System

Abstract

A system is provided.SOLUTION: This system is provided with a means for allowing an educator to input educational contents to a terminal, a means for transmitting the educational contents from the terminal to a server, a means for allowing the server to evaluate the educational contents by using a generation type artificial intelligence model, and to correct and reinforce them as necessary, a means for disclosing the corrected and reinforced educational contents on a platform, and a means for allowing a user to use the disclosed educational contents.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] ---

[0005] Conventional educational platforms relied on manual evaluation and correction of the quality of educational content, which was time-consuming, costly, and limited in accuracy. They also lacked appropriate support or counseling tailored to each user's learning progress. Furthermore, they lacked a system for fairly evaluating learning outcomes and providing rewards, making it difficult to motivate learners. Even for companies and local governments looking to improve their employees' skills, there was no unified learning management and evaluation system. To solve these problems, an efficient and fair educational platform was needed. [Means for solving the problem]

[0006] The present invention provides a means for educators to input educational content into a terminal and transmit it to a server from the terminal. The server includes a means for evaluating the educational content using a generative artificial intelligence model and modifying or enhancing it as necessary. The server also provides a means for publishing the modified or enhanced educational content on a platform and for users to use the published educational content. The present invention further includes a means for a user to input their interests and skill level into a terminal and for the server to generate an optimal learning plan for the user using a generative artificial intelligence model. The generated learning plan is sent to the user's terminal, providing a means for the user to proceed with their learning based on the learning plan. The server also includes a means for monitoring learning progress and generating appropriate counseling and support messages using a generative artificial intelligence model and transmitting them to the terminal. The present invention also provides a means for transmitting a user's learning completion data from the terminal to a server, which then records the learning completion data in NFT format on the blockchain. The server then includes a means for issuing reward tokens to users based on their learning results and notifying the terminal. The present invention also provides a means for corporate and local government administrators to log in to the platform, and the server aggregates and analyzes learning data in real time and displays it on an administrator dashboard. The server also includes a means for generating appropriate counseling and support messages for specific learners and transmitting them to the terminal. This will solve existing problems and create an efficient and fair educational platform.

[0007] ---

[0008] "Educational Content" is a general term for the contents of teaching materials, learning resources, courses, etc. used on the educational platform.

[0009] "Device" refers to an electronic device such as a computer, smartphone, or tablet that allows a user to access the educational platform.

[0010] "Server" refers to a central computer system that runs a set of computing resources and software that allows the educational platform to operate.

[0011] A "generative artificial intelligence model" is a machine learning model trained using large datasets, and is an algorithm that automatically performs complex tasks such as evaluating educational content and generating lesson plans.

[0012] "Correction" refers to the process of correcting deficiencies and errors detected by the generative artificial intelligence model in the educational content.

[0013] "Enrichment" refers to the process of providing additional explanations or improvements to make educational content more understandable and effective.

[0014] "Platform" refers to the entire online system through which educational content is provided and through which users learn.

[0015] A "learning plan" refers to a collection of learning objectives, materials, and courses created by a generative artificial intelligence model based on a user's interests and skill level.

[0016] "Study progress" refers to the progress of a user as he or she progresses with his or her studies based on a study plan.

[0017] "Counseling" refers to advice and support provided to users according to their learning progress.

[0018] "Support messages" refer to learning advice and encouraging messages that are generated by the generative artificial intelligence model according to the user's learning progress.

[0019] "Learning completion data" refers to data indicating that a user has completed a particular learning plan or course.

[0020] "Blockchain" is a distributed database technology that refers to a recording method that prevents data tampering and ensures reliability.

[0021] An "NFT (non-fungible token)" is a digital asset that proves unique ownership of specific data on a blockchain.

[0022] "Reward Token" refers to the digital assets issued by the platform in return for users' learning achievements.

[0023] "Administrator" refers to the person in charge at a company or local government who has the authority to operate the platform and manage the learning status of employees and citizens.

[0024] "Dashboard" refers to an interface that allows administrators to visualize learning data in real time and check analysis results. [Brief explanation of the drawings]

[0025] [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

[0026] 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.

[0027] First, the terms used in the following description will be explained.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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."

[0033] [First embodiment]

[0034] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0035] 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.

[0036] 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).

[0037] 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.

[0038] 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.

[0039] 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.

[0040] 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.

[0041] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0042] 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.

[0043] 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.

[0044] 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.

[0045] 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."

[0046] ---

[0047] The present invention relates to an educational platform that utilizes a generative artificial intelligence model. In this platform, educators input educational content into a terminal, and a server evaluates, corrects, enhances, and publishes it. The platform also generates an optimal learning plan based on the information entered by the user, monitors learning progress, and provides appropriate support. Furthermore, learning completion data is recorded on a blockchain, and reward tokens are issued according to learning results. Specific embodiments of the present invention are described below.

[0048] Creating a study plan

[0049] 1. Enter your user information

[0050] Users input their areas of interest, current skill level, and learning goals through the educational platform terminal. For example, a user may input, "I want to learn the basics of generative artificial intelligence."

[0051] 2. Transmission of User Information

[0052] The terminal transmits the input user information to the server.

[0053] 3. Generating optimal study plans

[0054] The server utilizes a generative artificial intelligence model based on the received user information to generate an optimal learning plan for the user, including recommended learning materials and courses.

[0055] 4. Submit your study plan

[0056] The server transmits the generated study plan to the user's terminal.

[0057] 5. View your study plan

[0058] The terminal displays the received study plan to the user, and the user can proceed with his / her studies based on it.

[0059] Learning support and counselling

[0060] 1. Monitoring your learning progress

[0061] The server monitors the user's learning progress in real time, analyzing learning logs and progress data to confirm whether the user is progressing according to the plan.

[0062] 2. Learning assistance decisions

[0063] The server uses a generative artificial intelligence model to generate counseling and assistance messages if the user is behind or if appropriate support is needed. For example, if the user stops studying for a certain period of time, the server generates an encouraging message.

[0064] 3. Sending an assist message

[0065] The server transmits the generated assist message to the user's terminal.

[0066] 4. Display of assist messages

[0067] The terminal notifies the user of an assist message and provides the necessary support.

[0068] Content Creation and Evaluation

[0069] 1. Content Creation

[0070] Educators input new educational content into the terminal and send it to the server, for example, creating an "introductory course in Python programming."

[0071] 2. Submitting Content

[0072] The terminal transmits the created content to the server.

[0073] 3. Content Rating

[0074] The server evaluates the received content using a generative artificial intelligence model, specifically checking the accuracy of grammar and content, and assessing the ease of understanding for the user.

[0075] 4. Content Modifications and Enhancements

[0076] Based on the evaluation results, the server automatically corrects and enhances the content, for example, correcting deficiencies and errors and inserting necessary additional explanations and examples.

[0077] 5. Publishing Content

[0078] The server will then publish the modified and enhanced content on the platform, making it available to other users.

[0079] Learning history and reward management

[0080] 1. Record your learning completion

[0081] A user completes a designated learning plan or course.

[0082] 2. Sending training data

[0083] The terminal notifies the server that the learning is complete.

[0084] 3. Managing your learning history

[0085] The server records the received learning completion data on the blockchain in NFT format, which prevents data tampering and ensures reliability.

[0086] 4. Issuance of rewards

[0087] The server issues reward tokens to the user according to the results of the learning and notifies the terminal.

[0088] 5. Display of Rewards

[0089] The terminal displays information about the reward tokens issued to the user.

[0090] Functions for businesses and local governments

[0091] 1. Administrator login

[0092] Administrators of companies and local governments log in to the platform's administration screen.

[0093] 2. Aggregation and analysis of learning status

[0094] The server collects and analyzes the learning data of all employees and citizens in real time.

[0095] 3. View the dashboard

[0096] The server displays the results of the aggregation and analysis on an administrator dashboard, allowing administrators to grasp the learning status in a unified manner.

[0097] 4. Providing the support you need

[0098] The server uses a generative artificial intelligence model to generate messages when an individual learner needs appropriate counseling or support.

[0099] 5. Sending a support message

[0100] The server transmits the generated support message to the learner's terminal.

[0101] As described above, as a mode for implementing the invention, the system of the present invention provides an efficient and fair educational environment for educators, users, and corporate and local government administrators. At each step, generative AI models and blockchain technology are utilized to improve the quality of educational content, manage learning progress, and provide fair rewards.

[0102] The processing flow will be explained below.

[0103] ---

[0104] Creating a study plan

[0105] Step 1:

[0106] A user logs into the educational platform and inputs their area of ​​interest, current skill level, and learning objectives through a terminal.

[0107] Step 2:

[0108] The terminal transmits the input user information to the server.

[0109] Step 3:

[0110] The server inputs the received user information into a generative artificial intelligence model to generate an optimal learning plan for the user.

[0111] Step 4:

[0112] The server transmits the generated study plan to the user's terminal.

[0113] Step 5:

[0114] The terminal displays the received study plan to the user, and the user starts studying based on it.

[0115] Learning support and counselling

[0116] Step 1:

[0117] The server monitors the user's learning progress in real time, and periodically collects and analyzes learning logs and progress data.

[0118] Step 2:

[0119] The server evaluates the user's learning progress and level of understanding based on the data collected and analyzed.

[0120] Step 3:

[0121] If the server determines that progress is slow or that appropriate support is needed, it uses a generative artificial intelligence model to generate counseling or assistance messages.

[0122] Step 4:

[0123] The server transmits the generated assist message to the user's terminal.

[0124] Step 5:

[0125] The terminal notifies the user of an assist message, allowing the user to receive the necessary support.

[0126] Content Creation and Evaluation

[0127] Step 1:

[0128] An educator inputs new educational content into a terminal and transmits it to a server.

[0129] Step 2:

[0130] The terminal transmits the created content to the server.

[0131] Step 3:

[0132] The server evaluates the received content using a generative artificial intelligence model, checking the accuracy of grammar and content and assessing the ease of understanding for the user.

[0133] Step 4:

[0134] The server automatically corrects and enhances the content based on the evaluation results, correcting deficiencies and errors and inserting additional explanations and examples where necessary.

[0135] Step 5:

[0136] The server publishes the modified and enhanced content on the platform, making it available to other users.

[0137] Learning history and reward management

[0138] Step 1:

[0139] A user completes a designated learning plan or course.

[0140] Step 2:

[0141] The terminal notifies the server that the learning is complete.

[0142] Step 3:

[0143] The server records the received learning completion data on the blockchain in NFT format.

[0144] Step 4:

[0145] The server issues reward tokens to the user according to the results of their learning and notifies the terminal.

[0146] Step 5:

[0147] The terminal displays information about the reward tokens issued to the user.

[0148] Functions for businesses and local governments

[0149] Step 1:

[0150] Administrators from companies and local governments log in to the platform's administration screen.

[0151] Step 2:

[0152] The server collects and analyzes the learning data of all employees and citizens in real time.

[0153] Step 3:

[0154] The server displays the aggregated and analyzed results on the administrator dashboard.

[0155] Step 4:

[0156] If the server determines that a particular learner needs appropriate counseling or support, it generates a message using a generative artificial intelligence model.

[0157] Step 5:

[0158] The server transmits the generated support message to the learner's terminal.

[0159] The above is a specific processing flow in the platform of the present invention.

[0160] Example 1

[0161] 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."

[0162] Current education platforms do not adequately improve the quality of educational content, manage learning progress, or provide rewards based on learning outcomes. They also lack effective learning support, limiting the ways in which users can find optimal learning plans based on their interests and skill levels. Furthermore, there is a lack of mechanisms for companies and local governments to centrally manage the learning status of their employees and citizens and provide appropriate support.

[0163] 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.

[0164] In this invention, the server includes a means for evaluating the accuracy and understandability of educational content and making necessary improvements; a means for monitoring a user's learning activity in real time and generating counseling and assistance messages using a generative artificial intelligence model; a means for transmitting the generated learning plan and counseling messages to the user's device; a means for recording learning completion data in NFT format using blockchain technology; and a means for issuing reward tokens based on learning outcomes and notifying the user's device. This enables the improvement of the quality of educational content, management of learning progress, and provision of fair rewards based on learning outcomes. It also enables companies and local governments to centrally manage and support learners.

[0165] "Educator" is the person responsible for inputting educational content into the platform and imparting knowledge and skills to learners.

[0166] A "terminal" is a device that allows a user or educator to access the educational platform and input or display data.

[0167] A "server" is a central processing unit that processes input data, generates learning plans, and evaluates educational content.

[0168] A "generative artificial intelligence model" is an algorithm that generates appropriate assistance messages and learning plans based on user input information and educational content.

[0169] "Educational content" refers to educational materials and content created by educators, and is the subject matter for learners to study.

[0170] The "platform" is an online system that allows educators and learners to share educational content with each other and advance their learning.

[0171] A "study plan" is a study schedule and list of recommended learning materials generated based on the user's skill level and interests.

[0172] A "counseling message" is a message provided by the generative artificial intelligence model based on the user's learning progress to encourage increased motivation and progress in learning.

[0173] "Blockchain" is a distributed ledger technology that securely records learning completion data and prevents tampering.

[0174] The "NFT format" is a format that records learning completion data as a unique digital asset.

[0175] "Reward tokens" are digital rewards issued to users based on their learning outcomes and are used to receive rewards and benefits.

[0176] A "dashboard" is a graphical user interface provided to administrators to grasp the learning situation in real time.

[0177] This invention relates to an educational platform that utilizes a generative artificial intelligence model. Educators input educational content into a terminal, and the server evaluates, corrects, enhances, and publishes it. The platform also generates optimal learning plans based on the information entered by users, monitors their learning progress, and provides appropriate support. Furthermore, learning completion data is recorded on a blockchain, and reward tokens are issued according to learning outcomes.

[0178] Creating a study plan

[0179] Enter your user information:

[0180] A user logs in to the educational platform and inputs their area of ​​interest, current skill level, and learning goals into the device. For example, the user might input, "I want to learn the basics of generative artificial intelligence."

[0181] Sending user information:

[0182] The device sends the information entered by the user to the server. Specifically, the data is sent in JSON format via a REST API.

[0183] Generate optimal study plans:

[0184] The server receives the user information and uses a generative artificial intelligence model (e.g., GPT-4) to generate an optimal learning plan, which includes recommended learning materials and courses.

[0185] Submit and view your study plan:

[0186] The generated study plan is sent to the user's device, where it is displayed, allowing the user to proceed with their studies based on the displayed plan.

[0187] Learning support and counselling

[0188] Progress monitoring:

[0189] The server monitors users' learning activities in real time, collecting log data such as the time spent viewing learning materials and quiz results.

[0190] Learning assistance decision making and message generation:

[0191] The server analyzes the user's progress data and uses a generative artificial intelligence model to generate counseling and assistance messages, such as "Let's review this chapter again" if the user is behind or needs specific assistance.

[0192] Sending and viewing assist messages:

[0193] The server sends the generated assist message to the user's device, which displays it in the form of a notification or a pop-up.

[0194] Content Creation and Evaluation

[0195] Creating and submitting content:

[0196] Educators create educational content using an editor and send it to the server via their devices. The content sent can be a variety of formats, including text files and multimedia files.

[0197] Rate and modify content:

[0198] The server uses a generative artificial intelligence model to evaluate the content, checking for grammatical and content accuracy, and assessing its ease of understanding for users, automatically correcting and enhancing it as needed.

[0199] Content Publishing:

[0200] The modified and enhanced content will be published on the platform through the server and made available to other users.

[0201] Learning history and reward management

[0202] Recording learning completion and sending data:

[0203] When a user completes a learning plan or course, the device notifies the server of that data.

[0204] Manage your learning history:

[0205] The server records the received learning completion data on the blockchain in NFT format, which prevents data tampering and ensures reliability.

[0206] Issuing and Displaying Rewards:

[0207] Depending on the results of the learning, the server issues reward tokens to the user and notifies the terminal. The terminal displays the issued reward token information to the user. For example, it is added to the user's dashboard.

[0208] Functions for businesses and local governments

[0209] Administrator login and data aggregation and analysis:

[0210] Corporate and local government administrators log in to the platform's management screen, and the server compiles and analyzes the learning data of all employees and citizens in real time, using data analysis technology.

[0211] View the dashboard and provide support:

[0212] The aggregated and analyzed results are displayed on the administrator dashboard, and counseling and support messages appropriate for each learner are generated.

[0213] Examples of concrete examples and prompts

[0214] Examples:

[0215] If User A types in "I want to learn the basics of Python," the system will suggest online courses and materials as the optimal learning plan for User A, monitor their progress in real time, and send support messages.

[0216] If Educator B creates an "introductory course on data science," the system will evaluate the content, automatically correct and enhance any areas for improvement, and then publish it.

[0217] Example prompt sentence:

[0218] Please provide some code examples to help me understand the basics of Python.

[0219] "Please explain some introductory topics in data science."

[0220] This concludes the description of the "Mode for carrying out the invention." This will enable improvements in the quality of educational content, proper management of users' learning progress, and fair reward provision.

[0221] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0222] Step 1:

[0223] Entering user information

[0224] A user logs in to the educational platform terminal and enters their area of ​​interest, current skill level, and learning goals. For example, a user may enter, "I want to learn the basics of generative artificial intelligence."

[0225] Input: Area of ​​interest, skill level, learning goals.

[0226] Output: User input information.

[0227] Step 2:

[0228] Sending user information

[0229] The terminal sends the information entered by the user to the server, using the REST API to send data in JSON format.

[0230] Input: User-entered information.

[0231] Output: User information received on the server side.

[0232] Step 3:

[0233] Generate optimal study plans

[0234] The server generates an optimal learning plan based on the received user information using a generative artificial intelligence model (e.g., GPT-4). The AI ​​model analyzes large amounts of educational data and selects learning materials and courses that are appropriate for the user.

[0235] Input: User information received by the server.

[0236] Output: A generated learning plan (a list of recommended materials and courses).

[0237] Step 4:

[0238] Submitting and Viewing Learning Plans

[0239] The server sends the generated learning plan to the user's device in JSON format.

[0240] The device parses the received JSON data and displays a learning plan to the user, including recommended learning materials and course links.

[0241] Input: The generated lesson plan.

[0242] Output: The learning plan displayed on the user's device.

[0243] Step 5:

[0244] Monitoring learning progress

[0245] The server monitors users' learning activities in real time, collects learning logs (time spent viewing learning materials and quiz results), and analyzes progress data.

[0246] Input: Learning log, progress data.

[0247] Output: Analysis results (evaluation of whether the user is progressing according to the plan).

[0248] Step 6:

[0249] Learning assistance decisions and message generation

[0250] The server generates counseling and assistance messages using a generative artificial intelligence model based on the analysis results. If progress is delayed, it generates a specific assistance message (e.g., "Let's review this chapter again").

[0251] Input: Analysis results.

[0252] Output: The generated assist message.

[0253] Step 7:

[0254] Sending and displaying assist messages

[0255] The server transmits the generated assist message to the user's terminal.

[0256] The device displays an assist message to the user using a pop-up or notification.

[0257] Input: The generated assist message.

[0258] Output: Assist message displayed on the user's terminal.

[0259] Step 8:

[0260] Creating and Submitting Content

[0261] Educators use the editor of the educational platform to create new educational content, which can be text files or multimedia files, and send them to the server via their devices.

[0262] Input: Educational content created by educators.

[0263] Output: The content sent to the server.

[0264] Step 9:

[0265] Evaluate and correct content

[0266] The server uses a generative artificial intelligence model to evaluate the content, checking for grammatical accuracy, content accuracy, and user comprehension, and automatically corrects and enhances it as needed.

[0267] Input: The content sent to the server.

[0268] Output: Corrected and enhanced content.

[0269] Step 10:

[0270] Publishing content

[0271] The server will then publish the modified and enhanced content on the platform, making it available to other users.

[0272] Input: revised and enhanced content.

[0273] Output: Content published on the platform.

[0274] Step 11:

[0275] Recording learning completion and sending data

[0276] When a user completes a designated learning plan or course, the device notifies the server of that data.

[0277] Input: Completed training data.

[0278] Output: Learning completion data notified to the server.

[0279] Step 12:

[0280] Managing learning history

[0281] The server records the received learning completion data on the blockchain in NFT format, which prevents data tampering and ensures reliability.

[0282] Input: Learning completion data notified to the server.

[0283] Output: Training completion data recorded on the blockchain as an NFT.

[0284] Step 13:

[0285] Issuing and Displaying Rewards

[0286] The server issues and notifies the user of a reward token based on the results of their learning.

[0287] The terminal displays the received reward token information on the dashboard.

[0288] Input: Learning outcome data.

[0289] Output: Information about reward tokens issued to users.

[0290] Step 14:

[0291] Administrator login and data collection and analysis

[0292] Business and local government administrators log in to the platform's management screen, and the server compiles and analyzes the learning data of all employees and citizens in real time, using data analysis technology to identify trends.

[0293] Input: employee and citizen learning data.

[0294] Output: Aggregation and analysis results displayed on the management screen.

[0295] Step 15:

[0296] Viewing the dashboard and providing support

[0297] The server displays the aggregated and analyzed results on an administrator dashboard and generates counseling and support messages appropriate for each individual learner.

[0298] Input: Aggregation and analysis results.

[0299] Output: Generated counseling or support messages.

[0300] The above are the processing steps of the program for this system. The specific operations performed at each step, as well as their inputs and outputs, have been explained in detail.

[0301] (Application example 1)

[0302] 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."

[0303] Conventional educational platforms have faced issues such as inconsistent quality of educational content and difficulty in responding flexibly to user progress. Furthermore, there was a lack of means to provide appropriate information and support in real time when training staff and responding to customers in physical stores. Furthermore, there was an inadequate system for reliably recording users' learning outcomes and issuing appropriate rewards. There is a need to solve these issues and provide a high-quality, efficient educational environment and customer support.

[0304] 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.

[0305] In this invention, the server includes a means for an educator to input educational content into a terminal, a means for transmitting the educational content from the terminal to the server, a means for the server to evaluate the educational content using a generative artificial intelligence model and modify or enhance it as necessary, a means for publishing the modified or enhanced educational content on the platform, a means for users to use the published educational content, a means for providing product information and counseling in real time using a smart device, and a means for providing real-time answers to customer questions using a generative artificial intelligence model. This enables improved quality of educational content, flexible learning support, and efficient staff training and customer service in physical stores. Furthermore, by utilizing a generative artificial intelligence model and blockchain technology, the reliability of learning outcomes can be ensured and fair rewards can be provided.

[0306] "Educators" refers to instructors and teachers who provide educational content.

[0307] "Educational content" refers to the information and materials that learners are expected to acquire.

[0308] "Terminal" refers to an electronic device that allows a user or educator to input information and communicate with a server.

[0309] "Server" refers to a centralized computer system for processing information and using generative artificial intelligence models.

[0310] A "generative artificial intelligence model" refers to an artificial intelligence system that has the ability to learn from data and generate new information.

[0311] "Evaluation" refers to the process by which a generative artificial intelligence model examines the quality and suitability of educational content.

[0312] "Modification and enhancement" refers to the process of improving educational content and making it easier to understand based on the evaluation results.

[0313] "Publishing" refers to the act of displaying the revised or enhanced educational content on the Platform and making it accessible to Users.

[0314] "Platform" refers to the entire system for providing educational content and learning plans.

[0315] "User" refers to an individual who uses the educational platform and learns.

[0316] "Interests and skill level" refers to information that indicates the areas the user wants to learn and their current learning progress.

[0317] "Study Plan" refers to a study plan that combines learning materials and courses that are best suited to the user.

[0318] "Progress" refers to information that indicates the user's learning situation and level of achievement.

[0319] "Counseling and support messages" refer to advice and encouraging messages provided by the generative artificial intelligence model to help the user learn.

[0320] A "smart device" refers to a device that is connected to the Internet and has sensors and processing capabilities.

[0321] "Real-time" refers to instantaneous processing and response of information.

[0322] "Product information" refers to data such as detailed descriptions and usage instructions for products sold in physical stores.

[0323] "Customer service" refers to the work of responding to customer questions and requests in physical stores.

[0324] "Learning Completion Data" means records generated when a user completes a particular learning plan or course.

[0325] "Blockchain" refers to a distributed ledger technology that prevents data tampering and ensures reliability.

[0326] "NFT format" refers to data in the form of a non-fungible token that represents a unique digital asset on a blockchain.

[0327] "Reward tokens" refer to digital currencies or points issued for learning outcomes.

[0328] To implement the present invention, the following steps and associated hardware and software are used.

[0329] System configuration

[0330] Server: This plays a central role in the system. It uses generative AI models to provide educational content and counseling, monitors learning progress, and issues appropriate rewards. The server uses cloud infrastructure such as Microsoft Azure Server or AWS EC2.

[0331] Terminal: A device that users and educators use to input information and communicate with the server. Examples include smartphones, tablets, PCs, and smart glasses. HoloLens 2 and Google Glass Enterprise Edition 2 are used as smart glasses.

[0332] Generative AI model: Performs various AI processes such as evaluating educational content, generating learning plans, and generating counseling messages. Specifically, OpenAI's GPT-3.5 model is used.

[0333] Blockchain: Used to ensure the reliability of learning completion data, and uses Ethereum and Hyperledger.

[0334] Input and evaluation of educational content

[0335] Educators input educational content into their devices and send it to the server. The server uses a generative AI model to evaluate the content and correct or enhance it as needed. For example, it checks grammar, content accuracy, and understandability. The corrected or enhanced educational content is published on the platform and available to other users.

[0336] Generate a learning plan

[0337] The user inputs their areas of interest and current skill level into the device. The server uses a generative artificial intelligence model based on the received information to generate an optimal learning plan. This plan includes recommended learning materials and courses and is sent to the device. The user then proceeds with their studies based on this learning plan.

[0338] Progress monitoring and counseling

[0339] The server monitors the user's learning progress in real time, analyzing learning logs and progress data to confirm whether the user is following the learning plan. If progress is falling behind, the server uses a generative artificial intelligence model to generate appropriate counseling and support messages and send them to the user's device.

[0340] Use of smart devices

[0341] Store staff can use smart glasses to provide real-time product information and customer consultations. Generative AI models are used to provide quick answers to customer questions. This system enhances staff training and customer service.

[0342] Recording learning completion data and issuing reward tokens

[0343] When a user completes a designated learning plan, the learning completion data is sent from the device to the server. The server records the learning completion data on the blockchain in NFT format. It also issues reward tokens to the user based on their learning results and notifies the device. This reward token information is also displayed on the smart device.

[0344] Examples of concrete examples and prompts

[0345] As a concrete example, consider a case where a customer asks a store staff member wearing smart glasses about a new smartphone. The staff member speaks to the smart glasses, and the server uses voice recognition to convert the question into text and send it to a generative artificial intelligence model. The answer generated by the AI ​​is displayed on the screen, and the staff member can relay it to the customer.

[0346] Example prompt sentence:

[0347] "If a customer asks about a new smartphone, provide them with the latest information."

[0348] "Generate training plans for new staff."

[0349] This will enable improved quality of educational content, flexible learning support, and efficient staff training and customer support in physical stores. By utilizing generative AI models and blockchain technology, it will be possible to ensure the reliability of learning results and provide fair compensation.

[0350] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0351] Step 1:

[0352] The educator inputs the educational content into the device. The input data here is educational content such as text information, images, and videos. The device converts this information into a format and sends it to the server.

[0353] Step 2:

[0354] The server passes the received educational content to a generative AI model for evaluation. Specifically, it checks the accuracy of grammar and content, as well as ease of understanding. During this process, the generative AI model analyzes the text and metadata to generate an evaluation result.

[0355] Step 3:

[0356] The server modifies and enhances the educational content based on the evaluation results, for example, correcting deficiencies and errors and inserting necessary additional explanations and examples. The modified and enhanced educational content is generated and made available for publication.

[0357] Step 4:

[0358] The server publishes the revised and enhanced educational content on the platform, and the published content is registered in a database in a format that can be accessed by other users.

[0359] Step 5:

[0360] Users log in to the platform and input their areas of interest and current skill level into their device. A learning plan is generated based on this input information, and specific items include areas of interest, skill level, and learning objectives.

[0361] Step 6:

[0362] The server uses a generative AI model based on the input data received from the user to generate an optimal learning plan. Data processing here includes analyzing the user profile and selecting learning materials from a database.

[0363] Step 7:

[0364] The server sends the generated learning plan to the user's device, which displays the received learning plan to the user and guides them to the next learning step.

[0365] Step 8:

[0366] The user progresses through their studies based on the study plan. Their progress is recorded as login history and study log, and periodically sent to the server.

[0367] Step 9:

[0368] The server monitors the user's learning progress in real time, analyzes the learning log and progress data, and generates appropriate counseling and support messages using a generative artificial intelligence model.

[0369] Step 10:

[0370] Once the support message is generated, the server sends it to the user's terminal, which notifies the user of the received message and provides the necessary support.

[0371] Step 11:

[0372] Staff use smart glasses to assist customers in brick-and-mortar stores. Customers' questions are entered by voice, and the device sends the information to a server.

[0373] Step 12:

[0374] The server uses speech recognition technology to convert the question into text and uses a generative artificial intelligence model to generate an answer, which is then displayed on the smart glasses' display.

[0375] Step 13:

[0376] When a user completes a learning plan, the user sends the data from the device to the server. The learning completion data includes the course studied and the achievement level.

[0377] Step 14:

[0378] The server receives the learning completion data and records it on the blockchain in NFT format, which ensures the data is tamper-proof and reliable.

[0379] Step 15:

[0380] The server issues reward tokens based on the user's learning results and notifies the terminal, which then displays the reward token information to the user and provides instructions on how to use it.

[0381] 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.

[0382] ---

[0383] The present invention relates to an educational platform that utilizes a generative artificial intelligence model and an emotion engine. In this platform, educators input educational content into a terminal, and a server evaluates, corrects, enhances, and publishes it. The platform also generates an optimal learning plan based on the information entered by the user, monitors learning progress while recognizing the user's emotions using an emotion engine, and provides appropriate support and counseling. Furthermore, learning completion data is recorded on a blockchain, and reward tokens are issued according to learning results. Specific embodiments of the present invention are described below.

[0384] Creating a study plan

[0385] 1. Enter your user information

[0386] Users input their areas of interest, current skill level, and learning goals through the educational platform terminal. For example, a user may input, "I want to learn the basics of generative artificial intelligence."

[0387] 2. Transmission of User Information

[0388] The terminal transmits the input user information to the server.

[0389] 3. Generating optimal study plans

[0390] The server utilizes a generative artificial intelligence model based on the received user information to generate an optimal learning plan for the user, including recommended learning materials and courses.

[0391] 4. Submit your study plan

[0392] The server transmits the generated study plan to the user's terminal.

[0393] 5. View your study plan

[0394] The terminal displays the received study plan to the user, and the user starts studying based on it.

[0395] Learning support and counselling

[0396] 1. Monitoring your learning progress

[0397] The server monitors the user's learning progress in real time, periodically collecting and analyzing learning logs and progress data.

[0398] 2. Collecting Emotional Data

[0399] The device uses an emotion engine to collect emotional data from the user while they are learning, including information obtained through facial expression recognition and voice analysis.

[0400] 3. Sending Emotional Data

[0401] The terminal transmits the collected emotion data to the server.

[0402] 4. Learning assistance decisions

[0403] The server evaluates the user's learning progress and emotional state based on the received learning progress data and emotional data.

[0404] 5. Generate a support message

[0405] The server uses a generative artificial intelligence model to generate counseling and support messages based on the user's emotional state, for example, a message recommending a break if the user is tired.

[0406] 6. Sending a support message

[0407] The server sends the generated support message to the user's terminal.

[0408] 7. Displaying support messages

[0409] The terminal notifies the user of a support message, so that the user can receive the necessary support.

[0410] Content Creation and Evaluation

[0411] 1. Content Creation

[0412] Educators input new educational content into the terminal and send it to the server, for example, creating an "introductory course in Python programming."

[0413] 2. Submitting Content

[0414] The terminal transmits the created content to the server.

[0415] 3. Content Rating

[0416] The server evaluates the received content using a generative artificial intelligence model, specifically checking the accuracy of grammar and content, and assessing the ease of understanding for the user.

[0417] 4. Content Modifications and Enhancements

[0418] Based on the evaluation results, the server automatically corrects and enhances the content, correcting deficiencies and errors and inserting additional explanations and examples where necessary.

[0419] 5. Publishing Content

[0420] The server will then publish the modified and enhanced content on the platform, making it available to other users.

[0421] Learning history and reward management

[0422] 1. Record your learning completion

[0423] A user completes a designated learning plan or course.

[0424] 2. Sending training data

[0425] The terminal notifies the server that the learning is complete.

[0426] 3. Managing your learning history

[0427] The server records the received learning completion data on the blockchain in NFT format, which prevents data tampering and ensures reliability.

[0428] 4. Issuance of rewards

[0429] The server issues reward tokens to the user according to the results of the learning and notifies the terminal.

[0430] 5. Display of Rewards

[0431] The terminal displays information about the reward tokens issued to the user.

[0432] Functions for businesses and local governments

[0433] 1. Administrator login

[0434] Administrators of companies and local governments log in to the platform's administration screen.

[0435] 2. Aggregation and analysis of learning status

[0436] The server collects and analyzes the learning data of all employees and citizens in real time.

[0437] 3. View the dashboard

[0438] The server displays the results of the aggregation and analysis on an administrator dashboard, allowing administrators to grasp the learning status in a unified manner.

[0439] 4. Providing the support you need

[0440] The server uses a generative artificial intelligence model to generate messages when an individual learner needs appropriate counseling or support.

[0441] 5. Sending a support message

[0442] The server transmits the generated support message to the learner's terminal.

[0443] As described above, as a mode for implementing the invention, the system of the present invention provides an efficient and fair educational environment for educators, users, and corporate and local government administrators. At each step, generative AI models, emotion engines, and blockchain technology are utilized to improve the quality of educational content, manage learning progress, and provide fair rewards.

[0444] The processing flow will be explained below.

[0445] Now, let's explain the specific steps of a specific process in more detail.

[0446] ---

[0447] Creating a study plan

[0448] Step 1:

[0449] Users input their areas of interest, current skill level, and learning goals through the educational platform terminal. For example, a user may input, "I want to learn the basics of generative artificial intelligence."

[0450] Step 2:

[0451] The terminal transmits the input user information to the server.

[0452] Step 3:

[0453] The server inputs the received user information into a generative artificial intelligence model to generate an optimal learning plan for the user. The generated learning plan includes recommended learning materials and courses, which are selected based on the user's skill level and learning goals.

[0454] Step 4:

[0455] The server transmits the generated study plan to the user's terminal.

[0456] Step 5:

[0457] The terminal displays the received study plan to the user, and the user starts studying based on it.

[0458] ---

[0459] Learning support and counselling

[0460] Step 1:

[0461] The server monitors the user's learning progress in real time, and progress data is collected periodically and recorded as a learning log.

[0462] Step 2:

[0463] The device uses an emotion engine to collect emotion data from the user while the user is learning, for example, through facial expression recognition or voice analysis.

[0464] Step 3:

[0465] The terminal transmits the collected emotion data to the server.

[0466] Step 4:

[0467] The server evaluates the user's learning progress and emotional state based on the received learning progress data and emotional data, using a generative artificial intelligence model to confirm whether the user is progressing as expected.

[0468] Step 5:

[0469] The server generates counseling and support messages based on the user's emotional state. For example, if the server determines that the user is tired, it generates a message such as "Take a short break."

[0470] Step 6:

[0471] The server sends the generated support message to the user's terminal.

[0472] Step 7:

[0473] The terminal notifies the user of a support message, so that the user can receive the necessary support.

[0474] ---

[0475] Content Creation and Evaluation

[0476] Step 1:

[0477] Educators input new educational content into the terminal and send it to the server, for example, creating an "introductory course in Python programming."

[0478] Step 2:

[0479] The terminal transmits the created content to the server.

[0480] Step 3:

[0481] The server evaluates the received content using a generative artificial intelligence model, specifically checking the accuracy of grammar and content, and assessing the ease of understanding for the user.

[0482] Step 4:

[0483] Based on the evaluation results, the server automatically corrects and enhances the content, for example, correcting deficiencies and errors and inserting additional explanations and examples where necessary.

[0484] Step 5:

[0485] The server will then publish the modified and enhanced content on the platform, making it available to other users.

[0486] ---

[0487] Learning history and reward management

[0488] Step 1:

[0489] A user completes a designated learning plan or course.

[0490] Step 2:

[0491] The terminal notifies the server that the learning is complete.

[0492] Step 3:

[0493] The server then records the received learning completion data on the blockchain in NFT format, which prevents tampering and ensures the reliability of the learning history.

[0494] Step 4:

[0495] The server issues reward tokens to the user according to the results of the learning and notifies the terminal.

[0496] Step 5:

[0497] The terminal displays information about the reward tokens issued to the user.

[0498] ---

[0499] Functions for businesses and local governments

[0500] Step 1:

[0501] Administrators of companies and local governments log in to the platform's administration screen.

[0502] Step 2:

[0503] The server collects and analyzes the learning data of all employees and citizens in real time.

[0504] Step 3:

[0505] The server displays the results of the aggregation and analysis on an administrator dashboard, allowing administrators to grasp the learning status in a unified manner.

[0506] Step 4:

[0507] If the server determines that a particular learner needs appropriate counseling or support, it generates a message using a generative artificial intelligence model.

[0508] Step 5:

[0509] The server transmits the generated support message to the learner's terminal.

[0510] ---

[0511] The above are the specific processing steps of the present invention. By combining a generative AI model, an emotion engine, and blockchain technology, the present invention improves the quality of educational content, manages learning progress, and provides fair rewards.

[0512] Example 2

[0513] 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."

[0514] Current educational platforms lack the ability to monitor and support individual users' learning progress and emotional state in real time. Furthermore, assessment and correction of learning content is not carried out promptly, and the quality of the results is often inconsistent. Furthermore, there is no reliable recording of learning outcomes or fair distribution of rewards. This leads to issues such as a decline in learner motivation and a lack of improvement in learning efficiency.

[0515] 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. In this invention, the server includes a means for an educator to input educational content into a terminal, a means for transmitting the educational content from the terminal to the server, a means for the server to evaluate the educational content using a generative artificial intelligence model and modify or enhance it as necessary, a means for publishing the modified or enhanced educational content on a platform, a means for a learner to use the published educational content, a means for a learner to input learning goals and skill levels into a terminal, a means for transmitting learner information from the terminal to the server, a means for the server to generate an optimal learning plan for a learner using a generative artificial intelligence model, a means for transmitting the generated learning plan to the learner's terminal, a means for the terminal to display the generated learning plan to the learner and for the learner to proceed with learning based on it, a means for the server to monitor the learner's learning progress in real time, and a means for the terminal to display an emotional emotion. The platform includes a means for collecting learners' emotional data using an engine and transmitting it to a server, a means for the server to analyze the collected learning progress data and emotional data, generate appropriate counseling and support messages, and transmit them to the device, a means for the learner's learning completion data to be transmitted from the device to the server, a means for the server to record the learning completion data on the blockchain in NFT format, a means for the server to issue reward tokens to learners according to their learning outcomes and notify the device, a means for a company or local government administrator to log in to the platform's management screen, a means for the server to aggregate and analyze the learning data of all learners, a means for the server to display the results of the server's aggregation and analysis on an administrator dashboard, and a means for the server to generate appropriate counseling and support messages for each learner and transmit them to the device. This enables real-time monitoring and support of individual users' learning progress and emotional states, rapid evaluation and correction of educational content, reliable recording of learning outcomes, and fair distribution of rewards.

[0516] "Educators" refers to experts and teachers who design and teach educational content.

[0517] "Terminal" refers to an electronic device used to access the educational platform and input information.

[0518] "Server" refers to a central processing unit that processes, stores, transmits and receives data over a network.

[0519] A "generative artificial intelligence model" refers to a machine learning algorithm that generates natural language, providing optimal responses and generating results based on user input.

[0520] "Learner" refers to an individual who learns educational content through the educational platform.

[0521] "Educational content" refers to the content of teaching materials and lessons designed to impart specific knowledge or skills.

[0522] "Study plan" refers to a suggested learning approach or plan based on the learner's goals and skill level.

[0523] An "emotion engine" refers to software that analyzes a user's facial expressions and voice data to recognize their emotional state.

[0524] "Counseling" refers to helping learners to provide psychological support during their learning process.

[0525] "Support messages" refer to guidance and encouragement messages sent based on the user's learning progress and emotional state.

[0526] "Blockchain" refers to a technology that manages transaction records on a distributed network to ensure data reliability.

[0527] "NFT format" refers to a technology for representing digital data in the form of non-fungible tokens.

[0528] "Reward tokens" refer to digital assets issued based on learning outcomes.

[0529] "Corporate or local government administrator" refers to the person in charge of operating and managing the educational platform in a specific organization or region.

[0530] "Administration screen" refers to a dedicated interface for operating and managing a system or platform.

[0531] A "dashboard" refers to a screen that displays data aggregation and analysis results in real time.

[0532] This invention relates to an educational platform that utilizes a generative artificial intelligence model and an emotion engine. This platform allows educators to input educational content, which is then evaluated, revised, and reinforced using a generative artificial intelligence model, providing learners with optimal learning plans. It also monitors learners' progress and emotional state in real time and provides appropriate counseling and support messages. Furthermore, learning outcomes are recorded on a blockchain, and fair reward tokens are issued to maintain and improve learners' motivation.

[0533] Hardware and software used

[0534] Hardware:

[0535] Device: Electronic device such as a personal computer, smartphone, or tablet.

[0536] Server: Central processing unit that processes and stores data

[0537] software:

[0538] Generative AI models: Natural language generation models (e.g., ChatGPT, GPT-4)

[0539] Emotion engine: facial expression recognition software (e.g., Emotion API)

[0540] Blockchain technology: Data recording technology in the form of NFTs

[0541] Creating study plans and providing counseling

[0542] Example 1: Creating a study plan

[0543] A user logs in to the educational platform terminal and enters their area of ​​interest, current skill level, and learning objectives. For example, they might enter "I want to learn the basics of generative artificial intelligence," "Beginner level," or "I want to learn new technologies."

[0544] The terminal transmits this information to the server.

[0545] The server uses a generative artificial intelligence model to generate an optimal learning plan. The prompt is "Please generate the optimal learning plan based on the user's interests, skill level, and goals."

[0546] The server transmits the generated study plan to the terminal and displays it to the user.

[0547] Example 2: Providing counseling and support messages

[0548] The server collects the user's learning progress data in real time and also collects emotion data using an emotion engine.

[0549] The device uses a camera and microphone to collect user emotion data and transmits it to a server.

[0550] The server analyzes the collected data and evaluates the user's progress and emotional state.

[0551] The server uses a generative artificial intelligence model to generate counseling and support messages according to the user's emotional state. The prompt text is "If the user is tired, please generate a message recommending that he or she take a break."

[0552] The server sends the generated support message to the device, which then displays it to the user, such as "You seem tired, so please take a 10-minute break."

[0553] Recording learning results and issuing rewards

[0554] Example 3: Recording learning outcomes and issuing reward tokens

[0555] After the user completes the learning plan, the terminal transmits learning completion data to the server.

[0556] The server records this data on the blockchain in NFT format, which prevents data tampering and increases reliability.

[0557] The server issues reward tokens based on the learning results and notifies the terminal of the information.

[0558] The terminal displays information about the reward tokens issued to the user.

[0559] Management functions for businesses and local governments

[0560] Example 4: Real-time management and support

[0561] Administrators from companies and local governments log in to the platform's administration screen.

[0562] The server collects and analyzes data from all learners in real time and displays it on an administrator dashboard.

[0563] The server generates an appropriate support message for each learner as needed and transmits it to the terminal.

[0564] In this way, the system of the present invention monitors each user's learning progress and emotional state in real time and provides appropriate support to improve learning efficiency and motivation. It also improves the quality of educational content and provides a fair learning environment by recording learning results and issuing reward tokens.

[0565] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0566] Step 1:

[0567] Users log in to the educational platform terminal and enter their areas of interest, current skill level, and learning goals. For example, they can enter information such as "I want to learn the basics of generative artificial intelligence," "Beginner level," or "I want to learn new technologies." This input information becomes the basis for generating subsequent learning plans.

[0568] Step 2:

[0569] The device sends the entered user information to the server. Specifically, data such as the user ID, areas of interest, skill level, and learning goals is sent to the API endpoint via the HTTPS protocol. The input data at this stage is stored on the server.

[0570] Step 3:

[0571] The server receives the user information and uses a generative artificial intelligence model to generate an optimal learning plan. Specifically, the server inputs the prompt "Please generate the optimal learning plan based on the user's areas of interest, skill level, and goals" to the generative AI model. The generative AI model performs data calculations based on this information, generates a learning plan tailored to each individual user, and outputs the results.

[0572] Step 4:

[0573] The server sends the generated learning plan to the user's device. The data sent is the details of the generated learning plan, which is output as an API response from the server to the device.

[0574] Step 5:

[0575] The device displays the received learning plan to the user. For example, links to "Basic Course on Generative Artificial Intelligence" and "Recommended Learning Materials" are displayed on the web browser screen. The user can then access the displayed learning plan and begin learning.

[0576] Step 6:

[0577] The server monitors the user's learning progress in real time. It periodically collects and analyzes data such as when the user accesses the learning materials, the study time, and test results, and stores the data in a database. The input data at this stage becomes the user's learning log.

[0578] Step 7:

[0579] The device uses an emotion engine to collect emotional data from the user during training. It uses a camera and microphone to collect emotional data in real time through facial expression recognition and voice analysis. This emotional data is also sent by the device to the server.

[0580] Step 8:

[0581] The server analyzes the received learning progress data and emotional data, which evaluates the user's learning situation and emotional state. Based on the analysis results, it generates appropriate counseling and support messages. For example, the server can input a prompt to the generative AI model such as, "If the user is tired, please generate a message recommending that he or she take a break."

[0582] Step 9:

[0583] The server sends the generated counseling or support message to the user's terminal. The data sent is the text of the support message, which is output as a response from the server to the terminal.

[0584] Step 10:

[0585] The device will display support messages to the user, such as "You seem tired, please take a 10-minute break," allowing the user to receive the necessary rest and support.

[0586] Step 11:

[0587] When a user completes a learning plan or course, the data is sent from the device to the server. A learning completion notification is sent as an API request and saved as input data on the server.

[0588] Step 12:

[0589] The server records the learning completion data on the blockchain in NFT format, which ensures the reliability and tamper-proofness of the data.

[0590] Step 13:

[0591] The server issues a reward token to the user based on their learning results and sends a notification to the terminal. Information about this reward token is output as a response from the server to the terminal.

[0592] Step 14:

[0593] The terminal displays information about the reward tokens issued to the user, allowing the user to check the rewards according to their learning results and maintain motivation for the next lesson.

[0594] (Application example 2)

[0595] 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."

[0596] Traditional educational platforms lack support that can flexibly adapt to learners' progress and emotional state. As a result, they can only provide uniform learning support, making it difficult to maximize the motivation and learning effectiveness of individual learners. Furthermore, they lack the means to ensure the reliability of learning outcomes and properly evaluate them, which can make it difficult for learners to feel a sense of accomplishment and reduce their persistence in learning. Furthermore, because they do not provide appropriate incentives for learning outcomes, learners' interest and motivation can be lost.

[0597] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0598] In this invention, the server includes a means for educators to evaluate educational content and modify or enhance it as necessary, a means for analyzing the user's learning progress data and emotional data and generating support messages, a means for sending the generated learning plan and support messages to the user, and a means for recording learning completion data on the blockchain and issuing reward tokens. This makes it possible to provide support tailored to each learner's progress and emotional state, which is expected to improve learning effectiveness and maintain motivation. Furthermore, the reliability and fair evaluation of learning outcomes are ensured, and learners gain a sense of accomplishment, encouraging them to continue learning. Furthermore, the reward tokens provide an incentive for learning, increasing interest and motivation in learning.

[0599] "Educator" refers to an individual or organization that creates and delivers educational content.

[0600] "Terminal" refers to an electronic device used by an educator or user for input and output.

[0601] "Server" refers to the central processing unit that processes and manages data for the entire educational platform.

[0602] "Generative AI model" refers to an AI algorithm that evaluates, corrects, and reinforces educational content, generates learning plans, and generates support messages.

[0603] An "emotion engine" refers to technology that analyzes a user's facial expressions and voice data to evaluate their emotional state.

[0604] "Platform" refers to the entire online system for supporting educators in providing content and users in learning.

[0605] "User" refers to an individual who uses the educational platform to learn.

[0606] A "study plan" refers to a study plan that is optimal for a user, generated based on the user's interests and skill level.

[0607] "Study progress data" refers to data that indicates the progress of a user's studies.

[0608] "Emotion data" refers to data indicative of a user's emotional state collected using an emotion engine.

[0609] A "support message" refers to a message containing support content that is generated by a generative artificial intelligence model based on a user's learning progress data and emotional data and sent to the user.

[0610] "Study completion data" refers to data indicating that a user has completed a specified learning plan or course.

[0611] "Blockchain" refers to a technology that uses distributed ledger technology to record learning completion data to prevent tampering.

[0612] "NFT format" refers to a method of recording data in non-fungible token format.

[0613] "Reward token" refers to a digital reward issued based on a user's learning achievements.

[0614] This invention relates to an educational platform using a generative artificial intelligence model and an emotion engine. This platform evaluates and corrects educational content provided by educators, creates learning plans and monitors progress for users, generates support messages using emotion data, records learning outcomes on a blockchain, and issues reward tokens.

[0615] Use of generative artificial intelligence models

[0616] The server uses a generative artificial intelligence model to evaluate the educational content entered by educators and correct or enhance it as needed. This process uses algorithms to evaluate grammatical accuracy, content consistency, and user comprehension.

[0617] Emotion data collection and analysis

[0618] When users use the educational platform, they learn through smart devices (smartphones, smart glasses, head-mounted displays). These devices are equipped with cameras and microphones to collect the user's facial expressions and voice. The server uses an emotion engine to analyze this data and evaluate the user's emotional state in real time.

[0619] Creating a study plan and monitoring progress

[0620] The server uses a generative artificial intelligence model to generate an optimal learning plan based on user information (areas of interest, skill level, learning goals). The generated learning plan is sent to the user's device, and the user proceeds with their studies based on it. The server periodically collects and analyzes the user's learning progress data.

[0621] Generate a support message

[0622] The server uses a generative artificial intelligence model to generate appropriate support messages based on the collected learning progress data and user emotion data. For example, if the learning progress is slow or the user feels fatigued, a message recommending a break or a message offering additional learning resources is generated.

[0623] Blockchain and Reward Tokens

[0624] When a user completes a learning plan or course, the server records the learning completion data on the blockchain in NFT format, ensuring data tamper-proofing and reliability. Depending on the learning results, the server issues reward tokens to the user and provides incentives by notifying the device.

[0625] Specific examples

[0626] Example prompt for generating a lesson plan:

[0627] "The user's area of ​​interest is 'generative artificial intelligence'. Their skill level is 'beginner' and their learning goal is 'learn the basics'. Please generate the optimal learning plan based on this."

[0628] Example prompt for generating a support message:

[0629] "User's progress data is '75% complete'. Sentiment data indicates 'Exhausted'. Please generate a support message appropriate for this state."

[0630] As described above, the system of the present invention provides an efficient and fair educational environment for educators, users, and corporate and local government administrators. At each step, generative AI models, emotion engines, and blockchain technology are utilized to improve the quality of educational content, manage learning progress, and provide fair rewards.

[0631] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0632] Step 1:

[0633] Entering user information

[0634] The user inputs their area of ​​interest, skill level, and learning goals through the terminal. For example, they might input, "I want to learn the basics of generative artificial intelligence." Input: Information the user inputs into the terminal (area of ​​interest, skill level, learning goals). Output: This information is sent from the terminal to the server.

[0635] Step 2:

[0636] Sending user information

[0637] The terminal sends the user information entered in step 1 to the server. Input: Data entered by the user. Output: Data sent from the terminal to the server.

[0638] Step 3:

[0639] Generate optimal study plans

[0640] The server uses a generative artificial intelligence model based on the received user information to generate an optimal study plan for the user. Input: User information. Data processing: The generative artificial intelligence model analyzes the data and generates an appropriate study plan. Output: Generated study plan.

[0641] Step 4:

[0642] Submit your study plan

[0643] The server sends the generated learning plan to the user's device. Input: Learning plan. Output: Sending the learning plan from the server to the device.

[0644] Step 5:

[0645] View your learning plan

[0646] The device displays the received study plan to the user, who then begins studying based on it. Input: Study plan sent from the server. Output: Study plan displayed on the device.

[0647] Step 6:

[0648] Monitoring learning progress

[0649] The server monitors the user's learning progress in real time. Input: User's learning log and progress data. Data calculation: Data analysis is performed to grasp the learning progress. Output: Analysis results.

[0650] Step 7:

[0651] Collecting Emotional Data

[0652] The device collects the user's facial expressions and voice during training through the emotion engine. Input: Facial expression and voice data collected through the camera and microphone. Output: Emotion data.

[0653] Step 8:

[0654] Sending emotional data

[0655] The device sends the collected emotion data to the server. Input: Collected emotion data. Output: Data transmission from the device to the server.

[0656] Step 9:

[0657] Learning assistance decisions

[0658] The server evaluates the user's state based on the received learning progress data and emotion data. Input: Learning progress data and emotion data. Data calculation: Data analysis for state evaluation. Output: Evaluation of the user's learning state.

[0659] Step 10:

[0660] Generate a support message

[0661] The server uses a generative artificial intelligence model to generate a support message according to the learning status. Input: Evaluation results. Data processing: Generation of support message. Output: Generated support message.

[0662] Step 11:

[0663] Send a support message

[0664] The server sends the generated support message to the user's terminal. Input: Support message. Output: Sending the support message.

[0665] Step 12:

[0666] Displaying a support message

[0667] The terminal notifies the user of the support message, allowing the user to receive the necessary support. Input: Support message. Output: Support message displayed on the terminal.

[0668] Step 13:

[0669] Sending learning completion data

[0670] When the user completes the specified learning plan or course, the device sends learning completion data to the server. Input: Learning completion data. Output: Completion data sent from the device to the server.

[0671] Step 14:

[0672] Recording of learning completion data

[0673] The server records the received learning completion data in NFT format on the blockchain. Input: Learning completion data. Data processing: Recording to the blockchain. Output: Recorded data.

[0674] Step 15:

[0675] Reward Token Issuance

[0676] The server issues reward tokens to users according to their learning results and notifies the terminal. Input: Learning results data. Output: Issuance and notification of reward tokens.

[0677] Step 16:

[0678] View Reward Tokens

[0679] The terminal displays information about the reward tokens issued to the user. Input: Reward token information. Output: Reward token information displayed on the terminal.

[0680] 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.

[0681] 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.

[0682] 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.

[0683] [Second embodiment]

[0684] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0685] 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.

[0686] 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).

[0687] 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.

[0688] 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.

[0689] 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).

[0690] 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.

[0691] 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.

[0692] 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.

[0693] 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.

[0694] 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.

[0695] 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."

[0696] ---

[0697] The present invention relates to an educational platform that utilizes a generative artificial intelligence model. In this platform, educators input educational content into a terminal, and a server evaluates, corrects, enhances, and publishes it. The platform also generates an optimal learning plan based on the information entered by the user, monitors learning progress, and provides appropriate support. Furthermore, learning completion data is recorded on a blockchain, and reward tokens are issued according to learning results. Specific embodiments of the present invention are described below.

[0698] Creating a study plan

[0699] 1. Enter your user information

[0700] Users input their areas of interest, current skill level, and learning goals through the educational platform terminal. For example, a user may input, "I want to learn the basics of generative artificial intelligence."

[0701] 2. Transmission of User Information

[0702] The terminal transmits the input user information to the server.

[0703] 3. Generating optimal study plans

[0704] The server utilizes a generative artificial intelligence model based on the received user information to generate an optimal learning plan for the user, including recommended learning materials and courses.

[0705] 4. Submit your study plan

[0706] The server transmits the generated study plan to the user's terminal.

[0707] 5. View your study plan

[0708] The terminal displays the received study plan to the user, and the user can proceed with his / her studies based on it.

[0709] Learning support and counselling

[0710] 1. Monitoring your learning progress

[0711] The server monitors the user's learning progress in real time, analyzing learning logs and progress data to confirm whether the user is progressing according to the plan.

[0712] 2. Learning assistance decisions

[0713] The server uses a generative artificial intelligence model to generate counseling and assistance messages if the user is behind or if appropriate support is needed. For example, if the user stops studying for a certain period of time, the server generates an encouraging message.

[0714] 3. Sending an assist message

[0715] The server transmits the generated assist message to the user's terminal.

[0716] 4. Display of assist messages

[0717] The terminal notifies the user of an assist message and provides the necessary support.

[0718] Content Creation and Evaluation

[0719] 1. Content Creation

[0720] Educators input new educational content into the terminal and send it to the server, for example, creating an "introductory course in Python programming."

[0721] 2. Submitting Content

[0722] The terminal transmits the created content to the server.

[0723] 3. Content Rating

[0724] The server evaluates the received content using a generative artificial intelligence model, specifically checking the accuracy of grammar and content, and assessing the ease of understanding for the user.

[0725] 4. Content Modifications and Enhancements

[0726] Based on the evaluation results, the server automatically corrects and enhances the content, for example, correcting deficiencies and errors and inserting necessary additional explanations and examples.

[0727] 5. Publishing Content

[0728] The server will then publish the modified and enhanced content on the platform, making it available to other users.

[0729] Learning history and reward management

[0730] 1. Record your learning completion

[0731] A user completes a designated learning plan or course.

[0732] 2. Sending training data

[0733] The terminal notifies the server that the learning is complete.

[0734] 3. Managing your learning history

[0735] The server records the received learning completion data on the blockchain in NFT format, which prevents data tampering and ensures reliability.

[0736] 4. Issuance of rewards

[0737] The server issues reward tokens to the user according to the results of the learning and notifies the terminal.

[0738] 5. Display of Rewards

[0739] The terminal displays information about the reward tokens issued to the user.

[0740] Functions for businesses and local governments

[0741] 1. Administrator login

[0742] Administrators of companies and local governments log in to the platform's administration screen.

[0743] 2. Aggregation and analysis of learning status

[0744] The server collects and analyzes the learning data of all employees and citizens in real time.

[0745] 3. View the dashboard

[0746] The server displays the results of the aggregation and analysis on an administrator dashboard, allowing administrators to grasp the learning status in a unified manner.

[0747] 4. Providing the support you need

[0748] The server uses a generative artificial intelligence model to generate messages when an individual learner needs appropriate counseling or support.

[0749] 5. Sending a support message

[0750] The server transmits the generated support message to the learner's terminal.

[0751] As described above, as a mode for implementing the invention, the system of the present invention provides an efficient and fair educational environment for educators, users, and corporate and local government administrators. At each step, generative AI models and blockchain technology are utilized to improve the quality of educational content, manage learning progress, and provide fair rewards.

[0752] The processing flow will be explained below.

[0753] ---

[0754] Creating a study plan

[0755] Step 1:

[0756] A user logs into the educational platform and inputs their area of ​​interest, current skill level, and learning objectives through a terminal.

[0757] Step 2:

[0758] The terminal transmits the input user information to the server.

[0759] Step 3:

[0760] The server inputs the received user information into a generative artificial intelligence model to generate an optimal learning plan for the user.

[0761] Step 4:

[0762] The server transmits the generated study plan to the user's terminal.

[0763] Step 5:

[0764] The terminal displays the received study plan to the user, and the user starts studying based on it.

[0765] Learning support and counselling

[0766] Step 1:

[0767] The server monitors the user's learning progress in real time, and periodically collects and analyzes learning logs and progress data.

[0768] Step 2:

[0769] The server evaluates the user's learning progress and level of understanding based on the data collected and analyzed.

[0770] Step 3:

[0771] If the server determines that progress is slow or that appropriate support is needed, it uses a generative artificial intelligence model to generate counseling or assistance messages.

[0772] Step 4:

[0773] The server transmits the generated assist message to the user's terminal.

[0774] Step 5:

[0775] The terminal notifies the user of an assist message, allowing the user to receive the necessary support.

[0776] Content Creation and Evaluation

[0777] Step 1:

[0778] An educator inputs new educational content into a terminal and transmits it to a server.

[0779] Step 2:

[0780] The terminal transmits the created content to the server.

[0781] Step 3:

[0782] The server evaluates the received content using a generative artificial intelligence model, checking the accuracy of grammar and content and assessing the ease of understanding for the user.

[0783] Step 4:

[0784] The server automatically corrects and enhances the content based on the evaluation results, correcting deficiencies and errors and inserting additional explanations and examples where necessary.

[0785] Step 5:

[0786] The server publishes the modified and enhanced content on the platform, making it available to other users.

[0787] Learning history and reward management

[0788] Step 1:

[0789] A user completes a designated learning plan or course.

[0790] Step 2:

[0791] The terminal notifies the server that the learning is complete.

[0792] Step 3:

[0793] The server records the received learning completion data on the blockchain in NFT format.

[0794] Step 4:

[0795] The server issues reward tokens to the user according to the results of their learning and notifies the terminal.

[0796] Step 5:

[0797] The terminal displays information about the reward tokens issued to the user.

[0798] Functions for businesses and local governments

[0799] Step 1:

[0800] Administrators from companies and local governments log in to the platform's administration screen.

[0801] Step 2:

[0802] The server collects and analyzes the learning data of all employees and citizens in real time.

[0803] Step 3:

[0804] The server displays the aggregated and analyzed results on the administrator dashboard.

[0805] Step 4:

[0806] If the server determines that a particular learner needs appropriate counseling or support, it generates a message using a generative artificial intelligence model.

[0807] Step 5:

[0808] The server transmits the generated support message to the learner's terminal.

[0809] The above is a specific processing flow in the platform of the present invention.

[0810] Example 1

[0811] 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."

[0812] Current education platforms do not adequately improve the quality of educational content, manage learning progress, or provide rewards based on learning outcomes. They also lack effective learning support, limiting the ways in which users can find optimal learning plans based on their interests and skill levels. Furthermore, there is a lack of mechanisms for companies and local governments to centrally manage the learning status of their employees and citizens and provide appropriate support.

[0813] 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.

[0814] In this invention, the server includes a means for evaluating the accuracy and understandability of educational content and making necessary improvements; a means for monitoring a user's learning activity in real time and generating counseling and assistance messages using a generative artificial intelligence model; a means for transmitting the generated learning plan and counseling messages to the user's device; a means for recording learning completion data in NFT format using blockchain technology; and a means for issuing reward tokens based on learning outcomes and notifying the user's device. This enables the improvement of the quality of educational content, management of learning progress, and provision of fair rewards based on learning outcomes. It also enables companies and local governments to centrally manage and support learners.

[0815] "Educator" is the person responsible for inputting educational content into the platform and imparting knowledge and skills to learners.

[0816] A "terminal" is a device that allows a user or educator to access the educational platform and input or display data.

[0817] A "server" is a central processing unit that processes input data, generates learning plans, and evaluates educational content.

[0818] A "generative artificial intelligence model" is an algorithm that generates appropriate assistance messages and learning plans based on user input information and educational content.

[0819] "Educational content" refers to educational materials and content created by educators, and is the subject matter for learners to study.

[0820] The "platform" is an online system that allows educators and learners to share educational content with each other and advance their learning.

[0821] A "study plan" is a study schedule and list of recommended learning materials generated based on the user's skill level and interests.

[0822] A "counseling message" is a message provided by the generative artificial intelligence model based on the user's learning progress to encourage increased motivation and progress in learning.

[0823] "Blockchain" is a distributed ledger technology that securely records learning completion data and prevents tampering.

[0824] The "NFT format" is a format that records learning completion data as a unique digital asset.

[0825] "Reward tokens" are digital rewards issued to users based on their learning outcomes and are used to receive rewards and benefits.

[0826] A "dashboard" is a graphical user interface provided to administrators to grasp the learning situation in real time.

[0827] This invention relates to an educational platform that utilizes a generative artificial intelligence model. Educators input educational content into a terminal, and the server evaluates, corrects, enhances, and publishes it. The platform also generates optimal learning plans based on the information entered by users, monitors their learning progress, and provides appropriate support. Furthermore, learning completion data is recorded on a blockchain, and reward tokens are issued according to learning outcomes.

[0828] Creating a study plan

[0829] Enter your user information:

[0830] A user logs in to the educational platform and inputs their area of ​​interest, current skill level, and learning goals into the device. For example, the user might input, "I want to learn the basics of generative artificial intelligence."

[0831] Sending user information:

[0832] The device sends the information entered by the user to the server. Specifically, the data is sent in JSON format via a REST API.

[0833] Generate optimal study plans:

[0834] The server receives the user information and uses a generative artificial intelligence model (e.g., GPT-4) to generate an optimal learning plan, which includes recommended learning materials and courses.

[0835] Submit and view your study plan:

[0836] The generated study plan is sent to the user's device, where it is displayed, allowing the user to proceed with their studies based on the displayed plan.

[0837] Learning support and counselling

[0838] Progress monitoring:

[0839] The server monitors users' learning activities in real time, collecting log data such as the time spent viewing learning materials and quiz results.

[0840] Learning assistance decision making and message generation:

[0841] The server analyzes the user's progress data and uses a generative artificial intelligence model to generate counseling and assistance messages, such as "Let's review this chapter again" if the user is behind or needs specific assistance.

[0842] Sending and viewing assist messages:

[0843] The server sends the generated assist message to the user's device, which displays it in the form of a notification or a pop-up.

[0844] Content Creation and Evaluation

[0845] Creating and submitting content:

[0846] Educators create educational content using an editor and send it to the server via their devices. The content sent can be a variety of formats, including text files and multimedia files.

[0847] Rate and modify content:

[0848] The server uses a generative artificial intelligence model to evaluate the content, checking for grammatical and content accuracy, and assessing its ease of understanding for users, automatically correcting and enhancing it as needed.

[0849] Content Publishing:

[0850] The modified and enhanced content will be published on the platform through the server and made available to other users.

[0851] Learning history and reward management

[0852] Recording learning completion and sending data:

[0853] When a user completes a learning plan or course, the device notifies the server of that data.

[0854] Manage your learning history:

[0855] The server records the received learning completion data on the blockchain in NFT format, which prevents data tampering and ensures reliability.

[0856] Issuing and Displaying Rewards:

[0857] Depending on the results of the learning, the server issues reward tokens to the user and notifies the terminal. The terminal displays the issued reward token information to the user. For example, it is added to the user's dashboard.

[0858] Functions for businesses and local governments

[0859] Administrator login and data aggregation and analysis:

[0860] Corporate and local government administrators log in to the platform's management screen, and the server compiles and analyzes the learning data of all employees and citizens in real time, using data analysis technology.

[0861] View the dashboard and provide support:

[0862] The aggregated and analyzed results are displayed on the administrator dashboard, and counseling and support messages appropriate for each learner are generated.

[0863] Examples of concrete examples and prompts

[0864] Examples:

[0865] If User A types in "I want to learn the basics of Python," the system will suggest online courses and materials as the optimal learning plan for User A, monitor their progress in real time, and send support messages.

[0866] If Educator B creates an "introductory course on data science," the system will evaluate the content, automatically correct and enhance any areas for improvement, and then publish it.

[0867] Example prompt sentence:

[0868] Please provide some code examples to help me understand the basics of Python.

[0869] "Please explain some introductory topics in data science."

[0870] This concludes the description of the "Mode for carrying out the invention." This will enable improvements in the quality of educational content, proper management of users' learning progress, and fair reward provision.

[0871] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0872] Step 1:

[0873] Entering user information

[0874] A user logs in to the educational platform terminal and enters their area of ​​interest, current skill level, and learning goals. For example, a user may enter, "I want to learn the basics of generative artificial intelligence."

[0875] Input: Area of ​​interest, skill level, learning goals.

[0876] Output: User input information.

[0877] Step 2:

[0878] Sending user information

[0879] The terminal sends the information entered by the user to the server, using the REST API to send data in JSON format.

[0880] Input: User-entered information.

[0881] Output: User information received on the server side.

[0882] Step 3:

[0883] Generate optimal study plans

[0884] The server generates an optimal learning plan based on the received user information using a generative artificial intelligence model (e.g., GPT-4). The AI ​​model analyzes large amounts of educational data and selects learning materials and courses that are appropriate for the user.

[0885] Input: User information received by the server.

[0886] Output: A generated learning plan (a list of recommended materials and courses).

[0887] Step 4:

[0888] Submitting and Viewing Learning Plans

[0889] The server sends the generated learning plan to the user's device in JSON format.

[0890] The device parses the received JSON data and displays a learning plan to the user, including recommended learning materials and course links.

[0891] Input: The generated lesson plan.

[0892] Output: The learning plan displayed on the user's device.

[0893] Step 5:

[0894] Monitoring learning progress

[0895] The server monitors users' learning activities in real time, collects learning logs (time spent viewing learning materials and quiz results), and analyzes progress data.

[0896] Input: Learning log, progress data.

[0897] Output: Analysis results (evaluation of whether the user is progressing according to the plan).

[0898] Step 6:

[0899] Learning assistance decisions and message generation

[0900] The server generates counseling and assistance messages using a generative artificial intelligence model based on the analysis results. If progress is delayed, it generates a specific assistance message (e.g., "Let's review this chapter again").

[0901] Input: Analysis results.

[0902] Output: The generated assist message.

[0903] Step 7:

[0904] Sending and displaying assist messages

[0905] The server transmits the generated assist message to the user's terminal.

[0906] The device displays an assist message to the user using a pop-up or notification.

[0907] Input: The generated assist message.

[0908] Output: Assist message displayed on the user's terminal.

[0909] Step 8:

[0910] Creating and Submitting Content

[0911] Educators use the editor of the educational platform to create new educational content, which can be text files or multimedia files, and send them to the server via their devices.

[0912] Input: Educational content created by educators.

[0913] Output: The content sent to the server.

[0914] Step 9:

[0915] Evaluate and correct content

[0916] The server uses a generative artificial intelligence model to evaluate the content, checking for grammatical accuracy, content accuracy, and user comprehension, and automatically corrects and enhances it as needed.

[0917] Input: The content sent to the server.

[0918] Output: Corrected and enhanced content.

[0919] Step 10:

[0920] Publishing content

[0921] The server will then publish the modified and enhanced content on the platform, making it available to other users.

[0922] Input: revised and enhanced content.

[0923] Output: Content published on the platform.

[0924] Step 11:

[0925] Recording learning completion and sending data

[0926] When a user completes a designated learning plan or course, the device notifies the server of that data.

[0927] Input: Completed training data.

[0928] Output: Learning completion data notified to the server.

[0929] Step 12:

[0930] Managing learning history

[0931] The server records the received learning completion data on the blockchain in NFT format, which prevents data tampering and ensures reliability.

[0932] Input: Learning completion data notified to the server.

[0933] Output: Training completion data recorded on the blockchain as an NFT.

[0934] Step 13:

[0935] Issuing and Displaying Rewards

[0936] The server issues and notifies the user of a reward token based on the results of their learning.

[0937] The terminal displays the received reward token information on the dashboard.

[0938] Input: Learning outcome data.

[0939] Output: Information about reward tokens issued to users.

[0940] Step 14:

[0941] Administrator login and data collection and analysis

[0942] Business and local government administrators log in to the platform's management screen, and the server compiles and analyzes the learning data of all employees and citizens in real time, using data analysis technology to identify trends.

[0943] Input: employee and citizen learning data.

[0944] Output: Aggregation and analysis results displayed on the management screen.

[0945] Step 15:

[0946] Viewing the dashboard and providing support

[0947] The server displays the aggregated and analyzed results on an administrator dashboard and generates counseling and support messages appropriate for each individual learner.

[0948] Input: Aggregation and analysis results.

[0949] Output: Generated counseling or support messages.

[0950] The above are the processing steps of the program for this system. The specific operations performed at each step, as well as their inputs and outputs, have been explained in detail.

[0951] (Application example 1)

[0952] 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."

[0953] Conventional educational platforms have faced issues such as inconsistent quality of educational content and difficulty in responding flexibly to user progress. Furthermore, there was a lack of means to provide appropriate information and support in real time when training staff and responding to customers in physical stores. Furthermore, there was an inadequate system for reliably recording users' learning outcomes and issuing appropriate rewards. There is a need to solve these issues and provide a high-quality, efficient educational environment and customer support.

[0954] 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.

[0955] In this invention, the server includes a means for an educator to input educational content into a terminal, a means for transmitting the educational content from the terminal to the server, a means for the server to evaluate the educational content using a generative artificial intelligence model and modify or enhance it as necessary, a means for publishing the modified or enhanced educational content on the platform, a means for users to use the published educational content, a means for providing product information and counseling in real time using a smart device, and a means for providing real-time answers to customer questions using a generative artificial intelligence model. This enables improved quality of educational content, flexible learning support, and efficient staff training and customer service in physical stores. Furthermore, by utilizing a generative artificial intelligence model and blockchain technology, the reliability of learning outcomes can be ensured and fair rewards can be provided.

[0956] "Educators" refers to instructors and teachers who provide educational content.

[0957] "Educational content" refers to the information and materials that learners are expected to acquire.

[0958] "Terminal" refers to an electronic device that allows a user or educator to input information and communicate with a server.

[0959] "Server" refers to a centralized computer system for processing information and using generative artificial intelligence models.

[0960] A "generative artificial intelligence model" refers to an artificial intelligence system that has the ability to learn from data and generate new information.

[0961] "Evaluation" refers to the process by which a generative artificial intelligence model examines the quality and suitability of educational content.

[0962] "Modification and enhancement" refers to the process of improving educational content and making it easier to understand based on the evaluation results.

[0963] "Publishing" refers to the act of displaying the revised or enhanced educational content on the Platform and making it accessible to Users.

[0964] "Platform" refers to the entire system for providing educational content and learning plans.

[0965] "User" refers to an individual who uses the educational platform and learns.

[0966] "Interests and skill level" refers to information that indicates the areas the user wants to learn and their current learning progress.

[0967] "Study Plan" refers to a study plan that combines learning materials and courses that are best suited to the user.

[0968] "Progress" refers to information that indicates the user's learning situation and level of achievement.

[0969] "Counseling and support messages" refer to advice and encouraging messages provided by the generative artificial intelligence model to help the user learn.

[0970] A "smart device" refers to a device that is connected to the Internet and has sensors and processing capabilities.

[0971] "Real-time" refers to instantaneous processing and response of information.

[0972] "Product information" refers to data such as detailed descriptions and usage instructions for products sold in physical stores.

[0973] "Customer service" refers to the work of responding to customer questions and requests in physical stores.

[0974] "Learning Completion Data" means records generated when a user completes a particular learning plan or course.

[0975] "Blockchain" refers to a distributed ledger technology that prevents data tampering and ensures reliability.

[0976] "NFT format" refers to data in the form of a non-fungible token that represents a unique digital asset on a blockchain.

[0977] "Reward tokens" refer to digital currencies or points issued for learning outcomes.

[0978] To implement the present invention, the following steps and associated hardware and software are used.

[0979] System configuration

[0980] Server: This plays a central role in the system. It uses generative AI models to provide educational content and counseling, monitors learning progress, and issues appropriate rewards. The server uses cloud infrastructure such as Microsoft Azure Server or AWS EC2.

[0981] Terminal: A device that users and educators use to input information and communicate with the server. Examples include smartphones, tablets, PCs, and smart glasses. HoloLens 2 and Google Glass Enterprise Edition 2 are used as smart glasses.

[0982] Generative AI model: Performs various AI processes such as evaluating educational content, generating learning plans, and generating counseling messages. Specifically, OpenAI's GPT-3.5 model is used.

[0983] Blockchain: Used to ensure the reliability of learning completion data, and uses Ethereum and Hyperledger.

[0984] Input and evaluation of educational content

[0985] Educators input educational content into their devices and send it to the server. The server uses a generative AI model to evaluate the content and correct or enhance it as needed. For example, it checks grammar, content accuracy, and understandability. The corrected or enhanced educational content is published on the platform and available to other users.

[0986] Generate a learning plan

[0987] The user inputs their areas of interest and current skill level into the device. The server uses a generative artificial intelligence model based on the received information to generate an optimal learning plan. This plan includes recommended learning materials and courses and is sent to the device. The user then proceeds with their studies based on this learning plan.

[0988] Progress monitoring and counseling

[0989] The server monitors the user's learning progress in real time, analyzing learning logs and progress data to confirm whether the user is following the learning plan. If progress is falling behind, the server uses a generative artificial intelligence model to generate appropriate counseling and support messages and send them to the user's device.

[0990] Use of smart devices

[0991] Store staff can use smart glasses to provide real-time product information and customer consultations. Generative AI models are used to provide quick answers to customer questions. This system enhances staff training and customer service.

[0992] Recording learning completion data and issuing reward tokens

[0993] When a user completes a designated learning plan, the learning completion data is sent from the device to the server. The server records the learning completion data on the blockchain in NFT format. It also issues reward tokens to the user based on their learning results and notifies the device. This reward token information is also displayed on the smart device.

[0994] Examples of concrete examples and prompts

[0995] As a concrete example, consider a case where a customer asks a store staff member wearing smart glasses about a new smartphone. The staff member speaks to the smart glasses, and the server uses voice recognition to convert the question into text and send it to a generative artificial intelligence model. The answer generated by the AI ​​is displayed on the screen, and the staff member can relay it to the customer.

[0996] Example prompt sentence:

[0997] "If a customer asks about a new smartphone, provide them with the latest information."

[0998] "Generate training plans for new staff."

[0999] This will enable improved quality of educational content, flexible learning support, and efficient staff training and customer support in physical stores. By utilizing generative AI models and blockchain technology, it will be possible to ensure the reliability of learning results and provide fair compensation.

[1000] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1001] Step 1:

[1002] The educator inputs the educational content into the device. The input data here is educational content such as text information, images, and videos. The device converts this information into a format and sends it to the server.

[1003] Step 2:

[1004] The server passes the received educational content to a generative AI model for evaluation. Specifically, it checks the accuracy of grammar and content, as well as ease of understanding. During this process, the generative AI model analyzes the text and metadata to generate an evaluation result.

[1005] Step 3:

[1006] The server modifies and enhances the educational content based on the evaluation results, for example, correcting deficiencies and errors and inserting necessary additional explanations and examples. The modified and enhanced educational content is generated and made available for publication.

[1007] Step 4:

[1008] The server publishes the revised and enhanced educational content on the platform, and the published content is registered in a database in a format that can be accessed by other users.

[1009] Step 5:

[1010] Users log in to the platform and input their areas of interest and current skill level into their device. A learning plan is generated based on this input information, and specific items include areas of interest, skill level, and learning objectives.

[1011] Step 6:

[1012] The server uses a generative AI model based on the input data received from the user to generate an optimal learning plan. Data processing here includes analyzing the user profile and selecting learning materials from a database.

[1013] Step 7:

[1014] The server sends the generated learning plan to the user's device, which displays the received learning plan to the user and guides them to the next learning step.

[1015] Step 8:

[1016] The user progresses through their studies based on the study plan. Their progress is recorded as login history and study log, and periodically sent to the server.

[1017] Step 9:

[1018] The server monitors the user's learning progress in real time, analyzes the learning log and progress data, and generates appropriate counseling and support messages using a generative artificial intelligence model.

[1019] Step 10:

[1020] Once the support message is generated, the server sends it to the user's terminal, which notifies the user of the received message and provides the necessary support.

[1021] Step 11:

[1022] Staff use smart glasses to assist customers in brick-and-mortar stores. Customers' questions are entered by voice, and the device sends the information to a server.

[1023] Step 12:

[1024] The server uses speech recognition technology to convert the question into text and uses a generative artificial intelligence model to generate an answer, which is then displayed on the smart glasses' display.

[1025] Step 13:

[1026] When a user completes a learning plan, the user sends the data from the device to the server. The learning completion data includes the course studied and the achievement level.

[1027] Step 14:

[1028] The server receives the learning completion data and records it on the blockchain in NFT format, which ensures the data is tamper-proof and reliable.

[1029] Step 15:

[1030] The server issues reward tokens based on the user's learning results and notifies the terminal, which then displays the reward token information to the user and provides instructions on how to use it.

[1031] 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.

[1032] ---

[1033] The present invention relates to an educational platform that utilizes a generative artificial intelligence model and an emotion engine. In this platform, educators input educational content into a terminal, and a server evaluates, corrects, enhances, and publishes it. The platform also generates an optimal learning plan based on the information entered by the user, monitors learning progress while recognizing the user's emotions using an emotion engine, and provides appropriate support and counseling. Furthermore, learning completion data is recorded on a blockchain, and reward tokens are issued according to learning results. Specific embodiments of the present invention are described below.

[1034] Creating a study plan

[1035] 1. Enter your user information

[1036] Users input their areas of interest, current skill level, and learning goals through the educational platform terminal. For example, a user may input, "I want to learn the basics of generative artificial intelligence."

[1037] 2. Transmission of User Information

[1038] The terminal transmits the input user information to the server.

[1039] 3. Generating optimal study plans

[1040] The server utilizes a generative artificial intelligence model based on the received user information to generate an optimal learning plan for the user, including recommended learning materials and courses.

[1041] 4. Submit your study plan

[1042] The server transmits the generated study plan to the user's terminal.

[1043] 5. View your study plan

[1044] The terminal displays the received study plan to the user, and the user starts studying based on it.

[1045] Learning support and counselling

[1046] 1. Monitoring your learning progress

[1047] The server monitors the user's learning progress in real time, periodically collecting and analyzing learning logs and progress data.

[1048] 2. Collecting Emotional Data

[1049] The device uses an emotion engine to collect emotional data from the user while they are learning, including information obtained through facial expression recognition and voice analysis.

[1050] 3. Sending Emotional Data

[1051] The terminal transmits the collected emotion data to the server.

[1052] 4. Learning assistance decisions

[1053] The server evaluates the user's learning progress and emotional state based on the received learning progress data and emotional data.

[1054] 5. Generate a support message

[1055] The server uses a generative artificial intelligence model to generate counseling and support messages based on the user's emotional state, for example, a message recommending a break if the user is tired.

[1056] 6. Sending a support message

[1057] The server sends the generated support message to the user's terminal.

[1058] 7. Displaying support messages

[1059] The terminal notifies the user of a support message, so that the user can receive the necessary support.

[1060] Content Creation and Evaluation

[1061] 1. Content Creation

[1062] Educators input new educational content into the terminal and send it to the server, for example, creating an "introductory course in Python programming."

[1063] 2. Submitting Content

[1064] The terminal transmits the created content to the server.

[1065] 3. Content Rating

[1066] The server evaluates the received content using a generative artificial intelligence model, specifically checking the accuracy of grammar and content, and assessing the ease of understanding for the user.

[1067] 4. Content Modifications and Enhancements

[1068] Based on the evaluation results, the server automatically corrects and enhances the content, correcting deficiencies and errors and inserting additional explanations and examples where necessary.

[1069] 5. Publishing Content

[1070] The server will then publish the modified and enhanced content on the platform, making it available to other users.

[1071] Learning history and reward management

[1072] 1. Record your learning completion

[1073] A user completes a designated learning plan or course.

[1074] 2. Sending training data

[1075] The terminal notifies the server that the learning is complete.

[1076] 3. Managing your learning history

[1077] The server records the received learning completion data on the blockchain in NFT format, which prevents data tampering and ensures reliability.

[1078] 4. Issuance of rewards

[1079] The server issues reward tokens to the user according to the results of the learning and notifies the terminal.

[1080] 5. Display of Rewards

[1081] The terminal displays information about the reward tokens issued to the user.

[1082] Functions for businesses and local governments

[1083] 1. Administrator login

[1084] Administrators of companies and local governments log in to the platform's administration screen.

[1085] 2. Aggregation and analysis of learning status

[1086] The server collects and analyzes the learning data of all employees and citizens in real time.

[1087] 3. View the dashboard

[1088] The server displays the results of the aggregation and analysis on an administrator dashboard, allowing administrators to grasp the learning status in a unified manner.

[1089] 4. Providing the support you need

[1090] The server uses a generative artificial intelligence model to generate messages when an individual learner needs appropriate counseling or support.

[1091] 5. Sending a support message

[1092] The server transmits the generated support message to the learner's terminal.

[1093] As described above, as a mode for implementing the invention, the system of the present invention provides an efficient and fair educational environment for educators, users, and corporate and local government administrators. At each step, generative AI models, emotion engines, and blockchain technology are utilized to improve the quality of educational content, manage learning progress, and provide fair rewards.

[1094] The processing flow will be explained below.

[1095] Now, let's explain the specific steps of a specific process in more detail.

[1096] ---

[1097] Creating a study plan

[1098] Step 1:

[1099] Users input their areas of interest, current skill level, and learning goals through the educational platform terminal. For example, a user may input, "I want to learn the basics of generative artificial intelligence."

[1100] Step 2:

[1101] The terminal transmits the input user information to the server.

[1102] Step 3:

[1103] The server inputs the received user information into a generative artificial intelligence model to generate an optimal learning plan for the user. The generated learning plan includes recommended learning materials and courses, which are selected based on the user's skill level and learning goals.

[1104] Step 4:

[1105] The server transmits the generated study plan to the user's terminal.

[1106] Step 5:

[1107] The terminal displays the received study plan to the user, and the user starts studying based on it.

[1108] ---

[1109] Learning support and counselling

[1110] Step 1:

[1111] The server monitors the user's learning progress in real time, and progress data is collected periodically and recorded as a learning log.

[1112] Step 2:

[1113] The device uses an emotion engine to collect emotion data from the user while the user is learning, for example, through facial expression recognition or voice analysis.

[1114] Step 3:

[1115] The terminal transmits the collected emotion data to the server.

[1116] Step 4:

[1117] The server evaluates the user's learning progress and emotional state based on the received learning progress data and emotional data, using a generative artificial intelligence model to confirm whether the user is progressing as expected.

[1118] Step 5:

[1119] The server generates counseling and support messages based on the user's emotional state. For example, if the server determines that the user is tired, it generates a message such as "Take a short break."

[1120] Step 6:

[1121] The server sends the generated support message to the user's terminal.

[1122] Step 7:

[1123] The terminal notifies the user of a support message, so that the user can receive the necessary support.

[1124] ---

[1125] Content Creation and Evaluation

[1126] Step 1:

[1127] Educators input new educational content into the terminal and send it to the server, for example, creating an "introductory course in Python programming."

[1128] Step 2:

[1129] The terminal transmits the created content to the server.

[1130] Step 3:

[1131] The server evaluates the received content using a generative artificial intelligence model, specifically checking the accuracy of grammar and content, and assessing the ease of understanding for the user.

[1132] Step 4:

[1133] Based on the evaluation results, the server automatically corrects and enhances the content, for example, correcting deficiencies and errors and inserting additional explanations and examples where necessary.

[1134] Step 5:

[1135] The server will then publish the modified and enhanced content on the platform, making it available to other users.

[1136] ---

[1137] Learning history and reward management

[1138] Step 1:

[1139] A user completes a designated learning plan or course.

[1140] Step 2:

[1141] The terminal notifies the server that the learning is complete.

[1142] Step 3:

[1143] The server then records the received learning completion data on the blockchain in NFT format, which prevents tampering and ensures the reliability of the learning history.

[1144] Step 4:

[1145] The server issues reward tokens to the user according to the results of the learning and notifies the terminal.

[1146] Step 5:

[1147] The terminal displays information about the reward tokens issued to the user.

[1148] ---

[1149] Functions for businesses and local governments

[1150] Step 1:

[1151] Administrators of companies and local governments log in to the platform's administration screen.

[1152] Step 2:

[1153] The server collects and analyzes the learning data of all employees and citizens in real time.

[1154] Step 3:

[1155] The server displays the results of the aggregation and analysis on an administrator dashboard, allowing administrators to grasp the learning status in a unified manner.

[1156] Step 4:

[1157] If the server determines that a particular learner needs appropriate counseling or support, it generates a message using a generative artificial intelligence model.

[1158] Step 5:

[1159] The server transmits the generated support message to the learner's terminal.

[1160] ---

[1161] The above are the specific processing steps of the present invention. By combining a generative AI model, an emotion engine, and blockchain technology, the present invention improves the quality of educational content, manages learning progress, and provides fair rewards.

[1162] Example 2

[1163] 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."

[1164] Current educational platforms lack the ability to monitor and support individual users' learning progress and emotional state in real time. Furthermore, assessment and correction of learning content is not carried out promptly, and the quality of the results is often inconsistent. Furthermore, there is no reliable recording of learning outcomes or fair distribution of rewards. This leads to issues such as a decline in learner motivation and a lack of improvement in learning efficiency.

[1165] 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. In this invention, the server includes a means for an educator to input educational content into a terminal, a means for transmitting the educational content from the terminal to the server, a means for the server to evaluate the educational content using a generative artificial intelligence model and modify or enhance it as necessary, a means for publishing the modified or enhanced educational content on a platform, a means for a learner to use the published educational content, a means for a learner to input learning goals and skill levels into a terminal, a means for transmitting learner information from the terminal to the server, a means for the server to generate an optimal learning plan for a learner using a generative artificial intelligence model, a means for transmitting the generated learning plan to the learner's terminal, a means for the terminal to display the generated learning plan to the learner and for the learner to proceed with learning based on it, a means for the server to monitor the learner's learning progress in real time, and a means for the terminal to display an emotional emotion. The platform includes a means for collecting learners' emotional data using an engine and transmitting it to a server, a means for the server to analyze the collected learning progress data and emotional data, generate appropriate counseling and support messages, and transmit them to the device, a means for the learner's learning completion data to be transmitted from the device to the server, a means for the server to record the learning completion data on the blockchain in NFT format, a means for the server to issue reward tokens to learners according to their learning outcomes and notify the device, a means for a company or local government administrator to log in to the platform's management screen, a means for the server to aggregate and analyze the learning data of all learners, a means for the server to display the results of the server's aggregation and analysis on an administrator dashboard, and a means for the server to generate appropriate counseling and support messages for each learner and transmit them to the device. This enables real-time monitoring and support of individual users' learning progress and emotional states, rapid evaluation and correction of educational content, reliable recording of learning outcomes, and fair distribution of rewards.

[1166] "Educators" refers to experts and teachers who design and teach educational content.

[1167] "Terminal" refers to an electronic device used to access the educational platform and input information.

[1168] "Server" refers to a central processing unit that processes, stores, transmits and receives data over a network.

[1169] A "generative artificial intelligence model" refers to a machine learning algorithm that generates natural language, providing optimal responses and generating results based on user input.

[1170] "Learner" refers to an individual who learns educational content through the educational platform.

[1171] "Educational content" refers to the content of teaching materials and lessons designed to impart specific knowledge or skills.

[1172] "Study plan" refers to a suggested learning approach or plan based on the learner's goals and skill level.

[1173] An "emotion engine" refers to software that analyzes a user's facial expressions and voice data to recognize their emotional state.

[1174] "Counseling" refers to helping learners to provide psychological support during their learning process.

[1175] "Support messages" refer to guidance and encouragement messages sent based on the user's learning progress and emotional state.

[1176] "Blockchain" refers to a technology that manages transaction records on a distributed network to ensure data reliability.

[1177] "NFT format" refers to a technology for representing digital data in the form of non-fungible tokens.

[1178] "Reward tokens" refer to digital assets issued based on learning outcomes.

[1179] "Corporate or local government administrator" refers to the person in charge of operating and managing the educational platform in a specific organization or region.

[1180] "Administration screen" refers to a dedicated interface for operating and managing a system or platform.

[1181] A "dashboard" refers to a screen that displays data aggregation and analysis results in real time.

[1182] This invention relates to an educational platform that utilizes a generative artificial intelligence model and an emotion engine. This platform allows educators to input educational content, which is then evaluated, revised, and reinforced using a generative artificial intelligence model, providing learners with optimal learning plans. It also monitors learners' progress and emotional state in real time and provides appropriate counseling and support messages. Furthermore, learning outcomes are recorded on a blockchain, and fair reward tokens are issued to maintain and improve learners' motivation.

[1183] Hardware and software used

[1184] Hardware:

[1185] Device: Electronic device such as a personal computer, smartphone, or tablet.

[1186] Server: Central processing unit that processes and stores data

[1187] software:

[1188] Generative AI models: Natural language generation models (e.g., ChatGPT, GPT-4)

[1189] Emotion engine: facial expression recognition software (e.g., Emotion API)

[1190] Blockchain technology: Data recording technology in the form of NFTs

[1191] Creating study plans and providing counseling

[1192] Example 1: Creating a study plan

[1193] A user logs in to the educational platform terminal and enters their area of ​​interest, current skill level, and learning objectives. For example, they might enter "I want to learn the basics of generative artificial intelligence," "Beginner level," or "I want to learn new technologies."

[1194] The terminal transmits this information to the server.

[1195] The server uses a generative artificial intelligence model to generate an optimal learning plan. The prompt is "Please generate the optimal learning plan based on the user's interests, skill level, and goals."

[1196] The server transmits the generated study plan to the terminal and displays it to the user.

[1197] Example 2: Providing counseling and support messages

[1198] The server collects the user's learning progress data in real time and also collects emotion data using an emotion engine.

[1199] The device uses a camera and microphone to collect user emotion data and transmits it to a server.

[1200] The server analyzes the collected data and evaluates the user's progress and emotional state.

[1201] The server uses a generative artificial intelligence model to generate counseling and support messages according to the user's emotional state. The prompt text is "If the user is tired, please generate a message recommending that he or she take a break."

[1202] The server sends the generated support message to the device, which then displays it to the user, such as "You seem tired, so please take a 10-minute break."

[1203] Recording learning results and issuing rewards

[1204] Example 3: Recording learning outcomes and issuing reward tokens

[1205] After the user completes the learning plan, the terminal transmits learning completion data to the server.

[1206] The server records this data on the blockchain in NFT format, which prevents data tampering and increases reliability.

[1207] The server issues reward tokens based on the learning results and notifies the terminal of the information.

[1208] The terminal displays information about the reward tokens issued to the user.

[1209] Management functions for businesses and local governments

[1210] Example 4: Real-time management and support

[1211] Administrators from companies and local governments log in to the platform's administration screen.

[1212] The server collects and analyzes data from all learners in real time and displays it on an administrator dashboard.

[1213] The server generates an appropriate support message for each learner as needed and transmits it to the terminal.

[1214] In this way, the system of the present invention monitors each user's learning progress and emotional state in real time and provides appropriate support to improve learning efficiency and motivation. It also improves the quality of educational content and provides a fair learning environment by recording learning results and issuing reward tokens.

[1215] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1216] Step 1:

[1217] Users log in to the educational platform terminal and enter their areas of interest, current skill level, and learning goals. For example, they can enter information such as "I want to learn the basics of generative artificial intelligence," "Beginner level," or "I want to learn new technologies." This input information becomes the basis for generating subsequent learning plans.

[1218] Step 2:

[1219] The device sends the entered user information to the server. Specifically, data such as the user ID, areas of interest, skill level, and learning goals is sent to the API endpoint via the HTTPS protocol. The input data at this stage is stored on the server.

[1220] Step 3:

[1221] The server receives the user information and uses a generative artificial intelligence model to generate an optimal learning plan. Specifically, the server inputs the prompt "Please generate the optimal learning plan based on the user's areas of interest, skill level, and goals" to the generative AI model. The generative AI model performs data calculations based on this information, generates a learning plan tailored to each individual user, and outputs the results.

[1222] Step 4:

[1223] The server sends the generated learning plan to the user's device. The data sent is the details of the generated learning plan, which is output as an API response from the server to the device.

[1224] Step 5:

[1225] The device displays the received learning plan to the user. For example, links to "Basic Course on Generative Artificial Intelligence" and "Recommended Learning Materials" are displayed on the web browser screen. The user can then access the displayed learning plan and begin learning.

[1226] Step 6:

[1227] The server monitors the user's learning progress in real time. It periodically collects and analyzes data such as when the user accesses the learning materials, the study time, and test results, and stores the data in a database. The input data at this stage becomes the user's learning log.

[1228] Step 7:

[1229] The device uses an emotion engine to collect emotional data from the user during training. It uses a camera and microphone to collect emotional data in real time through facial expression recognition and voice analysis. This emotional data is also sent by the device to the server.

[1230] Step 8:

[1231] The server analyzes the received learning progress data and emotional data, which evaluates the user's learning situation and emotional state. Based on the analysis results, it generates appropriate counseling and support messages. For example, the server can input a prompt to the generative AI model such as, "If the user is tired, please generate a message recommending that he or she take a break."

[1232] Step 9:

[1233] The server sends the generated counseling or support message to the user's terminal. The data sent is the text of the support message, which is output as a response from the server to the terminal.

[1234] Step 10:

[1235] The device will display support messages to the user, such as "You seem tired, please take a 10-minute break," allowing the user to receive the necessary rest and support.

[1236] Step 11:

[1237] When a user completes a learning plan or course, the data is sent from the device to the server. A learning completion notification is sent as an API request and saved as input data on the server.

[1238] Step 12:

[1239] The server records the learning completion data on the blockchain in NFT format, which ensures the reliability and tamper-proofness of the data.

[1240] Step 13:

[1241] The server issues a reward token to the user based on their learning results and sends a notification to the terminal. Information about this reward token is output as a response from the server to the terminal.

[1242] Step 14:

[1243] The terminal displays information about the reward tokens issued to the user, allowing the user to check the rewards according to their learning results and maintain motivation for the next lesson.

[1244] (Application example 2)

[1245] 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."

[1246] Traditional educational platforms lack support that can flexibly adapt to learners' progress and emotional state. As a result, they can only provide uniform learning support, making it difficult to maximize the motivation and learning effectiveness of individual learners. Furthermore, they lack the means to ensure the reliability of learning outcomes and properly evaluate them, which can make it difficult for learners to feel a sense of accomplishment and reduce their persistence in learning. Furthermore, because they do not provide appropriate incentives for learning outcomes, learners' interest and motivation can be lost.

[1247] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1248] In this invention, the server includes a means for educators to evaluate educational content and modify or enhance it as necessary, a means for analyzing the user's learning progress data and emotional data and generating support messages, a means for sending the generated learning plan and support messages to the user, and a means for recording learning completion data on the blockchain and issuing reward tokens. This makes it possible to provide support tailored to each learner's progress and emotional state, which is expected to improve learning effectiveness and maintain motivation. Furthermore, the reliability and fair evaluation of learning outcomes are ensured, and learners gain a sense of accomplishment, encouraging them to continue learning. Furthermore, the reward tokens provide an incentive for learning, increasing interest and motivation in learning.

[1249] "Educator" refers to an individual or organization that creates and delivers educational content.

[1250] "Terminal" refers to an electronic device used by an educator or user for input and output.

[1251] "Server" refers to the central processing unit that processes and manages data for the entire educational platform.

[1252] "Generative AI model" refers to an AI algorithm that evaluates, corrects, and reinforces educational content, generates learning plans, and generates support messages.

[1253] An "emotion engine" refers to technology that analyzes a user's facial expressions and voice data to evaluate their emotional state.

[1254] "Platform" refers to the entire online system for supporting educators in providing content and users in learning.

[1255] "User" refers to an individual who uses the educational platform to learn.

[1256] A "study plan" refers to a study plan that is optimal for a user, generated based on the user's interests and skill level.

[1257] "Study progress data" refers to data that indicates the progress of a user's studies.

[1258] "Emotion data" refers to data indicative of a user's emotional state collected using an emotion engine.

[1259] A "support message" refers to a message containing support content that is generated by a generative artificial intelligence model based on a user's learning progress data and emotional data and sent to the user.

[1260] "Study completion data" refers to data indicating that a user has completed a specified learning plan or course.

[1261] "Blockchain" refers to a technology that uses distributed ledger technology to record learning completion data to prevent tampering.

[1262] "NFT format" refers to a method of recording data in non-fungible token format.

[1263] "Reward token" refers to a digital reward issued based on a user's learning achievements.

[1264] This invention relates to an educational platform using a generative artificial intelligence model and an emotion engine. This platform evaluates and corrects educational content provided by educators, creates learning plans and monitors progress for users, generates support messages using emotion data, records learning outcomes on a blockchain, and issues reward tokens.

[1265] Use of generative artificial intelligence models

[1266] The server uses a generative artificial intelligence model to evaluate the educational content entered by educators and correct or enhance it as needed. This process uses algorithms to evaluate grammatical accuracy, content consistency, and user comprehension.

[1267] Emotion data collection and analysis

[1268] When users use the educational platform, they learn through smart devices (smartphones, smart glasses, head-mounted displays). These devices are equipped with cameras and microphones to collect the user's facial expressions and voice. The server uses an emotion engine to analyze this data and evaluate the user's emotional state in real time.

[1269] Creating a study plan and monitoring progress

[1270] The server uses a generative artificial intelligence model to generate an optimal learning plan based on user information (areas of interest, skill level, learning goals). The generated learning plan is sent to the user's device, and the user proceeds with their studies based on it. The server periodically collects and analyzes the user's learning progress data.

[1271] Generate a support message

[1272] The server uses a generative artificial intelligence model to generate appropriate support messages based on the collected learning progress data and user emotion data. For example, if the learning progress is slow or the user feels fatigued, a message recommending a break or a message offering additional learning resources is generated.

[1273] Blockchain and Reward Tokens

[1274] When a user completes a learning plan or course, the server records the learning completion data on the blockchain in NFT format, ensuring data tamper-proofing and reliability. Depending on the learning results, the server issues reward tokens to the user and provides incentives by notifying the device.

[1275] Specific examples

[1276] Example prompt for generating a lesson plan:

[1277] "The user's area of ​​interest is 'generative artificial intelligence'. Their skill level is 'beginner' and their learning goal is 'learn the basics'. Please generate the optimal learning plan based on this."

[1278] Example prompt for generating a support message:

[1279] "User's progress data is '75% complete'. Sentiment data indicates 'Exhausted'. Please generate a support message appropriate for this state."

[1280] As described above, the system of the present invention provides an efficient and fair educational environment for educators, users, and corporate and local government administrators. At each step, generative AI models, emotion engines, and blockchain technology are utilized to improve the quality of educational content, manage learning progress, and provide fair rewards.

[1281] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1282] Step 1:

[1283] Entering user information

[1284] The user inputs their area of ​​interest, skill level, and learning goals through the terminal. For example, they might input, "I want to learn the basics of generative artificial intelligence." Input: Information the user inputs into the terminal (area of ​​interest, skill level, learning goals). Output: This information is sent from the terminal to the server.

[1285] Step 2:

[1286] Sending user information

[1287] The terminal sends the user information entered in step 1 to the server. Input: Data entered by the user. Output: Data sent from the terminal to the server.

[1288] Step 3:

[1289] Generate optimal study plans

[1290] The server uses a generative artificial intelligence model based on the received user information to generate an optimal study plan for the user. Input: User information. Data processing: The generative artificial intelligence model analyzes the data and generates an appropriate study plan. Output: Generated study plan.

[1291] Step 4:

[1292] Submit your study plan

[1293] The server sends the generated learning plan to the user's device. Input: Learning plan. Output: Sending the learning plan from the server to the device.

[1294] Step 5:

[1295] View your learning plan

[1296] The device displays the received study plan to the user, who then begins studying based on it. Input: Study plan sent from the server. Output: Study plan displayed on the device.

[1297] Step 6:

[1298] Monitoring learning progress

[1299] The server monitors the user's learning progress in real time. Input: User's learning log and progress data. Data calculation: Data analysis is performed to grasp the learning progress. Output: Analysis results.

[1300] Step 7:

[1301] Collecting Emotional Data

[1302] The device collects the user's facial expressions and voice during training through the emotion engine. Input: Facial expression and voice data collected through the camera and microphone. Output: Emotion data.

[1303] Step 8:

[1304] Sending emotional data

[1305] The device sends the collected emotion data to the server. Input: Collected emotion data. Output: Data transmission from the device to the server.

[1306] Step 9:

[1307] Learning assistance decisions

[1308] The server evaluates the user's state based on the received learning progress data and emotion data. Input: Learning progress data and emotion data. Data calculation: Data analysis for state evaluation. Output: Evaluation of the user's learning state.

[1309] Step 10:

[1310] Generate a support message

[1311] The server uses a generative artificial intelligence model to generate a support message according to the learning status. Input: Evaluation results. Data processing: Generation of support message. Output: Generated support message.

[1312] Step 11:

[1313] Send a support message

[1314] The server sends the generated support message to the user's terminal. Input: Support message. Output: Sending the support message.

[1315] Step 12:

[1316] Displaying a support message

[1317] The terminal notifies the user of the support message, allowing the user to receive the necessary support. Input: Support message. Output: Support message displayed on the terminal.

[1318] Step 13:

[1319] Sending learning completion data

[1320] When the user completes the specified learning plan or course, the device sends learning completion data to the server. Input: Learning completion data. Output: Completion data sent from the device to the server.

[1321] Step 14:

[1322] Recording of learning completion data

[1323] The server records the received learning completion data in NFT format on the blockchain. Input: Learning completion data. Data processing: Recording to the blockchain. Output: Recorded data.

[1324] Step 15:

[1325] Reward Token Issuance

[1326] The server issues reward tokens to users according to their learning results and notifies the terminal. Input: Learning results data. Output: Issuance and notification of reward tokens.

[1327] Step 16:

[1328] View Reward Tokens

[1329] The terminal displays information about the reward tokens issued to the user. Input: Reward token information. Output: Reward token information displayed on the terminal.

[1330] 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.

[1331] 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.

[1332] 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.

[1333] [Third embodiment]

[1334] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1335] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1336] 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).

[1337] 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.

[1338] 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.

[1339] 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).

[1340] 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.

[1341] 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.

[1342] 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.

[1343] 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.

[1344] 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.

[1345] 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."

[1346] ---

[1347] The present invention relates to an educational platform that utilizes a generative artificial intelligence model. In this platform, educators input educational content into a terminal, and a server evaluates, corrects, enhances, and publishes it. The platform also generates an optimal learning plan based on the information entered by the user, monitors learning progress, and provides appropriate support. Furthermore, learning completion data is recorded on a blockchain, and reward tokens are issued according to learning results. Specific embodiments of the present invention are described below.

[1348] Creating a study plan

[1349] 1. Enter your user information

[1350] Users input their areas of interest, current skill level, and learning goals through the educational platform terminal. For example, a user may input, "I want to learn the basics of generative artificial intelligence."

[1351] 2. Transmission of User Information

[1352] The terminal transmits the input user information to the server.

[1353] 3. Generating optimal study plans

[1354] The server utilizes a generative artificial intelligence model based on the received user information to generate an optimal learning plan for the user, including recommended learning materials and courses.

[1355] 4. Submit your study plan

[1356] The server transmits the generated study plan to the user's terminal.

[1357] 5. View your study plan

[1358] The terminal displays the received study plan to the user, and the user can proceed with his / her studies based on it.

[1359] Learning support and counselling

[1360] 1. Monitoring your learning progress

[1361] The server monitors the user's learning progress in real time, analyzing learning logs and progress data to confirm whether the user is progressing according to the plan.

[1362] 2. Learning assistance decisions

[1363] The server uses a generative artificial intelligence model to generate counseling and assistance messages if the user is behind or if appropriate support is needed. For example, if the user stops studying for a certain period of time, the server generates an encouraging message.

[1364] 3. Sending an assist message

[1365] The server transmits the generated assist message to the user's terminal.

[1366] 4. Display of assist messages

[1367] The terminal notifies the user of an assist message and provides the necessary support.

[1368] Content Creation and Evaluation

[1369] 1. Content Creation

[1370] Educators input new educational content into the terminal and send it to the server, for example, creating an "introductory course in Python programming."

[1371] 2. Submitting Content

[1372] The terminal transmits the created content to the server.

[1373] 3. Content Rating

[1374] The server evaluates the received content using a generative artificial intelligence model, specifically checking the accuracy of grammar and content, and assessing the ease of understanding for the user.

[1375] 4. Content Modifications and Enhancements

[1376] Based on the evaluation results, the server automatically corrects and enhances the content, for example, correcting deficiencies and errors and inserting necessary additional explanations and examples.

[1377] 5. Publishing Content

[1378] The server will then publish the modified and enhanced content on the platform, making it available to other users.

[1379] Learning history and reward management

[1380] 1. Record your learning completion

[1381] A user completes a designated learning plan or course.

[1382] 2. Sending training data

[1383] The terminal notifies the server that the learning is complete.

[1384] 3. Managing your learning history

[1385] The server records the received learning completion data on the blockchain in NFT format, which prevents data tampering and ensures reliability.

[1386] 4. Issuance of rewards

[1387] The server issues reward tokens to the user according to the results of the learning and notifies the terminal.

[1388] 5. Display of Rewards

[1389] The terminal displays information about the reward tokens issued to the user.

[1390] Functions for businesses and local governments

[1391] 1. Administrator login

[1392] Administrators of companies and local governments log in to the platform's administration screen.

[1393] 2. Aggregation and analysis of learning status

[1394] The server collects and analyzes the learning data of all employees and citizens in real time.

[1395] 3. View the dashboard

[1396] The server displays the results of the aggregation and analysis on an administrator dashboard, allowing administrators to grasp the learning status in a unified manner.

[1397] 4. Providing the support you need

[1398] The server uses a generative artificial intelligence model to generate messages when an individual learner needs appropriate counseling or support.

[1399] 5. Sending a support message

[1400] The server transmits the generated support message to the learner's terminal.

[1401] As described above, as a mode for implementing the invention, the system of the present invention provides an efficient and fair educational environment for educators, users, and corporate and local government administrators. At each step, generative AI models and blockchain technology are utilized to improve the quality of educational content, manage learning progress, and provide fair rewards.

[1402] The processing flow will be explained below.

[1403] ---

[1404] Creating a study plan

[1405] Step 1:

[1406] A user logs into the educational platform and inputs their area of ​​interest, current skill level, and learning objectives through a terminal.

[1407] Step 2:

[1408] The terminal transmits the input user information to the server.

[1409] Step 3:

[1410] The server inputs the received user information into a generative artificial intelligence model to generate an optimal learning plan for the user.

[1411] Step 4:

[1412] The server transmits the generated study plan to the user's terminal.

[1413] Step 5:

[1414] The terminal displays the received study plan to the user, and the user starts studying based on it.

[1415] Learning support and counselling

[1416] Step 1:

[1417] The server monitors the user's learning progress in real time, and periodically collects and analyzes learning logs and progress data.

[1418] Step 2:

[1419] The server evaluates the user's learning progress and level of understanding based on the data collected and analyzed.

[1420] Step 3:

[1421] If the server determines that progress is slow or that appropriate support is needed, it uses a generative artificial intelligence model to generate counseling or assistance messages.

[1422] Step 4:

[1423] The server transmits the generated assist message to the user's terminal.

[1424] Step 5:

[1425] The terminal notifies the user of an assist message, allowing the user to receive the necessary support.

[1426] Content Creation and Evaluation

[1427] Step 1:

[1428] An educator inputs new educational content into a terminal and transmits it to a server.

[1429] Step 2:

[1430] The terminal transmits the created content to the server.

[1431] Step 3:

[1432] The server evaluates the received content using a generative artificial intelligence model, checking the accuracy of grammar and content and assessing the ease of understanding for the user.

[1433] Step 4:

[1434] The server automatically corrects and enhances the content based on the evaluation results, correcting deficiencies and errors and inserting additional explanations and examples where necessary.

[1435] Step 5:

[1436] The server publishes the modified and enhanced content on the platform, making it available to other users.

[1437] Learning history and reward management

[1438] Step 1:

[1439] A user completes a designated learning plan or course.

[1440] Step 2:

[1441] The terminal notifies the server that the learning is complete.

[1442] Step 3:

[1443] The server records the received learning completion data on the blockchain in NFT format.

[1444] Step 4:

[1445] The server issues reward tokens to the user according to the results of their learning and notifies the terminal.

[1446] Step 5:

[1447] The terminal displays information about the reward tokens issued to the user.

[1448] Functions for businesses and local governments

[1449] Step 1:

[1450] Administrators from companies and local governments log in to the platform's administration screen.

[1451] Step 2:

[1452] The server collects and analyzes the learning data of all employees and citizens in real time.

[1453] Step 3:

[1454] The server displays the aggregated and analyzed results on the administrator dashboard.

[1455] Step 4:

[1456] If the server determines that a particular learner needs appropriate counseling or support, it generates a message using a generative artificial intelligence model.

[1457] Step 5:

[1458] The server transmits the generated support message to the learner's terminal.

[1459] The above is a specific processing flow in the platform of the present invention.

[1460] Example 1

[1461] 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."

[1462] Current education platforms do not adequately improve the quality of educational content, manage learning progress, or provide rewards based on learning outcomes. They also lack effective learning support, limiting the ways in which users can find optimal learning plans based on their interests and skill levels. Furthermore, there is a lack of mechanisms for companies and local governments to centrally manage the learning status of their employees and citizens and provide appropriate support.

[1463] 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.

[1464] In this invention, the server includes a means for evaluating the accuracy and understandability of educational content and making necessary improvements; a means for monitoring a user's learning activity in real time and generating counseling and assistance messages using a generative artificial intelligence model; a means for transmitting the generated learning plan and counseling messages to the user's device; a means for recording learning completion data in NFT format using blockchain technology; and a means for issuing reward tokens based on learning outcomes and notifying the user's device. This enables the improvement of the quality of educational content, management of learning progress, and provision of fair rewards based on learning outcomes. It also enables companies and local governments to centrally manage and support learners.

[1465] "Educator" is the person responsible for inputting educational content into the platform and imparting knowledge and skills to learners.

[1466] A "terminal" is a device that allows a user or educator to access the educational platform and input or display data.

[1467] A "server" is a central processing unit that processes input data, generates learning plans, and evaluates educational content.

[1468] A "generative artificial intelligence model" is an algorithm that generates appropriate assistance messages and learning plans based on user input information and educational content.

[1469] "Educational content" refers to educational materials and content created by educators, and is the subject matter for learners to study.

[1470] The "platform" is an online system that allows educators and learners to share educational content with each other and advance their learning.

[1471] A "study plan" is a study schedule and list of recommended learning materials generated based on the user's skill level and interests.

[1472] A "counseling message" is a message provided by the generative artificial intelligence model based on the user's learning progress to encourage increased motivation and progress in learning.

[1473] "Blockchain" is a distributed ledger technology that securely records learning completion data and prevents tampering.

[1474] The "NFT format" is a format that records learning completion data as a unique digital asset.

[1475] "Reward tokens" are digital rewards issued to users based on their learning outcomes and are used to receive rewards and benefits.

[1476] A "dashboard" is a graphical user interface provided to administrators to grasp the learning situation in real time.

[1477] This invention relates to an educational platform that utilizes a generative artificial intelligence model. Educators input educational content into a terminal, and the server evaluates, corrects, enhances, and publishes it. The platform also generates optimal learning plans based on the information entered by users, monitors their learning progress, and provides appropriate support. Furthermore, learning completion data is recorded on a blockchain, and reward tokens are issued according to learning outcomes.

[1478] Creating a study plan

[1479] Enter your user information:

[1480] A user logs in to the educational platform and inputs their area of ​​interest, current skill level, and learning goals into the device. For example, the user might input, "I want to learn the basics of generative artificial intelligence."

[1481] Sending user information:

[1482] The device sends the information entered by the user to the server. Specifically, the data is sent in JSON format via a REST API.

[1483] Generate optimal study plans:

[1484] The server receives the user information and uses a generative artificial intelligence model (e.g., GPT-4) to generate an optimal learning plan, which includes recommended learning materials and courses.

[1485] Submit and view your study plan:

[1486] The generated study plan is sent to the user's device, where it is displayed, allowing the user to proceed with their studies based on the displayed plan.

[1487] Learning support and counselling

[1488] Progress monitoring:

[1489] The server monitors users' learning activities in real time, collecting log data such as the time spent viewing learning materials and quiz results.

[1490] Learning assistance decision making and message generation:

[1491] The server analyzes the user's progress data and uses a generative artificial intelligence model to generate counseling and assistance messages, such as "Let's review this chapter again" if the user is behind or needs specific assistance.

[1492] Sending and viewing assist messages:

[1493] The server sends the generated assist message to the user's device, which displays it in the form of a notification or a pop-up.

[1494] Content Creation and Evaluation

[1495] Creating and submitting content:

[1496] Educators create educational content using an editor and send it to the server via their devices. The content sent can be a variety of formats, including text files and multimedia files.

[1497] Rate and modify content:

[1498] The server uses a generative artificial intelligence model to evaluate the content, checking for grammatical and content accuracy, and assessing its ease of understanding for users, automatically correcting and enhancing it as needed.

[1499] Content Publishing:

[1500] The modified and enhanced content will be published on the platform through the server and made available to other users.

[1501] Learning history and reward management

[1502] Recording learning completion and sending data:

[1503] When a user completes a learning plan or course, the device notifies the server of that data.

[1504] Manage your learning history:

[1505] The server records the received learning completion data on the blockchain in NFT format, which prevents data tampering and ensures reliability.

[1506] Issuing and Displaying Rewards:

[1507] Depending on the results of the learning, the server issues reward tokens to the user and notifies the terminal. The terminal displays the issued reward token information to the user. For example, it is added to the user's dashboard.

[1508] Functions for businesses and local governments

[1509] Administrator login and data aggregation and analysis:

[1510] Corporate and local government administrators log in to the platform's management screen, and the server compiles and analyzes the learning data of all employees and citizens in real time, using data analysis technology.

[1511] View the dashboard and provide support:

[1512] The aggregated and analyzed results are displayed on the administrator dashboard, and counseling and support messages appropriate for each learner are generated.

[1513] Examples of concrete examples and prompts

[1514] Examples:

[1515] If User A types in "I want to learn the basics of Python," the system will suggest online courses and materials as the optimal learning plan for User A, monitor their progress in real time, and send support messages.

[1516] If Educator B creates an "introductory course on data science," the system will evaluate the content, automatically correct and enhance any areas for improvement, and then publish it.

[1517] Example prompt sentence:

[1518] Please provide some code examples to help me understand the basics of Python.

[1519] "Please explain some introductory topics in data science."

[1520] This concludes the description of the "Mode for carrying out the invention." This will enable improvements in the quality of educational content, proper management of users' learning progress, and fair reward provision.

[1521] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1522] Step 1:

[1523] Entering user information

[1524] A user logs in to the educational platform terminal and enters their area of ​​interest, current skill level, and learning goals. For example, a user may enter, "I want to learn the basics of generative artificial intelligence."

[1525] Input: Area of ​​interest, skill level, learning goals.

[1526] Output: User input information.

[1527] Step 2:

[1528] Sending user information

[1529] The terminal sends the information entered by the user to the server, using the REST API to send data in JSON format.

[1530] Input: User-entered information.

[1531] Output: User information received on the server side.

[1532] Step 3:

[1533] Generate optimal study plans

[1534] The server generates an optimal learning plan based on the received user information using a generative artificial intelligence model (e.g., GPT-4). The AI ​​model analyzes large amounts of educational data and selects learning materials and courses that are appropriate for the user.

[1535] Input: User information received by the server.

[1536] Output: A generated learning plan (a list of recommended materials and courses).

[1537] Step 4:

[1538] Submitting and Viewing Learning Plans

[1539] The server sends the generated learning plan to the user's device in JSON format.

[1540] The device parses the received JSON data and displays a learning plan to the user, including recommended learning materials and course links.

[1541] Input: The generated lesson plan.

[1542] Output: The learning plan displayed on the user's device.

[1543] Step 5:

[1544] Monitoring learning progress

[1545] The server monitors users' learning activities in real time, collects learning logs (time spent viewing learning materials and quiz results), and analyzes progress data.

[1546] Input: Learning log, progress data.

[1547] Output: Analysis results (evaluation of whether the user is progressing according to the plan).

[1548] Step 6:

[1549] Learning assistance decisions and message generation

[1550] The server generates counseling and assistance messages using a generative artificial intelligence model based on the analysis results. If progress is delayed, it generates a specific assistance message (e.g., "Let's review this chapter again").

[1551] Input: Analysis results.

[1552] Output: The generated assist message.

[1553] Step 7:

[1554] Sending and displaying assist messages

[1555] The server transmits the generated assist message to the user's terminal.

[1556] The device displays an assist message to the user using a pop-up or notification.

[1557] Input: The generated assist message.

[1558] Output: Assist message displayed on the user's terminal.

[1559] Step 8:

[1560] Creating and Submitting Content

[1561] Educators use the editor of the educational platform to create new educational content, which can be text files or multimedia files, and send them to the server via their devices.

[1562] Input: Educational content created by educators.

[1563] Output: The content sent to the server.

[1564] Step 9:

[1565] Evaluate and correct content

[1566] The server uses a generative artificial intelligence model to evaluate the content, checking for grammatical accuracy, content accuracy, and user comprehension, and automatically corrects and enhances it as needed.

[1567] Input: The content sent to the server.

[1568] Output: Corrected and enhanced content.

[1569] Step 10:

[1570] Publishing content

[1571] The server will then publish the modified and enhanced content on the platform, making it available to other users.

[1572] Input: revised and enhanced content.

[1573] Output: Content published on the platform.

[1574] Step 11:

[1575] Recording learning completion and sending data

[1576] When a user completes a designated learning plan or course, the device notifies the server of that data.

[1577] Input: Completed training data.

[1578] Output: Learning completion data notified to the server.

[1579] Step 12:

[1580] Managing learning history

[1581] The server records the received learning completion data on the blockchain in NFT format, which prevents data tampering and ensures reliability.

[1582] Input: Learning completion data notified to the server.

[1583] Output: Training completion data recorded on the blockchain as an NFT.

[1584] Step 13:

[1585] Issuing and Displaying Rewards

[1586] The server issues and notifies the user of a reward token based on the results of their learning.

[1587] The terminal displays the received reward token information on the dashboard.

[1588] Input: Learning outcome data.

[1589] Output: Information about reward tokens issued to users.

[1590] Step 14:

[1591] Administrator login and data collection and analysis

[1592] Business and local government administrators log in to the platform's management screen, and the server compiles and analyzes the learning data of all employees and citizens in real time, using data analysis technology to identify trends.

[1593] Input: employee and citizen learning data.

[1594] Output: Aggregation and analysis results displayed on the management screen.

[1595] Step 15:

[1596] Viewing the dashboard and providing support

[1597] The server displays the aggregated and analyzed results on an administrator dashboard and generates counseling and support messages appropriate for each individual learner.

[1598] Input: Aggregation and analysis results.

[1599] Output: Generated counseling or support messages.

[1600] The above are the processing steps of the program for this system. The specific operations performed at each step, as well as their inputs and outputs, have been explained in detail.

[1601] (Application example 1)

[1602] 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."

[1603] Conventional educational platforms have faced issues such as inconsistent quality of educational content and difficulty in responding flexibly to user progress. Furthermore, there was a lack of means to provide appropriate information and support in real time when training staff and responding to customers in physical stores. Furthermore, there was an inadequate system for reliably recording users' learning outcomes and issuing appropriate rewards. There is a need to solve these issues and provide a high-quality, efficient educational environment and customer support.

[1604] 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.

[1605] In this invention, the server includes a means for an educator to input educational content into a terminal, a means for transmitting the educational content from the terminal to the server, a means for the server to evaluate the educational content using a generative artificial intelligence model and modify or enhance it as necessary, a means for publishing the modified or enhanced educational content on the platform, a means for users to use the published educational content, a means for providing product information and counseling in real time using a smart device, and a means for providing real-time answers to customer questions using a generative artificial intelligence model. This enables improved quality of educational content, flexible learning support, and efficient staff training and customer service in physical stores. Furthermore, by utilizing a generative artificial intelligence model and blockchain technology, the reliability of learning outcomes can be ensured and fair rewards can be provided.

[1606] "Educators" refers to instructors and teachers who provide educational content.

[1607] "Educational content" refers to the information and materials that learners are expected to acquire.

[1608] "Terminal" refers to an electronic device that allows a user or educator to input information and communicate with a server.

[1609] "Server" refers to a centralized computer system for processing information and using generative artificial intelligence models.

[1610] A "generative artificial intelligence model" refers to an artificial intelligence system that has the ability to learn from data and generate new information.

[1611] "Evaluation" refers to the process by which a generative artificial intelligence model examines the quality and suitability of educational content.

[1612] "Modification and enhancement" refers to the process of improving educational content and making it easier to understand based on the evaluation results.

[1613] "Publishing" refers to the act of displaying the revised or enhanced educational content on the Platform and making it accessible to Users.

[1614] "Platform" refers to the entire system for providing educational content and learning plans.

[1615] "User" refers to an individual who uses the educational platform and learns.

[1616] "Interests and skill level" refers to information that indicates the areas the user wants to learn and their current learning progress.

[1617] "Study Plan" refers to a study plan that combines learning materials and courses that are best suited to the user.

[1618] "Progress" refers to information that indicates the user's learning situation and level of achievement.

[1619] "Counseling and support messages" refer to advice and encouraging messages provided by the generative artificial intelligence model to help the user learn.

[1620] A "smart device" refers to a device that is connected to the Internet and has sensors and processing capabilities.

[1621] "Real-time" refers to instantaneous processing and response of information.

[1622] "Product information" refers to data such as detailed descriptions and usage instructions for products sold in physical stores.

[1623] "Customer service" refers to the work of responding to customer questions and requests in physical stores.

[1624] "Learning Completion Data" means records generated when a user completes a particular learning plan or course.

[1625] "Blockchain" refers to a distributed ledger technology that prevents data tampering and ensures reliability.

[1626] "NFT format" refers to data in the form of a non-fungible token that represents a unique digital asset on a blockchain.

[1627] "Reward tokens" refer to digital currencies or points issued for learning outcomes.

[1628] To implement the present invention, the following steps and associated hardware and software are used.

[1629] System configuration

[1630] Server: This plays a central role in the system. It uses generative AI models to provide educational content and counseling, monitors learning progress, and issues appropriate rewards. The server uses cloud infrastructure such as Microsoft Azure Server or AWS EC2.

[1631] Terminal: A device that users and educators use to input information and communicate with the server. Examples include smartphones, tablets, PCs, and smart glasses. HoloLens 2 and Google Glass Enterprise Edition 2 are used as smart glasses.

[1632] Generative AI model: Performs various AI processes such as evaluating educational content, generating learning plans, and generating counseling messages. Specifically, OpenAI's GPT-3.5 model is used.

[1633] Blockchain: Used to ensure the reliability of learning completion data, and uses Ethereum and Hyperledger.

[1634] Input and evaluation of educational content

[1635] Educators input educational content into their devices and send it to the server. The server uses a generative AI model to evaluate the content and correct or enhance it as needed. For example, it checks grammar, content accuracy, and understandability. The corrected or enhanced educational content is published on the platform and available to other users.

[1636] Generate a learning plan

[1637] The user inputs their areas of interest and current skill level into the device. The server uses a generative artificial intelligence model based on the received information to generate an optimal learning plan. This plan includes recommended learning materials and courses and is sent to the device. The user then proceeds with their studies based on this learning plan.

[1638] Progress monitoring and counseling

[1639] The server monitors the user's learning progress in real time, analyzing learning logs and progress data to confirm whether the user is following the learning plan. If progress is falling behind, the server uses a generative artificial intelligence model to generate appropriate counseling and support messages and send them to the user's device.

[1640] Use of smart devices

[1641] Store staff can use smart glasses to provide real-time product information and customer consultations. Generative AI models are used to provide quick answers to customer questions. This system enhances staff training and customer service.

[1642] Recording learning completion data and issuing reward tokens

[1643] When a user completes a designated learning plan, the learning completion data is sent from the device to the server. The server records the learning completion data on the blockchain in NFT format. It also issues reward tokens to the user based on their learning results and notifies the device. This reward token information is also displayed on the smart device.

[1644] Examples of concrete examples and prompts

[1645] As a concrete example, consider a case where a customer asks a store staff member wearing smart glasses about a new smartphone. The staff member speaks to the smart glasses, and the server uses voice recognition to convert the question into text and send it to a generative artificial intelligence model. The answer generated by the AI ​​is displayed on the screen, and the staff member can relay it to the customer.

[1646] Example prompt sentence:

[1647] "If a customer asks about a new smartphone, provide them with the latest information."

[1648] "Generate training plans for new staff."

[1649] This will enable improved quality of educational content, flexible learning support, and efficient staff training and customer support in physical stores. By utilizing generative AI models and blockchain technology, it will be possible to ensure the reliability of learning results and provide fair compensation.

[1650] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1651] Step 1:

[1652] The educator inputs the educational content into the device. The input data here is educational content such as text information, images, and videos. The device converts this information into a format and sends it to the server.

[1653] Step 2:

[1654] The server passes the received educational content to a generative AI model for evaluation. Specifically, it checks the accuracy of grammar and content, as well as ease of understanding. During this process, the generative AI model analyzes the text and metadata to generate an evaluation result.

[1655] Step 3:

[1656] The server modifies and enhances the educational content based on the evaluation results, for example, correcting deficiencies and errors and inserting necessary additional explanations and examples. The modified and enhanced educational content is generated and made available for publication.

[1657] Step 4:

[1658] The server publishes the revised and enhanced educational content on the platform, and the published content is registered in a database in a format that can be accessed by other users.

[1659] Step 5:

[1660] Users log in to the platform and input their areas of interest and current skill level into their device. A learning plan is generated based on this input information, and specific items include areas of interest, skill level, and learning objectives.

[1661] Step 6:

[1662] The server uses a generative AI model based on the input data received from the user to generate an optimal learning plan. Data processing here includes analyzing the user profile and selecting learning materials from a database.

[1663] Step 7:

[1664] The server sends the generated learning plan to the user's device, which displays the received learning plan to the user and guides them to the next learning step.

[1665] Step 8:

[1666] The user progresses through their studies based on the study plan. Their progress is recorded as login history and study log, and periodically sent to the server.

[1667] Step 9:

[1668] The server monitors the user's learning progress in real time, analyzes the learning log and progress data, and generates appropriate counseling and support messages using a generative artificial intelligence model.

[1669] Step 10:

[1670] Once the support message is generated, the server sends it to the user's terminal, which notifies the user of the received message and provides the necessary support.

[1671] Step 11:

[1672] Staff use smart glasses to assist customers in brick-and-mortar stores. Customers' questions are entered by voice, and the device sends the information to a server.

[1673] Step 12:

[1674] The server uses speech recognition technology to convert the question into text and uses a generative artificial intelligence model to generate an answer, which is then displayed on the smart glasses' display.

[1675] Step 13:

[1676] When a user completes a learning plan, the user sends the data from the device to the server. The learning completion data includes the course studied and the achievement level.

[1677] Step 14:

[1678] The server receives the learning completion data and records it on the blockchain in NFT format, which ensures the data is tamper-proof and reliable.

[1679] Step 15:

[1680] The server issues reward tokens based on the user's learning results and notifies the terminal, which then displays the reward token information to the user and provides instructions on how to use it.

[1681] 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.

[1682] ---

[1683] The present invention relates to an educational platform that utilizes a generative artificial intelligence model and an emotion engine. In this platform, educators input educational content into a terminal, and a server evaluates, corrects, enhances, and publishes it. The platform also generates an optimal learning plan based on the information entered by the user, monitors learning progress while recognizing the user's emotions using an emotion engine, and provides appropriate support and counseling. Furthermore, learning completion data is recorded on a blockchain, and reward tokens are issued according to learning results. Specific embodiments of the present invention are described below.

[1684] Creating a study plan

[1685] 1. Enter your user information

[1686] Users input their areas of interest, current skill level, and learning goals through the educational platform terminal. For example, a user may input, "I want to learn the basics of generative artificial intelligence."

[1687] 2. Transmission of User Information

[1688] The terminal transmits the input user information to the server.

[1689] 3. Generating optimal study plans

[1690] The server utilizes a generative artificial intelligence model based on the received user information to generate an optimal learning plan for the user, including recommended learning materials and courses.

[1691] 4. Submit your study plan

[1692] The server transmits the generated study plan to the user's terminal.

[1693] 5. View your study plan

[1694] The terminal displays the received study plan to the user, and the user starts studying based on it.

[1695] Learning support and counselling

[1696] 1. Monitoring your learning progress

[1697] The server monitors the user's learning progress in real time, periodically collecting and analyzing learning logs and progress data.

[1698] 2. Collecting Emotional Data

[1699] The device uses an emotion engine to collect emotional data from the user while they are learning, including information obtained through facial expression recognition and voice analysis.

[1700] 3. Sending Emotional Data

[1701] The terminal transmits the collected emotion data to the server.

[1702] 4. Learning assistance decisions

[1703] The server evaluates the user's learning progress and emotional state based on the received learning progress data and emotional data.

[1704] 5. Generate a support message

[1705] The server uses a generative artificial intelligence model to generate counseling and support messages based on the user's emotional state, for example, a message recommending a break if the user is tired.

[1706] 6. Sending a support message

[1707] The server sends the generated support message to the user's terminal.

[1708] 7. Displaying support messages

[1709] The terminal notifies the user of a support message, so that the user can receive the necessary support.

[1710] Content Creation and Evaluation

[1711] 1. Content Creation

[1712] Educators input new educational content into the terminal and send it to the server, for example, creating an "introductory course in Python programming."

[1713] 2. Submitting Content

[1714] The terminal transmits the created content to the server.

[1715] 3. Content Rating

[1716] The server evaluates the received content using a generative artificial intelligence model, specifically checking the accuracy of grammar and content, and assessing the ease of understanding for the user.

[1717] 4. Content Modifications and Enhancements

[1718] Based on the evaluation results, the server automatically corrects and enhances the content, correcting deficiencies and errors and inserting additional explanations and examples where necessary.

[1719] 5. Publishing Content

[1720] The server will then publish the modified and enhanced content on the platform, making it available to other users.

[1721] Learning history and reward management

[1722] 1. Record your learning completion

[1723] A user completes a designated learning plan or course.

[1724] 2. Sending training data

[1725] The terminal notifies the server that the learning is complete.

[1726] 3. Managing your learning history

[1727] The server records the received learning completion data on the blockchain in NFT format, which prevents data tampering and ensures reliability.

[1728] 4. Issuance of rewards

[1729] The server issues reward tokens to the user according to the results of the learning and notifies the terminal.

[1730] 5. Display of Rewards

[1731] The terminal displays information about the reward tokens issued to the user.

[1732] Functions for businesses and local governments

[1733] 1. Administrator login

[1734] Administrators of companies and local governments log in to the platform's administration screen.

[1735] 2. Aggregation and analysis of learning status

[1736] The server collects and analyzes the learning data of all employees and citizens in real time.

[1737] 3. View the dashboard

[1738] The server displays the results of the aggregation and analysis on an administrator dashboard, allowing administrators to grasp the learning status in a unified manner.

[1739] 4. Providing the support you need

[1740] The server uses a generative artificial intelligence model to generate messages when an individual learner needs appropriate counseling or support.

[1741] 5. Sending a support message

[1742] The server transmits the generated support message to the learner's terminal.

[1743] As described above, as a mode for implementing the invention, the system of the present invention provides an efficient and fair educational environment for educators, users, and corporate and local government administrators. At each step, generative AI models, emotion engines, and blockchain technology are utilized to improve the quality of educational content, manage learning progress, and provide fair rewards.

[1744] The processing flow will be explained below.

[1745] Now, let's explain the specific steps of a specific process in more detail.

[1746] ---

[1747] Creating a study plan

[1748] Step 1:

[1749] Users input their areas of interest, current skill level, and learning goals through the educational platform terminal. For example, a user may input, "I want to learn the basics of generative artificial intelligence."

[1750] Step 2:

[1751] The terminal transmits the input user information to the server.

[1752] Step 3:

[1753] The server inputs the received user information into a generative artificial intelligence model to generate an optimal learning plan for the user. The generated learning plan includes recommended learning materials and courses, which are selected based on the user's skill level and learning goals.

[1754] Step 4:

[1755] The server transmits the generated study plan to the user's terminal.

[1756] Step 5:

[1757] The terminal displays the received study plan to the user, and the user starts studying based on it.

[1758] ---

[1759] Learning support and counselling

[1760] Step 1:

[1761] The server monitors the user's learning progress in real time, and progress data is collected periodically and recorded as a learning log.

[1762] Step 2:

[1763] The device uses an emotion engine to collect emotion data from the user while the user is learning, for example, through facial expression recognition or voice analysis.

[1764] Step 3:

[1765] The terminal transmits the collected emotion data to the server.

[1766] Step 4:

[1767] The server evaluates the user's learning progress and emotional state based on the received learning progress data and emotional data, using a generative artificial intelligence model to confirm whether the user is progressing as expected.

[1768] Step 5:

[1769] The server generates counseling and support messages based on the user's emotional state. For example, if the server determines that the user is tired, it generates a message such as "Take a short break."

[1770] Step 6:

[1771] The server sends the generated support message to the user's terminal.

[1772] Step 7:

[1773] The terminal notifies the user of a support message, so that the user can receive the necessary support.

[1774] ---

[1775] Content Creation and Evaluation

[1776] Step 1:

[1777] Educators input new educational content into the terminal and send it to the server, for example, creating an "introductory course in Python programming."

[1778] Step 2:

[1779] The terminal transmits the created content to the server.

[1780] Step 3:

[1781] The server evaluates the received content using a generative artificial intelligence model, specifically checking the accuracy of grammar and content, and assessing the ease of understanding for the user.

[1782] Step 4:

[1783] Based on the evaluation results, the server automatically corrects and enhances the content, for example, correcting deficiencies and errors and inserting additional explanations and examples where necessary.

[1784] Step 5:

[1785] The server will then publish the modified and enhanced content on the platform, making it available to other users.

[1786] ---

[1787] Learning history and reward management

[1788] Step 1:

[1789] A user completes a designated learning plan or course.

[1790] Step 2:

[1791] The terminal notifies the server that the learning is complete.

[1792] Step 3:

[1793] The server then records the received learning completion data on the blockchain in NFT format, which prevents tampering and ensures the reliability of the learning history.

[1794] Step 4:

[1795] The server issues reward tokens to the user according to the results of the learning and notifies the terminal.

[1796] Step 5:

[1797] The terminal displays information about the reward tokens issued to the user.

[1798] ---

[1799] Functions for businesses and local governments

[1800] Step 1:

[1801] Administrators of companies and local governments log in to the platform's administration screen.

[1802] Step 2:

[1803] The server collects and analyzes the learning data of all employees and citizens in real time.

[1804] Step 3:

[1805] The server displays the results of the aggregation and analysis on an administrator dashboard, allowing administrators to grasp the learning status in a unified manner.

[1806] Step 4:

[1807] If the server determines that a particular learner needs appropriate counseling or support, it generates a message using a generative artificial intelligence model.

[1808] Step 5:

[1809] The server transmits the generated support message to the learner's terminal.

[1810] ---

[1811] The above are the specific processing steps of the present invention. By combining a generative AI model, an emotion engine, and blockchain technology, the present invention improves the quality of educational content, manages learning progress, and provides fair rewards.

[1812] Example 2

[1813] 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."

[1814] Current educational platforms lack the ability to monitor and support individual users' learning progress and emotional state in real time. Furthermore, assessment and correction of learning content is not carried out promptly, and the quality of the results is often inconsistent. Furthermore, there is no reliable recording of learning outcomes or fair distribution of rewards. This leads to issues such as a decline in learner motivation and a lack of improvement in learning efficiency.

[1815] 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. In this invention, the server includes a means for an educator to input educational content into a terminal, a means for transmitting the educational content from the terminal to the server, a means for the server to evaluate the educational content using a generative artificial intelligence model and modify or enhance it as necessary, a means for publishing the modified or enhanced educational content on a platform, a means for a learner to use the published educational content, a means for a learner to input learning goals and skill levels into a terminal, a means for transmitting learner information from the terminal to the server, a means for the server to generate an optimal learning plan for a learner using a generative artificial intelligence model, a means for transmitting the generated learning plan to the learner's terminal, a means for the terminal to display the generated learning plan to the learner and for the learner to proceed with learning based on it, a means for the server to monitor the learner's learning progress in real time, and a means for the terminal to display an emotional emotion. The platform includes a means for collecting learners' emotional data using an engine and transmitting it to a server, a means for the server to analyze the collected learning progress data and emotional data, generate appropriate counseling and support messages, and transmit them to the device, a means for the learner's learning completion data to be transmitted from the device to the server, a means for the server to record the learning completion data on the blockchain in NFT format, a means for the server to issue reward tokens to learners according to their learning outcomes and notify the device, a means for a company or local government administrator to log in to the platform's management screen, a means for the server to aggregate and analyze the learning data of all learners, a means for the server to display the results of the server's aggregation and analysis on an administrator dashboard, and a means for the server to generate appropriate counseling and support messages for each learner and transmit them to the device. This enables real-time monitoring and support of individual users' learning progress and emotional states, rapid evaluation and correction of educational content, reliable recording of learning outcomes, and fair distribution of rewards.

[1816] "Educators" refers to experts and teachers who design and teach educational content.

[1817] "Terminal" refers to an electronic device used to access the educational platform and input information.

[1818] "Server" refers to a central processing unit that processes, stores, transmits and receives data over a network.

[1819] A "generative artificial intelligence model" refers to a machine learning algorithm that generates natural language, providing optimal responses and generating results based on user input.

[1820] "Learner" refers to an individual who learns educational content through the educational platform.

[1821] "Educational content" refers to the content of teaching materials and lessons designed to impart specific knowledge or skills.

[1822] "Study plan" refers to a suggested learning approach or plan based on the learner's goals and skill level.

[1823] An "emotion engine" refers to software that analyzes a user's facial expressions and voice data to recognize their emotional state.

[1824] "Counseling" refers to helping learners to provide psychological support during their learning process.

[1825] "Support messages" refer to guidance and encouragement messages sent based on the user's learning progress and emotional state.

[1826] "Blockchain" refers to a technology that manages transaction records on a distributed network to ensure data reliability.

[1827] "NFT format" refers to a technology for representing digital data in the form of non-fungible tokens.

[1828] "Reward tokens" refer to digital assets issued based on learning outcomes.

[1829] "Corporate or local government administrator" refers to the person in charge of operating and managing the educational platform in a specific organization or region.

[1830] "Administration screen" refers to a dedicated interface for operating and managing a system or platform.

[1831] A "dashboard" refers to a screen that displays data aggregation and analysis results in real time.

[1832] This invention relates to an educational platform that utilizes a generative artificial intelligence model and an emotion engine. This platform allows educators to input educational content, which is then evaluated, revised, and reinforced using a generative artificial intelligence model, providing learners with optimal learning plans. It also monitors learners' progress and emotional state in real time and provides appropriate counseling and support messages. Furthermore, learning outcomes are recorded on a blockchain, and fair reward tokens are issued to maintain and improve learners' motivation.

[1833] Hardware and software used

[1834] Hardware:

[1835] Device: Electronic device such as a personal computer, smartphone, or tablet.

[1836] Server: Central processing unit that processes and stores data

[1837] software:

[1838] Generative AI models: Natural language generation models (e.g., ChatGPT, GPT-4)

[1839] Emotion engine: facial expression recognition software (e.g., Emotion API)

[1840] Blockchain technology: Data recording technology in the form of NFTs

[1841] Creating study plans and providing counseling

[1842] Example 1: Creating a study plan

[1843] A user logs in to the educational platform terminal and enters their area of ​​interest, current skill level, and learning objectives. For example, they might enter "I want to learn the basics of generative artificial intelligence," "Beginner level," or "I want to learn new technologies."

[1844] The terminal transmits this information to the server.

[1845] The server uses a generative artificial intelligence model to generate an optimal learning plan. The prompt is "Please generate the optimal learning plan based on the user's interests, skill level, and goals."

[1846] The server transmits the generated study plan to the terminal and displays it to the user.

[1847] Example 2: Providing counseling and support messages

[1848] The server collects the user's learning progress data in real time and also collects emotion data using an emotion engine.

[1849] The device uses a camera and microphone to collect user emotion data and transmits it to a server.

[1850] The server analyzes the collected data and evaluates the user's progress and emotional state.

[1851] The server uses a generative artificial intelligence model to generate counseling and support messages according to the user's emotional state. The prompt text is "If the user is tired, please generate a message recommending that he or she take a break."

[1852] The server sends the generated support message to the device, which then displays it to the user, such as "You seem tired, so please take a 10-minute break."

[1853] Recording learning results and issuing rewards

[1854] Example 3: Recording learning outcomes and issuing reward tokens

[1855] After the user completes the learning plan, the terminal transmits learning completion data to the server.

[1856] The server records this data on the blockchain in NFT format, which prevents data tampering and increases reliability.

[1857] The server issues reward tokens based on the learning results and notifies the terminal of the information.

[1858] The terminal displays information about the reward tokens issued to the user.

[1859] Management functions for businesses and local governments

[1860] Example 4: Real-time management and support

[1861] Administrators from companies and local governments log in to the platform's administration screen.

[1862] The server collects and analyzes data from all learners in real time and displays it on an administrator dashboard.

[1863] The server generates an appropriate support message for each learner as needed and transmits it to the terminal.

[1864] In this way, the system of the present invention monitors each user's learning progress and emotional state in real time and provides appropriate support to improve learning efficiency and motivation. It also improves the quality of educational content and provides a fair learning environment by recording learning results and issuing reward tokens.

[1865] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1866] Step 1:

[1867] Users log in to the educational platform terminal and enter their areas of interest, current skill level, and learning goals. For example, they can enter information such as "I want to learn the basics of generative artificial intelligence," "Beginner level," or "I want to learn new technologies." This input information becomes the basis for generating subsequent learning plans.

[1868] Step 2:

[1869] The device sends the entered user information to the server. Specifically, data such as the user ID, areas of interest, skill level, and learning goals is sent to the API endpoint via the HTTPS protocol. The input data at this stage is stored on the server.

[1870] Step 3:

[1871] The server receives the user information and uses a generative artificial intelligence model to generate an optimal learning plan. Specifically, the server inputs the prompt "Please generate the optimal learning plan based on the user's areas of interest, skill level, and goals" to the generative AI model. The generative AI model performs data calculations based on this information, generates a learning plan tailored to each individual user, and outputs the results.

[1872] Step 4:

[1873] The server sends the generated learning plan to the user's device. The data sent is the details of the generated learning plan, which is output as an API response from the server to the device.

[1874] Step 5:

[1875] The device displays the received learning plan to the user. For example, links to "Basic Course on Generative Artificial Intelligence" and "Recommended Learning Materials" are displayed on the web browser screen. The user can then access the displayed learning plan and begin learning.

[1876] Step 6:

[1877] The server monitors the user's learning progress in real time. It periodically collects and analyzes data such as when the user accesses the learning materials, the study time, and test results, and stores the data in a database. The input data at this stage becomes the user's learning log.

[1878] Step 7:

[1879] The device uses an emotion engine to collect emotional data from the user during training. It uses a camera and microphone to collect emotional data in real time through facial expression recognition and voice analysis. This emotional data is also sent by the device to the server.

[1880] Step 8:

[1881] The server analyzes the received learning progress data and emotional data, which evaluates the user's learning situation and emotional state. Based on the analysis results, it generates appropriate counseling and support messages. For example, the server can input a prompt to the generative AI model such as, "If the user is tired, please generate a message recommending that he or she take a break."

[1882] Step 9:

[1883] The server sends the generated counseling or support message to the user's terminal. The data sent is the text of the support message, which is output as a response from the server to the terminal.

[1884] Step 10:

[1885] The device will display support messages to the user, such as "You seem tired, please take a 10-minute break," allowing the user to receive the necessary rest and support.

[1886] Step 11:

[1887] When a user completes a learning plan or course, the data is sent from the device to the server. A learning completion notification is sent as an API request and saved as input data on the server.

[1888] Step 12:

[1889] The server records the learning completion data on the blockchain in NFT format, which ensures the reliability and tamper-proofness of the data.

[1890] Step 13:

[1891] The server issues a reward token to the user based on their learning results and sends a notification to the terminal. Information about this reward token is output as a response from the server to the terminal.

[1892] Step 14:

[1893] The terminal displays information about the reward tokens issued to the user, allowing the user to check the rewards according to their learning results and maintain motivation for the next lesson.

[1894] (Application example 2)

[1895] 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."

[1896] Traditional educational platforms lack support that can flexibly adapt to learners' progress and emotional state. As a result, they can only provide uniform learning support, making it difficult to maximize the motivation and learning effectiveness of individual learners. Furthermore, they lack the means to ensure the reliability of learning outcomes and properly evaluate them, which can make it difficult for learners to feel a sense of accomplishment and reduce their persistence in learning. Furthermore, because they do not provide appropriate incentives for learning outcomes, learners' interest and motivation can be lost.

[1897] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1898] In this invention, the server includes a means for educators to evaluate educational content and modify or enhance it as necessary, a means for analyzing the user's learning progress data and emotional data and generating support messages, a means for sending the generated learning plan and support messages to the user, and a means for recording learning completion data on the blockchain and issuing reward tokens. This makes it possible to provide support tailored to each learner's progress and emotional state, which is expected to improve learning effectiveness and maintain motivation. Furthermore, the reliability and fair evaluation of learning outcomes are ensured, and learners gain a sense of accomplishment, encouraging them to continue learning. Furthermore, the reward tokens provide an incentive for learning, increasing interest and motivation in learning.

[1899] "Educator" refers to an individual or organization that creates and delivers educational content.

[1900] "Terminal" refers to an electronic device used by an educator or user for input and output.

[1901] "Server" refers to the central processing unit that processes and manages data for the entire educational platform.

[1902] "Generative AI model" refers to an AI algorithm that evaluates, corrects, and reinforces educational content, generates learning plans, and generates support messages.

[1903] An "emotion engine" refers to technology that analyzes a user's facial expressions and voice data to evaluate their emotional state.

[1904] "Platform" refers to the entire online system for supporting educators in providing content and users in learning.

[1905] "User" refers to an individual who uses the educational platform to learn.

[1906] A "study plan" refers to a study plan that is optimal for a user, generated based on the user's interests and skill level.

[1907] "Study progress data" refers to data that indicates the progress of a user's studies.

[1908] "Emotion data" refers to data indicative of a user's emotional state collected using an emotion engine.

[1909] A "support message" refers to a message containing support content that is generated by a generative artificial intelligence model based on a user's learning progress data and emotional data and sent to the user.

[1910] "Study completion data" refers to data indicating that a user has completed a specified learning plan or course.

[1911] "Blockchain" refers to a technology that uses distributed ledger technology to record learning completion data to prevent tampering.

[1912] "NFT format" refers to a method of recording data in non-fungible token format.

[1913] "Reward token" refers to a digital reward issued based on a user's learning achievements.

[1914] This invention relates to an educational platform using a generative artificial intelligence model and an emotion engine. This platform evaluates and corrects educational content provided by educators, creates learning plans and monitors progress for users, generates support messages using emotion data, records learning outcomes on a blockchain, and issues reward tokens.

[1915] Use of generative artificial intelligence models

[1916] The server uses a generative artificial intelligence model to evaluate the educational content entered by educators and correct or enhance it as needed. This process uses algorithms to evaluate grammatical accuracy, content consistency, and user comprehension.

[1917] Emotion data collection and analysis

[1918] When users use the educational platform, they learn through smart devices (smartphones, smart glasses, head-mounted displays). These devices are equipped with cameras and microphones to collect the user's facial expressions and voice. The server uses an emotion engine to analyze this data and evaluate the user's emotional state in real time.

[1919] Creating a study plan and monitoring progress

[1920] The server uses a generative artificial intelligence model to generate an optimal learning plan based on user information (areas of interest, skill level, learning goals). The generated learning plan is sent to the user's device, and the user proceeds with their studies based on it. The server periodically collects and analyzes the user's learning progress data.

[1921] Generate a support message

[1922] The server uses a generative artificial intelligence model to generate appropriate support messages based on the collected learning progress data and user emotion data. For example, if the learning progress is slow or the user feels fatigued, a message recommending a break or a message offering additional learning resources is generated.

[1923] Blockchain and Reward Tokens

[1924] When a user completes a learning plan or course, the server records the learning completion data on the blockchain in NFT format, ensuring data tamper-proofing and reliability. Depending on the learning results, the server issues reward tokens to the user and provides incentives by notifying the device.

[1925] Specific examples

[1926] Example prompt for generating a lesson plan:

[1927] "The user's area of ​​interest is 'generative artificial intelligence'. Their skill level is 'beginner' and their learning goal is 'learn the basics'. Please generate the optimal learning plan based on this."

[1928] Example prompt for generating a support message:

[1929] "User's progress data is '75% complete'. Sentiment data indicates 'Exhausted'. Please generate a support message appropriate for this state."

[1930] As described above, the system of the present invention provides an efficient and fair educational environment for educators, users, and corporate and local government administrators. At each step, generative AI models, emotion engines, and blockchain technology are utilized to improve the quality of educational content, manage learning progress, and provide fair rewards.

[1931] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1932] Step 1:

[1933] Entering user information

[1934] The user inputs their area of ​​interest, skill level, and learning goals through the terminal. For example, they might input, "I want to learn the basics of generative artificial intelligence." Input: Information the user inputs into the terminal (area of ​​interest, skill level, learning goals). Output: This information is sent from the terminal to the server.

[1935] Step 2:

[1936] Sending user information

[1937] The terminal sends the user information entered in step 1 to the server. Input: Data entered by the user. Output: Data sent from the terminal to the server.

[1938] Step 3:

[1939] Generate optimal study plans

[1940] The server uses a generative artificial intelligence model based on the received user information to generate an optimal study plan for the user. Input: User information. Data processing: The generative artificial intelligence model analyzes the data and generates an appropriate study plan. Output: Generated study plan.

[1941] Step 4:

[1942] Submit your study plan

[1943] The server sends the generated learning plan to the user's device. Input: Learning plan. Output: Sending the learning plan from the server to the device.

[1944] Step 5:

[1945] View your learning plan

[1946] The device displays the received study plan to the user, who then begins studying based on it. Input: Study plan sent from the server. Output: Study plan displayed on the device.

[1947] Step 6:

[1948] Monitoring learning progress

[1949] The server monitors the user's learning progress in real time. Input: User's learning log and progress data. Data calculation: Data analysis is performed to grasp the learning progress. Output: Analysis results.

[1950] Step 7:

[1951] Collecting Emotional Data

[1952] The device collects the user's facial expressions and voice during training through the emotion engine. Input: Facial expression and voice data collected through the camera and microphone. Output: Emotion data.

[1953] Step 8:

[1954] Sending emotional data

[1955] The device sends the collected emotion data to the server. Input: Collected emotion data. Output: Data transmission from the device to the server.

[1956] Step 9:

[1957] Learning assistance decisions

[1958] The server evaluates the user's state based on the received learning progress data and emotion data. Input: Learning progress data and emotion data. Data calculation: Data analysis for state evaluation. Output: Evaluation of the user's learning state.

[1959] Step 10:

[1960] Generate a support message

[1961] The server uses a generative artificial intelligence model to generate a support message according to the learning status. Input: Evaluation results. Data processing: Generation of support message. Output: Generated support message.

[1962] Step 11:

[1963] Send a support message

[1964] The server sends the generated support message to the user's terminal. Input: Support message. Output: Sending the support message.

[1965] Step 12:

[1966] Displaying a support message

[1967] The terminal notifies the user of the support message, allowing the user to receive the necessary support. Input: Support message. Output: Support message displayed on the terminal.

[1968] Step 13:

[1969] Sending learning completion data

[1970] When the user completes the specified learning plan or course, the device sends learning completion data to the server. Input: Learning completion data. Output: Completion data sent from the device to the server.

[1971] Step 14:

[1972] Recording of learning completion data

[1973] The server records the received learning completion data in NFT format on the blockchain. Input: Learning completion data. Data processing: Recording to the blockchain. Output: Recorded data.

[1974] Step 15:

[1975] Reward Token Issuance

[1976] The server issues reward tokens to users according to their learning results and notifies the terminal. Input: Learning results data. Output: Issuance and notification of reward tokens.

[1977] Step 16:

[1978] View Reward Tokens

[1979] The terminal displays information about the reward tokens issued to the user. Input: Reward token information. Output: Reward token information displayed on the terminal.

[1980] 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.

[1981] 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.

[1982] 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.

[1983] [Fourth embodiment]

[1984] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1985] 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.

[1986] 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).

[1987] 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.

[1988] 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.

[1989] 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).

[1990] 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.

[1991] 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.

[1992] 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.

[1993] 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.

[1994] 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.

[1995] 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.

[1996] 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."

[1997] ---

[1998] The present invention relates to an educational platform that utilizes a generative artificial intelligence model. In this platform, educators input educational content into a terminal, and a server evaluates, corrects, enhances, and publishes it. The platform also generates an optimal learning plan based on the information entered by the user, monitors learning progress, and provides appropriate support. Furthermore, learning completion data is recorded on a blockchain, and reward tokens are issued according to learning results. Specific embodiments of the present invention are described below.

[1999] Creating a study plan

[2000] 1. Enter your user information

[2001] Users input their areas of interest, current skill level, and learning goals through the educational platform terminal. For example, a user may input, "I want to learn the basics of generative artificial intelligence."

[2002] 2. Transmission of User Information

[2003] The terminal transmits the input user information to the server.

[2004] 3. Generating optimal study plans

[2005] The server utilizes a generative artificial intelligence model based on the received user information to generate an optimal learning plan for the user, including recommended learning materials and courses.

[2006] 4. Submit your study plan

[2007] The server transmits the generated study plan to the user's terminal.

[2008] 5. View your study plan

[2009] The terminal displays the received study plan to the user, and the user can proceed with his / her studies based on it.

[2010] Learning support and counselling

[2011] 1. Monitoring your learning progress

[2012] The server monitors the user's learning progress in real time, analyzing learning logs and progress data to confirm whether the user is progressing according to the plan.

[2013] 2. Learning assistance decisions

[2014] The server uses a generative artificial intelligence model to generate counseling and assistance messages if the user is behind or if appropriate support is needed. For example, if the user stops studying for a certain period of time, the server generates an encouraging message.

[2015] 3. Sending an assist message

[2016] The server transmits the generated assist message to the user's terminal.

[2017] 4. Display of assist messages

[2018] The terminal notifies the user of an assist message and provides the necessary support.

[2019] Content Creation and Evaluation

[2020] 1. Content Creation

[2021] Educators input new educational content into the terminal and send it to the server, for example, creating an "introductory course in Python programming."

[2022] 2. Submitting Content

[2023] The terminal transmits the created content to the server.

[2024] 3. Content Rating

[2025] The server evaluates the received content using a generative artificial intelligence model, specifically checking the accuracy of grammar and content, and assessing the ease of understanding for the user.

[2026] 4. Content Modifications and Enhancements

[2027] Based on the evaluation results, the server automatically corrects and enhances the content, for example, correcting deficiencies and errors and inserting necessary additional explanations and examples.

[2028] 5. Publishing Content

[2029] The server will then publish the modified and enhanced content on the platform, making it available to other users.

[2030] Learning history and reward management

[2031] 1. Record your learning completion

[2032] A user completes a designated learning plan or course.

[2033] 2. Sending training data

[2034] The terminal notifies the server that the learning is complete.

[2035] 3. Managing your learning history

[2036] The server records the received learning completion data on the blockchain in NFT format, which prevents data tampering and ensures reliability.

[2037] 4. Issuance of rewards

[2038] The server issues reward tokens to the user according to the results of the learning and notifies the terminal.

[2039] 5. Display of Rewards

[2040] The terminal displays information about the reward tokens issued to the user.

[2041] Functions for businesses and local governments

[2042] 1. Administrator login

[2043] Administrators of companies and local governments log in to the platform's administration screen.

[2044] 2. Aggregation and analysis of learning status

[2045] The server collects and analyzes the learning data of all employees and citizens in real time.

[2046] 3. View the dashboard

[2047] The server displays the results of the aggregation and analysis on an administrator dashboard, allowing administrators to grasp the learning status in a unified manner.

[2048] 4. Providing the support you need

[2049] The server uses a generative artificial intelligence model to generate messages when an individual learner needs appropriate counseling or support.

[2050] 5. Sending a support message

[2051] The server transmits the generated support message to the learner's terminal.

[2052] As described above, as a mode for implementing the invention, the system of the present invention provides an efficient and fair educational environment for educators, users, and corporate and local government administrators. At each step, generative AI models and blockchain technology are utilized to improve the quality of educational content, manage learning progress, and provide fair rewards.

[2053] The processing flow will be explained below.

[2054] ---

[2055] Creating a study plan

[2056] Step 1:

[2057] A user logs into the educational platform and inputs their area of ​​interest, current skill level, and learning objectives through a terminal.

[2058] Step 2:

[2059] The terminal transmits the input user information to the server.

[2060] Step 3:

[2061] The server inputs the received user information into a generative artificial intelligence model to generate an optimal learning plan for the user.

[2062] Step 4:

[2063] The server transmits the generated study plan to the user's terminal.

[2064] Step 5:

[2065] The terminal displays the received study plan to the user, and the user starts studying based on it.

[2066] Learning support and counselling

[2067] Step 1:

[2068] The server monitors the user's learning progress in real time, and periodically collects and analyzes learning logs and progress data.

[2069] Step 2:

[2070] The server evaluates the user's learning progress and level of understanding based on the data collected and analyzed.

[2071] Step 3:

[2072] If the server determines that progress is slow or that appropriate support is needed, it uses a generative artificial intelligence model to generate counseling or assistance messages.

[2073] Step 4:

[2074] The server transmits the generated assist message to the user's terminal.

[2075] Step 5:

[2076] The terminal notifies the user of an assist message, allowing the user to receive the necessary support.

[2077] Content Creation and Evaluation

[2078] Step 1:

[2079] An educator inputs new educational content into a terminal and transmits it to a server.

[2080] Step 2:

[2081] The terminal transmits the created content to the server.

[2082] Step 3:

[2083] The server evaluates the received content using a generative artificial intelligence model, checking the accuracy of grammar and content and assessing the ease of understanding for the user.

[2084] Step 4:

[2085] The server automatically corrects and enhances the content based on the evaluation results, correcting deficiencies and errors and inserting additional explanations and examples where necessary.

[2086] Step 5:

[2087] The server publishes the modified and enhanced content on the platform, making it available to other users.

[2088] Learning history and reward management

[2089] Step 1:

[2090] A user completes a designated learning plan or course.

[2091] Step 2:

[2092] The terminal notifies the server that the learning is complete.

[2093] Step 3:

[2094] The server records the received learning completion data on the blockchain in NFT format.

[2095] Step 4:

[2096] The server issues reward tokens to the user according to the results of their learning and notifies the terminal.

[2097] Step 5:

[2098] The terminal displays information about the reward tokens issued to the user.

[2099] Functions for businesses and local governments

[2100] Step 1:

[2101] Administrators from companies and local governments log in to the platform's administration screen.

[2102] Step 2:

[2103] The server collects and analyzes the learning data of all employees and citizens in real time.

[2104] Step 3:

[2105] The server displays the aggregated and analyzed results on the administrator dashboard.

[2106] Step 4:

[2107] If the server determines that a particular learner needs appropriate counseling or support, it generates a message using a generative artificial intelligence model.

[2108] Step 5:

[2109] The server transmits the generated support message to the learner's terminal.

[2110] The above is a specific processing flow in the platform of the present invention.

[2111] Example 1

[2112] 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."

[2113] Current education platforms do not adequately improve the quality of educational content, manage learning progress, or provide rewards based on learning outcomes. They also lack effective learning support, limiting the ways in which users can find optimal learning plans based on their interests and skill levels. Furthermore, there is a lack of mechanisms for companies and local governments to centrally manage the learning status of their employees and citizens and provide appropriate support.

[2114] 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.

[2115] In this invention, the server includes a means for evaluating the accuracy and understandability of educational content and making necessary improvements; a means for monitoring a user's learning activity in real time and generating counseling and assistance messages using a generative artificial intelligence model; a means for transmitting the generated learning plan and counseling messages to the user's device; a means for recording learning completion data in NFT format using blockchain technology; and a means for issuing reward tokens based on learning outcomes and notifying the user's device. This enables the improvement of the quality of educational content, management of learning progress, and provision of fair rewards based on learning outcomes. It also enables companies and local governments to centrally manage and support learners.

[2116] "Educator" is the person responsible for inputting educational content into the platform and imparting knowledge and skills to learners.

[2117] A "terminal" is a device that allows a user or educator to access the educational platform and input or display data.

[2118] A "server" is a central processing unit that processes input data, generates learning plans, and evaluates educational content.

[2119] A "generative artificial intelligence model" is an algorithm that generates appropriate assistance messages and learning plans based on user input information and educational content.

[2120] "Educational content" refers to educational materials and content created by educators, and is the subject matter for learners to study.

[2121] The "platform" is an online system that allows educators and learners to share educational content with each other and advance their learning.

[2122] A "study plan" is a study schedule and list of recommended learning materials generated based on the user's skill level and interests.

[2123] A "counseling message" is a message provided by the generative artificial intelligence model based on the user's learning progress to encourage increased motivation and progress in learning.

[2124] "Blockchain" is a distributed ledger technology that securely records learning completion data and prevents tampering.

[2125] The "NFT format" is a format that records learning completion data as a unique digital asset.

[2126] "Reward tokens" are digital rewards issued to users based on their learning outcomes and are used to receive rewards and benefits.

[2127] A "dashboard" is a graphical user interface provided to administrators to grasp the learning situation in real time.

[2128] This invention relates to an educational platform that utilizes a generative artificial intelligence model. Educators input educational content into a terminal, and the server evaluates, corrects, enhances, and publishes it. The platform also generates optimal learning plans based on the information entered by users, monitors their learning progress, and provides appropriate support. Furthermore, learning completion data is recorded on a blockchain, and reward tokens are issued according to learning outcomes.

[2129] Creating a study plan

[2130] Enter your user information:

[2131] A user logs in to the educational platform and inputs their area of ​​interest, current skill level, and learning goals into the device. For example, the user might input, "I want to learn the basics of generative artificial intelligence."

[2132] Sending user information:

[2133] The device sends the information entered by the user to the server. Specifically, the data is sent in JSON format via a REST API.

[2134] Generate optimal study plans:

[2135] The server receives the user information and uses a generative artificial intelligence model (e.g., GPT-4) to generate an optimal learning plan, which includes recommended learning materials and courses.

[2136] Submit and view your study plan:

[2137] The generated study plan is sent to the user's device, where it is displayed, allowing the user to proceed with their studies based on the displayed plan.

[2138] Learning support and counselling

[2139] Progress monitoring:

[2140] The server monitors users' learning activities in real time, collecting log data such as the time spent viewing learning materials and quiz results.

[2141] Learning assistance decision making and message generation:

[2142] The server analyzes the user's progress data and uses a generative artificial intelligence model to generate counseling and assistance messages, such as "Let's review this chapter again" if the user is behind or needs specific assistance.

[2143] Sending and viewing assist messages:

[2144] The server sends the generated assist message to the user's device, which displays it in the form of a notification or a pop-up.

[2145] Content Creation and Evaluation

[2146] Creating and submitting content:

[2147] Educators create educational content using an editor and send it to the server via their devices. The content sent can be a variety of formats, including text files and multimedia files.

[2148] Rate and modify content:

[2149] The server uses a generative artificial intelligence model to evaluate the content, checking for grammatical and content accuracy, and assessing its ease of understanding for users, automatically correcting and enhancing it as needed.

[2150] Content Publishing:

[2151] The modified and enhanced content will be published on the platform through the server and made available to other users.

[2152] Learning history and reward management

[2153] Recording learning completion and sending data:

[2154] When a user completes a learning plan or course, the device notifies the server of that data.

[2155] Manage your learning history:

[2156] The server records the received learning completion data on the blockchain in NFT format, which prevents data tampering and ensures reliability.

[2157] Issuing and Displaying Rewards:

[2158] Depending on the results of the learning, the server issues reward tokens to the user and notifies the terminal. The terminal displays the issued reward token information to the user. For example, it is added to the user's dashboard.

[2159] Functions for businesses and local governments

[2160] Administrator login and data aggregation and analysis:

[2161] Corporate and local government administrators log in to the platform's management screen, and the server compiles and analyzes the learning data of all employees and citizens in real time, using data analysis technology.

[2162] View the dashboard and provide support:

[2163] The aggregated and analyzed results are displayed on the administrator dashboard, and counseling and support messages appropriate for each learner are generated.

[2164] Examples of concrete examples and prompts

[2165] Examples:

[2166] If User A types in "I want to learn the basics of Python," the system will suggest online courses and materials as the optimal learning plan for User A, monitor their progress in real time, and send support messages.

[2167] If Educator B creates an "introductory course on data science," the system will evaluate the content, automatically correct and enhance any areas for improvement, and then publish it.

[2168] Example prompt sentence:

[2169] Please provide some code examples to help me understand the basics of Python.

[2170] "Please explain some introductory topics in data science."

[2171] This concludes the description of the "Mode for carrying out the invention." This will enable improvements in the quality of educational content, proper management of users' learning progress, and fair reward provision.

[2172] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2173] Step 1:

[2174] Entering user information

[2175] A user logs in to the educational platform terminal and enters their area of ​​interest, current skill level, and learning goals. For example, a user may enter, "I want to learn the basics of generative artificial intelligence."

[2176] Input: Area of ​​interest, skill level, learning goals.

[2177] Output: User input information.

[2178] Step 2:

[2179] Sending user information

[2180] The terminal sends the information entered by the user to the server, using the REST API to send data in JSON format.

[2181] Input: User-entered information.

[2182] Output: User information received on the server side.

[2183] Step 3:

[2184] Generate optimal study plans

[2185] The server generates an optimal learning plan based on the received user information using a generative artificial intelligence model (e.g., GPT-4). The AI ​​model analyzes large amounts of educational data and selects learning materials and courses that are appropriate for the user.

[2186] Input: User information received by the server.

[2187] Output: A generated learning plan (a list of recommended materials and courses).

[2188] Step 4:

[2189] Submitting and Viewing Learning Plans

[2190] The server sends the generated learning plan to the user's device in JSON format.

[2191] The device parses the received JSON data and displays a learning plan to the user, including recommended learning materials and course links.

[2192] Input: The generated lesson plan.

[2193] Output: The learning plan displayed on the user's device.

[2194] Step 5:

[2195] Monitoring learning progress

[2196] The server monitors users' learning activities in real time, collects learning logs (time spent viewing learning materials and quiz results), and analyzes progress data.

[2197] Input: Learning log, progress data.

[2198] Output: Analysis results (evaluation of whether the user is progressing according to the plan).

[2199] Step 6:

[2200] Learning assistance decisions and message generation

[2201] The server generates counseling and assistance messages using a generative artificial intelligence model based on the analysis results. If progress is delayed, it generates a specific assistance message (e.g., "Let's review this chapter again").

[2202] Input: Analysis results.

[2203] Output: The generated assist message.

[2204] Step 7:

[2205] Sending and displaying assist messages

[2206] The server transmits the generated assist message to the user's terminal.

[2207] The device displays an assist message to the user using a pop-up or notification.

[2208] Input: The generated assist message.

[2209] Output: Assist message displayed on the user's terminal.

[2210] Step 8:

[2211] Creating and Submitting Content

[2212] Educators use the editor of the educational platform to create new educational content, which can be text files or multimedia files, and send them to the server via their devices.

[2213] Input: Educational content created by educators.

[2214] Output: The content sent to the server.

[2215] Step 9:

[2216] Evaluate and correct content

[2217] The server uses a generative artificial intelligence model to evaluate the content, checking for grammatical accuracy, content accuracy, and user comprehension, and automatically corrects and enhances it as needed.

[2218] Input: The content sent to the server.

[2219] Output: Corrected and enhanced content.

[2220] Step 10:

[2221] Publishing content

[2222] The server will then publish the modified and enhanced content on the platform, making it available to other users.

[2223] Input: revised and enhanced content.

[2224] Output: Content published on the platform.

[2225] Step 11:

[2226] Recording learning completion and sending data

[2227] When a user completes a designated learning plan or course, the device notifies the server of that data.

[2228] Input: Completed training data.

[2229] Output: Learning completion data notified to the server.

[2230] Step 12:

[2231] Managing learning history

[2232] The server records the received learning completion data on the blockchain in NFT format, which prevents data tampering and ensures reliability.

[2233] Input: Learning completion data notified to the server.

[2234] Output: Training completion data recorded on the blockchain as an NFT.

[2235] Step 13:

[2236] Issuing and Displaying Rewards

[2237] The server issues and notifies the user of a reward token based on the results of their learning.

[2238] The terminal displays the received reward token information on the dashboard.

[2239] Input: Learning outcome data.

[2240] Output: Information about reward tokens issued to users.

[2241] Step 14:

[2242] Administrator login and data collection and analysis

[2243] Business and local government administrators log in to the platform's management screen, and the server compiles and analyzes the learning data of all employees and citizens in real time, using data analysis technology to identify trends.

[2244] Input: employee and citizen learning data.

[2245] Output: Aggregation and analysis results displayed on the management screen.

[2246] Step 15:

[2247] Viewing the dashboard and providing support

[2248] The server displays the aggregated and analyzed results on an administrator dashboard and generates counseling and support messages appropriate for each individual learner.

[2249] Input: Aggregation and analysis results.

[2250] Output: Generated counseling or support messages.

[2251] The above are the processing steps of the program for this system. The specific operations performed at each step, as well as their inputs and outputs, have been explained in detail.

[2252] (Application example 1)

[2253] 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."

[2254] Conventional educational platforms have faced issues such as inconsistent quality of educational content and difficulty in responding flexibly to user progress. Furthermore, there was a lack of means to provide appropriate information and support in real time when training staff and responding to customers in physical stores. Furthermore, there was an inadequate system for reliably recording users' learning outcomes and issuing appropriate rewards. There is a need to solve these issues and provide a high-quality, efficient educational environment and customer support.

[2255] 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.

[2256] In this invention, the server includes a means for an educator to input educational content into a terminal, a means for transmitting the educational content from the terminal to the server, a means for the server to evaluate the educational content using a generative artificial intelligence model and modify or enhance it as necessary, a means for publishing the modified or enhanced educational content on the platform, a means for users to use the published educational content, a means for providing product information and counseling in real time using a smart device, and a means for providing real-time answers to customer questions using a generative artificial intelligence model. This enables improved quality of educational content, flexible learning support, and efficient staff training and customer service in physical stores. Furthermore, by utilizing a generative artificial intelligence model and blockchain technology, the reliability of learning outcomes can be ensured and fair rewards can be provided.

[2257] "Educators" refers to instructors and teachers who provide educational content.

[2258] "Educational content" refers to the information and materials that learners are expected to acquire.

[2259] "Terminal" refers to an electronic device that allows a user or educator to input information and communicate with a server.

[2260] "Server" refers to a centralized computer system for processing information and using generative artificial intelligence models.

[2261] A "generative artificial intelligence model" refers to an artificial intelligence system that has the ability to learn from data and generate new information.

[2262] "Evaluation" refers to the process by which a generative artificial intelligence model examines the quality and suitability of educational content.

[2263] "Modification and enhancement" refers to the process of improving educational content and making it easier to understand based on the evaluation results.

[2264] "Publishing" refers to the act of displaying the revised or enhanced educational content on the Platform and making it accessible to Users.

[2265] "Platform" refers to the entire system for providing educational content and learning plans.

[2266] "User" refers to an individual who uses the educational platform and learns.

[2267] "Interests and skill level" refers to information that indicates the areas the user wants to learn and their current learning progress.

[2268] "Study Plan" refers to a study plan that combines learning materials and courses that are best suited to the user.

[2269] "Progress" refers to information that indicates the user's learning situation and level of achievement.

[2270] "Counseling and support messages" refer to advice and encouraging messages provided by the generative artificial intelligence model to help the user learn.

[2271] A "smart device" refers to a device that is connected to the Internet and has sensors and processing capabilities.

[2272] "Real-time" refers to instantaneous processing and response of information.

[2273] "Product information" refers to data such as detailed descriptions and usage instructions for products sold in physical stores.

[2274] "Customer service" refers to the work of responding to customer questions and requests in physical stores.

[2275] "Learning Completion Data" means records generated when a user completes a particular learning plan or course.

[2276] "Blockchain" refers to a distributed ledger technology that prevents data tampering and ensures reliability.

[2277] "NFT format" refers to data in the form of a non-fungible token that represents a unique digital asset on a blockchain.

[2278] "Reward tokens" refer to digital currencies or points issued for learning outcomes.

[2279] To implement the present invention, the following steps and associated hardware and software are used.

[2280] System configuration

[2281] Server: This plays a central role in the system. It uses generative AI models to provide educational content and counseling, monitors learning progress, and issues appropriate rewards. The server uses cloud infrastructure such as Microsoft Azure Server or AWS EC2.

[2282] Terminal: A device that users and educators use to input information and communicate with the server. Examples include smartphones, tablets, PCs, and smart glasses. HoloLens 2 and Google Glass Enterprise Edition 2 are used as smart glasses.

[2283] Generative AI model: Performs various AI processes such as evaluating educational content, generating learning plans, and generating counseling messages. Specifically, OpenAI's GPT-3.5 model is used.

[2284] Blockchain: Used to ensure the reliability of learning completion data, and uses Ethereum and Hyperledger.

[2285] Input and evaluation of educational content

[2286] Educators input educational content into their devices and send it to the server. The server uses a generative AI model to evaluate the content and correct or enhance it as needed. For example, it checks grammar, content accuracy, and understandability. The corrected or enhanced educational content is published on the platform and available to other users.

[2287] Generate a learning plan

[2288] The user inputs their areas of interest and current skill level into the device. The server uses a generative artificial intelligence model based on the received information to generate an optimal learning plan. This plan includes recommended learning materials and courses and is sent to the device. The user then proceeds with their studies based on this learning plan.

[2289] Progress monitoring and counseling

[2290] The server monitors the user's learning progress in real time, analyzing learning logs and progress data to confirm whether the user is following the learning plan. If progress is falling behind, the server uses a generative artificial intelligence model to generate appropriate counseling and support messages and send them to the user's device.

[2291] Use of smart devices

[2292] Store staff can use smart glasses to provide real-time product information and customer consultations. Generative AI models are used to provide quick answers to customer questions. This system enhances staff training and customer service.

[2293] Recording learning completion data and issuing reward tokens

[2294] When a user completes a designated learning plan, the learning completion data is sent from the device to the server. The server records the learning completion data on the blockchain in NFT format. It also issues reward tokens to the user based on their learning results and notifies the device. This reward token information is also displayed on the smart device.

[2295] Examples of concrete examples and prompts

[2296] As a concrete example, consider a case where a customer asks a store staff member wearing smart glasses about a new smartphone. The staff member speaks to the smart glasses, and the server uses voice recognition to convert the question into text and send it to a generative artificial intelligence model. The answer generated by the AI ​​is displayed on the screen, and the staff member can relay it to the customer.

[2297] Example prompt sentence:

[2298] "If a customer asks about a new smartphone, provide them with the latest information."

[2299] "Generate training plans for new staff."

[2300] This will enable improved quality of educational content, flexible learning support, and efficient staff training and customer support in physical stores. By utilizing generative AI models and blockchain technology, it will be possible to ensure the reliability of learning results and provide fair compensation.

[2301] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2302] Step 1:

[2303] The educator inputs the educational content into the device. The input data here is educational content such as text information, images, and videos. The device converts this information into a format and sends it to the server.

[2304] Step 2:

[2305] The server passes the received educational content to a generative AI model for evaluation. Specifically, it checks the accuracy of grammar and content, as well as ease of understanding. During this process, the generative AI model analyzes the text and metadata to generate an evaluation result.

[2306] Step 3:

[2307] The server modifies and enhances the educational content based on the evaluation results, for example, correcting deficiencies and errors and inserting necessary additional explanations and examples. The modified and enhanced educational content is generated and made available for publication.

[2308] Step 4:

[2309] The server publishes the revised and enhanced educational content on the platform, and the published content is registered in a database in a format that can be accessed by other users.

[2310] Step 5:

[2311] Users log in to the platform and input their areas of interest and current skill level into their device. A learning plan is generated based on this input information, and specific items include areas of interest, skill level, and learning objectives.

[2312] Step 6:

[2313] The server uses a generative AI model based on the input data received from the user to generate an optimal learning plan. Data processing here includes analyzing the user profile and selecting learning materials from a database.

[2314] Step 7:

[2315] The server sends the generated learning plan to the user's device, which displays the received learning plan to the user and guides them to the next learning step.

[2316] Step 8:

[2317] The user progresses through their studies based on the study plan. Their progress is recorded as login history and study log, and periodically sent to the server.

[2318] Step 9:

[2319] The server monitors the user's learning progress in real time, analyzes the learning log and progress data, and generates appropriate counseling and support messages using a generative artificial intelligence model.

[2320] Step 10:

[2321] Once the support message is generated, the server sends it to the user's terminal, which notifies the user of the received message and provides the necessary support.

[2322] Step 11:

[2323] Staff use smart glasses to assist customers in brick-and-mortar stores. Customers' questions are entered by voice, and the device sends the information to a server.

[2324] Step 12:

[2325] The server uses speech recognition technology to convert the question into text and uses a generative artificial intelligence model to generate an answer, which is then displayed on the smart glasses' display.

[2326] Step 13:

[2327] When a user completes a learning plan, the user sends the data from the device to the server. The learning completion data includes the course studied and the achievement level.

[2328] Step 14:

[2329] The server receives the learning completion data and records it on the blockchain in NFT format, which ensures the data is tamper-proof and reliable.

[2330] Step 15:

[2331] The server issues reward tokens based on the user's learning results and notifies the terminal, which then displays the reward token information to the user and provides instructions on how to use it.

[2332] 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.

[2333] ---

[2334] The present invention relates to an educational platform that utilizes a generative artificial intelligence model and an emotion engine. In this platform, educators input educational content into a terminal, and a server evaluates, corrects, enhances, and publishes it. The platform also generates an optimal learning plan based on the information entered by the user, monitors learning progress while recognizing the user's emotions using an emotion engine, and provides appropriate support and counseling. Furthermore, learning completion data is recorded on a blockchain, and reward tokens are issued according to learning results. Specific embodiments of the present invention are described below.

[2335] Creating a study plan

[2336] 1. Enter your user information

[2337] Users input their areas of interest, current skill level, and learning goals through the educational platform terminal. For example, a user may input, "I want to learn the basics of generative artificial intelligence."

[2338] 2. Transmission of User Information

[2339] The terminal transmits the input user information to the server.

[2340] 3. Generating optimal study plans

[2341] The server utilizes a generative artificial intelligence model based on the received user information to generate an optimal learning plan for the user, including recommended learning materials and courses.

[2342] 4. Submit your study plan

[2343] The server transmits the generated study plan to the user's terminal.

[2344] 5. View your study plan

[2345] The terminal displays the received study plan to the user, and the user starts studying based on it.

[2346] Learning support and counselling

[2347] 1. Monitoring your learning progress

[2348] The server monitors the user's learning progress in real time, periodically collecting and analyzing learning logs and progress data.

[2349] 2. Collecting Emotional Data

[2350] The device uses a...

Claims

1. A means for an educator to input educational content into the terminal; A means for transmitting educational content from the terminal to a server; A means for the server to evaluate the educational content using a generative artificial intelligence model and modify or enhance it as necessary; A means to publish revised and enhanced educational content on the platform; A system that includes a means for users to access published educational content.

2. a means for the user to input their interests and skill level into the terminal; A means for the server to generate an optimal learning plan for the user using a generative artificial intelligence model; means for transmitting the generated learning plan to a user's terminal; A means for the user to proceed with learning based on the learning plan; a means for the server to monitor learning progress; 2. The system according to claim 1, wherein the server includes means for generating appropriate counseling or support messages using a generative artificial intelligence model and transmitting the messages to the terminal.

3. means for transmitting user learning completion data from the terminal to the server; A means for the server to record the learning completion data on the blockchain in NFT format; 2. The system according to claim 1, further comprising means for the server to issue a reward token to the user in accordance with the learning result and notify the terminal of the reward token.

4. A way for company and local government administrators to log in to the platform, The server aggregates and analyzes the learning data in real time and displays it on the administrator dashboard.

2. The system according to claim 1, wherein the server comprises means for generating counseling and support messages appropriate for a particular learner and transmitting the messages to the terminal.

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