention, the server includes means for inputting and saving personal information and interest information of a learner, means for generating a learning plan using a generation AI that acquires and analyzes the saved personal information and interest information, means for providing a learning experience in a virtual reality environment based on the generated learning plan, means for providing an online community where multiple learners can interact online, an emotion engine for analyzing the emotional state of the learner, and means for dynamically adjusting the learning plan based on information obtained from the emotion engine. This makes it possible to provide individually optimized learning plans and adjust the learning plan in accordance with the emotional state in real time.

[0657] "Learners" refers to individuals participating in educational activities, and in this system, the focus is primarily on out-of-school children.

[0658] "Personal information" refers to information that can identify a specific individual, including name, age, email address, etc.

[0659] "Interest information" refers to information about subjects or topics in which a learner is particularly interested.

[0660] "Generative AI" is artificial intelligence that performs specific tasks based on stored data, and in this case refers to an AI model that generates a learning plan.

[0661] "Study Plan" means an educational instruction plan optimized for an individual learner, including targeted content and activities.

[0662] "Virtual reality environment" refers to a virtual three-dimensional space generated using computer technology and used as a means to provide a learning experience.

[0663] An "online community" refers to a platform where multiple learners can interact over the Internet.

[0664] "Emotion engine" refers to technology that analyzes a learner's facial expressions, voice, and text data to determine their emotional state.

[0665] "Dynamic adjustment" refers to the process by which the system automatically modifies the learning plan in response to changing conditions in real time.

[0666] "Feedback" refers to assessment and advice provided based on learners' activities and progress.

[0667] This invention is a system that provides an optimal learning experience for children who are not attending school, and aims to improve the effectiveness of learning and the quality of counseling by combining an emotion engine. The system includes a learning plan generated based on the learner's personal information and interests, a learning experience in a virtual reality environment, an online community, and emotion analysis using an emotion engine.

[0668] First, the user accesses the system using their own device (PC, tablet, smartphone, etc.). The user accesses a form to enter personal information and interest information, and enters the required information. This data is temporarily stored on the device and then sent to the server. The server contains a database, and the received data is stored using a database management system (e.g., MySQL or PostgreSQL).

[0669] The server then uses a generative AI model (such as OpenAI's GPT-3) to analyze the stored data. The server takes into account the user's interests and past learning history to generate a personalized, optimized learning plan. This plan includes learning materials and activities that address the learner's interests. For example, if a user indicates an interest in "biology," the AI ​​will generate a detailed learning plan on the molecular structure of DNA.

[0670] The generated learning plan is sent from the server to the user's device. To progress through the learning process, the user wears a VR headset (e.g., Oculus Rift) and experiences the learning content in a virtual reality environment. Specifically, learners can observe the molecular structure of DNA in 3D and deepen their understanding by answering interactive quizzes in the VR environment.

[0671] This system incorporates an emotion engine that analyzes the learner's emotional state in real time. The emotion engine analyzes the user's facial expressions, voice, and text data to determine their emotional state. For example, if the user shows a confused expression, the emotion engine recognizes this and notifies the server. The server dynamically adjusts the learning plan based on feedback from the emotion engine. Specifically, it may provide additional explanations or recommend counseling.

[0672] Furthermore, users can join online communities and interact with other learners. The server manages community data in real time, ensuring that posts and comments are updated immediately. An emotion engine is also used within the online community to analyze the emotional state of users during interactions and provide appropriate feedback and support.

[0673] As a concrete example, consider the case where Learner B is using the system for the first time. Learner B creates an account and enters personal information and "history" as a subject of interest. The data is sent to the server and saved. The server then uses generative AI to generate a lesson plan on history. The plan includes content about the ancient Egyptian civilization and allows the learner to experience the pyramid construction process in a virtual reality environment.

[0674] Learner B follows the plan generated using the device, puts on a VR headset, and takes a virtual tour of a construction site in Egypt. Interactive quizzes are provided during the tour, and Learner B deepens his or her understanding of the ancient civilization by answering them as the tour progresses. In addition, an emotion engine monitors Learner B's emotional state while learning, and if Learner B shows a confused expression, the server immediately adjusts the learning content. Learner B can also participate in an online community and exchange opinions with other learners.

[0675] For generative AI models, use prompts like the following:

[0676] Prompt: "Student B is interested in the ancient Egyptian civilization. Generate a detailed lesson plan for Student B to use in a virtual reality environment using a VR headset."

[0677] In this way, the present invention provides learners with individually optimized learning experiences and emotional support, thereby improving learning effectiveness and psychological support at the same time.

[0678] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0679] Step 1: The user accesses the system and enters personal information and interest information.

[0680] Users access the system using their own devices (PC, tablet, smartphone). A form is displayed in which the user can enter personal information (such as name, age, and email address) and interest information (interesting subjects and topics). This data is temporarily stored on the device.

[0681] Input: Personal information and interests from the user.

[0682] Output: Input data that is temporarily stored on the device.

[0683] Step 2: The terminal sends the input data to the server.

[0684] The personal information and interest information temporarily stored on the device is sent to a server, where it is received and stored in a database.

[0685] Input: Input data temporarily stored on the device.

[0686] Output: The data sent to the server.

[0687] Step 3: The server saves the data in the database.

[0688] The server will store the received personal information and interest information permanently using a database management system (e.g., MySQL or PostgreSQL). This data will be used for subsequent analysis.

[0689] Input: The data sent to the server.

[0690] Output: Data stored in the database.

[0691] Step 4: The server generates a learning plan using the generative AI model.

[0692] The server generates a learning plan using a generative AI model (e.g., OpenAI's GPT-3) based on the user's personal information and interests stored in the database. The generative AI model analyzes the user's interests and past learning history and outputs an individually optimized learning plan.

[0693] Input: User data stored in the database.

[0694] Output: The generated lesson plan.

[0695] Step 5: The server sends the generated learning plan to the user's device.

[0696] The server then sends the generated learning plan to the user's device, which includes links to learning content and learning experiences in a virtual reality environment.

[0697] Input: The generated lesson plan.

[0698] Output: The study plan sent to the user's device.

[0699] Step 6: The user begins studying according to the study plan.

[0700] The user begins learning based on the received learning plan. Specifically, they put on a VR headset (e.g., Oculus Rift) and experience the learning content in a virtual reality environment. The user deepens their learning through interactive quizzes and activities.

[0701] Input: The study plan sent to the user's device.

[0702] Output: A learning experience in a VR environment.

[0703] Step 7: The emotion engine analyzes the user's emotional state during the learning process.

[0704] The emotion engine analyzes the user's facial expressions, voice, and text data in real time during learning to determine their emotional state (e.g., confusion, excitement, etc.). The analysis results of the emotion engine are sent to the server.

[0705] Input: User's facial expressions, voice, and text data.

[0706] Output: Parsed emotional state.

[0707] Step 8: The server dynamically adjusts the learning plan based on the emotional state.

[0708] The server dynamically adjusts the learning plan based on feedback from the emotion engine, for example, providing additional explanations or recommending counseling if the user is confused.

[0709] Input: Parsed emotional state.

[0710] Output: A tailored study plan.

[0711] Step 9: Users join the online community.

[0712] Users can join online communities within the system and interact with other learners. The server manages community posts and comments in real time and updates them instantly. An emotion engine is also used within the community to analyze the emotional state of users during interactions and provide appropriate feedback and support.

[0713] Input: User posts and comments.

[0714] Output: Online community interaction data.

[0715] (Application example 2)

[0716] 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."

[0717] In modern society, there is a need for appropriate learning support for children who are not attending school. However, there are not enough systems that provide individually optimized learning experiences or that can grasp children's emotional states in real time and respond appropriately. Furthermore, there are no established methods for students to interact with other students and deepen their understanding of their studies without feeling isolated.

[0718] 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 inputting and saving personal information and interest information of a learner, a learning plan generation device means for acquiring and analyzing the saved personal information and interest information, means for providing a learning experience in a virtual reality environment based on the generated learning plan, an emotion analysis engine means for analyzing the emotional state of the learner in real time, means for dynamically adjusting the learning plan based on the analyzed emotional state, and means for providing an online community in which multiple learners can interact online. This makes it possible to provide individually optimized learning experiences and emotional support for children who are not attending school, and to improve their learning effectiveness through interactions with other learners.

[0719] A "learning plan generation device" is a device that generates an optimal learning plan based on a learner's personal information and interest information.

[0720] A "virtual reality environment" is a computer-generated virtual environment that allows learners to have a realistic experience.

[0721] An "emotion analysis engine" is a device that analyzes a learner's facial expressions, voice, and text data to determine their emotional state in real time.

[0722] An "online community" is a virtual space where multiple learners can interact with each other and share information via the Internet.

[0723] A "learning plan" is a plan of learning content and activities that is structured based on the learner's interests and learning history.

[0724] An "interactive experience" is one in which learners actively participate and deepen their learning through two-way interaction.

[0725] "Feedback" is advice or corrective instruction provided based on a learner's learning progress or emotional state.

[0726] "Learning content" refers to the teaching materials and resources provided to learners, including text, images, video, audio, etc.

[0727] This invention is a system that provides optimal learning experiences for children who are not attending school, and aims to improve the effectiveness of learning and the quality of counseling by combining an emotion engine. The system consists of a learning plan generator, a virtual reality environment, an emotion analysis engine, and an online community.

[0728] First, a learner accesses the system from a terminal and enters personal information and information about their interests. This input data is sent to the server and stored in the server's database. The server then uses a learning plan generation device to analyze this data and generate an optimal learning plan for each learner. For example, if a learner is interested in history, a learning plan about ancient civilizations will be generated.

[0729] The generated learning plan is sent from the server to the learner's device and presented to them through the device. The learner then wears smart glasses or a head-mounted display and experiences the learning content in a virtual reality environment. For example, they can deepen their understanding by observing the construction process of the ancient Egyptian pyramids in 3D.

[0730] The emotion analysis engine analyzes the learner's facial expressions, voice, and text data in real time to determine their emotional state. If the learner feels confused or stressed, the emotion analysis engine sends that information to the server, which then dynamically adjusts the learning plan, for example by adding detailed explanations of difficult parts.

[0731] Learners can also participate in online communities and interact with other learners. The server manages the data from these online communities in real time and uses an emotion analysis engine to determine the emotional state of learners during their interactions. This allows appropriate feedback and support to be provided.

[0732] As a concrete example, consider the case where Learner B uses the system for the first time. Learner B creates an account and enters personal information and "history" as his or her subject of interest. The data is sent to the server and saved. The server uses generative AI to generate a history lesson plan and provides a learning experience in a virtual reality environment. If Learner B shows a confused expression, the emotion analysis engine detects this and the server adjusts the learning content.

[0733] An example of a prompt for a generative AI model is:

[0734] "A student shows a confused expression during a history lesson. Based on this, we provide additional explanations and generate advice from an AI counselor."

[0735] This allows the invention to realize an effective system that provides individually optimized learning experiences and emotional support to children who are not attending school.

[0736] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0737] Step 1:

[0738] This is the process where a user accesses the system from a terminal and inputs personal information and interest information. The input data is sent to the server and stored in the server's database. This is used as the basis for building a user profile. The input here is name, age, subjects of interest, etc., and the output is the profile data stored on the server.

[0739] Step 2:

[0740] The server retrieves the stored personal information and interest information, analyzes it using a learning plan generator, and generates an individually optimized learning plan. A generative AI model is used to create a plan containing detailed learning content based on past learning history and interest information. The input is profile data and past learning history, and the output is an individually customized learning plan.

[0741] Step 3:

[0742] The generated learning plan is sent from the server to the device. The user wears smart glasses or a head-mounted display and experiences the learning content in a virtual reality environment. Specifically, 3D models and interactive quizzes are used to provide visually realistic learning. The input here is the learning plan, and the output is the display of the learning content in a VR environment.

[0743] Step 4:

[0744] The emotion analysis engine analyzes the user's facial expression, voice, and text data in real time to determine their emotional state. For example, if a learner shows a confused expression, the facial expression data is sent to the server. The input here is real-time emotional data, and the output is the analyzed emotional state.

[0745] Step 5:

[0746] The server dynamically adjusts the learning plan based on the analyzed emotional state. For example, if the user is confused, the server receives that information and provides additional explanations or supplementary learning materials. The input is the analyzed emotional data, and the output is an adjusted learning plan.

[0747] Step 6:

[0748] Users can participate in online communities and interact with other learners. The server manages online community data in real time and uses an emotion analysis engine to determine the emotional state of learners during interactions. The input is real-time community data, and the output is appropriate feedback and support.

[0749] Through these steps, the system delivers an individually optimized learning experience and dynamically adjusts learning plans based on emotional state.

[0750] 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.

[0751] 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.

[0752] 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.

[0753] [Third embodiment]

[0754] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0755] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0756] 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).

[0757] 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.

[0758] 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.

[0759] 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).

[0760] 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.

[0761] 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.

[0762] 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.

[0763] 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.

[0764] 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.

[0765] 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."

[0766] The present invention is a system that provides an optimal learning experience for children who are not attending school, and the following means are used to realize this.

[0767] First, a learner accesses the system and enters personal information and interest information. Through this process, data such as the learner's name, age, academic level, and areas of interest are collected. This data is sent from the user's device to the server. This information is stored on the server and used to generate a learning plan.

[0768] The server then uses generative AI to analyze the collected data and generate an optimal learning plan for each individual. The generative AI automatically selects and plans relevant learning content based on the learner's interests and learning history. For example, a learner interested in history would be provided with a detailed learning plan on ancient Egyptian civilization.

[0769] The generated lesson plan is sent from the server to the user's device. The user can proceed with their studies based on this plan. The lesson plan includes experiential learning in a virtual reality environment, such as a virtual tour of the construction site of an Egyptian pyramid or a three-dimensional observation of the molecular structure of DNA. These VR experiences are realized by connecting the device to a VR headset or related devices.

[0770] Furthermore, learners can participate in online communities and interact with other learners. The server manages community data in real time and provides an environment that is easy to use even when multiple learners access the site simultaneously. Learners can share their learning progress and experiences, and exchange questions and advice.

[0771] Additionally, learners can use the counseling service if necessary. When a user accesses the counseling page and enters the details of their consultation, the server sends the data to an AI counselor. The AI ​​counselor analyzes the received information and provides appropriate advice and feedback. This helps to alleviate any anxieties or worries the learner may have.

[0772] Specific examples

[0773] For example, consider the case where Learner A is using an application for the first time. Learner A creates an account on their device and enters their name, age, subjects of interest (such as history), and current learning level. This information is sent to the server and stored. The server then uses generative AI to generate a detailed history lesson plan. This plan focuses on the ancient Egyptian civilization and includes content that allows the learner to experience the pyramid construction process in virtual reality.

[0774] Learner A follows the lesson plan generated on the device, puts on a VR headset, and takes a virtual tour of a construction site in Egypt. Interactive quizzes are provided during the tour, and Learner A can progress by answering them. This experience allows Learner A to deepen his understanding of ancient civilizations.

[0775] Furthermore, Learner A can access the online community and exchange opinions about Egyptian civilization with other learners. Finally, if Learner A wants to use counseling services, he or she can access the counseling page and enter his or her concerns about learning. The server will provide appropriate advice through an AI counselor to ease Learner A's anxiety.

[0776] As described above, this system can improve self-esteem and provide effective learning support to children who are not attending school by providing them with individually optimized learning experiences and opportunities for interaction.

[0777] The processing flow will be explained below.

[0778] Step 1:

[0779] A user launches the application and accesses the account creation page, where they enter information such as their name, age, subjects of interest, and learning level.

[0780] Step 2:

[0781] The device stores the input information in temporary memory and sends it to the server as JSON format data.

[0782] Step 3:

[0783] The server parses the received JSON data, stores the learner's personal information and interests in a database, and sends the user a confirmation message to create an account.

[0784] Step 4:

[0785] The server retrieves the user's learning history and interest information from the database and prepares to pass it on to the generation AI.

[0786] Step 5:

[0787] The generative AI analyzes the acquired data and generates an optimal learning plan for the user, which includes highly relevant learning content and experiences in a virtual reality environment.

[0788] Step 6:

[0789] The server stores the generated learning plan in a database and sends it to the user's device.

[0790] Step 7:

[0791] The user can view the lesson plan on the device and begin learning in a virtual reality environment. For example, the user can select the construction process of the Egyptian pyramids.

[0792] Step 8:

[0793] The device launches a VR module based on the selected learning content, and the user experiences learning in a virtual environment using a VR headset.

[0794] Step 9:

[0795] After the user has completed the VR learning experience, their learning progress is recorded on the device and sent to the server.

[0796] Step 10:

[0797] The learning progress received by the server is stored in a database and used to generate the next learning plan.

[0798] Step 11:

[0799] Users can access online communities to connect with other learners and post their learning experiences and questions.

[0800] Step 12:

[0801] The server manages community posting data in real time and notifies other users. The device receives the updated information and updates the community screen.

[0802] Step 13:

[0803] The user accesses the counseling page and enters the details of the consultation. The device sends the input data to the server.

[0804] Step 14:

[0805] The server passes the received counseling data to the AI ​​counselor, who then analyzes the input and generates appropriate advice and feedback.

[0806] Step 15:

[0807] The server sends the generated advice to the user's device, which displays the advice, and the user receives feedback.

[0808] Example 1

[0809] 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."

[0810] In modern society, it is becoming increasingly important for children who are not attending school to continue learning effectively and to improve their self-esteem. In particular, there is a need for individually optimized learning experiences and opportunities for interaction to reduce feelings of isolation. However, the traditional education system has not been able to adequately meet these needs.

[0811] 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.

[0812] In this invention, the server includes means for inputting and saving personal information and interest information of learners, means for generating a learning plan using a generation AI that acquires and analyzes the saved personal information and interest information, means for providing a learning experience in a virtual reality environment based on the generated learning plan, means for providing an online community where multiple learners can interact online, and means for transmitting the consultation details input by the learner to an AI counselor and providing appropriate advice and feedback. This provides individually optimized learning experiences and a place for interaction for children who are not attending school, improves their self-esteem, and enables effective learning support.

[0813] "Student" means an individual who uses the system and studies according to a study plan.

[0814] "Personal information" refers to information that can be used to identify a specific individual, such as a learner's name, age, academic level, and areas of interest.

[0815] "Interest information" refers to information that indicates a learner's interest or curiosity in a particular field or subject.

[0816] "Generative AI" refers to artificial intelligence that analyzes input data and generates individually optimized learning plans.

[0817] A "learning plan" is a learning plan or content generated by generative AI that is optimized for each individual learner.

[0818] A "virtual reality environment" is a computer-generated virtual learning environment that a user experiences using a device such as a VR headset.

[0819] An "online community" is a platform where multiple learners can interact and share information over the Internet.

[0820] An "AI counselor" is an artificial intelligence that analyzes the content of learners' consultations and provides appropriate advice and feedback.

[0821] An "interactive experience" is a two-way learning experience that progresses through learner participation and response.

[0822] "Feedback" refers to evaluation and advice provided to learners regarding their learning progress and behavior.

[0823] The present invention is a system that provides optimal learning experiences for children who are not attending school. This system is composed of users, terminals, and a server.

[0824] First, a user accesses the system using a device (such as a PC or smartphone). The user enters personal information and interest information such as name, age, academic level, and areas of interest. This information is sent from the user's device to the server and stored on the server.

[0825] The server analyzes the stored data and generates a learning plan using a generative AI model, which generates an individually optimized learning plan based on the input data. The software used for this includes machine learning libraries such as Python and TensorFlow.

[0826] The generated learning plan is sent from the server to the user's device and displayed on the device. The learning plan includes experiential learning in a virtual reality (VR) environment. Using a device such as a VR headset, users can experience a virtual tour of, for example, the ancient civilization of Egypt. This allows learners to deepen their understanding through interactive experiences.

[0827] Learners can also join online communities and interact with other learners. The server also manages the data of these online communities and updates it in real time, providing a comfortable environment for multiple learners to access the system simultaneously.

[0828] Furthermore, if users have any concerns about their studies, they can use the counseling service. When users input their concerns, the data is sent to a server, which then sends it to an AI counselor. The AI ​​counselor analyzes the concerns and provides appropriate advice and feedback.

[0829] Specific examples

[0830] For example, consider the case of Learner A using the system for the first time. Learner A creates an account on a device and enters his or her name, age, subjects of interest (such as history), and current academic level. This information is sent to and stored on the server. The server then uses a generative AI model to generate a detailed history lesson plan. This plan focuses on the ancient Egyptian civilization and includes content that allows the learner to experience the pyramid construction process in virtual reality.

[0831] Learner A follows the lesson plan generated on the device, puts on a VR headset, and takes a virtual tour of a construction site in Egypt. Interactive quizzes are provided during the tour, and Learner A can progress by answering them. This experience allows Learner A to deepen his understanding of ancient civilizations.

[0832] Furthermore, Learner A can access the online community and exchange opinions about Egyptian civilization with other learners. Finally, if Learner A wants to use counseling services, he or she can access the counseling page and enter his or her concerns about learning. The server will provide appropriate advice through an AI counselor to ease Learner A's anxiety.

[0833] Prompt Sentence Examples

[0834] "Student A is interested in history. Based on his current academic level and ongoing learning, generate a lesson plan on the ancient Egyptian civilization."

[0835] In this way, this system can provide children who are not attending school with individually optimized learning experiences and opportunities for interaction, thereby improving their self-esteem and providing effective learning support.

[0836] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0837] Program processing steps

[0838] Step 1: Enter and submit user information

[0839] Specific behavior:

[0840] A user accesses the system using a terminal and logs in by entering authentication information such as a username and password.

[0841] After logging in, users access a form where they can enter personal information and interests (such as name, age, academic level, and subjects of interest).

[0842] The input information is sent from the terminal to the server by pressing the send button.

[0843] input:

[0844] User personal information and interest information

[0845] output:

[0846] User information sent to the server

[0847] Step 2: Save your data

[0848] Specific behavior:

[0849] The server receives the user's personal information and interest information sent from the terminal.

[0850] Stores the received data in an internal database (e.g., MySQL or PostgreSQL).

[0851] input:

[0852] User information sent

[0853] output:

[0854] User information stored in a database

[0855] Step 3: Analyze the data and generate a learning plan

[0856] Specific behavior:

[0857] The server retrieves the user's personal information and interest information from the database.

[0858] The acquired data is then fed into a generative AI model, using a machine learning library such as TensorFlow or PyTorch.

[0859] A generative AI model analyzes the data and generates an individually optimized learning plan.

[0860] input:

[0861] User information retrieved from the database

[0862] output:

[0863] Generated Learning Plan

[0864] Step 4: Submit your study plan

[0865] Specific behavior:

[0866] The server transmits the generated study plan to the user's terminal.

[0867] The device receives the study plan and displays it to the user.

[0868] input:

[0869] Generated Learning Plan

[0870] output:

[0871] Study plans sent to the user's device

[0872] Step 5: Virtual reality learning experience

[0873] Specific behavior:

[0874] The user uses the device to set up a virtual reality (VR) learning environment by putting on a VR headset and launching a corresponding VR application.

[0875] The VR application creates a virtual reality environment based on the learning plan received from the server, providing the user with experiential learning.

[0876] input:

[0877] Learning plans sent to users

[0878] output:

[0879] Virtual reality learning experiences provided to users

[0880] Step 6: Access the online community

[0881] Specific behavior:

[0882] Users use terminals to access online communities within the system.

[0883] The server manages access from multiple users and updates data in real time.

[0884] Users can exchange opinions, ask questions, and post with other learners within the community.

[0885] input:

[0886] User information for community participation

[0887] output:

[0888] Real-time updated community data

[0889] Step 7: Access counseling services

[0890] Specific behavior:

[0891] The user accesses the counseling page using a terminal and inputs the concerns and questions about their studies.

[0892] The server sends the input data to the AI ​​counselor, who then analyzes the data using natural language processing technology and generates appropriate advice.

[0893] The advice is sent back to the user's terminal via the server and displayed on the screen.

[0894] input:

[0895] User consultation details

[0896] output:

[0897] Advice from an AI counselor

[0898] Through these steps, we can provide individually optimized learning experiences and opportunities for interaction for children who are not attending school, thereby improving their self-esteem.

[0899] (Application example 1)

[0900] 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."

[0901] The challenge is how to provide an individually optimized learning environment to improve technical skills and learning outcomes for children who are not attending school or for employee training. Traditional learning programs and training have made it difficult to provide optimal learning plans tailored to individual interests and skill levels. Furthermore, there has been a lack of methods to provide effective learning experiences, which has made it easy for learners to become isolated and difficult for them to continue learning.

[0902] 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.

[0903] In this invention, the server includes means for inputting and storing personal information and interest information of learners, means for generating a learning plan using a generation AI that acquires and analyzes the stored personal information and interest information, means for providing a learning experience in a virtual reality environment based on the generated learning plan, means for providing an online community where multiple learners can interact online, and means for providing an operation simulation in a virtual reality environment based on the generated learning plan to improve technical skills. This makes it possible to provide an optimal learning experience for individual learners and engineers, and to improve their technical skills and learning outcomes.

[0904] "Personal information and interest information of learners" refers to information that indicates the characteristics and interests of individual learners, such as the learner's name, age, academic ability / skill level, and areas of interest.

[0905] A "learning plan" is a plan that includes learning content and schedules that are optimal for a learner, created by a generative AI based on the learner's personal information and interests.

[0906] "Generative AI" is an artificial intelligence technology that analyzes a large amount of collected information and generates the optimal learning plan for each learner.

[0907] A "virtual reality environment" is a virtual space where learners can use a VR headset or similar device to experience real places and things in a highly realistic way.

[0908] An "online community" is a virtual communication platform where multiple learners can interact via the Internet.

[0909] An "operation simulation" is a virtual simulation that allows you to simulate the experience of specific operations or tasks in a virtual reality environment.

[0910] The present invention relates to a system for providing an optimal learning experience to a learner, and more particularly to a method for generating a learning program using a VR environment and an online community. The embodiment of the present invention is configured as follows.

[0911] Program Generation and Explanation

[0912] The server collects and stores personal information and interest information from the learner's device, including the learner's name, age, academic and technical level, and areas of interest. It also uses a generative AI to analyze this information. The generative AI uses a machine learning algorithm to generate an optimal learning plan based on the collected information.

[0913] The generated learning plans include simulated operations in a virtual reality environment. Learners can use a VR headset to experience real-world environments and operations in a virtual space. For example, in the case of automation technology training, robot operation and troubleshooting scenarios are simulated.

[0914] The server also provides an online community, creating an environment where multiple learners can interact in real time, allowing them to share their knowledge and experiences and maintain their motivation to learn.

[0915] Additionally, the generative AI tracks learners' progress and provides feedback, helping them to continually improve their learning.

[0916] Hardware and Software Use

[0917] Hardware: VR headset (e.g., Oculus Rift), user device (e.g., tablet, PC)

[0918] Software: Flask (Python web framework), generative AI model (for generating learning plans), VR simulation software, community platform, AI counseling system

[0919] Specific examples

[0920] When an engineer wants to learn how to operate a new robot, they access a terminal and enter their name, age, areas of interest, and level of automation technology skill. This information is stored on a server and analyzed by the generating AI. The generated learning plan includes simulations of operating the robot and troubleshooting.

[0921] Engineers put on a VR headset and begin practicing in a virtual environment, where they can actually operate the robot and answer interactive quizzes.

[0922] Engineers can also join online communities to deepen their learning while interacting with other like-minded engineers. Finally, they can consult with an AI counselor about their technical concerns and questions and receive appropriate advice.

[0923] Prompt Sentence Examples

[0924] Technician Information:

[0925] Name: Yamada

[0926] Age: 35

[0927] Area of ​​interest: Automation technology

[0928] Current Skill Level: Intermediate

[0929] Generate a personalized learning plan for this technician, including virtual reality simulations and interactive training modules.

[0930] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0931] Step 1:

[0932] A user creates an account by entering personal information and interests using a device. Specifically, the user enters their name, age, academic and technical level, and areas of interest. The entered information is sent from the device to a server and stored.

[0933] Input: User's personal information and interests

[0934] Output: User information stored on the server

[0935] Step 2:

[0936] The server retrieves the stored personal information and interest information and passes it to the generation AI, which analyzes this information and generates an optimal learning plan for the user. The learning plan includes specific learning content and operation simulations in a virtual reality environment.

[0937] Input: Stored Personal Information and Interests

[0938] Data processing: Information analysis using generative AI

[0939] Output: Optimal study plan

[0940] Step 3:

[0941] The server sends the generated learning plan to the user's device. The user then checks the learning plan and sets up the device to begin the learning experience in the virtual reality environment. Specifically, the user prepares a VR headset and enters the virtual environment.

[0942] Input: Optimal Study Plan

[0943] Output: The lesson plan displayed on the user's device

[0944] Step 4:

[0945] The user puts on a VR headset and begins simulating operations in a virtual reality environment. The server tracks the user's movements within the virtual environment and provides interactive quizzes and feedback. For example, a simulated robot operation or troubleshooting scenario is performed.

[0946] Input: User operation data, virtual reality environment

[0947] Output: Interactive quiz, feedback

[0948] Step 5:

[0949] The server tracks the user's learning progress and provides feedback based on the learning plan. The progress data is analyzed to present the user with additional learning content and advice.

[0950] Input: User progress data

[0951] Data processing: Analysis of progress data

[0952] Output: Feedback, additional learning content

[0953] Step 6:

[0954] Users access online communities and interact with other learners. The server manages data within the communities and supports smooth communication in real time. Users share their knowledge in forums and Q&A sessions.

[0955] Input: User's community participation information

[0956] Output: Interaction data within the online community

[0957] Step 7:

[0958] Users consult an AI counselor about their worries and questions about their studies. The server passes the user's question to the AI ​​counselor, who then responds with appropriate advice. The AI ​​counselor uses natural language processing to analyze the user's question and generate the most appropriate answer.

[0959] Input: User question data

[0960] Data processing: Question analysis using natural language processing

[0961] Output: Advice from an AI counselor

[0962] 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.

[0963] This invention is a system that provides an optimal learning experience for children who are not attending school, and aims to improve the effectiveness of learning and the quality of counseling by combining an emotion engine. The system includes a learning plan generated based on the learner's personal information and interests, a learning experience in a virtual reality environment, an online community, and emotion analysis using an emotion engine.

[0964] Specific operations and processing flow

[0965] First, a learner accesses the system and enters their personal information and interests. The data collected during this process is sent from the user's device to a server and stored in a database.

[0966] The server then uses generative AI to analyze the learner's data and generate a personalized learning plan that includes learning content selected based on the learner's interests and learning history. For example, if a user is interested in biology, a detailed learning plan on the molecular structure of DNA will be generated.

[0967] The generated learning plan is sent from the server to the user's device, and the user proceeds with their learning based on this plan. Specifically, the user can observe the molecular structure of DNA in 3D in a virtual reality environment, which deepens their understanding.

[0968] The emotion engine analyzes the user's facial expressions, voice, and text data to determine the user's emotional state in real time. For example, if the user shows a confused expression while studying, the emotion engine will recognize this and notify the server.

[0969] Based on this, the server dynamically adjusts the learning plan, for example by providing additional, clearer explanations or recommending counseling services.

[0970] Furthermore, users can participate in online communities and interact with other learners. The server manages community data in real time, ensuring that each user's posts and comments are updated immediately.

[0971] Emotion engines are also used in online communities to provide appropriate feedback and support by determining the emotional state of users as they interact with each other.

[0972] Specific examples

[0973] For example, consider the case where Learner B is using the system for the first time. Learner B creates an account and enters personal information and "history" as his or her subject of interest. The data is sent to the server and saved. The server then uses generative AI to generate a lesson plan on history. The plan includes content about the ancient Egyptian civilization, allowing the learner to experience the pyramid construction process in a virtual reality environment.

[0974] Learner B follows the lesson plan generated using the device, puts on a VR headset, and takes a virtual tour of a construction site in Egypt. Interactive quizzes are provided during the tour, and Learner B progresses by answering them. This experience allows Learner B to deepen his understanding of ancient civilizations.

[0975] Furthermore, Learner B's emotional state is monitored using an emotion engine. For example, if Learner B shows a confused expression, the server collects this information and immediately adjusts the learning content. Learner B also participates in an online community where he or she exchanges opinions about Egyptian civilization with other learners.

[0976] If Learner B enters their learning concerns on the counseling page, the AI ​​counselor will analyze them and provide appropriate advice. If the emotion engine recognizes stress or anxiety from the user's facial expressions or voice, the server will provide more specific and useful feedback.

[0977] As described above, the present invention realizes a system that achieves both learning effectiveness and psychological support by providing each learner with an individually optimized learning experience and emotional support.

[0978] The processing flow will be explained below.

[0979] Step 1:

[0980] A user launches the application and accesses the account creation page, where they enter information such as their name, age, subjects of interest, and learning level.

[0981] Step 2:

[0982] The device stores the input information in temporary memory and sends it to the server as JSON format data.

[0983] Step 3:

[0984] The server parses the received JSON data, stores the learner's personal information and interests in a database, and sends the user a confirmation message to create an account.

[0985] Step 4:

[0986] The server retrieves the user's learning history and interest information from the database and prepares to pass it on to the generation AI.

[0987] Step 5:

[0988] The AI ​​analyzes the acquired data and generates a learning plan that is optimal for the user. For example, if a user is interested in "history," it generates a plan that includes learning content such as "ancient Egyptian civilization."

[0989] Step 6:

[0990] The server stores the generated learning plan in a database and sends it to the user's device.

[0991] Step 7:

[0992] The user can view the lesson plan on the device and begin learning in a virtual reality environment. For example, the user can select the construction process of the Egyptian pyramids.

[0993] Step 8:

[0994] The device launches a VR module based on the selected learning content, and the user experiences learning in a virtual environment using a VR headset.

[0995] Step 9:

[0996] After the user has completed the VR learning experience, their learning progress is recorded on the device and sent to the server.

[0997] Step 10:

[0998] The learning progress received by the server is stored in a database and used to generate the next learning plan.

[0999] Step 11:

[1000] Users can access online communities to connect with other learners and post their learning experiences and questions.

[1001] Step 12:

[1002] The server manages community posting data in real time and notifies other users. The device receives the updated information and updates the community screen.

[1003] Step 13:

[1004] The user uses the emotion engine to recognize their emotional state during training by collecting facial and voice data using a camera and microphone, which is then sent from the device to a server.

[1005] Step 14:

[1006] The server passes the received emotional data to the emotion engine, which analyzes the user's emotional state in real time, for example, recognizing if the user is confused.

[1007] Step 15:

[1008] It provides a way for the server to dynamically adjust the learning plan based on the analysis results from the emotion engine. For example, if the user is confused, the server can provide additional explanations or hints.

[1009] Step 16:

[1010] As users continue to learn, they receive feedback based on their emotional changes. The emotion engine continuously monitors the user's emotional state and provides support as needed.

[1011] Step 17:

[1012] The user accesses the counseling page and enters the details of the consultation. The device sends the input data to the server.

[1013] Step 18:

[1014] The server passes the received counseling data to the AI ​​counselor, who then analyzes the input and generates appropriate advice and feedback.

[1015] Step 19:

[1016] The server sends the generated advice to the user's device, which displays the advice. The user receives feedback. The emotion engine monitors the user's emotional state during counseling and provides additional support.

[1017] The above steps will create a system that provides individually optimized learning experiences and emotional support, achieving both learning effectiveness and psychological support.

[1018] Example 2

[1019] 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."

[1020] Current learning systems are unable to provide learning plans that are adapted to each learner's emotional state and interests, limiting their effectiveness. Another issue is that it is difficult to provide optimal learning experiences and psychological support for children who are not attending school. Therefore, there is a need for a system that can simultaneously provide individually optimized learning experiences and psychological support by analyzing a learner's emotional state and dynamically adjusting learning plans in real time.

[1021] 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.

[1022] In this invention, the server includes means for inputting and saving personal information and interest information of a learner, means for generating a learning plan using a generation AI that acquires and analyzes the saved personal information and interest information, means for providing a learning experience in a virtual reality environment based on the generated learning plan, means for providing an online community where multiple learners can interact online, an emotion engine for analyzing the emotional state of the learner, and means for dynamically adjusting the learning plan based on information obtained from the emotion engine. This makes it possible to provide individually optimized learning plans and adjust the learning plan in accordance with the emotional state in real time.

[1023] "Learners" refers to individuals participating in educational activities, and in this system, the focus is primarily on out-of-school children.

[1024] "Personal information" refers to information that can identify a specific individual, including name, age, email address, etc.

[1025] "Interest information" refers to information about subjects or topics in which a learner is particularly interested.

[1026] "Generative AI" is artificial intelligence that performs specific tasks based on stored data, and in this case refers to an AI model that generates a learning plan.

[1027] "Study Plan" means an educational instruction plan optimized for an individual learner, including targeted content and activities.

[1028] "Virtual reality environment" refers to a virtual three-dimensional space generated using computer technology and used as a means to provide a learning experience.

[1029] An "online community" refers to a platform where multiple learners can interact over the Internet.

[1030] "Emotion engine" refers to technology that analyzes a learner's facial expressions, voice, and text data to determine their emotional state.

[1031] "Dynamic adjustment" refers to the process by which the system automatically modifies the learning plan in response to changing conditions in real time.

[1032] "Feedback" refers to assessment and advice provided based on learners' activities and progress.

[1033] This invention is a system that provides an optimal learning experience for children who are not attending school, and aims to improve the effectiveness of learning and the quality of counseling by combining an emotion engine. The system includes a learning plan generated based on the learner's personal information and interests, a learning experience in a virtual reality environment, an online community, and emotion analysis using an emotion engine.

[1034] First, the user accesses the system using their own device (PC, tablet, smartphone, etc.). The user accesses a form to enter personal information and interest information, and enters the required information. This data is temporarily stored on the device and then sent to the server. The server contains a database, and the received data is stored using a database management system (e.g., MySQL or PostgreSQL).

[1035] The server then uses a generative AI model (such as OpenAI's GPT-3) to analyze the stored data. The server takes into account the user's interests and past learning history to generate a personalized, optimized learning plan. This plan includes learning materials and activities that address the learner's interests. For example, if a user indicates an interest in "biology," the AI ​​will generate a detailed learning plan on the molecular structure of DNA.

[1036] The generated learning plan is sent from the server to the user's device. To progress through the learning process, the user wears a VR headset (e.g., Oculus Rift) and experiences the learning content in a virtual reality environment. Specifically, learners can observe the molecular structure of DNA in 3D and deepen their understanding by answering interactive quizzes in the VR environment.

[1037] This system incorporates an emotion engine that analyzes the learner's emotional state in real time. The emotion engine analyzes the user's facial expressions, voice, and text data to determine their emotional state. For example, if the user shows a confused expression, the emotion engine recognizes this and notifies the server. The server dynamically adjusts the learning plan based on feedback from the emotion engine. Specifically, it may provide additional explanations or recommend counseling.

[1038] Furthermore, users can join online communities and interact with other learners. The server manages community data in real time, ensuring that posts and comments are updated immediately. An emotion engine is also used within the online community to analyze the emotional state of users during interactions and provide appropriate feedback and support.

[1039] As a concrete example, consider the case where Learner B is using the system for the first time. Learner B creates an account and enters personal information and "history" as a subject of interest. The data is sent to the server and saved. The server then uses generative AI to generate a lesson plan on history. The plan includes content about the ancient Egyptian civilization and allows the learner to experience the pyramid construction process in a virtual reality environment.

[1040] Learner B follows the plan generated using the device, puts on a VR headset, and takes a virtual tour of a construction site in Egypt. Interactive quizzes are provided during the tour, and Learner B deepens his or her understanding of the ancient civilization by answering them as the tour progresses. In addition, an emotion engine monitors Learner B's emotional state while learning, and if Learner B shows a confused expression, the server immediately adjusts the learning content. Learner B can also participate in an online community and exchange opinions with other learners.

[1041] For generative AI models, use prompts like the following:

[1042] Prompt: "Student B is interested in the ancient Egyptian civilization. Generate a detailed lesson plan for Student B to use in a virtual reality environment using a VR headset."

[1043] In this way, the present invention provides learners with individually optimized learning experiences and emotional support, thereby improving learning effectiveness and psychological support at the same time.

[1044] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1045] Step 1: The user accesses the system and enters personal information and interest information.

[1046] Users access the system using their own devices (PC, tablet, smartphone). A form is displayed in which the user can enter personal information (such as name, age, and email address) and interest information (interesting subjects and topics). This data is temporarily stored on the device.

[1047] Input: Personal information and interests from the user.

[1048] Output: Input data that is temporarily stored on the device.

[1049] Step 2: The terminal sends the input data to the server.

[1050] The personal information and interest information temporarily stored on the device is sent to a server, where it is received and stored in a database.

[1051] Input: Input data temporarily stored on the device.

[1052] Output: The data sent to the server.

[1053] Step 3: The server saves the data in the database.

[1054] The server will store the received personal information and interest information permanently using a database management system (e.g., MySQL or PostgreSQL). This data will be used for subsequent analysis.

[1055] Input: The data sent to the server.

[1056] Output: Data stored in the database.

[1057] Step 4: The server generates a learning plan using the generative AI model.

[1058] The server generates a learning plan using a generative AI model (e.g., OpenAI's GPT-3) based on the user's personal information and interests stored in the database. The generative AI model analyzes the user's interests and past learning history and outputs an individually optimized learning plan.

[1059] Input: User data stored in the database.

[1060] Output: The generated lesson plan.

[1061] Step 5: The server sends the generated learning plan to the user's device.

[1062] The server then sends the generated learning plan to the user's device, which includes links to learning content and learning experiences in a virtual reality environment.

[1063] Input: The generated lesson plan.

[1064] Output: The study plan sent to the user's device.

[1065] Step 6: The user begins studying according to the study plan.

[1066] The user begins learning based on the received learning plan. Specifically, they put on a VR headset (e.g., Oculus Rift) and experience the learning content in a virtual reality environment. The user deepens their learning through interactive quizzes and activities.

[1067] Input: The study plan sent to the user's device.

[1068] Output: A learning experience in a VR environment.

[1069] Step 7: The emotion engine analyzes the user's emotional state during the learning process.

[1070] The emotion engine analyzes the user's facial expressions, voice, and text data in real time during learning to determine their emotional state (e.g., confusion, excitement, etc.). The analysis results of the emotion engine are sent to the server.

[1071] Input: User's facial expressions, voice, and text data.

[1072] Output: Parsed emotional state.

[1073] Step 8: The server dynamically adjusts the learning plan based on the emotional state.

[1074] The server dynamically adjusts the learning plan based on feedback from the emotion engine, for example, providing additional explanations or recommending counseling if the user is confused.

[1075] Input: Parsed emotional state.

[1076] Output: A tailored study plan.

[1077] Step 9: Users join the online community.

[1078] Users can join online communities within the system and interact with other learners. The server manages community posts and comments in real time and updates them instantly. An emotion engine is also used within the community to analyze the emotional state of users during interactions and provide appropriate feedback and support.

[1079] Input: User posts and comments.

[1080] Output: Online community interaction data.

[1081] (Application example 2)

[1082] 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."

[1083] In modern society, there is a need for appropriate learning support for children who are not attending school. However, there are not enough systems that provide individually optimized learning experiences or that can grasp children's emotional states in real time and respond appropriately. Furthermore, there are no established methods for students to interact with other students and deepen their understanding of their studies without feeling isolated.

[1084] 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 inputting and saving personal information and interest information of a learner, a learning plan generation device means for acquiring and analyzing the saved personal information and interest information, means for providing a learning experience in a virtual reality environment based on the generated learning plan, an emotion analysis engine means for analyzing the emotional state of the learner in real time, means for dynamically adjusting the learning plan based on the analyzed emotional state, and means for providing an online community in which multiple learners can interact online. This makes it possible to provide individually optimized learning experiences and emotional support for children who are not attending school, and to improve their learning effectiveness through interactions with other learners.

[1085] A "learning plan generation device" is a device that generates an optimal learning plan based on a learner's personal information and interest information.

[1086] A "virtual reality environment" is a computer-generated virtual environment that allows learners to have a realistic experience.

[1087] An "emotion analysis engine" is a device that analyzes a learner's facial expressions, voice, and text data to determine their emotional state in real time.

[1088] An "online community" is a virtual space where multiple learners can interact with each other and share information via the Internet.

[1089] A "learning plan" is a plan of learning content and activities that is structured based on the learner's interests and learning history.

[1090] An "interactive experience" is one in which learners actively participate and deepen their learning through two-way interaction.

[1091] "Feedback" is advice or corrective instruction provided based on a learner's learning progress or emotional state.

[1092] "Learning content" refers to the teaching materials and resources provided to learners, including text, images, video, audio, etc.

[1093] This invention is a system that provides optimal learning experiences for children who are not attending school, and aims to improve the effectiveness of learning and the quality of counseling by combining an emotion engine. The system consists of a learning plan generator, a virtual reality environment, an emotion analysis engine, and an online community.

[1094] First, a learner accesses the system from a terminal and enters personal information and information about their interests. This input data is sent to the server and stored in the server's database. The server then uses a learning plan generation device to analyze this data and generate an optimal learning plan for each learner. For example, if a learner is interested in history, a learning plan about ancient civilizations will be generated.

[1095] The generated learning plan is sent from the server to the learner's device and presented to them through the device. The learner then wears smart glasses or a head-mounted display and experiences the learning content in a virtual reality environment. For example, they can deepen their understanding by observing the construction process of the ancient Egyptian pyramids in 3D.

[1096] The emotion analysis engine analyzes the learner's facial expressions, voice, and text data in real time to determine their emotional state. If the learner feels confused or stressed, the emotion analysis engine sends that information to the server, which then dynamically adjusts the learning plan, for example by adding detailed explanations of difficult parts.

[1097] Learners can also participate in online communities and interact with other learners. The server manages the data from these online communities in real time and uses an emotion analysis engine to determine the emotional state of learners during their interactions. This allows appropriate feedback and support to be provided.

[1098] As a concrete example, consider the case where Learner B uses the system for the first time. Learner B creates an account and enters personal information and "history" as his or her subject of interest. The data is sent to the server and saved. The server uses generative AI to generate a history lesson plan and provides a learning experience in a virtual reality environment. If Learner B shows a confused expression, the emotion analysis engine detects this and the server adjusts the learning content.

[1099] An example of a prompt for a generative AI model is:

[1100] "A student shows a confused expression during a history lesson. Based on this, we provide additional explanations and generate advice from an AI counselor."

[1101] This allows the invention to realize an effective system that provides individually optimized learning experiences and emotional support to children who are not attending school.

[1102] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1103] Step 1:

[1104] This is the process where a user accesses the system from a terminal and inputs personal information and interest information. The input data is sent to the server and stored in the server's database. This is used as the basis for building a user profile. The input here is name, age, subjects of interest, etc., and the output is the profile data stored on the server.

[1105] Step 2:

[1106] The server retrieves the stored personal information and interest information, analyzes it using a learning plan generator, and generates an individually optimized learning plan. A generative AI model is used to create a plan containing detailed learning content based on past learning history and interest information. The input is profile data and past learning history, and the output is an individually customized learning plan.

[1107] Step 3:

[1108] The generated learning plan is sent from the server to the device. The user wears smart glasses or a head-mounted display and experiences the learning content in a virtual reality environment. Specifically, 3D models and interactive quizzes are used to provide visually realistic learning. The input here is the learning plan, and the output is the display of the learning content in a VR environment.

[1109] Step 4:

[1110] The emotion analysis engine analyzes the user's facial expression, voice, and text data in real time to determine their emotional state. For example, if a learner shows a confused expression, the facial expression data is sent to the server. The input here is real-time emotional data, and the output is the analyzed emotional state.

[1111] Step 5:

[1112] The server dynamically adjusts the learning plan based on the analyzed emotional state. For example, if the user is confused, the server receives that information and provides additional explanations or supplementary learning materials. The input is the analyzed emotional data, and the output is an adjusted learning plan.

[1113] Step 6:

[1114] Users can participate in online communities and interact with other learners. The server manages online community data in real time and uses an emotion analysis engine to determine the emotional state of learners during interactions. The input is real-time community data, and the output is appropriate feedback and support.

[1115] Through these steps, the system delivers an individually optimized learning experience and dynamically adjusts learning plans based on emotional state.

[1116] 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.

[1117] 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.

[1118] 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.

[1119] [Fourth embodiment]

[1120] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1121] 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.

[1122] 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).

[1123] 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.

[1124] 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.

[1125] 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).

[1126] 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.

[1127] 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.

[1128] 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.

[1129] 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.

[1130] 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.

[1131] 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.

[1132] 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."

[1133] The present invention is a system that provides an optimal learning experience for children who are not attending school, and the following means are used to realize this.

[1134] First, a learner accesses the system and enters personal information and interest information. Through this process, data such as the learner's name, age, academic level, and areas of interest are collected. This data is sent from the user's device to the server. This information is stored on the server and used to generate a learning plan.

[1135] The server then uses generative AI to analyze the collected data and generate an optimal learning plan for each individual. The generative AI automatically selects and plans relevant learning content based on the learner's interests and learning history. For example, a learner interested in history would be provided with a detailed learning plan on ancient Egyptian civilization.

[1136] The generated lesson plan is sent from the server to the user's device. The user can proceed with their studies based on this plan. The lesson plan includes experiential learning in a virtual reality environment, such as a virtual tour of the construction site of an Egyptian pyramid or a three-dimensional observation of the molecular structure of DNA. These VR experiences are realized by connecting the device to a VR headset or related devices.

[1137] Furthermore, learners can participate in online communities and interact with other learners. The server manages community data in real time and provides an environment that is easy to use even when multiple learners access the site simultaneously. Learners can share their learning progress and experiences, and exchange questions and advice.

[1138] Additionally, learners can use the counseling service if necessary. When a user accesses the counseling page and enters the details of their consultation, the server sends the data to an AI counselor. The AI ​​counselor analyzes the received information and provides appropriate advice and feedback. This helps to alleviate any anxieties or worries the learner may have.

[1139] Specific examples

[1140] For example, consider the case where Learner A is using an application for the first time. Learner A creates an account on their device and enters their name, age, subjects of interest (such as history), and current learning level. This information is sent to the server and stored. The server then uses generative AI to generate a detailed history lesson plan. This plan focuses on the ancient Egyptian civilization and includes content that allows the learner to experience the pyramid construction process in virtual reality.

[1141] Learner A follows the lesson plan generated on the device, puts on a VR headset, and takes a virtual tour of a construction site in Egypt. Interactive quizzes are provided during the tour, and Learner A can progress by answering them. This experience allows Learner A to deepen his understanding of ancient civilizations.

[1142] Furthermore, Learner A can access the online community and exchange opinions about Egyptian civilization with other learners. Finally, if Learner A wants to use counseling services, he or she can access the counseling page and enter his or her concerns about learning. The server will provide appropriate advice through an AI counselor to ease Learner A's anxiety.

[1143] As described above, this system can improve self-esteem and provide effective learning support to children who are not attending school by providing them with individually optimized learning experiences and opportunities for interaction.

[1144] The processing flow will be explained below.

[1145] Step 1:

[1146] A user launches the application and accesses the account creation page, where they enter information such as their name, age, subjects of interest, and learning level.

[1147] Step 2:

[1148] The device stores the input information in temporary memory and sends it to the server as JSON format data.

[1149] Step 3:

[1150] The server parses the received JSON data, stores the learner's personal information and interests in a database, and sends the user a confirmation message to create an account.

[1151] Step 4:

[1152] The server retrieves the user's learning history and interest information from the database and prepares to pass it on to the generation AI.

[1153] Step 5:

[1154] The generative AI analyzes the acquired data and generates an optimal learning plan for the user, which includes highly relevant learning content and experiences in a virtual reality environment.

[1155] Step 6:

[1156] The server stores the generated learning plan in a database and sends it to the user's device.

[1157] Step 7:

[1158] The user can view the lesson plan on the device and begin learning in a virtual reality environment. For example, the user can select the construction process of the Egyptian pyramids.

[1159] Step 8:

[1160] The device launches a VR module based on the selected learning content, and the user experiences learning in a virtual environment using a VR headset.

[1161] Step 9:

[1162] After the user has completed the VR learning experience, their learning progress is recorded on the device and sent to the server.

[1163] Step 10:

[1164] The learning progress received by the server is stored in a database and used to generate the next learning plan.

[1165] Step 11:

[1166] Users can access online communities to connect with other learners and post their learning experiences and questions.

[1167] Step 12:

[1168] The server manages community posting data in real time and notifies other users. The device receives the updated information and updates the community screen.

[1169] Step 13:

[1170] The user accesses the counseling page and enters the details of the consultation. The device sends the input data to the server.

[1171] Step 14:

[1172] The server passes the received counseling data to the AI ​​counselor, who then analyzes the input and generates appropriate advice and feedback.

[1173] Step 15:

[1174] The server sends the generated advice to the user's device, which displays the advice, and the user receives feedback.

[1175] Example 1

[1176] 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."

[1177] In modern society, it is becoming increasingly important for children who are not attending school to continue learning effectively and to improve their self-esteem. In particular, there is a need for individually optimized learning experiences and opportunities for interaction to reduce feelings of isolation. However, the traditional education system has not been able to adequately meet these needs.

[1178] 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.

[1179] In this invention, the server includes means for inputting and saving personal information and interest information of learners, means for generating a learning plan using a generation AI that acquires and analyzes the saved personal information and interest information, means for providing a learning experience in a virtual reality environment based on the generated learning plan, means for providing an online community where multiple learners can interact online, and means for transmitting the consultation details input by the learner to an AI counselor and providing appropriate advice and feedback. This provides individually optimized learning experiences and a place for interaction for children who are not attending school, improves their self-esteem, and enables effective learning support.

[1180] "Student" means an individual who uses the system and studies according to a study plan.

[1181] "Personal information" refers to information that can be used to identify a specific individual, such as a learner's name, age, academic level, and areas of interest.

[1182] "Interest information" refers to information that indicates a learner's interest or curiosity in a particular field or subject.

[1183] "Generative AI" refers to artificial intelligence that analyzes input data and generates individually optimized learning plans.

[1184] A "learning plan" is a learning plan or content generated by generative AI that is optimized for each individual learner.

[1185] A "virtual reality environment" is a computer-generated virtual learning environment that a user experiences using a device such as a VR headset.

[1186] An "online community" is a platform where multiple learners can interact and share information over the Internet.

[1187] An "AI counselor" is an artificial intelligence that analyzes the content of learners' consultations and provides appropriate advice and feedback.

[1188] An "interactive experience" is a two-way learning experience that progresses through learner participation and response.

[1189] "Feedback" refers to evaluation and advice provided to learners regarding their learning progress and behavior.

[1190] The present invention is a system that provides optimal learning experiences for children who are not attending school. This system is composed of users, terminals, and a server.

[1191] First, a user accesses the system using a device (such as a PC or smartphone). The user enters personal information and interest information such as name, age, academic level, and areas of interest. This information is sent from the user's device to the server and stored on the server.

[1192] The server analyzes the stored data and generates a learning plan using a generative AI model, which generates an individually optimized learning plan based on the input data. The software used for this includes machine learning libraries such as Python and TensorFlow.

[1193] The generated learning plan is sent from the server to the user's device and displayed on the device. The learning plan includes experiential learning in a virtual reality (VR) environment. Using a device such as a VR headset, users can experience a virtual tour of, for example, the ancient civilization of Egypt. This allows learners to deepen their understanding through interactive experiences.

[1194] Learners can also join online communities and interact with other learners. The server also manages the data of these online communities and updates it in real time, providing a comfortable environment for multiple learners to access the system simultaneously.

[1195] Furthermore, if users have any concerns about their studies, they can use the counseling service. When users input their concerns, the data is sent to a server, which then sends it to an AI counselor. The AI ​​counselor analyzes the concerns and provides appropriate advice and feedback.

[1196] Specific examples

[1197] For example, consider the case of Learner A using the system for the first time. Learner A creates an account on a device and enters his or her name, age, subjects of interest (such as history), and current academic level. This information is sent to and stored on the server. The server then uses a generative AI model to generate a detailed history lesson plan. This plan focuses on the ancient Egyptian civilization and includes content that allows the learner to experience the pyramid construction process in virtual reality.

[1198] Learner A follows the lesson plan generated on the device, puts on a VR headset, and takes a virtual tour of a construction site in Egypt. Interactive quizzes are provided during the tour, and Learner A can progress by answering them. This experience allows Learner A to deepen his understanding of ancient civilizations.

[1199] Furthermore, Learner A can access the online community and exchange opinions about Egyptian civilization with other learners. Finally, if Learner A wants to use counseling services, he or she can access the counseling page and enter his or her concerns about learning. The server will provide appropriate advice through an AI counselor to ease Learner A's anxiety.

[1200] Prompt Sentence Examples

[1201] "Student A is interested in history. Based on his current academic level and ongoing learning, generate a lesson plan on the ancient Egyptian civilization."

[1202] In this way, this system can provide children who are not attending school with individually optimized learning experiences and opportunities for interaction, thereby improving their self-esteem and providing effective learning support.

[1203] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1204] Program processing steps

[1205] Step 1: Enter and submit user information

[1206] Specific behavior:

[1207] A user accesses the system using a terminal and logs in by entering authentication information such as a username and password.

[1208] After logging in, users access a form where they can enter personal information and interests (such as name, age, academic level, and subjects of interest).

[1209] The input information is sent from the terminal to the server by pressing the send button.

[1210] input:

[1211] User personal information and interest information

[1212] output:

[1213] User information sent to the server

[1214] Step 2: Save your data

[1215] Specific behavior:

[1216] The server receives the user's personal information and interest information sent from the terminal.

[1217] Stores the received data in an internal database (e.g., MySQL or PostgreSQL).

[1218] input:

[1219] User information sent

[1220] output:

[1221] User information stored in a database

[1222] Step 3: Analyze the data and generate a learning plan

[1223] Specific behavior:

[1224] The server retrieves the user's personal information and interest information from the database.

[1225] The acquired data is then fed into a generative AI model, using a machine learning library such as TensorFlow or PyTorch.

[1226] A generative AI model analyzes the data and generates an individually optimized learning plan.

[1227] input:

[1228] User information retrieved from the database

[1229] output:

[1230] Generated Learning Plan

[1231] Step 4: Submit your study plan

[1232] Specific behavior:

[1233] The server transmits the generated study plan to the user's terminal.

[1234] The device receives the study plan and displays it to the user.

[1235] input:

[1236] Generated Learning Plan

[1237] output:

[1238] Study plans sent to the user's device

[1239] Step 5: Virtual reality learning experience

[1240] Specific behavior:

[1241] The user uses the device to set up a virtual reality (VR) learning environment by putting on a VR headset and launching a corresponding VR application.

[1242] The VR application creates a virtual reality environment based on the learning plan received from the server, providing the user with experiential learning.

[1243] input:

[1244] Learning plans sent to users

[1245] output:

[1246] Virtual reality learning experiences provided to users

[1247] Step 6: Access the online community

[1248] Specific behavior:

[1249] Users use terminals to access online communities within the system.

[1250] The server manages access from multiple users and updates data in real time.

[1251] Users can exchange opinions, ask questions, and post with other learners within the community.

[1252] input:

[1253] User information for community participation

[1254] output:

[1255] Real-time updated community data

[1256] Step 7: Access counseling services

[1257] Specific behavior:

[1258] The user accesses the counseling page using a terminal and inputs the concerns and questions about their studies.

[1259] The server sends the input data to the AI ​​counselor, who then analyzes the data using natural language processing technology and generates appropriate advice.

[1260] The advice is sent back to the user's terminal via the server and displayed on the screen.

[1261] input:

[1262] User consultation details

[1263] output:

[1264] Advice from an AI counselor

[1265] Through these steps, we can provide individually optimized learning experiences and opportunities for interaction for children who are not attending school, thereby improving their self-esteem.

[1266] (Application example 1)

[1267] 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."

[1268] The challenge is how to provide an individually optimized learning environment to improve technical skills and learning outcomes for children who are not attending school or for employee training. Traditional learning programs and training have made it difficult to provide optimal learning plans tailored to individual interests and skill levels. Furthermore, there has been a lack of methods to provide effective learning experiences, which has made it easy for learners to become isolated and difficult for them to continue learning.

[1269] 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.

[1270] In this invention, the server includes means for inputting and storing personal information and interest information of learners, means for generating a learning plan using a generation AI that acquires and analyzes the stored personal information and interest information, means for providing a learning experience in a virtual reality environment based on the generated learning plan, means for providing an online community where multiple learners can interact online, and means for providing an operation simulation in a virtual reality environment based on the generated learning plan to improve technical skills. This makes it possible to provide an optimal learning experience for individual learners and engineers, and to improve their technical skills and learning outcomes.

[1271] "Personal information and interest information of learners" refers to information that indicates the characteristics and interests of individual learners, such as the learner's name, age, academic ability / skill level, and areas of interest.

[1272] A "learning plan" is a plan that includes learning content and schedules that are optimal for a learner, created by a generative AI based on the learner's personal information and interests.

[1273] "Generative AI" is an artificial intelligence technology that analyzes a large amount of collected information and generates the optimal learning plan for each learner.

[1274] A "virtual reality environment" is a virtual space where learners can use a VR headset or similar device to experience real places and things in a highly realistic way.

[1275] An "online community" is a virtual communication platform where multiple learners can interact via the Internet.

[1276] An "operation simulation" is a virtual simulation that allows you to simulate the experience of specific operations or tasks in a virtual reality environment.

[1277] The present invention relates to a system for providing an optimal learning experience to a learner, and more particularly to a method for generating a learning program using a VR environment and an online community. The embodiment of the present invention is configured as follows.

[1278] Program Generation and Explanation

[1279] The server collects and stores personal information and interest information from the learner's device, including the learner's name, age, academic and technical level, and areas of interest. It also uses a generative AI to analyze this information. The generative AI uses a machine learning algorithm to generate an optimal learning plan based on the collected information.

[1280] The generated learning plans include simulated operations in a virtual reality environment. Learners can use a VR headset to experience real-world environments and operations in a virtual space. For example, in the case of automation technology training, robot operation and troubleshooting scenarios are simulated.

[1281] The server also provides an online community, creating an environment where multiple learners can interact in real time, allowing them to share their knowledge and experiences and maintain their motivation to learn.

[1282] Additionally, the generative AI tracks learners' progress and provides feedback, helping them to continually improve their learning.

[1283] Hardware and Software Use

[1284] Hardware: VR headset (e.g., Oculus Rift), user device (e.g., tablet, PC)

[1285] Software: Flask (Python web framework), generative AI model (for generating learning plans), VR simulation software, community platform, AI counseling system

[1286] Specific examples

[1287] When an engineer wants to learn how to operate a new robot, they access a terminal and enter their name, age, areas of interest, and level of automation technology skill. This information is stored on a server and analyzed by the generating AI. The generated learning plan includes simulations of operating the robot and troubleshooting.

[1288] Engineers put on a VR headset and begin practicing in a virtual environment, where they can actually operate the robot and answer interactive quizzes.

[1289] Engineers can also join online communities to deepen their learning while interacting with other like-minded engineers. Finally, they can consult with an AI counselor about their technical concerns and questions and receive appropriate advice.

[1290] Prompt Sentence Examples

[1291] Technician Information:

[1292] Name: Yamada

[1293] Age: 35

[1294] Area of ​​interest: Automation technology

[1295] Current Skill Level: Intermediate

[1296] Generate a personalized learning plan for this technician, including virtual reality simulations and interactive training modules.

[1297] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1298] Step 1:

[1299] A user creates an account by entering personal information and interests using a device. Specifically, the user enters their name, age, academic and technical level, and areas of interest. The entered information is sent from the device to a server and stored.

[1300] Input: User's personal information and interests

[1301] Output: User information stored on the server

[1302] Step 2:

[1303] The server retrieves the stored personal information and interest information and passes it to the generation AI, which analyzes this information and generates an optimal learning plan for the user. The learning plan includes specific learning content and operation simulations in a virtual reality environment.

[1304] Input: Stored Personal Information and Interests

[1305] Data processing: Information analysis using generative AI

[1306] Output: Optimal study plan

[1307] Step 3:

[1308] The server sends the generated learning plan to the user's device. The user then checks the learning plan and sets up the device to begin the learning experience in the virtual reality environment. Specifically, the user prepares a VR headset and enters the virtual environment.

[1309] Input: Optimal Study Plan

[1310] Output: The lesson plan displayed on the user's device

[1311] Step 4:

[1312] The user puts on a VR headset and begins simulating operations in a virtual reality environment. The server tracks the user's movements within the virtual environment and provides interactive quizzes and feedback. For example, a simulated robot operation or troubleshooting scenario is performed.

[1313] Input: User operation data, virtual reality environment

[1314] Output: Interactive quiz, feedback

[1315] Step 5:

[1316] The server tracks the user's learning progress and provides feedback based on the learning plan. The progress data is analyzed to present the user with additional learning content and advice.

[1317] Input: User progress data

[1318] Data processing: Analysis of progress data

[1319] Output: Feedback, additional learning content

[1320] Step 6:

[1321] Users access online communities and interact with other learners. The server manages data within the communities and supports smooth communication in real time. Users share their knowledge in forums and Q&A sessions.

[1322] Input: User's community participation information

[1323] Output: Interaction data within the online community

[1324] Step 7:

[1325] Users consult an AI counselor about their worries and questions about their studies. The server passes the user's question to the AI ​​counselor, who then responds with appropriate advice. The AI ​​counselor uses natural language processing to analyze the user's question and generate the most appropriate answer.

[1326] Input: User question data

[1327] Data processing: Question analysis using natural language processing

[1328] Output: Advice from an AI counselor

[1329] 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.

[1330] This invention is a system that provides an optimal learning experience for children who are not attending school, and aims to improve the effectiveness of learning and the quality of counseling by combining an emotion engine. The system includes a learning plan generated based on the learner's personal information and interests, a learning experience in a virtual reality environment, an online community, and emotion analysis using an emotion engine.

[1331] Specific operations and processing flow

[1332] First, a learner accesses the system and enters their personal information and interests. The data collected during this process is sent from the user's device to a server and stored in a database.

[1333] The server then uses generative AI to analyze the learner's data and generate a personalized learning plan that includes learning content selected based on the learner's interests and learning history. For example, if a user is interested in biology, a detailed learning plan on the molecular structure of DNA will be generated.

[1334] The generated learning plan is sent from the server to the user's device, and the user proceeds with their learning based on this plan. Specifically, the user can observe the molecular structure of DNA in 3D in a virtual reality environment, which deepens their understanding.

[1335] The emotion engine analyzes the user's facial expressions, voice, and text data to determine the user's emotional state in real time. For example, if the user shows a confused expression while studying, the emotion engine will recognize this and notify the server.

[1336] Based on this, the server dynamically adjusts the learning plan, for example by providing additional, clearer explanations or recommending counseling services.

[1337] Furthermore, users can participate in online communities and interact with other learners. The server manages community data in real time, ensuring that each user's posts and comments are updated immediately.

[1338] Emotion engines are also used in online communities to provide appropriate feedback and support by determining the emotional state of users as they interact with each other.

[1339] Specific examples

[1340] For example, consider the case where Learner B is using the system for the first time. Learner B creates an account and enters personal information and "history" as his or her subject of interest. The data is sent to the server and saved. The server then uses generative AI to generate a lesson plan on history. The plan includes content about the ancient Egyptian civilization, allowing the learner to experience the pyramid construction process in a virtual reality environment.

[1341] Learner B follows the lesson plan generated using the device, puts on a VR headset, and takes a virtual tour of a construction site in Egypt. Interactive quizzes are provided during the tour, and Learner B progresses by answering them. This experience allows Learner B to deepen his understanding of ancient civilizations.

[1342] Furthermore, Learner B's emotional state is monitored using an emotion engine. For example, if Learner B shows a confused expression, the server collects this information and immediately adjusts the learning content. Learner B also participates in an online community where he or she exchanges opinions about Egyptian civilization with other learners.

[1343] If Learner B enters their learning concerns on the counseling page, the AI ​​counselor will analyze them and provide appropriate advice. If the emotion engine recognizes stress or anxiety from the user's facial expressions or voice, the server will provide more specific and useful feedback.

[1344] As described above, the present invention realizes a system that achieves both learning effectiveness and psychological support by providing each learner with an individually optimized learning experience and emotional support.

[1345] The processing flow will be explained below.

[1346] Step 1:

[1347] A user launches the application and accesses the account creation page, where they enter information such as their name, age, subjects of interest, and learning level.

[1348] Step 2:

[1349] The device stores the input information in temporary memory and sends it to the server as JSON format data.

[1350] Step 3:

[1351] The server parses the received JSON data, stores the learner's personal information and interests in a database, and sends the user a confirmation message to create an account.

[1352] Step 4:

[1353] The server retrieves the user's learning history and interest information from the database and prepares to pass it on to the generation AI.

[1354] Step 5:

[1355] The AI ​​analyzes the acquired data and generates a learning plan that is optimal for the user. For example, if a user is interested in "history," it generates a plan that includes learning content such as "ancient Egyptian civilization."

[1356] Step 6:

[1357] The server stores the generated learning plan in a database and sends it to the user's device.

[1358] Step 7:

[1359] The user can view the lesson plan on the device and begin learning in a virtual reality environment. For example, the user can select the construction process of the Egyptian pyramids.

[1360] Step 8:

[1361] The device launches a VR module based on the selected learning content, and the user experiences learning in a virtual environment using a VR headset.

[1362] Step 9:

[1363] After the user has completed the VR learning experience, their learning progress is recorded on the device and sent to the server.

[1364] Step 10:

[1365] The learning progress received by the server is stored in a database and used to generate the next learning plan.

[1366] Step 11:

[1367] Users can access online communities to connect with other learners and post their learning experiences and questions.

[1368] Step 12:

[1369] The server manages community posting data in real time and notifies other users. The device receives the updated information and updates the community screen.

[1370] Step 13:

[1371] The user uses the emotion engine to recognize their emotional state during training by collecting facial and voice data using a camera and microphone, which is then sent from the device to a server.

[1372] Step 14:

[1373] The server passes the received emotional data to the emotion engine, which analyzes the user's emotional state in real time, for example, recognizing if the user is confused.

[1374] Step 15:

[1375] It provides a way for the server to dynamically adjust the learning plan based on the analysis results from the emotion engine. For example, if the user is confused, the server can provide additional explanations or hints.

[1376] Step 16:

[1377] As users continue to learn, they receive feedback based on their emotional changes. The emotion engine continuously monitors the user's emotional state and provides support as needed.

[1378] Step 17:

[1379] The user accesses the counseling page and enters the details of the consultation. The device sends the input data to the server.

[1380] Step 18:

[1381] The server passes the received counseling data to the AI ​​counselor, who then analyzes the input and generates appropriate advice and feedback.

[1382] Step 19:

[1383] The server sends the generated advice to the user's device, which displays the advice. The user receives feedback. The emotion engine monitors the user's emotional state during counseling and provides additional support.

[1384] The above steps will create a system that provides individually optimized learning experiences and emotional support, achieving both learning effectiveness and psychological support.

[1385] Example 2

[1386] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1387] Current learning systems are unable to provide learning plans that are adapted to each learner's emotional state and interests, limiting their effectiveness. Another issue is that it is difficult to provide optimal learning experiences and psychological support for children who are not attending school. Therefore, there is a need for a system that can simultaneously provide individually optimized learning experiences and psychological support by analyzing a learner's emotional state and dynamically adjusting learning plans in real time.

[1388] 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.

[1389] In this invention, the server includes means for inputting and saving personal information and interest information of a learner, means for generating a learning plan using a generation AI that acquires and analyzes the saved personal information and interest information, means for providing a learning experience in a virtual reality environment based on the generated learning plan, means for providing an online community where multiple learners can interact online, an emotion engine for analyzing the emotional state of the learner, and means for dynamically adjusting the learning plan based on information obtained from the emotion engine. This makes it possible to provide individually optimized learning plans and adjust the learning plan in accordance with the emotional state in real time.

[1390] "Learners" refers to individuals participating in educational activities, and in this system, the focus is primarily on out-of-school children.

[1391] "Personal information" refers to information that can identify a specific individual, including name, age, email address, etc.

[1392] "Interest information" refers to information about subjects or topics in which a learner is particularly interested.

[1393] "Generative AI" is artificial intelligence that performs specific tasks based on stored data, and in this case refers to an AI model that generates a learning plan.

[1394] "Study Plan" means an educational instruction plan optimized for an individual learner, including targeted content and activities.

[1395] "Virtual reality environment" refers to a virtual three-dimensional space generated using computer technology and used as a means to provide a learning experience.

[1396] An "online community" refers to a platform where multiple learners can interact over the Internet.

[1397] "Emotion engine" refers to technology that analyzes a learner's facial expressions, voice, and text data to determine their emotional state.

[1398] "Dynamic adjustment" refers to the process by which the system automatically modifies the learning plan in response to changing conditions in real time.

[1399] "Feedback" refers to assessment and advice provided based on learners' activities and progress.

[1400] This invention is a system that provides an optimal learning experience for children who are not attending school, and aims to improve the effectiveness of learning and the quality of counseling by combining an emotion engine. The system includes a learning plan generated based on the learner's personal information and interests, a learning experience in a virtual reality environment, an online community, and emotion analysis using an emotion engine.

[1401] First, the user accesses the system using their own device (PC, tablet, smartphone, etc.). The user accesses a form to enter personal information and interest information, and enters the required information. This data is temporarily stored on the device and then sent to the server. The server contains a database, and the received data is stored using a database management system (e.g., MySQL or PostgreSQL).

[1402] The server then uses a generative AI model (such as OpenAI's GPT-3) to analyze the stored data. The server takes into account the user's interests and past learning history to generate a personalized, optimized learning plan. This plan includes learning materials and activities that address the learner's interests. For example, if a user indicates an interest in "biology," the AI ​​will generate a detailed learning plan on the molecular structure of DNA.

[1403] The generated learning plan is sent from the server to the user's device. To progress through the learning process, the user wears a VR headset (e.g., Oculus Rift) and experiences the learning content in a virtual reality environment. Specifically, learners can observe the molecular structure of DNA in 3D and deepen their understanding by answering interactive quizzes in the VR environment.

[1404] This system incorporates an emotion engine that analyzes the learner's emotional state in real time. The emotion engine analyzes the user's facial expressions, voice, and text data to determine their emotional state. For example, if the user shows a confused expression, the emotion engine recognizes this and notifies the server. The server dynamically adjusts the learning plan based on feedback from the emotion engine. Specifically, it may provide additional explanations or recommend counseling.

[1405] Furthermore, users can join online communities and interact with other learners. The server manages community data in real time, ensuring that posts and comments are updated immediately. An emotion engine is also used within the online community to analyze the emotional state of users during interactions and provide appropriate feedback and support.

[1406] As a concrete example, consider the case where Learner B is using the system for the first time. Learner B creates an account and enters personal information and "history" as a subject of interest. The data is sent to the server and saved. The server then uses generative AI to generate a lesson plan on history. The plan includes content about the ancient Egyptian civilization and allows the learner to experience the pyramid construction process in a virtual reality environment.

[1407] Learner B follows the plan generated using the device, puts on a VR headset, and takes a virtual tour of a construction site in Egypt. Interactive quizzes are provided during the tour, and Learner B deepens his or her understanding of the ancient civilization by answering them as the tour progresses. In addition, an emotion engine monitors Learner B's emotional state while learning, and if Learner B shows a confused expression, the server immediately adjusts the learning content. Learner B can also participate in an online community and exchange opinions with other learners.

[1408] For generative AI models, use prompts like the following:

[1409] Prompt: "Student B is interested in the ancient Egyptian civilization. Generate a detailed lesson plan for Student B to use in a virtual reality environment using a VR headset."

[1410] In this way, the present invention provides learners with individually optimized learning experiences and emotional support, thereby improving learning effectiveness and psychological support at the same time.

[1411] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1412] Step 1: The user accesses the system and enters personal information and interest information.

[1413] Users access the system using their own devices (PC, tablet, smartphone). A form is displayed in which the user can enter personal information (such as name, age, and email address) and interest information (interesting subjects and topics). This data is temporarily stored on the device.

[1414] Input: Personal information and interests from the user.

[1415] Output: Input data that is temporarily stored on the device.

[1416] Step 2: The terminal sends the input data to the server.

[1417] The personal information and interest information temporarily stored on the device is sent to a server, where it is received and stored in a database.

[1418] Input: Input data temporarily stored on the device.

[1419] Output: The data sent to the server.

[1420] Step 3: The server saves the data in the database.

[1421] The server will store the received personal information and interest information permanently using a database management system (e.g., MySQL or PostgreSQL). This data will be used for subsequent analysis.

[1422] Input: The data sent to the server.

[1423] Output: Data stored in the database.

[1424] Step 4: The server generates a learning plan using the generative AI model.

[1425] The server generates a learning plan using a generative AI model (e.g., OpenAI's GPT-3) based on the user's personal information and interests stored in the database. The generative AI model analyzes the user's interests and past learning history and outputs an individually optimized learning plan.

[1426] Input: User data stored in the database.

[1427] Output: The generated lesson plan.

[1428] Step 5: The server sends the generated learning plan to the user's device.

[1429] The server then sends the generated learning plan to the user's device, which includes links to learning content and learning experiences in a virtual reality environment.

[1430] Input: The generated lesson plan.

[1431] Output: The study plan sent to the user's device.

[1432] Step 6: The user begins studying according to the study plan.

[1433] The user begins learning based on the received learning plan. Specifically, they put on a VR headset (e.g., Oculus Rift) and experience the learning content in a virtual reality environment. The user deepens their learning through interactive quizzes and activities.

[1434] Input: The study plan sent to the user's device.

[1435] Output: A learning experience in a VR environment.

[1436] Step 7: The emotion engine analyzes the user's emotional state during the learning process.

[1437] The emotion engine analyzes the user's facial expressions, voice, and text data in real time during learning to determine their emotional state (e.g., confusion, excitement, etc.). The analysis results of the emotion engine are sent to the server.

[1438] Input: User's facial expressions, voice, and text data.

[1439] Output: Parsed emotional state.

[1440] Step 8: The server dynamically adjusts the learning plan based on the emotional state.

[1441] The server dynamically adjusts the learning plan based on feedback from the emotion engine, for example, providing additional explanations or recommending counseling if the user is confused.

[1442] Input: Parsed emotional state.

[1443] Output: A tailored study plan.

[1444] Step 9: Users join the online community.

[1445] Users can join online communities within the system and interact with other learners. The server manages community posts and comments in real time and updates them instantly. An emotion engine is also used within the community to analyze the emotional state of users during interactions and provide appropriate feedback and support.

[1446] Input: User posts and comments.

[1447] Output: Online community interaction data.

[1448] (Application example 2)

[1449] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1450] In modern society, there is a need for appropriate learning support for children who are not attending school. However, there are not enough systems that provide individually optimized learning experiences or that can grasp children's emotional states in real time and respond appropriately. Furthermore, there are no established methods for students to interact with other students and deepen their understanding of their studies without feeling isolated.

[1451] 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 inputting and saving personal information and interest information of a learner, a learning plan generation device means for acquiring and analyzing the saved personal information and interest information, means for providing a learning experience in a virtual reality environment based on the generated learning plan, an emotion analysis engine means for analyzing the emotional state of the learner in real time, means for dynamically adjusting the learning plan based on the analyzed emotional state, and means for providing an online community in which multiple learners can interact online. This makes it possible to provide individually optimized learning experiences and emotional support for children who are not attending school, and to improve their learning effectiveness through interactions with other learners.

[1452] A "learning plan generation device" is a device that generates an optimal learning plan based on a learner's personal information and interest information.

[1453] A "virtual reality environment" is a computer-generated virtual environment that allows learners to have a realistic experience.

[1454] An "emotion analysis engine" is a device that analyzes a learner's facial expressions, voice, and text data to determine their emotional state in real time.

[1455] An "online community" is a virtual space where multiple learners can interact with each other and share information via the Internet.

[1456] A "learning plan" is a plan of learning content and activities that is structured based on the learner's interests and learning history.

[1457] An "interactive experience" is one in which learners actively participate and deepen their learning through two-way interaction.

[1458] "Feedback" is advice or corrective instruction provided based on a learner's learning progress or emotional state.

[1459] "Learning content" refers to the teaching materials and resources provided to learners, including text, images, video, audio, etc.

[1460] This invention is a system that provides optimal learning experiences for children who are not attending school, and aims to improve the effectiveness of learning and the quality of counseling by combining an emotion engine. The system consists of a learning plan generator, a virtual reality environment, an emotion analysis engine, and an online community.

[1461] First, a learner accesses the system from a terminal and enters personal information and information about their interests. This input data is sent to the server and stored in the server's database. The server then uses a learning plan generation device to analyze this data and generate an optimal learning plan for each learner. For example, if a learner is interested in history, a learning plan about ancient civilizations will be generated.

[1462] The generated learning plan is sent from the server to the learner's device and presented to them through the device. The learner then wears smart glasses or a head-mounted display and experiences the learning content in a virtual reality environment. For example, they can deepen their understanding by observing the construction process of the ancient Egyptian pyramids in 3D.

[1463] The emotion analysis engine analyzes the learner's facial expressions, voice, and text data in real time to determine their emotional state. If the learner feels confused or stressed, the emotion analysis engine sends that information to the server, which then dynamically adjusts the learning plan, for example by adding detailed explanations of difficult parts.

[1464] Learners can also participate in online communities and interact with other learners. The server manages the data from these online communities in real time and uses an emotion analysis engine to determine the emotional state of learners during their interactions. This allows appropriate feedback and support to be provided.

[1465] As a concrete example, consider the case where Learner B uses the system for the first time. Learner B creates an account and enters personal information and "history" as his or her subject of interest. The data is sent to the server and saved. The server uses generative AI to generate a history lesson plan and provides a learning experience in a virtual reality environment. If Learner B shows a confused expression, the emotion analysis engine detects this and the server adjusts the learning content.

[1466] An example of a prompt for a generative AI model is:

[1467] "A student shows a confused expression during a history lesson. Based on this, we provide additional explanations and generate advice from an AI counselor."

[1468] This allows the invention to realize an effective system that provides individually optimized learning experiences and emotional support to children who are not attending school.

[1469] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1470] Step 1:

[1471] This is the process where a user accesses the system from a terminal and inputs personal information and interest information. The input data is sent to the server and stored in the server's database. This is used as the basis for building a user profile. The input here is name, age, subjects of interest, etc., and the output is the profile data stored on the server.

[1472] Step 2:

[1473] The server retrieves the stored personal information and interest information, analyzes it using a learning plan generator, and generates an individually optimized learning plan. A generative AI model is used to create a plan containing detailed learning content based on past learning history and interest information. The input is profile data and past learning history, and the output is an individually customized learning plan.

[1474] Step 3:

[1475] The generated learning plan is sent from the server to the device. The user wears smart glasses or a head-mounted display and experiences the learning content in a virtual reality environment. Specifically, 3D models and interactive quizzes are used to provide visually realistic learning. The input here is the learning plan, and the output is the display of the learning content in a VR environment.

[1476] Step 4:

[1477] The emotion analysis engine analyzes the user's facial expression, voice, and text data in real time to determine their emotional state. For example, if a learner shows a confused expression, the facial expression data is sent to the server. The input here is real-time emotional data, and the output is the analyzed emotional state.

[1478] Step 5:

[1479] The server dynamically adjusts the learning plan based on the analyzed emotional state. For example, if the user is confused, the server receives that information and provides additional explanations or supplementary learning materials. The input is the analyzed emotional data, and the output is an adjusted learning plan.

[1480] Step 6:

[1481] Users can participate in online communities and interact with other learners. The server manages online community data in real time and uses an emotion analysis engine to determine the emotional state of learners during interactions. The input is real-time community data, and the output is appropriate feedback and support.

[1482] Through these steps, the system delivers an individually optimized learning experience and dynamically adjusts learning plans based on emotional state.

[1483] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1484] 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.

[1485] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1486] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1487] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1488] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1489] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1490] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1491] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1492] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1493] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1494] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1495] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1496] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1497] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1498] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1499] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1500] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1501] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1502] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1503] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1504] The following is further disclosed regarding the above embodiment.

[1505] (Claim 1)

[1506] A means to input and save learner personal information and interest information;

[1507] A means to generate a learning plan using a generation AI that acquires and analyzes stored personal information and interest information;

[1508] a means for providing a learning experience in a virtual reality environment based on the generated learning plan;

[1509] A means for providing an online community where multiple learners can interact online;

[1510] A system including:

[1511] (Claim 2)

[1512] 10. The system of claim 1, further comprising means for displaying selected specific learning content based on the generated learning plan to provide an interactive experience.

[1513] (Claim 3)

[1514] 10. The system of claim 1, further comprising means for tracking a learner's learning progress based on the generated learning plan and providing feedback.

[1515] "Example 1"

[1516] (Claim 1)

[1517] A means to input and save learner personal information and interest information;

[1518] A means to generate a learning plan using a generation AI that acquires and analyzes stored personal information and interest information;

[1519] a means for providing a learning experience in a virtual reality environment based on the generated learning plan;

[1520] A means for providing an online community where multiple learners can interact online;

[1521] A means to send the learner's inputted consultation details to an AI counselor and provide appropriate advice and feedback;

[1522] A system including:

[1523] (Claim 2)

[1524] 10. The system of claim 1, further comprising means for displaying selected specific learning content based on the generated learning plan to provide an interactive experience.

[1525] (Claim 3)

[1526] 10. The system of claim 1, further comprising means for tracking a learner's learning progress based on the generated learning plan and providing feedback.

[1527] "Application Example 1"

[1528] (Claim 1)

[1529] A means to input and save learner personal information and interest information;

[1530] A means to generate a learning plan using a generation AI that acquires and analyzes stored personal information and interest information;

[1531] a means for providing a learning experience in a virtual reality environment based on the generated learning plan;

[1532] A means for providing an online community where multiple learners can interact online;

[1533] A means for improving technical skills by providing operational simulations in a virtual reality environment based on the generated learning plan; and

[1534] A system including:

[1535] (Claim 2)

[1536] 10. The system of claim 1, further comprising means for displaying selected specific learning content based on the generated learning plan to provide an interactive experience.

[1537] (Claim 3)

[1538] 10. The system of claim 1, further comprising means for tracking a learner's learning progress based on the generated learning plan and providing feedback.

[1539] "Example 2: Combining Emotion Engines"

[1540] (Claim 1)

[1541] A means to input and save learner personal information and interest information;

[1542] A means to generate a learning plan using a generation AI that acquires and analyzes stored personal information and interest information;

[1543] a means for providing a learning experience in a virtual reality environment based on the generated learning plan;

[1544] A means for providing an online community where multiple learners can interact online;

[1545] an emotion engine that analyzes the learner's emotional state;

[1546] a means for dynamically adjusting the learning plan based on information obtained from the emotion engine; and

[1547] A system including:

[1548] (Claim 2)

[1549] 10. The system of claim 1, further comprising means for displaying selected specific learning content based on the generated learning plan to provide an interactive experience.

[1550] (Claim 3)

[1551] 10. The system of claim 1, further comprising means for tracking a learner's learning progress based on the generated learning plan and providing feedback.

[1552] "Application example 2 when combining emotion engines"

[1553] (Claim 1)

[1554] A means to input and save learner personal information and interest information;

[1555] A learning plan generation device that acquires and analyzes the stored personal information and interest information;

[1556] a means for providing a learning experience in a virtual reality environment based on the generated learning plan;

[1557] a means for an emotion analysis engine to analyze the learner's emotional state in real time;

[1558] means for dynamically adjusting the learning plan based on the analyzed emotional state;

[1559] A means for providing an online community where multiple learners can interact online;

[1560] A system including:

[1561] (Claim 2)

[1562] 10. The system of claim 1, further comprising means for displaying selected specific learning content based on the generated learning plan to provide an interactive experience.

[1563] (Claim 3)

[1564] 10. The system of claim 1, further comprising means for tracking a learner's learning progress based on the generated learning plan and providing feedback. [Explanation of symbols]

[1565] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means to input and save learner personal information and interest information; A means to generate a learning plan using a generation AI that acquires and analyzes stored personal information and interest information; a means for providing a learning experience in a virtual reality environment based on the generated learning plan; A means for providing an online community where multiple learners can interact online; A system including:

2. The system of claim 1 , further comprising means for displaying specific learning content selected based on the generated learning plan to provide an interactive experience.

3. The system of claim 1 , further comprising means for tracking a learner's learning progress based on the generated learning plan and providing feedback.

Images