System

Abstract

A system is provided.SOLUTION: The system includes a means for registering skill information and qualification information of the education expert, a means for inputting need information from the education institution, a generation artificial intelligence means for analyzing the need information of the education expert and the education institution and generating optimal matching, and a means for notifying the education institution and the education expert of a matching result in a share platform for appropriately matching the education institution and the education expert.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] The present invention aims to solve the following problems that cause a decline in the quality of education at educational institutions. Specifically, these problems include a shortage of educational experts, their lack of knowledge of new required subjects (e.g., programming), and school consolidation and closure due to declining student populations. These problems limit educational institutions' ability to quickly find and employ the appropriate educational experts they need. The present invention addresses these problems in order to prevent these limitations from directly leading to a decline in productivity in Japan's future. [Means for solving the problem]

[0005] The present invention provides a sharing platform for properly matching educational institutions with educational experts. Specifically, the system includes the following elements: a means for registering the skill information and qualification information of educational experts, and a means for inputting needs information from educational institutions. It also includes a generating artificial intelligence means for analyzing the needs information of educational experts and educational institutions to generate optimal matches, and a means for notifying educational institutions and educational experts of the matching results.

[0006] The present invention also includes a server means for proposing interview dates and storing the selection results in a database, and a means for humans and generative artificial intelligence to evaluate the skill information and qualification information of educational experts. Furthermore, the present invention also includes a means for selecting optimal educational materials based on requests from educational institutions, notifying educational experts of the selected educational materials and providing download links, and a server means for automating management tasks and updating the education-related information in the database. This enables educational institutions to quickly and appropriately find and assign the educational experts they need.

[0007] An "educational expert" is someone who has specialized knowledge and experience in a particular field of education.

[0008] "Educational institution" means any institution that provides education, including any public or private school or learning facility.

[0009] "Share Platform" refers to an online system that connects educational professionals with educational institutions.

[0010] "Server" refers to a central computer for data storage, analysis, and communication.

[0011] "Device" refers to devices such as computers and smartphones used by educational professionals and users at educational institutions.

[0012] "Database" refers to a structured collection of data that allows information to be stored and retrieved.

[0013] "Generative artificial intelligence" refers to AI technology that analyzes the skills of educational professionals and the needs of educational institutions to generate optimal matches.

[0014] "Skills information" refers to information about the knowledge, skills, and experience possessed by educational professionals.

[0015] "Credentials" refers to information such as official certifications and licenses held by education professionals.

[0016] "Needs Information" refers to information about the qualifications and skills required for specific educational professionals sought by an educational institution.

[0017] "Interview Schedule" means the date and time of an interview between an education professional and an educational institution.

[0018] "Notification" refers to the act of the system conveying important information to the user.

[0019] "Educational Materials" refers to educational materials provided to solve a specific educational task.

[0020] "Administrative activities" refers to activities that involve entering, updating, and storing information related to educational institutions and education professionals. [Brief explanation of the drawings]

[0021] [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

[0022] 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.

[0023] First, the terms used in the following description will be explained.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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."

[0029] [First embodiment]

[0030] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0031] 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.

[0032] 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).

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0038] 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.

[0039] 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.

[0040] 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.

[0041] 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."

[0042] The present invention is a "share platform" for effectively matching educational institutions with educational experts. Specific embodiments of the present invention will be described below.

[0043] 1. Registration and Initial Evaluation of Educational Professionals

[0044] User (educational professional) registration

[0045] Education professionals access the sharing platform using their devices, enter basic information (such as name, contact details, qualifications, and skills), and upload files such as resumes and certificates.

[0046] The server stores the information entered by the education specialist and the uploaded files in a database.

[0047] AI-based initial assessment

[0048] The server accesses the newly stored information and files.

[0049] The server calls the generation AI and has it analyze information about the qualifications and skills of educational professionals.

[0050] The generation AI performs an initial evaluation based on the analysis results and generates an evaluation result.

[0051] The server stores the initial evaluation results in a database.

[0052] 2. Interview and detailed evaluation

[0053] Arranging interview schedules

[0054] The server will send an email to the education professional suggesting an interview date.

[0055] The educational expert can choose a convenient date from the provided dates and times and respond from their device.

[0056] The server stores the selected interview dates in a database and notifies the interviewer of the interview schedule.

[0057] Interview and detailed evaluation

[0058] The interviewer will conduct the video interview at the appointed date and time.

[0059] Interviewers enter their evaluations into the system based on the interview content, the educational professional's skills, and their personality.

[0060] The server stores the entered ratings in a database and again uses the generation AI to generate the final rating.

[0061] 3. Inputting needs and matching

[0062] Inputting school needs

[0063] The educational institution administrator logs into the platform from a terminal and enters the requirements for the required educational specialist.

[0064] The server stores the school's needs data in a database.

[0065] AI-based matching

[0066] The server searches a database of registered education professionals.

[0067] The generative AI matches the input school needs with the skills of educational experts and generates a list of the most suitable educational experts.

[0068] The server notifies the educational institution administrator of the generated list.

[0069] Final selection and placement

[0070] The educational institution's administrator will select suitable educational professionals from the notified list of candidates and schedule additional interviews if necessary.

[0071] The server sends a notification of the placement decision to the selected education professional.

[0072] The server stores the final decision in a database and updates the educational professional's placement information.

[0073] 4. Support and Management

[0074] Provision of supplementary teaching materials

[0075] The server periodically checks the skill profiles of the education professionals.

[0076] Generative AI collects the latest educational material information and selects the most suitable materials to fill the skill gaps of educational professionals.

[0077] The server will email the educational specialist a list of selected learning materials and provide a download link.

[0078] Educational professionals use the devices to download learning materials and conduct their studies.

[0079] Automating administrative tasks

[0080] Entering and updating faculty information:

[0081] Teachers enter new information (e.g., contact information changes) on their terminals.

[0082] The server immediately updates the database.

[0083] Attendance Management:

[0084] Faculty and staff enter their daily attendance information on their terminals.

[0085] The server receives this and automatically updates the attendance record.

[0086] Creating educational materials:

[0087] When a teacher sends the contents of educational materials to the server, the generating AI automatically applies the format and checks the content.

[0088] The server returns the generated educational materials to the instructor and accepts corrections as necessary.

[0089] 5. Updating Information

[0090] Constantly updated

[0091] The server periodically collects educational updates and curriculum changes.

[0092] The generative AI analyzes this new information and makes any necessary updates.

[0093] The server updates the database and notifies education professionals.

[0094] Educational professionals can check the latest information on their devices and update learning and curriculum as needed.

[0095] Specific examples

[0096] As a concrete example, here is the process that a public school in Tokyo goes through when it is looking for an educational expert with programming knowledge.

[0097] 1. Registration and evaluation of educational professionals

[0098] An educational expert A who is knowledgeable in programming registers in the system, enters his / her skills and qualifications, and uploads his / her resume.

[0099] The server receives this, and the generation AI analyzes it to complete the initial evaluation.

[0100] 2. Interview

[0101] The server proposes an interview date to Educational Specialist A. Educational Specialist A selects a convenient date and time, and the server confirms the interview date.

[0102] The interviewer conducts the video interview and inputs the evaluation into the server.

[0103] 3. Matching

[0104] The school's administrator logs into the system and enters the needs of programming educators.

[0105] The server's generation AI will compare the skill information of Educational Expert A and add him to the list as the most suitable candidate.

[0106] 4. Selection and Assignment

[0107] The school administrator selects educational expert A, the server notifies educational expert A, and then the assignment is decided.

[0108] This series of processes provides a system that can quickly and efficiently connect educational professionals sought by schools with educational institutions that suit the professionals' qualifications.

[0109] The processing flow will be explained below.

[0110] 1. Registration and Initial Evaluation of Educational Professionals

[0111] User (educational professional) registration

[0112] Step 1:

[0113] The user accesses the sharing platform website using a device and proceeds to the login or new registration screen.

[0114] Step 2:

[0115] Users enter basic information such as name, contact details, email address, qualifications, and skills, and upload resume and certificate files.

[0116] Step 3:

[0117] Once the user has entered all the information, they click the "Submit" button.

[0118] Step 4:

[0119] The server receives the information entered by the user and the uploaded files and stores them in a database.

[0120] AI-based initial assessment

[0121] Step 1:

[0122] The server accesses the newly stored information and files.

[0123] Step 2:

[0124] The server calls the generation AI and has it analyze information about the qualifications and skills of educational professionals.

[0125] Step 3:

[0126] The generation AI performs an initial evaluation based on the analysis results and generates an evaluation result.

[0127] Step 4:

[0128] The server stores the generated initial evaluation results in a database.

[0129] 2. Interview and detailed evaluation

[0130] Arranging interview schedules

[0131] Step 1:

[0132] The server sends an email to the education professional containing a suggested interview date.

[0133] Step 2:

[0134] The user (educational specialist) receives the email and responds to the system from a terminal to select a convenient date from the presented dates and times.

[0135] Step 3:

[0136] The server confirms the interview date and time selected by the user and stores it in a database.

[0137] Step 4:

[0138] The server notifies the interviewer of the selected interview schedule.

[0139] Interview and detailed evaluation

[0140] Step 1:

[0141] The interviewer will conduct a video interview with the education professional using a video interviewing tool at the appointed date and time.

[0142] Step 2:

[0143] Interviewers enter their evaluations into the system based on the interview content and the educational professional's skills and personality.

[0144] Step 3:

[0145] The server stores the evaluations entered by the interviewers in a database.

[0146] Step 4:

[0147] The server then uses the generation AI again based on the saved detailed evaluation information to generate the final evaluation.

[0148] 3. Inputting needs and matching

[0149] Inputting school needs

[0150] Step 1:

[0151] The educational institution administrator logs in to the share platform using a device.

[0152] Step 2:

[0153] Administrators input the required educational professional requirements (e.g., specific skills, years of experience, etc.).

[0154] Step 3:

[0155] The server stores the school needs data entered by the administrator in a database.

[0156] AI-based matching

[0157] Step 1:

[0158] The server searches a database of registered education professionals.

[0159] Step 2:

[0160] The generative AI matches the input needs of schools with the skill profiles of educational professionals.

[0161] Step 3:

[0162] Generative AI generates a list of the best educational experts.

[0163] Step 4:

[0164] The server notifies the educational institution administrator of the generated list.

[0165] Final selection and placement

[0166] Step 1:

[0167] The educational institution's administrator will select a suitable educational professional from the notified list of candidates.

[0168] Step 2:

[0169] Administrators will schedule additional interviews through the system if necessary.

[0170] Step 3:

[0171] The server confirms the administrator's selection result and sends a notification of the placement decision to the selected educational expert.

[0172] Step 4:

[0173] The server stores the final decision in a database and updates the educational professional's placement information.

[0174] 4. Support and Management

[0175] Provision of supplementary teaching materials

[0176] Step 1:

[0177] The server periodically checks the skill profile of the education professional.

[0178] Step 2:

[0179] Generative AI collects the latest educational material information and selects the most suitable materials to fill the skill gaps of educational professionals.

[0180] Step 3:

[0181] The server will email the educational specialist a list of selected learning materials and provide a download link.

[0182] Step 4:

[0183] Educational professionals use the devices to download learning materials and conduct their studies.

[0184] Automating administrative tasks

[0185] Step 1:

[0186] The user (teacher) uses the terminal to enter new information (e.g., contact information change).

[0187] Step 2:

[0188] The server immediately stores and updates the database with the new information it receives.

[0189] Step 3:

[0190] Faculty and staff enter their daily attendance information into the system from their terminals.

[0191] Step 4:

[0192] The server automatically updates the attendance record with the received attendance information.

[0193] Step 5:

[0194] The teacher sends the contents of the educational materials to the server.

[0195] Step 6:

[0196] The generation AI applies formatting and checks the content of the educational materials sent.

[0197] Step 7:

[0198] The server returns the generated educational materials to the instructor and accepts corrections as necessary.

[0199] 5. Updating Information

[0200] Constantly updated

[0201] Step 1:

[0202] The server periodically collects educational updates and curriculum changes.

[0203] Step 2:

[0204] The generative AI analyzes new information and makes necessary updates.

[0205] Step 3:

[0206] The server updates the database and notifies education professionals.

[0207] Step 4:

[0208] Educational professionals can check the latest information on their devices and update learning and curriculum as needed.

[0209] Example 1

[0210] 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."

[0211] In today's educational environment, it is difficult for educational institutions to quickly and efficiently find educational professionals with the specialized knowledge and skills they require. As a result, it takes time for educational institutions to hire suitable educational professionals, making it difficult to maintain the quality of education. Furthermore, educational professionals lack the means to have their skills and qualifications properly evaluated, making it difficult to find suitable positions. Furthermore, the time and effort required to obtain the latest educational materials and information is a significant burden. There is a need to build an efficient matching system to solve these issues.

[0212] 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.

[0213] In this invention, the server includes a means for recording the experience and qualification information of educational experts, a means for inputting requirement information from educational institutions, and a generating AI means for analyzing the requirement information of educational experts and educational institutions to generate optimal matches. This enables educational institutions to quickly and efficiently find educational experts with the expertise and skills they require. The server also includes a means for periodically checking the skill profiles of educational experts and selecting appropriate learning materials using a generating AI model, and a means for notifying educational experts of the selected learning materials and providing download links. This allows educational experts to keep their skills up to date at all times.

[0214] "Educational institutions" refers to facilities and organizations that carry out educational activities, including elementary schools, junior high schools, high schools, universities, and other educational institutions.

[0215] "Educational professionals" refers to professionals who have the qualifications and experience to provide instruction and education in educational institutions, including teachers, lecturers, and special education coordinators.

[0216] A "share platform" refers to an online system that connects multiple educational institutions and educational experts.

[0217] "Experience" refers to the practical experience and skills acquired by an educational professional, including teaching experience in a particular subject or program.

[0218] "Credentials" refers to any official qualifications or certifications held by an education professional, including teaching licenses and professional certifications.

[0219] "Requirements Information" refers to the specific skills, qualifications, and experience requirements of educational professionals sought by an educational institution.

[0220] "Analysis" refers to the process of analyzing input information, understanding its content, and making an evaluation.

[0221] "Generative AI means" refers to artificial intelligence technology that analyzes and evaluates input information to generate optimal candidates and teaching materials.

[0222] "Notification" refers to the act of communicating important information from the system to educational professionals and institutions, primarily via email or in-system notifications.

[0223] A "skills profile" refers to information that records an overview of the skills and experience of an educational professional.

[0224] "Instructional Materials" refers to educational materials and reference documents used by educational professionals to improve their skills.

[0225] "Download link" refers to the URL that educational professionals can use to obtain educational materials via the Internet.

[0226] "Administrative tasks" refers to the day-to-day administrative tasks of education professionals and institutions, such as updating contact details and managing attendance.

[0227] "Storage" refers to the act of saving and storing data or information in a database.

[0228] The present invention provides a sharing platform for effectively matching educational institutions with educational experts. This system has the function of registering the skills and qualifications of educational experts, automating the process of matching them with the requirements of educational institutions, and providing the educational experts with the most suitable educational materials.

[0229] Hardware and software used

[0230] Server: The computer that performs the main processing of this system, managing the database and running the AI ​​model.

[0231] Device: A computer, tablet, smartphone, or other device used by education professionals and administrators to enter information and receive notifications.

[0232] Generative AI model: An artificial intelligence technology that performs information analysis and evaluation, evaluating the skills of educational experts, generating matching lists, and selecting optimal teaching materials.

[0233] Program processing overview

[0234] 1. Registration and Initial Evaluation of Educational Professionals

[0235] User (educational professional): Uses a terminal to access the sharing platform, enters basic information such as name, contact details, qualifications, skills, etc., and uploads resumes and certificates. After completing the entry, the server stores this information in a database and sends a confirmation email to the user.

[0236] Server: Inputs the saved information and files into the generative AI model, analyzes the qualifications and skills of the educational expert, and performs an initial evaluation. The results are saved in a database, and an email is sent to the educational expert to notify them of the completion of the initial evaluation.

[0237] Example of how it works: An educational expert inputs skills such as "Python" or "Java," and the server requests the generated AI model to analyze them and saves the results.

[0238] Example prompt sentence:

[0239] "Make an initial assessment based on the skills information this education professional has."

[0240] 2. Interview and detailed evaluation

[0241] User (educational specialist): Checks the interview dates and times suggested by the server on the terminal and selects a suitable date and time. The server saves the selected date and time in the database and notifies the interviewer.

[0242] Server: The interviewer conducts the video interview at the specified date and time, and saves the results and evaluation in the database. The generative AI model is used again to perform the final evaluation, and the results are saved.

[0243] Example of specific operation: The interviewer conducts the interview using a video conferencing tool, inputs the evaluation details, and analyzes them using the generative AI model.

[0244] Example prompt sentence:

[0245] "Generate a final grade based on the interview evaluation results."

[0246] 3. Input and matching of school needs

[0247] User (educational institution administrator): Logs in to the sharing platform from a terminal and enters the necessary information on educational professionals. The server stores this information in a database.

[0248] Server: Retrieves information about educational professionals from the database, compares it with the school's requirements using a generative AI model, and generates a list of the best candidates. The list is then sent to the educational institution's administrator.

[0249] Example of specific operation: An educational institution inputs conditions such as "5 or more years of programming experience," and the server generates a list of candidates using a generative AI model and notifies them.

[0250] Example prompt sentence:

[0251] "Generate a list of educational professionals who best fit the needs of this school."

[0252] 4. Final selection and assignment

[0253] User (educational institution administrator): Selects appropriate educational specialists from the notified candidate list and schedules additional interviews if necessary. The server stores the selection results in a database and notifies the educational specialists of the placement decision.

[0254] Example of specific operation: Select from the candidate list and press the "Decide" button. A notification is automatically sent to the educational expert and the database is updated.

[0255] Example prompt sentence:

[0256] "Please send notification of placement decision to the selected educational professional."

[0257] 5. Support and Management

[0258] Server: Regularly checks the skill profiles of education experts and selects the most suitable learning materials using a generative AI model. It notifies education experts of the list of selected learning materials and provides download links. It also automates administrative tasks and updates the database.

[0259] User (educational specialist): Uses the download link from the device to obtain the learning materials and proceed with the study.

[0260] Example of specific operation: The server queries the skill data of the educational expert, and the generative AI selects and notifies the optimal teaching materials. The educational expert downloads the materials from the link.

[0261] Example prompt sentence:

[0262] "Select the most appropriate educational materials for this educational professional."

[0263] The server-based system automates a series of processes to quickly and efficiently match educational institutions with educational experts. Utilizing generative AI models, it seamlessly performs everything from skill assessment to matching, selection, and assignment, as well as providing teaching materials and updating information.

[0264] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0265] Step 1:

[0266] Register of Educational Professionals

[0267] Input: The user (education professional) uses a device to access the share platform, enters basic information such as name, contact details, qualifications, and skills, and uploads files of resumes and certificates.

[0268] Data processing and calculation: The server receives the input information and files, performs an initial data format check, and verifies the accuracy and completeness of the information.

[0269] Output: The server stores the received data in a database and sends the user a confirmation email.

[0270] Specific action: A user enters information into a system form and clicks the "Submit" button.

[0271] Step 2:

[0272] Initial evaluation by educational professionals

[0273] Input: Saved education professional information and uploaded files.

[0274] Data processing and calculation: The server retrieves new registration information from the database and inputs it into the generative AI model. The generative AI model analyzes skills and qualifications and generates evaluation results.

[0275] Output: The generated evaluation results are returned to the server and stored in the database. The server then sends the user an email to complete the initial evaluation.

[0276] Specific operation: The server inputs the data into the AI ​​analysis and stores the evaluation results in a database.

[0277] Step 3:

[0278] Arranging interview schedules

[0279] Input: Multiple interview dates and times suggested by the server.

[0280] Data processing and calculation: The educational expert selects a convenient date and time and sends it back to the server. The server saves the selected date and time in the database and notifies the interviewer.

[0281] Output: The selected interview date and time are saved in the database and the interviewer is notified of the schedule.

[0282] Specific behavior: The user selects a convenient date and time from the calendar form and submits it.

[0283] Step 4:

[0284] Interview and detailed evaluation

[0285] Input: Interview content and evaluation from the interviewer's video conferencing tool.

[0286] Data processing and calculation: Interviewers input their evaluations into the system, and the server stores them in a database. The generative AI model is then used again to make the final evaluation.

[0287] Output: The interview evaluation results and final evaluation are saved in the database.

[0288] Specific action: The interviewer enters information into the evaluation form and clicks the "Submit" button.

[0289] Step 5:

[0290] Inputting school needs

[0291] Input: Institution requirement information (such as required skills and experience).

[0292] Data processing and calculation: The server stores the input requirements information in a database and prepares for matching.

[0293] Output: Requirement information is saved in the database.

[0294] Specific action: The educational institution administrator fills in the required requirements on the form and clicks the "Submit" button.

[0295] Step 6:

[0296] Match Generation

[0297] Input: Education professional information and school requirement information in the database.

[0298] Data processing and calculation: The server retrieves the information in the database, inputs it into the generative AI model for matching, and generates a list of optimal educational experts.

[0299] Output: The generated list is sent to the institution administrator.

[0300] Specific operation: The server inputs the data into AI analysis, generates a result report, and notifies the administrator by email.

[0301] Step 7:

[0302] Final selection and placement

[0303] Input: A list of candidates selected by the institution's administrators.

[0304] Data processing and calculation: The server sends a notification to the selected education specialist and updates the assignment information in the database.

[0305] Output: An assignment notification is sent to the education specialist and the assignment information is saved in the database.

[0306] Specific action: The administrator selects from the candidate list and clicks the "Decide" button.

[0307] Step 8:

[0308] Provision of supplementary teaching materials

[0309] Input: Skills profiles of education professionals and up-to-date educational material information.

[0310] Data processing and calculation: The server passes the skill profile to the generative AI model to generate the optimal teaching material list. The selected teaching material list is notified to the educational expert.

[0311] Output: A list of materials and a download link will be sent to the education specialist.

[0312] Specific operation: The server inputs skill data into AI analysis, generates a list of teaching materials, and notifies the user.

[0313] Step 9:

[0314] Automating administrative tasks

[0315] Input: Faculty new information or daily attendance information.

[0316] Data processing and calculation: The server immediately updates the database with the input information. If necessary, it automatically performs management tasks using a generative AI model.

[0317] Output: The database is updated with the latest information.

[0318] Specific action: Faculty enters new information into the form and clicks the "Submit" button.

[0319] Step 10:

[0320] Information Update

[0321] Input: Latest education-related information and curriculum changes.

[0322] Data processing and calculation: The server periodically collects this new information, analyzes it using the generative AI model, and updates the database accordingly.

[0323] Output: The latest information is updated in the database and the education specialist is notified.

[0324] Specific operation: The server uses APIs and RSS feeds to collect the latest information, performs AI analysis, saves the results in a database, and notifies the user.

[0325] (Application example 1)

[0326] 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."

[0327] The previous system did not efficiently match educational institutions with educational experts, and the registration and evaluation of expert skills and qualifications was cumbersome. There were also issues with scheduling interviews and notifying selection results smoothly, which meant that the alignment between the needs of educational institutions and the skills of experts was not fully ensured. Furthermore, there was insufficient automation of the provision and management of educational materials.

[0328] 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.

[0329] In this invention, the server includes a means for registering skill information and qualification information of educational professionals, a means for inputting needs information from educational institutions, a generating artificial intelligence means for analyzing the needs information of educational professionals and educational institutions and generating optimal matches, a means for notifying educational institutions and educational professionals of the matching results, a means for educational professionals to input and update information via a smart device, and a video call means for supporting interviews, meetings, and the sharing of educational materials. This enables efficient matching between educational professionals and educational institutions, smooth interview arrangements and notifications, and the automation of the provision and management of educational materials.

[0330] An "educational institution" is an organization that provides educational services, such as a school, university, or vocational school.

[0331] An "educational professional" is a professional who has the qualifications and skills to specialize in education.

[0332] The "Share Platform" is an online system for sharing information and matching between educational experts and educational institutions.

[0333] "Skills information" is information about the professional abilities and experience of educational professionals.

[0334] "Credentials" refers to information about the various certifications and credentials held by education professionals.

[0335] "Needs information" refers to information about the skills, qualifications, and assignment conditions of professionals required by educational institutions.

[0336] "Generative AI" is an AI technology that analyzes input data and generates the most suitable matches between educational experts and educational institutions.

[0337] A "smart device" is a multi-function terminal that can connect to the Internet, such as a smartphone, smart glasses, or a head-mounted display.

[0338] "Video communication means" refers to a means for real-time video and audio communication using the Internet.

[0339] A "server" is a computer system that stores and manages various data, and analyzes, notifies, and operates on information.

[0340] "Notification means" refers to email or application messaging functions used to notify relevant parties of various information and results.

[0341] "Educational materials" are any type of learning material used by educational professionals in teaching or training.

[0342] "Administrative work" refers to administrative tasks such as updating education-related information, managing attendance, and creating materials.

[0343] "Automation" means that tasks that were previously performed manually can be performed automatically by machines or software.

[0344] The present invention relates to a sharing platform for efficiently matching educational institutions with educational experts. This system enables educational experts to appropriately match the requirements of educational institutions and quickly find experts with the skills required by the educational institutions. Specific embodiments of the system are described below.

[0345] 1. Registration and Initial Evaluation of Educational Professionals

[0346] User (educational professional) registration

[0347] Educational professionals access the sharing platform using a smart device (smartphone, smart glasses, head-mounted display), enter basic information (name, contact details, qualifications, skills, etc.), and upload resumes and certificate files. The server stores the information entered by the educational professionals and the uploaded files in a database.

[0348] AI-based initial assessment

[0349] The server accesses the newly saved information and files, invokes a generative AI (such as OpenAI's GPT-3) and has it analyze the information about the educational expert's qualifications and skills. The generative AI performs an initial evaluation based on the analysis results and generates an evaluation result. The server stores the initial evaluation result in a database.

[0350] 2. Interview and detailed evaluation

[0351] Arranging interview schedules

[0352] The server sends a notification to the educational specialist suggesting an interview date to the smart device. The educational specialist selects a convenient date from the suggested dates and responds from the device. The server saves the selected interview date in the database and notifies the interviewer of the interview schedule.

[0353] Interview and detailed evaluation

[0354] The interviewer will conduct the interview via video call at the appointed date and time. The interviewer will enter their evaluation of the interview content, the skills of the educational expert, and their personality into the system. The server will store the entered evaluation in a database and use the generative AI again to generate the final evaluation.

[0355] 3. Inputting needs and matching

[0356] Inputting school needs

[0357] The administrator of the educational institution logs in to the platform from a terminal and inputs the requirements for the educational specialists they need. The server stores the school's needs data in a database.

[0358] AI-based matching

[0359] The server searches the database of registered educational experts. The generation AI matches the input school's needs with the skills of the educational experts and generates a list of the most suitable educational experts. The server notifies the educational institution's administrator of the generated list.

[0360] Final selection and placement

[0361] The educational institution administrator selects a suitable educational expert from the notified candidate list and schedules additional interviews if necessary. The server then sends a notification of the placement decision to the selected educational expert. The server then saves the final decision in the database and updates the placement information of the educational expert.

[0362] 4. Provision and management of educational materials

[0363] Provision of supplementary teaching materials

[0364] The server periodically checks the skill profiles of education experts. The generation AI collects the latest educational material information and selects the most suitable materials to fill the education expert's skill gaps. The server notifies the education expert of the list of selected materials and provides a download link. The education expert downloads the materials using their device and begins studying.

[0365] Automating administrative tasks

[0366] Entering and updating faculty information:

[0367] The server instantly updates the database when education professionals enter new information (e.g., contact changes) at their devices.

[0368] Attendance Management:

[0369] Faculty and staff enter their daily attendance information on their terminals, and the server receives this information and automatically updates the attendance records.

[0370] Creating educational materials:

[0371] When a teacher sends the contents of educational materials to the server, the generation AI automatically applies formatting and checks the content, then returns the generated educational materials to the teacher and accepts corrections as necessary.

[0372] Specific examples

[0373] As a concrete example, here is the process that a public school in Tokyo goes through when it is looking for an educational expert with programming knowledge.

[0374] 1. Registration and evaluation of educational professionals

[0375] An educational expert A who is familiar with programming registers with the system, enters skill information and qualifications, and uploads a resume. The server receives this, and the generation AI analyzes it to complete an initial evaluation.

[0376] 2. Interview

[0377] The server proposes an interview date to Educational Expert A. Educational Expert A selects a convenient date and time, and the server confirms the interview date. The interviewer conducts the interview via video call and enters the evaluation into the server.

[0378] 3. Matching

[0379] The school administrator logs into the system and inputs their needs for programming educators. The server's generation AI compares this with the skill information of Educational Expert A and adds him or her to the list as the most suitable candidate.

[0380] 4. Selection and Assignment

[0381] The school administrator selects educational expert A, the server notifies educational expert A, and then the assignment is decided.

[0382] Example prompts to input to the generative AI model

[0383] plain

[0384] "Please rate an educational professional with expertise in programming education. Please make an initial assessment based on the following information: Qualifications: {Qualifications}, Skills: {Skills}"

[0385] The system allows educational institutions to quickly and efficiently connect with the educational professionals they need.

[0386] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0387] Step 1:

[0388] Registration and initial evaluation of educational professionals

[0389] Users (education professionals) access the sharing platform using their smart devices, enter basic information (such as name, contact details, qualifications, and skills), and upload resume and certificate files. This information and files are then sent to the server, which stores the data in a database. The entered data includes the education professional's skills and qualifications.

[0390] Next, the server calls a generative AI model (e.g., OpenAI's GPT-3) to generate a prompt that analyzes the uploaded information. An example of a prompt is, "Please evaluate the educational expert based on the following information: Qualifications: {Qualifications}, Skills: {Skills}." The generative AI performs an initial evaluation based on the analysis results and sends the results back to the server, where they are stored in a database. This stores the educational expert's basic information and initial evaluation results in the database.

[0391] Step 2:

[0392] Arranging interview schedules

[0393] The server sends a notification to the educational expert proposing an interview date. The notification is sent to the smart device, and the educational expert selects a convenient date from the specified dates and times and responds through the device. The server saves the selected interview date in the database and simultaneously notifies the interviewer of the interview schedule. Through this process, the interview date is confirmed for both the educational expert and the interviewer.

[0394] Step 3:

[0395] Interview and detailed evaluation

[0396] The interviewer will conduct the interview via video call at the appointed date and time. For the video call, an appropriate video call tool (e.g., Zoom, Microsoft Teams) will be used. After the interview, the interviewer will enter their evaluation into the system regarding the interview content, the educational expert's skills, and their personality. The server will then store the entered evaluation data in a database. The server will then again use the generative AI to perform a final evaluation. This result will be stored in the database, and the final evaluation result will be confirmed.

[0397] Step 4:

[0398] Inputting and matching needs

[0399] The administrator of the educational institution logs in to the platform using a terminal and enters the requirements for the educational specialists required. This data is sent to the server, which stores it in a database. The server then invokes the generation AI to match the needs of the educational institution with the skill information of registered educational specialists and generate a list of the most suitable educational specialists. This matching involves selecting specialists with the appropriate skills and experience based on the educational institution's conditions and requirements. The generated list is then notified to the administrator of the educational institution.

[0400] Step 5:

[0401] Final selection and placement

[0402] The educational institution administrator selects a suitable educational expert from the notified candidate list and schedules additional interviews if necessary. The server then sends a notification of the placement decision to the selected educational expert. This notification is delivered to the educational expert via their smart device. The server then saves the final decision in the database and updates the placement information of the educational expert. This allows the educational institution and the educational expert to be appropriately linked.

[0403] Step 6:

[0404] Provision and management of educational materials

[0405] The server periodically checks the skill profiles of education experts and uses generative AI to collect the latest educational material information. The AI ​​selects the most suitable educational materials to fill the education expert's skill gaps and notifies the education expert of the list. The notification includes a download link, and the education expert can download the materials using their device and study.

[0406] The server also has the ability to automate administrative tasks, efficiently updating education-related information, managing attendance, creating educational materials, etc. This will greatly simplify the administrative work of educational institutions.

[0407] This allows educational institutions to quickly and efficiently connect with the education professionals they need, and for education professionals to seamlessly receive the information and materials they need.

[0408] 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.

[0409] The present invention is a sharing platform for effectively matching educational institutions with educational professionals. This platform is combined with an emotion engine that recognizes and analyzes user emotions to achieve more accurate matching and improved service. Specific embodiments of the platform are described below.

[0410] 1. Registration and Initial Evaluation of Educational Professionals

[0411] User (educational professional) registration

[0412] Education professionals use their devices to access the sharing platform, enter basic information (such as name, contact details, qualifications, skills, etc.), and upload files of their resumes and certificates.

[0413] The server stores the information entered by the education specialist and the uploaded files in a database.

[0414] AI-based initial assessment

[0415] The server accesses the newly stored information and files.

[0416] The server calls the generation AI and has it analyze information about the qualifications and skills of educational professionals.

[0417] The generation AI performs an initial evaluation based on the analysis results and generates an evaluation result.

[0418] The server stores the generated initial evaluation results in a database.

[0419] 2. Interview and detailed evaluation

[0420] Arranging interview schedules

[0421] The server sends an email to the education professional suggesting an interview date.

[0422] The educational expert can choose a convenient date from the provided dates and times and respond from their device.

[0423] The server verifies the selected interview date and time and stores it in a database.

[0424] The server notifies the interviewer of the selected interview schedule.

[0425] Interview and detailed evaluation

[0426] The interviewer will conduct a video interview with the education professional using a video interviewing tool at the appointed date and time.

[0427] During the interview, the emotion engine analyzes the educational professional's facial expressions and voice to collect emotional data in real time.

[0428] Interviewers enter their evaluations into the system based on the content of the interview and the educational professional's skills and personality.

[0429] The emotion engine analyzes the collected emotional data and reflects it in the evaluation results.

[0430] The server stores the input ratings and analysis results in a database, and the generation AI generates the final rating.

[0431] 3. Inputting needs and matching

[0432] Inputting school needs

[0433] The educational institution administrator logs in to the share platform using a device.

[0434] Administrators input the required educational professional requirements (e.g., specific skills, years of experience, etc.).

[0435] The server stores the school needs data entered by the administrator in a database.

[0436] AI-based matching

[0437] The server searches a database of registered education professionals.

[0438] The generative AI matches the input needs of schools with the skill profiles of educational professionals.

[0439] Generative AI generates a list of the best educational experts.

[0440] The server notifies the educational institution administrator of the generated list.

[0441] Final selection and placement

[0442] The educational institution's administrator will select a suitable educational professional from the notified list of candidates.

[0443] If necessary, educational institution administrators can use the emotion engine to select the most suitable educational expert based on the candidate's emotion data.

[0444] The server verifies the selection results and sends a notification of the placement decision to the education specialist.

[0445] The server stores the final decision in a database and updates the educational professional's placement information.

[0446] 4. Support and Management

[0447] Provision of supplementary teaching materials

[0448] The server periodically checks the skill profiles of the education professionals.

[0449] Generative AI collects the latest educational material information and selects the most suitable materials to fill the skill gaps of educational professionals.

[0450] The server will email the educational specialist a list of selected learning materials and provide a download link.

[0451] Educational professionals use the devices to download learning materials and conduct their studies.

[0452] Automating administrative tasks

[0453] Entering and updating faculty information:

[0454] Teachers enter new information (e.g., contact information changes) on their terminals.

[0455] The server immediately updates the database.

[0456] Attendance Management:

[0457] Faculty and staff enter their daily attendance information on their terminals.

[0458] The server receives this and automatically updates the attendance record.

[0459] Creating educational materials:

[0460] When a teacher sends the contents of educational materials to the server, the generating AI automatically applies the format and checks the content.

[0461] The server returns the generated educational materials to the instructor and accepts corrections as necessary.

[0462] 5. Updating Information

[0463] Constantly updated

[0464] The server periodically collects educational updates and curriculum changes.

[0465] The generative AI analyzes this new information and makes any necessary updates.

[0466] The server updates the database and notifies education professionals.

[0467] Educational professionals can check the latest information on their devices and update learning and curriculum as needed.

[0468] Specific examples

[0469] As a concrete example, here is the process that a public school in Tokyo goes through when it is looking for an educational expert with programming knowledge.

[0470] 1. Registration and evaluation of educational professionals

[0471] An educational expert A who is knowledgeable in programming registers in the system, enters his / her skills and qualifications, and uploads his / her resume.

[0472] The server receives this, and the generation AI analyzes it to complete the initial evaluation.

[0473] 2. Interview

[0474] The server proposes an interview date to Educational Specialist A. Educational Specialist A selects a convenient date and time, and the server confirms the interview date.

[0475] The interviewer conducts the video interview, and the emotion engine collects emotional data in real time. The server stores the interviewer's evaluation and emotional data in a database, and the generative AI makes the final evaluation.

[0476] 3. Matching

[0477] The school's administrator logs into the system and enters the needs of programming educators.

[0478] The server's generation AI compares educational expert A's skill information with his / her emotional data and adds him / her to the list as the most suitable candidate.

[0479] 4. Selection and Assignment

[0480] The school administrator selects Educational Expert A and confirms that he is the best fit based on the emotional data. The server then sends a notification of the assignment decision to Educational Expert A. The final decision information is stored in the database.

[0481] This series of processes provides a system that can quickly and efficiently connect educational experts needed by schools with educational institutions that match the experts' aptitudes. Furthermore, by utilizing an emotion engine, it is expected that matching accuracy and service quality will be further improved.

[0482] The processing flow will be explained below.

[0483] 1. Registration and Initial Evaluation of Educational Professionals

[0484] User (educational professional) registration

[0485] Step 1:

[0486] The user accesses the sharing platform website using a device and proceeds to the login or new registration screen.

[0487] Step 2:

[0488] Users enter basic information such as name, contact details, email address, qualifications, and skills, and upload resume and certificate files.

[0489] Step 3:

[0490] Once the user has entered all the information, they click the "Submit" button.

[0491] Step 4:

[0492] The server receives the information entered by the user and the uploaded files and stores them in a database.

[0493] AI-based initial assessment

[0494] Step 1:

[0495] The server accesses the newly stored information and files.

[0496] Step 2:

[0497] The server calls the generation AI and has it analyze information about the qualifications and skills of educational professionals.

[0498] Step 3:

[0499] The generation AI performs an initial evaluation based on the analysis results and generates an evaluation result.

[0500] Step 4:

[0501] The server stores the generated initial evaluation results in a database.

[0502] 2. Interview and detailed evaluation

[0503] Arranging interview schedules

[0504] Step 1:

[0505] The server sends an email to the education professional containing a suggested interview date.

[0506] Step 2:

[0507] The user (educational specialist) receives the email and responds to the system from a terminal to select a convenient date from the presented dates and times.

[0508] Step 3:

[0509] The server confirms the interview date and time selected by the user and stores it in a database.

[0510] Step 4:

[0511] The server notifies the interviewer of the selected interview schedule.

[0512] Interview and detailed evaluation

[0513] Step 1:

[0514] The interviewer will conduct a video interview with the education professional using a video interviewing tool at the appointed date and time.

[0515] Step 2:

[0516] During the interview, the emotion engine analyzes the educational professional's facial expressions and voice to collect emotional data in real time.

[0517] Step 3:

[0518] Interviewers enter their evaluations into the system based on the content of the interview and the educational professional's skills and personality.

[0519] Step 4:

[0520] The emotion engine analyzes the collected emotional data and reflects it in the evaluation results.

[0521] Step 5:

[0522] The server stores the input ratings and analysis results in a database, and the generation AI generates the final rating.

[0523] 3. Inputting needs and matching

[0524] Inputting school needs

[0525] Step 1:

[0526] The educational institution administrator logs in to the share platform using a device.

[0527] Step 2:

[0528] Administrators input the required educational professional requirements (e.g., specific skills, years of experience, etc.).

[0529] Step 3:

[0530] The server stores the school needs data entered by the administrator in a database.

[0531] AI-based matching

[0532] Step 1:

[0533] The server searches a database of registered education professionals.

[0534] Step 2:

[0535] The generative AI matches the input needs of schools with the skill profiles of educational professionals.

[0536] Step 3:

[0537] Generative AI generates a list of the best educational experts.

[0538] Step 4:

[0539] The server notifies the educational institution administrator of the generated list.

[0540] Final selection and placement

[0541] Step 1:

[0542] The educational institution's administrator will select a suitable educational professional from the notified list of candidates.

[0543] Step 2:

[0544] Administrators will schedule additional interviews through the system if necessary.

[0545] Step 3:

[0546] Use an emotion engine to collect and analyze emotional data from education professionals to identify suitable candidates.

[0547] Step 4:

[0548] The server confirms the administrator's selection result and sends a notification of the placement decision to the selected educational expert.

[0549] Step 5:

[0550] The server stores the final decision in a database and updates the educational professional's placement information.

[0551] 4. Support and Management

[0552] Provision of supplementary teaching materials

[0553] Step 1:

[0554] The server periodically checks the skill profiles of the education professionals.

[0555] Step 2:

[0556] Generative AI collects the latest educational material information and selects the most suitable materials to fill the skill gaps of educational professionals.

[0557] Step 3:

[0558] The server will email the educational specialist a list of selected learning materials and provide a download link.

[0559] Step 4:

[0560] Educational professionals use the devices to download learning materials and conduct their studies.

[0561] Automating administrative tasks

[0562] Step 1:

[0563] The user (teacher) uses the terminal to enter new information (e.g., contact information change).

[0564] Step 2:

[0565] The server immediately stores and updates the database with the new information it receives.

[0566] Step 3:

[0567] Faculty and staff enter their daily attendance information into the system from their terminals.

[0568] Step 4:

[0569] The server automatically updates the attendance record with the received attendance information.

[0570] Step 5:

[0571] The teacher sends the contents of the educational materials to the server.

[0572] Step 6:

[0573] The generation AI applies formatting and checks the content of the educational materials sent.

[0574] Step 7:

[0575] The server returns the generated educational materials to the instructor and accepts corrections as necessary.

[0576] 5. Updating Information

[0577] Constantly updated

[0578] Step 1:

[0579] The server periodically collects educational updates and curriculum changes.

[0580] Step 2:

[0581] The generative AI analyzes new information and makes necessary updates.

[0582] Step 3:

[0583] The server updates the database and notifies education professionals.

[0584] Step 4:

[0585] Educational professionals can check the latest information on their devices and update learning and curriculum as needed.

[0586] Example 2

[0587] 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."

[0588] In today's educational environment, quickly and accurately finding educational professionals with the specialized skills required by educational institutions is a difficult challenge. In addition to simple skill matching, matching based on the personality and emotions of educational professionals is also required, but this is difficult to achieve with conventional systems. Furthermore, to improve the quality of education, it is important for educational professionals to have continuous access to the latest educational materials, but this process can also be cumbersome. A system that can efficiently solve these problems is needed.

[0589] 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.

[0590] In this invention, the server includes a means for registering the skill information and qualification information of educational experts, a means for inputting needs information from educational institutions, a generating artificial intelligence means for analyzing the needs information of educational experts and educational institutions to generate optimal matches, a means for notifying educational institutions and educational experts of the matching results, a means for collecting and analyzing emotional data to improve matching accuracy, a means for proposing interview dates and storing the selection results in a database, and a means for generating evaluation results for educational experts. This enables educational institutions to quickly and accurately find educational experts with the specialized skills and characteristics they require, enabling optimal matching with educational experts. Furthermore, since educational experts can easily access the latest educational materials, the quality of education can be expected to improve.

[0591] "Educational institution" refers to a school, university, college, or other organization that provides education or training to students.

[0592] "Educational professional" refers to an individual, such as a teacher, lecturer, or trainer, who has specialized knowledge and skills in a particular academic or technical field and is in a position to teach.

[0593] "Share Platform" refers to an information sharing and management tool that matches educational institutions and educational experts online.

[0594] "Generative AI" refers to AI technology that has the ability to analyze and judge input data and generate new information.

[0595] "Skills information" refers to data about the specific job functions and skills possessed by educational professionals.

[0596] "Credentials" refers to data about the certifications and licenses held by education professionals.

[0597] "Needs Information" refers to the requirements and requirements for education professionals, such as the specific skills and years of experience required by an educational institution.

[0598] "Emotional data" refers to emotional information based on the facial expressions and tone of voice of educational professionals collected through video interviews and audio analysis.

[0599] "Interview Schedule" refers to the plan and date and time for an interview with an educational professional at a specific date and time.

[0600] A "database" refers to a recording medium or platform for systematically storing and managing information.

[0601] "Evaluation results" refers to evaluation information regarding the skills and aptitude of educational professionals generated through analysis by generative artificial intelligence.

[0602] "Educational Materials" refers to learning materials and instructional content for use by educational institutions and educational professionals.

[0603] "Administrative tasks" refers to tasks such as information entry, attendance management, and preparation of educational materials that educational institutions and educational professionals perform on a daily basis.

[0604] The present invention is a sharing platform for effectively matching educational institutions with educational experts. This platform improves matching accuracy by using an emotion engine that collects and analyzes emotion data and generative AI. Specific embodiments of the platform are described below.

[0605] Registration and initial evaluation of educational professionals

[0606] User (educational professional) registration

[0607] Users (education professionals) access the sharing platform using their devices, then enter basic information (such as name, contact details, qualifications, skills, etc.) and upload resumes and certificate files. The server then stores this information in a database.

[0608] AI-based initial assessment

[0609] The server retrieves the newly saved information from the database and asks the generated AI to analyze it using the following prompt:

[0610] markdown

[0611] Please use the following information from educational experts to make your initial assessment.

[0612] Name: John Doe

[0613] Qualifications: Elementary school teacher's license, junior high school teacher's license (mathematics)

[0614] Skills: Programming (Python, JavaScript)

[0615] Years of experience: 10 years

[0616] Resume: [Resume file link]

[0617] When making your initial assessment, consider the type of qualifications, skill details, and years of experience.

[0618] The generation AI analyzes these data and generates an initial evaluation result, which the server stores in a database.

[0619] Interview and detailed evaluation

[0620] Arranging interview schedules

[0621] The server sends an email to the educational specialist proposing an interview date. The user (education specialist) selects a convenient date and time and responds from their terminal. The server confirms the selected interview date and time and saves it in the database. The server then notifies the interviewer of the interview schedule.

[0622] Interview and detailed evaluation

[0623] The interviewer will use a video interview tool to conduct an interview with the educational expert at the designated date and time. During the interview, the emotion engine will analyze the facial expressions and voice of the educational expert to collect emotional data in real time. The interviewer will then enter their evaluation of the interview content and the educational expert's skills and personality into the system. The emotion engine will analyze the collected emotional data and reflect it in the evaluation results. The server will store the entered evaluation and emotional data in a database, and the generation AI will generate the final evaluation.

[0624] Inputting and matching needs

[0625] Inputting school needs

[0626] The administrator of the educational institution logs in to the sharing platform using a terminal and inputs the requirements for the educational specialists they need. The server stores the input needs data in a database.

[0627] AI-based matching

[0628] The server searches for educational expert information in the database, and the generation AI matches the educational institution's needs with the educational expert's skill profile. The generation AI generates a list of optimal educational experts, and the server notifies the list to the educational institution's administrator.

[0629] Final selection and placement

[0630] The administrator of the educational institution selects suitable educational experts from the candidate list and, if necessary, selects the most suitable educational expert based on the emotional data. The server notifies the educational experts of the selection result and updates the database.

[0631] Support and Management

[0632] Provision of supplementary teaching materials

[0633] The server periodically checks the skill profiles of educational experts, and the generative AI selects the most suitable learning materials. The server then notifies the educational experts of the selected learning materials by email and provides them with a download link. The educational experts then download the learning materials using their devices and begin studying.

[0634] Automating administrative tasks

[0635] The server automates administrative tasks for educational professionals and institutions, including entering and updating teacher information, managing attendance, and creating educational materials. The server streamlines these tasks using generative AI and updates the database accordingly.

[0636] Information Update

[0637] The server regularly collects the latest educational information and changes in the curriculum, and the generative AI makes any necessary updates. The server then updates the database with this information and notifies educational experts. Educational experts can then check the new information on their devices and update their learning and curriculum as needed.

[0638] In this way, we provide a system that effectively matches educational institutions with educational experts. Furthermore, the combination of an emotion engine and generative AI improves matching accuracy and service quality.

[0639] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0640] Step 1: Register your education professional

[0641] input:

[0642] Basic information (name, contact details, qualifications, skills, etc.) entered by the user (educational specialist) on the device

[0643] Resume and certificate files to be uploaded

[0644] Specific behavior:

[0645] 1. The user (educational professional) accesses the sharing platform using a device.

[0646] 2. The user enters basic information into a web form.

[0647] 3. The user clicks the "Upload Resume" button and selects and uploads a resume file from the local file system.

[0648] Data processing:

[0649] The server receives the entered information and uploaded files and stores them as new records in the database.

[0650] output:

[0651] Educational professionals' basic information and resume files stored in the database

[0652] Step 2: Initial assessment by AI

[0653] input:

[0654] Basic information and resume files of educational professionals stored in a database

[0655] Specific behavior:

[0656] 1. The server retrieves the newly saved information and files from the database.

[0657] 2. The server sends the following prompt to the generating AI:

[0658] markdown

[0659] Please use the following information from educational experts to make your initial assessment.

[0660] Name: John Doe

[0661] Qualifications: Elementary school teacher's license, junior high school teacher's license (mathematics)

[0662] Skills: Programming (Python, JavaScript)

[0663] Years of experience: 10 years

[0664] Resume: [Resume file link]

[0665] When making your initial assessment, consider the type of qualifications, skill details, and years of experience.

[0666] Data processing:

[0667] The generative AI analyzes the information provided and makes an initial assessment of the educational professional's skills and aptitude.

[0668] output:

[0669] The generated initial evaluation results are saved in the database.

[0670] Step 3: Schedule an interview

[0671] input:

[0672] Basic information and initial evaluation results of educational experts stored in a database

[0673] Specific behavior:

[0674] 1. The server sends an email to the education professional proposing an interview date.

[0675] 2. The user (educational professional) clicks on the link in the email and selects a convenient date and time.

[0676] 3. The server confirms the selected date and time, saves it in the database, and notifies the interviewer of the interview schedule.

[0677] Data processing:

[0678] The server stores the selected date and time in a database and generates and sends a notification email.

[0679] output:

[0680] Interview schedule confirmed between educational experts and interviewers

[0681] Step 4: Interview and detailed assessment

[0682] input:

[0683] Scheduled interview date and time and basic information about the education professional

[0684] Specific behavior:

[0685] 1. The interviewer will conduct a video interview with the education professional using a video interviewing tool at the appointed date and time.

[0686] 2. During the interview, the emotion engine analyzes the educational expert's facial expressions and voice to collect emotional data in real time.

[0687] 3. The interviewer will enter their evaluation of the interview content and the educational professional's skills and personality.

[0688] Data processing:

[0689] The emotion engine analyzes the collected emotional data and reflects it in the evaluation results.

[0690] output:

[0691] The server stores the detailed evaluation and emotion data in a database, and the generation AI generates the final evaluation.

[0692] Step 5: Enter your school's needs

[0693] input:

[0694] Specific educational professional requirements entered by the educational institution administrator (e.g., specific skills or years of experience)

[0695] Specific behavior:

[0696] 1. The educational institution administrator logs in to the share platform using a device.

[0697] 2. The administrator enters the requirements for the educational specialists required in the "Needs Input" form.

[0698] Data processing:

[0699] The server stores the input needs information in a database.

[0700] output:

[0701] School needs data stored in a database

[0702] Step 6: AI matching

[0703] input:

[0704] Database of educational professional information and school needs data

[0705] Specific behavior:

[0706] 1. The server retrieves the educational professional's information from the database.

[0707] 2. The server uses the generative AI to match the needs of educational institutions with the skill profiles of educational professionals.

[0708] 3. Generative AI generates a list of the most suitable educational experts.

[0709] 4. The server notifies the institution's administrator of the list.

[0710] Data processing:

[0711] Generative AI uses a matching algorithm to select the most suitable educational expert.

[0712] output:

[0713] A list of the best education professionals to be notified to the educational institution's administrators

[0714] Step 7: Final selection and placement

[0715] input:

[0716] Notified Educational Specialist Candidate List

[0717] Specific behavior:

[0718] 1. The educational institution administrator selects the most suitable educational professional from the list of candidates.

[0719] 2. If necessary, select the most suitable educational expert based on the emotional data.

[0720] 3. The server notifies the educational specialist of the selection results and updates the assignment information in the database.

[0721] Data processing:

[0722] The server stores the selection results in a database and generates a notification email to send to the education specialist.

[0723] output:

[0724] Educational professionals are notified of placement decisions and the information is updated in the database.

[0725] Step 8: Providing supplementary materials

[0726] input:

[0727] Skill profiles of educational professionals stored in a database

[0728] Specific behavior:

[0729] 1. The server periodically checks the skill profile of the education professional.

[0730] 2. Generative AI collects the latest information from a database of online teaching materials and selects the materials that best suit the skills of educational professionals.

[0731] 3. The server will email the educational specialist a list of selected learning materials and provide a download link.

[0732] 4. The user (educational expert) downloads the learning materials from the download link and begins studying.

[0733] Data processing:

[0734] Generative AI selects the most appropriate educational materials to fill skill gaps and generates email notifications.

[0735] output:

[0736] A list of educational materials and download links provided by educational experts

[0737] Step 9: Automate administrative tasks

[0738] input:

[0739] Changes to faculty information, new attendance information, and draft educational materials

[0740] Specific behavior:

[0741] 1. The teacher logs in to the platform from their device and enters new information.

[0742] 2. The server verifies the entered information and updates the database.

[0743] 3. When a teacher uploads a draft of educational material, the server asks the generation AI to check the content and apply formatting.

[0744] 4. The generating AI checks and formats the materials, and the server returns the generated materials to the instructor.

[0745] Data processing:

[0746] The server immediately reflects the input information in the database, and the generating AI processes the educational materials.

[0747] output:

[0748] Updated faculty information, attendance data, and automatically generated teaching materials

[0749] Step 10: Update your information

[0750] input:

[0751] Educational updates and curriculum changes

[0752] Specific behavior:

[0753] 1. The server periodically collects educational updates and curriculum changes from online resources.

[0754] 2. The generation AI analyzes the collected information and generates the necessary updates.

[0755] 3. The server updates the database and notifies the education specialist.

[0756] 4. Educational professionals will be notified, review new information, and make learning and curriculum updates as needed.

[0757] Data processing:

[0758] The server and generating AI analyze new information and update the database accordingly.

[0759] output:

[0760] Updated latest education information and update notifications

[0761] (Application example 2)

[0762] 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."

[0763] Conventional systems for matching educational institutions with educational experts only matched experts based on their skills and qualifications, and were unable to consider users' emotions or aptitudes. As a result, the system was not well suited to actual educational settings, making it difficult to achieve a highly satisfying match. Furthermore, it was unable to generate appropriate advertisements or effectively promote to the target audience.

[0764] 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.

[0765] In this invention, the server includes a means for registering skill information and qualification information of educational experts, a means for inputting needs information from educational institutions, a means for analyzing user emotion data using an emotion engine, a means for generating advertisements based on the analysis results and notifying educational institutions and educational experts, and a means for the generating artificial intelligence to analyze the needs information of educational experts and educational institutions and generate optimal matches. This enables highly accurate matching that takes user emotion data into consideration, and enables the generation of effective targeted advertisements.

[0766] "Educational institution" is a general term for any organization that provides or manages educational activities.

[0767] An "educational expert" is an individual or organization with specialized knowledge and skills in a particular educational field.

[0768] A "share platform" is an online system that allows multiple users to share information and access each other's information.

[0769] "Skill information" is data about specific skills and knowledge that a user possesses.

[0770] "Credentials" means data relating to officially recognized abilities or qualifications held by a User.

[0771] "Needs information" is data that indicates the skills and qualifications of education professionals required by an educational institution.

[0772] "Emotion engine" is a general term for a software or hardware system that recognizes and analyzes a user's emotional state.

[0773] "Generative AI" is an AI system that has the ability to learn from large amounts of data and generate new information and analytical results.

[0774] "Matching" is the process of matching the needs of educational institutions with the skills and qualifications of educational professionals to find the best match.

[0775] "Ad generation" is the process of automatically creating advertising content for targeted users.

[0776] A "database" is a system for managing and storing large amounts of data, and has the ability to efficiently search for specific information.

[0777] The following system configuration is shown as an embodiment of the present invention.

[0778] System program generation

[0779] This system is a shared platform for effectively matching educational institutions with educational experts, and consists of the following elements:

[0780] A means of registering the skills and qualifications of education professionals.

[0781] A means of inputting needs information from educational institutions.

[0782] A means of analyzing user emotional data using an emotion engine.

[0783] A means of generating advertisements based on the analysis results and informing educational institutions and education professionals.

[0784] A means by which generative artificial intelligence analyzes the needs information of educational experts and educational institutions and generates optimal matches.

[0785] A server means to suggest interview dates and store the selection results in a database.

[0786] A means for human and generative artificial intelligence to evaluate the skills and credentials of educational professionals.

[0787] A means by which the emotion engine collects and analyzes the emotion data of educational professionals in real time.

[0788] A means of informing education professionals of selected educational materials and providing download links.

[0789] A server means to automate administrative tasks and update education-related information into a database.

[0790] A means of storing generated advertisements in a database and automating updates to advertisement content.

[0791] Hardware and software used

[0792] The following hardware and software are used in this system:

[0793] Server: A computer device that connects to a database and manages and processes data.

[0794] Terminal: A computer or smart device used by education professionals and institutions to access the system.

[0795] Emotion engine: Software for analyzing user emotion data.

[0796] Generative AI model: An artificial intelligence system that analyzes data from education experts and educational institutions to generate optimal matches and advertisements.

[0797] Database: A system for storing large amounts of data and efficiently retrieving needed information.

[0798] Data processing and calculation process

[0799] 1. Registration of Educational Professionals

[0800] Education professionals use terminals to access the system, enter their skills and qualifications, and upload their resumes, and the server stores this information in a database.

[0801] 2. Input your needs

[0802] The administrator of the educational institution logs in to the system using a terminal and inputs the requirements for the educational specialists required (e.g., specific skills, years of experience, etc.). The server stores the input needs data in a database.

[0803] 3. Emotion Data Analysis

[0804] The emotion engine analyzes the facial expressions and voice of education experts to generate real-time emotional data, which is then stored in a database for later use in the matching and ad generation process.

[0805] 4. Matching and Ad Generation

[0806] The server uses a generative artificial intelligence model to match the needs of educational institutions with the skill information of educational experts to generate the most suitable candidate list, and at the same time, it generates the most suitable advertising content taking into account the sentiment data and notifies the educational institutions and educational experts.

[0807] 5. Ad Updates and Delivery

[0808] The generated advertisements are stored in a database and updated as necessary, enabling effective promotions to be delivered to target users.

[0809] As a concrete example, the following prompt sentence is presented.

[0810] Prompt Sentence Examples

[0811] Educational institutions need: Professionals with experience in English language teaching

[0812] Sentiment data: Mostly positive feedback

[0813] Advertisement content: An educational institution specializing in English education in Tokyo is looking for new teachers. We are looking for professionals with extensive experience in English education.

[0814] In this way, by implementing the invention, the accuracy of matching educational institutions with educational experts is improved, and effective targeted advertisements are generated and delivered.

[0815] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0816] Step 1:

[0817] Register of Educational Professionals

[0818] Input: Education professionals use terminals to access the system, enter skill information, qualification information, and upload resumes.

[0819] Specific operations: Register information through an input form on the device and upload files to the server.

[0820] Data processing / calculation: The server receives this information, checks the format for consistency, and then stores it in the database.

[0821] Output: Educational expert information stored in a database.

[0822] Step 2:

[0823] Input your needs

[0824] Input: The administrator of the educational institution logs into the system using a terminal and inputs the required educational professional requirements.

[0825] Specific operation: Enter specific skills, years of experience, etc. into the input form on the terminal and send it to the server.

[0826] Data processing / calculation: The server stores the received needs information in a database and organizes it for use in future matching processes.

[0827] Output: Institutional needs information stored in a database.

[0828] Step 3:

[0829] Emotional Data Analysis

[0830] Input: Facial expression and speech data of educational experts.

[0831] Specific operation: The device sends facial expression and voice data collected during the interview and registration to the emotion engine.

[0832] Data processing / calculation: The emotion engine analyzes the data, quantifies the emotional state (positive or negative), and sends it to the server.

[0833] Output: Sentiment analysis results stored on the server.

[0834] Step 4:

[0835] Matching and Ad Generation

[0836] Input: educational institution needs information and education professionals' skill information and sentiment data.

[0837] Specific operation: The server calls the generation AI, compares the needs information with the skill information and emotion data, lists the most suitable education experts, and determines the content of the generated advertisement.

[0838] Data processing / calculation: Generative AI analyzes large amounts of data and generates optimal matching results and advertisements.

[0839] Output: Best match results and advertisements notified to educational institutions and education professionals.

[0840] Step 5:

[0841] Ad updates and delivery

[0842] Input: Generated ad content.

[0843] Specific operation: The server saves the generated advertisement in a database, updates the content as necessary, and delivers the advertisement to the target user.

[0844] Data processing / calculation: Refer to the database, monitor the effectiveness of the advertisement, and generate and deliver new advertisements if necessary.

[0845] Output: Updated advertisements delivered to educational institutions and education professionals.

[0846] This series of steps enables highly accurate matching that takes into account user emotional data, as well as the creation and delivery of effective targeted advertisements.

[0847] 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.

[0848] 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.

[0849] 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.

[0850] [Second embodiment]

[0851] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0852] 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.

[0853] 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).

[0854] 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.

[0855] 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.

[0856] 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).

[0857] 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.

[0858] 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.

[0859] 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.

[0860] 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.

[0861] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0862] 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."

[0863] The present invention is a "share platform" for effectively matching educational institutions with educational experts. Specific embodiments of the present invention will be described below.

[0864] 1. Registration and Initial Evaluation of Educational Professionals

[0865] User (educational professional) registration

[0866] Education professionals access the sharing platform using their devices, enter basic information (such as name, contact details, qualifications, and skills), and upload files such as resumes and certificates.

[0867] The server stores the information entered by the education specialist and the uploaded files in a database.

[0868] AI-based initial assessment

[0869] The server accesses the newly stored information and files.

[0870] The server calls the generation AI and has it analyze information about the qualifications and skills of educational professionals.

[0871] The generation AI performs an initial evaluation based on the analysis results and generates an evaluation result.

[0872] The server stores the initial evaluation results in a database.

[0873] 2. Interview and detailed evaluation

[0874] Arranging interview schedules

[0875] The server will send an email to the education professional suggesting an interview date.

[0876] The educational expert can choose a convenient date from the provided dates and times and respond from their device.

[0877] The server stores the selected interview dates in a database and notifies the interviewer of the interview schedule.

[0878] Interview and detailed evaluation

[0879] The interviewer will conduct the video interview at the appointed date and time.

[0880] Interviewers enter their evaluations into the system based on the interview content, the educational professional's skills, and their personality.

[0881] The server stores the entered ratings in a database and again uses the generation AI to generate the final rating.

[0882] 3. Inputting needs and matching

[0883] Inputting school needs

[0884] The educational institution administrator logs into the platform from a terminal and enters the requirements for the required educational specialist.

[0885] The server stores the school's needs data in a database.

[0886] AI-based matching

[0887] The server searches a database of registered education professionals.

[0888] The generative AI matches the input school needs with the skills of educational experts and generates a list of the most suitable educational experts.

[0889] The server notifies the educational institution administrator of the generated list.

[0890] Final selection and placement

[0891] The educational institution's administrator will select suitable educational professionals from the notified list of candidates and schedule additional interviews if necessary.

[0892] The server sends a notification of the placement decision to the selected education professional.

[0893] The server stores the final decision in a database and updates the educational professional's placement information.

[0894] 4. Support and Management

[0895] Provision of supplementary teaching materials

[0896] The server periodically checks the skill profiles of the education professionals.

[0897] Generative AI collects the latest educational material information and selects the most suitable materials to fill the skill gaps of educational professionals.

[0898] The server will email the educational specialist a list of selected learning materials and provide a download link.

[0899] Educational professionals use the devices to download learning materials and conduct their studies.

[0900] Automating administrative tasks

[0901] Entering and updating faculty information:

[0902] Teachers enter new information (e.g., contact information changes) on their terminals.

[0903] The server immediately updates the database.

[0904] Attendance Management:

[0905] Faculty and staff enter their daily attendance information on their terminals.

[0906] The server receives this and automatically updates the attendance record.

[0907] Creating educational materials:

[0908] When a teacher sends the contents of educational materials to the server, the generating AI automatically applies the format and checks the content.

[0909] The server returns the generated educational materials to the instructor and accepts corrections as necessary.

[0910] 5. Updating Information

[0911] Constantly updated

[0912] The server periodically collects educational updates and curriculum changes.

[0913] The generative AI analyzes this new information and makes any necessary updates.

[0914] The server updates the database and notifies education professionals.

[0915] Educational professionals can check the latest information on their devices and update learning and curriculum as needed.

[0916] Specific examples

[0917] As a concrete example, here is the process that a public school in Tokyo goes through when it is looking for an educational expert with programming knowledge.

[0918] 1. Registration and evaluation of educational professionals

[0919] An educational expert A who is knowledgeable in programming registers in the system, enters his / her skills and qualifications, and uploads his / her resume.

[0920] The server receives this, and the generation AI analyzes it to complete the initial evaluation.

[0921] 2. Interview

[0922] The server proposes an interview date to Educational Specialist A. Educational Specialist A selects a convenient date and time, and the server confirms the interview date.

[0923] The interviewer conducts the video interview and inputs the evaluation into the server.

[0924] 3. Matching

[0925] The school's administrator logs into the system and enters the needs of programming educators.

[0926] The server's generation AI will compare the skill information of Educational Expert A and add him to the list as the most suitable candidate.

[0927] 4. Selection and Assignment

[0928] The school administrator selects educational expert A, the server notifies educational expert A, and then the assignment is decided.

[0929] This series of processes provides a system that can quickly and efficiently connect educational professionals sought by schools with educational institutions that suit the professionals' qualifications.

[0930] The processing flow will be explained below.

[0931] 1. Registration and Initial Evaluation of Educational Professionals

[0932] User (educational professional) registration

[0933] Step 1:

[0934] The user accesses the sharing platform website using a device and proceeds to the login or new registration screen.

[0935] Step 2:

[0936] Users enter basic information such as name, contact details, email address, qualifications, and skills, and upload resume and certificate files.

[0937] Step 3:

[0938] Once the user has entered all the information, they click the "Submit" button.

[0939] Step 4:

[0940] The server receives the information entered by the user and the uploaded files and stores them in a database.

[0941] AI-based initial assessment

[0942] Step 1:

[0943] The server accesses the newly stored information and files.

[0944] Step 2:

[0945] The server calls the generation AI and has it analyze information about the qualifications and skills of educational professionals.

[0946] Step 3:

[0947] The generation AI performs an initial evaluation based on the analysis results and generates an evaluation result.

[0948] Step 4:

[0949] The server stores the generated initial evaluation results in a database.

[0950] 2. Interview and detailed evaluation

[0951] Arranging interview schedules

[0952] Step 1:

[0953] The server sends an email to the education professional containing a suggested interview date.

[0954] Step 2:

[0955] The user (educational specialist) receives the email and responds to the system from a terminal to select a convenient date from the presented dates and times.

[0956] Step 3:

[0957] The server confirms the interview date and time selected by the user and stores it in a database.

[0958] Step 4:

[0959] The server notifies the interviewer of the selected interview schedule.

[0960] Interview and detailed evaluation

[0961] Step 1:

[0962] The interviewer will conduct a video interview with the education professional using a video interviewing tool at the appointed date and time.

[0963] Step 2:

[0964] Interviewers enter their evaluations into the system based on the interview content and the educational professional's skills and personality.

[0965] Step 3:

[0966] The server stores the evaluations entered by the interviewers in a database.

[0967] Step 4:

[0968] The server then uses the generation AI again based on the saved detailed evaluation information to generate the final evaluation.

[0969] 3. Inputting needs and matching

[0970] Inputting school needs

[0971] Step 1:

[0972] The educational institution administrator logs in to the share platform using a device.

[0973] Step 2:

[0974] Administrators input the required educational professional requirements (e.g., specific skills, years of experience, etc.).

[0975] Step 3:

[0976] The server stores the school needs data entered by the administrator in a database.

[0977] AI-based matching

[0978] Step 1:

[0979] The server searches a database of registered education professionals.

[0980] Step 2:

[0981] The generative AI matches the input needs of schools with the skill profiles of educational professionals.

[0982] Step 3:

[0983] Generative AI generates a list of the best educational experts.

[0984] Step 4:

[0985] The server notifies the educational institution administrator of the generated list.

[0986] Final selection and placement

[0987] Step 1:

[0988] The educational institution's administrator will select a suitable educational professional from the notified list of candidates.

[0989] Step 2:

[0990] Administrators will schedule additional interviews through the system if necessary.

[0991] Step 3:

[0992] The server confirms the administrator's selection result and sends a notification of the placement decision to the selected educational expert.

[0993] Step 4:

[0994] The server stores the final decision in a database and updates the educational professional's placement information.

[0995] 4. Support and Management

[0996] Provision of supplementary teaching materials

[0997] Step 1:

[0998] The server periodically checks the skill profile of the education professional.

[0999] Step 2:

[1000] Generative AI collects the latest educational material information and selects the most suitable materials to fill the skill gaps of educational professionals.

[1001] Step 3:

[1002] The server will email the educational specialist a list of selected learning materials and provide a download link.

[1003] Step 4:

[1004] Educational professionals use the devices to download learning materials and conduct their studies.

[1005] Automating administrative tasks

[1006] Step 1:

[1007] The user (teacher) uses the terminal to enter new information (e.g., contact information change).

[1008] Step 2:

[1009] The server immediately stores and updates the database with the new information it receives.

[1010] Step 3:

[1011] Faculty and staff enter their daily attendance information into the system from their terminals.

[1012] Step 4:

[1013] The server automatically updates the attendance record with the received attendance information.

[1014] Step 5:

[1015] The teacher sends the contents of the educational materials to the server.

[1016] Step 6:

[1017] The generation AI applies formatting and checks the content of the educational materials sent.

[1018] Step 7:

[1019] The server returns the generated educational materials to the instructor and accepts corrections as necessary.

[1020] 5. Updating Information

[1021] Constantly updated

[1022] Step 1:

[1023] The server periodically collects educational updates and curriculum changes.

[1024] Step 2:

[1025] The generative AI analyzes new information and makes necessary updates.

[1026] Step 3:

[1027] The server updates the database and notifies education professionals.

[1028] Step 4:

[1029] Educational professionals can check the latest information on their devices and update learning and curriculum as needed.

[1030] Example 1

[1031] 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."

[1032] In today's educational environment, it is difficult for educational institutions to quickly and efficiently find educational professionals with the specialized knowledge and skills they require. As a result, it takes time for educational institutions to hire suitable educational professionals, making it difficult to maintain the quality of education. Furthermore, educational professionals lack the means to have their skills and qualifications properly evaluated, making it difficult to find suitable positions. Furthermore, the time and effort required to obtain the latest educational materials and information is a significant burden. There is a need to build an efficient matching system to solve these issues.

[1033] 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.

[1034] In this invention, the server includes a means for recording the experience and qualification information of educational experts, a means for inputting requirement information from educational institutions, and a generating AI means for analyzing the requirement information of educational experts and educational institutions to generate optimal matches. This enables educational institutions to quickly and efficiently find educational experts with the expertise and skills they require. The server also includes a means for periodically checking the skill profiles of educational experts and selecting appropriate learning materials using a generating AI model, and a means for notifying educational experts of the selected learning materials and providing download links. This allows educational experts to keep their skills up to date at all times.

[1035] "Educational institutions" refers to facilities and organizations that carry out educational activities, including elementary schools, junior high schools, high schools, universities, and other educational institutions.

[1036] "Educational professionals" refers to professionals who have the qualifications and experience to provide instruction and education in educational institutions, including teachers, lecturers, and special education coordinators.

[1037] A "share platform" refers to an online system that connects multiple educational institutions and educational experts.

[1038] "Experience" refers to the practical experience and skills acquired by an educational professional, including teaching experience in a particular subject or program.

[1039] "Credentials" refers to any official qualifications or certifications held by an education professional, including teaching licenses and professional certifications.

[1040] "Requirements Information" refers to the specific skills, qualifications, and experience requirements of educational professionals sought by an educational institution.

[1041] "Analysis" refers to the process of analyzing input information, understanding its content, and making an evaluation.

[1042] "Generative AI means" refers to artificial intelligence technology that analyzes and evaluates input information to generate optimal candidates and teaching materials.

[1043] "Notification" refers to the act of communicating important information from the system to educational professionals and institutions, primarily via email or in-system notifications.

[1044] A "skills profile" refers to information that records an overview of the skills and experience of an educational professional.

[1045] "Instructional Materials" refers to educational materials and reference documents used by educational professionals to improve their skills.

[1046] "Download link" refers to the URL that educational professionals can use to obtain educational materials via the Internet.

[1047] "Administrative tasks" refers to the day-to-day administrative tasks of education professionals and institutions, such as updating contact details and managing attendance.

[1048] "Storage" refers to the act of saving and storing data or information in a database.

[1049] The present invention provides a sharing platform for effectively matching educational institutions with educational experts. This system has the function of registering the skills and qualifications of educational experts, automating the process of matching them with the requirements of educational institutions, and providing the educational experts with the most suitable educational materials.

[1050] Hardware and software used

[1051] Server: The computer that performs the main processing of this system, managing the database and running the AI ​​model.

[1052] Device: A computer, tablet, smartphone, or other device used by education professionals and administrators to enter information and receive notifications.

[1053] Generative AI model: An artificial intelligence technology that performs information analysis and evaluation, evaluating the skills of educational experts, generating matching lists, and selecting optimal teaching materials.

[1054] Program processing overview

[1055] 1. Registration and Initial Evaluation of Educational Professionals

[1056] User (educational professional): Uses a terminal to access the sharing platform, enters basic information such as name, contact details, qualifications, skills, etc., and uploads resumes and certificates. After completing the entry, the server stores this information in a database and sends a confirmation email to the user.

[1057] Server: Inputs the saved information and files into the generative AI model, analyzes the qualifications and skills of the educational expert, and performs an initial evaluation. The results are saved in a database, and an email is sent to the educational expert to notify them of the completion of the initial evaluation.

[1058] Example of how it works: An educational expert inputs skills such as "Python" or "Java," and the server requests the generated AI model to analyze them and saves the results.

[1059] Example prompt sentence:

[1060] "Make an initial assessment based on the skills information this education professional has."

[1061] 2. Interview and detailed evaluation

[1062] User (educational specialist): Checks the interview dates and times suggested by the server on the terminal and selects a suitable date and time. The server saves the selected date and time in the database and notifies the interviewer.

[1063] Server: The interviewer conducts the video interview at the specified date and time, and saves the results and evaluation in the database. The generative AI model is used again to perform the final evaluation, and the results are saved.

[1064] Example of specific operation: The interviewer conducts the interview using a video conferencing tool, inputs the evaluation details, and analyzes them using the generative AI model.

[1065] Example prompt sentence:

[1066] "Generate a final grade based on the interview evaluation results."

[1067] 3. Input and matching of school needs

[1068] User (educational institution administrator): Logs in to the sharing platform from a terminal and enters the necessary information on educational professionals. The server stores this information in a database.

[1069] Server: Retrieves information about educational professionals from the database, compares it with the school's requirements using a generative AI model, and generates a list of the best candidates. The list is then sent to the educational institution's administrator.

[1070] Example of specific operation: An educational institution inputs conditions such as "5 or more years of programming experience," and the server generates a list of candidates using a generative AI model and notifies them.

[1071] Example prompt sentence:

[1072] "Generate a list of educational professionals who best fit the needs of this school."

[1073] 4. Final selection and assignment

[1074] User (educational institution administrator): Selects appropriate educational specialists from the notified candidate list and schedules additional interviews if necessary. The server stores the selection results in a database and notifies the educational specialists of the placement decision.

[1075] Example of specific operation: Select from the candidate list and press the "Decide" button. A notification is automatically sent to the educational expert and the database is updated.

[1076] Example prompt sentence:

[1077] "Please send notification of placement decision to the selected educational professional."

[1078] 5. Support and Management

[1079] Server: Regularly checks the skill profiles of education experts and selects the most suitable learning materials using a generative AI model. It notifies education experts of the list of selected learning materials and provides download links. It also automates administrative tasks and updates the database.

[1080] User (educational specialist): Uses the download link from the device to obtain the learning materials and proceed with the study.

[1081] Example of specific operation: The server queries the skill data of the educational expert, and the generative AI selects and notifies the optimal teaching materials. The educational expert downloads the materials from the link.

[1082] Example prompt sentence:

[1083] "Select the most appropriate educational materials for this educational professional."

[1084] The server-based system automates a series of processes to quickly and efficiently match educational institutions with educational experts. Utilizing generative AI models, it seamlessly performs everything from skill assessment to matching, selection, and assignment, as well as providing teaching materials and updating information.

[1085] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1086] Step 1:

[1087] Register of Educational Professionals

[1088] Input: The user (education professional) uses a device to access the share platform, enters basic information such as name, contact details, qualifications, and skills, and uploads files of resumes and certificates.

[1089] Data processing and calculation: The server receives the input information and files, performs an initial data format check, and verifies the accuracy and completeness of the information.

[1090] Output: The server stores the received data in a database and sends the user a confirmation email.

[1091] Specific action: A user enters information into a system form and clicks the "Submit" button.

[1092] Step 2:

[1093] Initial evaluation by educational professionals

[1094] Input: Saved education professional information and uploaded files.

[1095] Data processing and calculation: The server retrieves new registration information from the database and inputs it into the generative AI model. The generative AI model analyzes skills and qualifications and generates evaluation results.

[1096] Output: The generated evaluation results are returned to the server and stored in the database. The server then sends the user an email to complete the initial evaluation.

[1097] Specific operation: The server inputs the data into the AI ​​analysis and stores the evaluation results in a database.

[1098] Step 3:

[1099] Arranging interview schedules

[1100] Input: Multiple interview dates and times suggested by the server.

[1101] Data processing and calculation: The educational expert selects a convenient date and time and sends it back to the server. The server saves the selected date and time in the database and notifies the interviewer.

[1102] Output: The selected interview date and time are saved in the database and the interviewer is notified of the schedule.

[1103] Specific behavior: The user selects a convenient date and time from the calendar form and submits it.

[1104] Step 4:

[1105] Interview and detailed evaluation

[1106] Input: Interview content and evaluation from the interviewer's video conferencing tool.

[1107] Data processing and calculation: Interviewers input their evaluations into the system, and the server stores them in a database. The generative AI model is then used again to make the final evaluation.

[1108] Output: The interview evaluation results and final evaluation are saved in the database.

[1109] Specific action: The interviewer enters information into the evaluation form and clicks the "Submit" button.

[1110] Step 5:

[1111] Inputting school needs

[1112] Input: Institution requirement information (such as required skills and experience).

[1113] Data processing and calculation: The server stores the input requirements information in a database and prepares for matching.

[1114] Output: Requirement information is saved in the database.

[1115] Specific action: The educational institution administrator fills in the required requirements on the form and clicks the "Submit" button.

[1116] Step 6:

[1117] Match Generation

[1118] Input: Education professional information and school requirement information in the database.

[1119] Data processing and calculation: The server retrieves the information in the database, inputs it into the generative AI model for matching, and generates a list of optimal educational experts.

[1120] Output: The generated list is sent to the institution administrator.

[1121] Specific operation: The server inputs the data into AI analysis, generates a result report, and notifies the administrator by email.

[1122] Step 7:

[1123] Final selection and placement

[1124] Input: A list of candidates selected by the institution's administrators.

[1125] Data processing and calculation: The server sends a notification to the selected education specialist and updates the assignment information in the database.

[1126] Output: An assignment notification is sent to the education specialist and the assignment information is saved in the database.

[1127] Specific action: The administrator selects from the candidate list and clicks the "Decide" button.

[1128] Step 8:

[1129] Provision of supplementary teaching materials

[1130] Input: Skills profiles of education professionals and up-to-date educational material information.

[1131] Data processing and calculation: The server passes the skill profile to the generative AI model to generate the optimal teaching material list. The selected teaching material list is notified to the educational expert.

[1132] Output: A list of materials and a download link will be sent to the education specialist.

[1133] Specific operation: The server inputs skill data into AI analysis, generates a list of teaching materials, and notifies the user.

[1134] Step 9:

[1135] Automating administrative tasks

[1136] Input: Faculty new information or daily attendance information.

[1137] Data processing and calculation: The server immediately updates the database with the input information. If necessary, it automatically performs management tasks using a generative AI model.

[1138] Output: The database is updated with the latest information.

[1139] Specific action: Faculty enters new information into the form and clicks the "Submit" button.

[1140] Step 10:

[1141] Information Update

[1142] Input: Latest education-related information and curriculum changes.

[1143] Data processing and calculation: The server periodically collects this new information, analyzes it using the generative AI model, and updates the database accordingly.

[1144] Output: The latest information is updated in the database and the education specialist is notified.

[1145] Specific operation: The server uses APIs and RSS feeds to collect the latest information, performs AI analysis, saves the results in a database, and notifies the user.

[1146] (Application example 1)

[1147] 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."

[1148] The previous system did not efficiently match educational institutions with educational experts, and the registration and evaluation of expert skills and qualifications was cumbersome. There were also issues with scheduling interviews and notifying selection results smoothly, which meant that the alignment between the needs of educational institutions and the skills of experts was not fully ensured. Furthermore, there was insufficient automation of the provision and management of educational materials.

[1149] 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.

[1150] In this invention, the server includes a means for registering skill information and qualification information of educational professionals, a means for inputting needs information from educational institutions, a generating artificial intelligence means for analyzing the needs information of educational professionals and educational institutions and generating optimal matches, a means for notifying educational institutions and educational professionals of the matching results, a means for educational professionals to input and update information via a smart device, and a video call means for supporting interviews, meetings, and the sharing of educational materials. This enables efficient matching between educational professionals and educational institutions, smooth interview arrangements and notifications, and the automation of the provision and management of educational materials.

[1151] An "educational institution" is an organization that provides educational services, such as a school, university, or vocational school.

[1152] An "educational professional" is a professional who has the qualifications and skills to specialize in education.

[1153] The "Share Platform" is an online system for sharing information and matching between educational experts and educational institutions.

[1154] "Skills information" is information about the professional abilities and experience of educational professionals.

[1155] "Credentials" refers to information about the various certifications and credentials held by education professionals.

[1156] "Needs information" refers to information about the skills, qualifications, and assignment conditions of professionals required by educational institutions.

[1157] "Generative AI" is an AI technology that analyzes input data and generates the most suitable matches between educational experts and educational institutions.

[1158] A "smart device" is a multi-function terminal that can connect to the Internet, such as a smartphone, smart glasses, or a head-mounted display.

[1159] "Video communication means" refers to a means for real-time video and audio communication using the Internet.

[1160] A "server" is a computer system that stores and manages various data, and analyzes, notifies, and operates on information.

[1161] "Notification means" refers to email or application messaging functions used to notify relevant parties of various information and results.

[1162] "Educational materials" are any type of learning material used by educational professionals in teaching or training.

[1163] "Administrative work" refers to administrative tasks such as updating education-related information, managing attendance, and creating materials.

[1164] "Automation" means that tasks that were previously performed manually can be performed automatically by machines or software.

[1165] The present invention relates to a sharing platform for efficiently matching educational institutions with educational experts. This system enables educational experts to appropriately match the requirements of educational institutions and quickly find experts with the skills required by the educational institutions. Specific embodiments of the system are described below.

[1166] 1. Registration and Initial Evaluation of Educational Professionals

[1167] User (educational professional) registration

[1168] Educational professionals access the sharing platform using a smart device (smartphone, smart glasses, head-mounted display), enter basic information (name, contact details, qualifications, skills, etc.), and upload resumes and certificate files. The server stores the information entered by the educational professionals and the uploaded files in a database.

[1169] AI-based initial assessment

[1170] The server accesses the newly saved information and files, invokes a generative AI (such as OpenAI's GPT-3) and has it analyze the information about the educational expert's qualifications and skills. The generative AI performs an initial evaluation based on the analysis results and generates an evaluation result. The server stores the initial evaluation result in a database.

[1171] 2. Interview and detailed evaluation

[1172] Arranging interview schedules

[1173] The server sends a notification to the educational specialist suggesting an interview date to the smart device. The educational specialist selects a convenient date from the suggested dates and responds from the device. The server saves the selected interview date in the database and notifies the interviewer of the interview schedule.

[1174] Interview and detailed evaluation

[1175] The interviewer will conduct the interview via video call at the appointed date and time. The interviewer will enter their evaluation of the interview content, the skills of the educational expert, and their personality into the system. The server will store the entered evaluation in a database and use the generative AI again to generate the final evaluation.

[1176] 3. Inputting needs and matching

[1177] Inputting school needs

[1178] The administrator of the educational institution logs in to the platform from a terminal and inputs the requirements for the educational specialists they need. The server stores the school's needs data in a database.

[1179] AI-based matching

[1180] The server searches the database of registered educational experts. The generation AI matches the input school's needs with the skills of the educational experts and generates a list of the most suitable educational experts. The server notifies the educational institution's administrator of the generated list.

[1181] Final selection and placement

[1182] The educational institution administrator selects a suitable educational expert from the notified candidate list and schedules additional interviews if necessary. The server then sends a notification of the placement decision to the selected educational expert. The server then saves the final decision in the database and updates the placement information of the educational expert.

[1183] 4. Provision and management of educational materials

[1184] Provision of supplementary teaching materials

[1185] The server periodically checks the skill profiles of education experts. The generation AI collects the latest educational material information and selects the most suitable materials to fill the education expert's skill gaps. The server notifies the education expert of the list of selected materials and provides a download link. The education expert downloads the materials using their device and begins studying.

[1186] Automating administrative tasks

[1187] Entering and updating faculty information:

[1188] The server instantly updates the database when education professionals enter new information (e.g., contact changes) at their devices.

[1189] Attendance Management:

[1190] Faculty and staff enter their daily attendance information on their terminals, and the server receives this information and automatically updates the attendance records.

[1191] Creating educational materials:

[1192] When a teacher sends the contents of educational materials to the server, the generation AI automatically applies formatting and checks the content, then returns the generated educational materials to the teacher and accepts corrections as necessary.

[1193] Specific examples

[1194] As a concrete example, here is the process that a public school in Tokyo goes through when it is looking for an educational expert with programming knowledge.

[1195] 1. Registration and evaluation of educational professionals

[1196] An educational expert A who is familiar with programming registers with the system, enters skill information and qualifications, and uploads a resume. The server receives this, and the generation AI analyzes it to complete an initial evaluation.

[1197] 2. Interview

[1198] The server proposes an interview date to Educational Expert A. Educational Expert A selects a convenient date and time, and the server confirms the interview date. The interviewer conducts the interview via video call and enters the evaluation into the server.

[1199] 3. Matching

[1200] The school administrator logs into the system and inputs their needs for programming educators. The server's generation AI compares this with the skill information of Educational Expert A and adds him or her to the list as the most suitable candidate.

[1201] 4. Selection and Assignment

[1202] The school administrator selects educational expert A, the server notifies educational expert A, and then the assignment is decided.

[1203] Example prompts to input to the generative AI model

[1204] plain

[1205] "Please rate an educational professional with expertise in programming education. Please make an initial assessment based on the following information: Qualifications: {Qualifications}, Skills: {Skills}"

[1206] The system allows educational institutions to quickly and efficiently connect with the educational professionals they need.

[1207] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1208] Step 1:

[1209] Registration and initial evaluation of educational professionals

[1210] Users (education professionals) access the sharing platform using their smart devices, enter basic information (such as name, contact details, qualifications, and skills), and upload resume and certificate files. This information and files are then sent to the server, which stores the data in a database. The entered data includes the education professional's skills and qualifications.

[1211] Next, the server calls a generative AI model (e.g., OpenAI's GPT-3) to generate a prompt that analyzes the uploaded information. An example of a prompt is, "Please evaluate the educational expert based on the following information: Qualifications: {Qualifications}, Skills: {Skills}." The generative AI performs an initial evaluation based on the analysis results and sends the results back to the server, where they are stored in a database. This stores the educational expert's basic information and initial evaluation results in the database.

[1212] Step 2:

[1213] Arranging interview schedules

[1214] The server sends a notification to the educational expert proposing an interview date. The notification is sent to the smart device, and the educational expert selects a convenient date from the specified dates and times and responds through the device. The server saves the selected interview date in the database and simultaneously notifies the interviewer of the interview schedule. Through this process, the interview date is confirmed for both the educational expert and the interviewer.

[1215] Step 3:

[1216] Interview and detailed evaluation

[1217] The interviewer will conduct the interview via video call at the appointed date and time. For the video call, an appropriate video call tool (e.g., Zoom, Microsoft Teams) will be used. After the interview, the interviewer will enter their evaluation into the system regarding the interview content, the educational expert's skills, and their personality. The server will then store the entered evaluation data in a database. The server will then again use the generative AI to perform a final evaluation. This result will be stored in the database, and the final evaluation result will be confirmed.

[1218] Step 4:

[1219] Inputting and matching needs

[1220] The administrator of the educational institution logs in to the platform using a terminal and enters the requirements for the educational specialists required. This data is sent to the server, which stores it in a database. The server then invokes the generation AI to match the needs of the educational institution with the skill information of registered educational specialists and generate a list of the most suitable educational specialists. This matching involves selecting specialists with the appropriate skills and experience based on the educational institution's conditions and requirements. The generated list is then notified to the administrator of the educational institution.

[1221] Step 5:

[1222] Final selection and placement

[1223] The educational institution administrator selects a suitable educational expert from the notified candidate list and schedules additional interviews if necessary. The server then sends a notification of the placement decision to the selected educational expert. This notification is delivered to the educational expert via their smart device. The server then saves the final decision in the database and updates the placement information of the educational expert. This allows the educational institution and the educational expert to be appropriately linked.

[1224] Step 6:

[1225] Provision and management of educational materials

[1226] The server periodically checks the skill profiles of education experts and uses generative AI to collect the latest educational material information. The AI ​​selects the most suitable educational materials to fill the education expert's skill gaps and notifies the education expert of the list. The notification includes a download link, and the education expert can download the materials using their device and study.

[1227] The server also has the ability to automate administrative tasks, efficiently updating education-related information, managing attendance, creating educational materials, etc. This will greatly simplify the administrative work of educational institutions.

[1228] This allows educational institutions to quickly and efficiently connect with the education professionals they need, and for education professionals to seamlessly receive the information and materials they need.

[1229] 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.

[1230] The present invention is a sharing platform for effectively matching educational institutions with educational professionals. This platform is combined with an emotion engine that recognizes and analyzes user emotions to achieve more accurate matching and improved service. Specific embodiments of the platform are described below.

[1231] 1. Registration and Initial Evaluation of Educational Professionals

[1232] User (educational professional) registration

[1233] Education professionals use their devices to access the sharing platform, enter basic information (such as name, contact details, qualifications, skills, etc.), and upload files of their resumes and certificates.

[1234] The server stores the information entered by the education specialist and the uploaded files in a database.

[1235] AI-based initial assessment

[1236] The server accesses the newly stored information and files.

[1237] The server calls the generation AI and has it analyze information about the qualifications and skills of educational professionals.

[1238] The generation AI performs an initial evaluation based on the analysis results and generates an evaluation result.

[1239] The server stores the generated initial evaluation results in a database.

[1240] 2. Interview and detailed evaluation

[1241] Arranging interview schedules

[1242] The server sends an email to the education professional suggesting an interview date.

[1243] The educational expert can choose a convenient date from the provided dates and times and respond from their device.

[1244] The server verifies the selected interview date and time and stores it in a database.

[1245] The server notifies the interviewer of the selected interview schedule.

[1246] Interview and detailed evaluation

[1247] The interviewer will conduct a video interview with the education professional using a video interviewing tool at the appointed date and time.

[1248] During the interview, the emotion engine analyzes the educational professional's facial expressions and voice to collect emotional data in real time.

[1249] Interviewers enter their evaluations into the system based on the content of the interview and the educational professional's skills and personality.

[1250] The emotion engine analyzes the collected emotional data and reflects it in the evaluation results.

[1251] The server stores the input ratings and analysis results in a database, and the generation AI generates the final rating.

[1252] 3. Inputting needs and matching

[1253] Inputting school needs

[1254] The educational institution administrator logs in to the share platform using a device.

[1255] Administrators input the required educational professional requirements (e.g., specific skills, years of experience, etc.).

[1256] The server stores the school needs data entered by the administrator in a database.

[1257] AI-based matching

[1258] The server searches a database of registered education professionals.

[1259] The generative AI matches the input needs of schools with the skill profiles of educational professionals.

[1260] Generative AI generates a list of the best educational experts.

[1261] The server notifies the educational institution administrator of the generated list.

[1262] Final selection and placement

[1263] The educational institution's administrator will select a suitable educational professional from the notified list of candidates.

[1264] If necessary, educational institution administrators can use the emotion engine to select the most suitable educational expert based on the candidate's emotion data.

[1265] The server verifies the selection results and sends a notification of the placement decision to the education specialist.

[1266] The server stores the final decision in a database and updates the educational professional's placement information.

[1267] 4. Support and Management

[1268] Provision of supplementary teaching materials

[1269] The server periodically checks the skill profiles of the education professionals.

[1270] Generative AI collects the latest educational material information and selects the most suitable materials to fill the skill gaps of educational professionals.

[1271] The server will email the educational specialist a list of selected learning materials and provide a download link.

[1272] Educational professionals use the devices to download learning materials and conduct their studies.

[1273] Automating administrative tasks

[1274] Entering and updating faculty information:

[1275] Teachers enter new information (e.g., contact information changes) on their terminals.

[1276] The server immediately updates the database.

[1277] Attendance Management:

[1278] Faculty and staff enter their daily attendance information on their terminals.

[1279] The server receives this and automatically updates the attendance record.

[1280] Creating educational materials:

[1281] When a teacher sends the contents of educational materials to the server, the generating AI automatically applies the format and checks the content.

[1282] The server returns the generated educational materials to the instructor and accepts corrections as necessary.

[1283] 5. Updating Information

[1284] Constantly updated

[1285] The server periodically collects educational updates and curriculum changes.

[1286] The generative AI analyzes this new information and makes any necessary updates.

[1287] The server updates the database and notifies education professionals.

[1288] Educational professionals can check the latest information on their devices and update learning and curriculum as needed.

[1289] Specific examples

[1290] As a concrete example, here is the process that a public school in Tokyo goes through when it is looking for an educational expert with programming knowledge.

[1291] 1. Registration and evaluation of educational professionals

[1292] An educational expert A who is knowledgeable in programming registers in the system, enters his / her skills and qualifications, and uploads his / her resume.

[1293] The server receives this, and the generation AI analyzes it to complete the initial evaluation.

[1294] 2. Interview

[1295] The server proposes an interview date to Educational Specialist A. Educational Specialist A selects a convenient date and time, and the server confirms the interview date.

[1296] The interviewer conducts the video interview, and the emotion engine collects emotional data in real time. The server stores the interviewer's evaluation and emotional data in a database, and the generative AI makes the final evaluation.

[1297] 3. Matching

[1298] The school's administrator logs into the system and enters the needs of programming educators.

[1299] The server's generation AI compares educational expert A's skill information with his / her emotional data and adds him / her to the list as the most suitable candidate.

[1300] 4. Selection and Assignment

[1301] The school administrator selects Educational Expert A and confirms that he is the best fit based on the emotional data. The server then sends a notification of the assignment decision to Educational Expert A. The final decision information is stored in the database.

[1302] This series of processes provides a system that can quickly and efficiently connect educational experts needed by schools with educational institutions that match the experts' aptitudes. Furthermore, by utilizing an emotion engine, it is expected that matching accuracy and service quality will be further improved.

[1303] The processing flow will be explained below.

[1304] 1. Registration and Initial Evaluation of Educational Professionals

[1305] User (educational professional) registration

[1306] Step 1:

[1307] The user accesses the sharing platform website using a device and proceeds to the login or new registration screen.

[1308] Step 2:

[1309] Users enter basic information such as name, contact details, email address, qualifications, and skills, and upload resume and certificate files.

[1310] Step 3:

[1311] Once the user has entered all the information, they click the "Submit" button.

[1312] Step 4:

[1313] The server receives the information entered by the user and the uploaded files and stores them in a database.

[1314] AI-based initial assessment

[1315] Step 1:

[1316] The server accesses the newly stored information and files.

[1317] Step 2:

[1318] The server calls the generation AI and has it analyze information about the qualifications and skills of educational professionals.

[1319] Step 3:

[1320] The generation AI performs an initial evaluation based on the analysis results and generates an evaluation result.

[1321] Step 4:

[1322] The server stores the generated initial evaluation results in a database.

[1323] 2. Interview and detailed evaluation

[1324] Arranging interview schedules

[1325] Step 1:

[1326] The server sends an email to the education professional containing a suggested interview date.

[1327] Step 2:

[1328] The user (educational specialist) receives the email and responds to the system from a terminal to select a convenient date from the presented dates and times.

[1329] Step 3:

[1330] The server confirms the interview date and time selected by the user and stores it in a database.

[1331] Step 4:

[1332] The server notifies the interviewer of the selected interview schedule.

[1333] Interview and detailed evaluation

[1334] Step 1:

[1335] The interviewer will conduct a video interview with the education professional using a video interviewing tool at the appointed date and time.

[1336] Step 2:

[1337] During the interview, the emotion engine analyzes the educational professional's facial expressions and voice to collect emotional data in real time.

[1338] Step 3:

[1339] Interviewers enter their evaluations into the system based on the content of the interview and the educational professional's skills and personality.

[1340] Step 4:

[1341] The emotion engine analyzes the collected emotional data and reflects it in the evaluation results.

[1342] Step 5:

[1343] The server stores the input ratings and analysis results in a database, and the generation AI generates the final rating.

[1344] 3. Inputting needs and matching

[1345] Inputting school needs

[1346] Step 1:

[1347] The educational institution administrator logs in to the share platform using a device.

[1348] Step 2:

[1349] Administrators input the required educational professional requirements (e.g., specific skills, years of experience, etc.).

[1350] Step 3:

[1351] The server stores the school needs data entered by the administrator in a database.

[1352] AI-based matching

[1353] Step 1:

[1354] The server searches a database of registered education professionals.

[1355] Step 2:

[1356] The generative AI matches the input needs of schools with the skill profiles of educational professionals.

[1357] Step 3:

[1358] Generative AI generates a list of the best educational experts.

[1359] Step 4:

[1360] The server notifies the educational institution administrator of the generated list.

[1361] Final selection and placement

[1362] Step 1:

[1363] The educational institution's administrator will select a suitable educational professional from the notified list of candidates.

[1364] Step 2:

[1365] Administrators will schedule additional interviews through the system if necessary.

[1366] Step 3:

[1367] Use an emotion engine to collect and analyze emotional data from education professionals to identify suitable candidates.

[1368] Step 4:

[1369] The server confirms the administrator's selection result and sends a notification of the placement decision to the selected educational expert.

[1370] Step 5:

[1371] The server stores the final decision in a database and updates the educational professional's placement information.

[1372] 4. Support and Management

[1373] Provision of supplementary teaching materials

[1374] Step 1:

[1375] The server periodically checks the skill profiles of the education professionals.

[1376] Step 2:

[1377] Generative AI collects the latest educational material information and selects the most suitable materials to fill the skill gaps of educational professionals.

[1378] Step 3:

[1379] The server will email the educational specialist a list of selected learning materials and provide a download link.

[1380] Step 4:

[1381] Educational professionals use the devices to download learning materials and conduct their studies.

[1382] Automating administrative tasks

[1383] Step 1:

[1384] The user (teacher) uses the terminal to enter new information (e.g., contact information change).

[1385] Step 2:

[1386] The server immediately stores and updates the database with the new information it receives.

[1387] Step 3:

[1388] Faculty and staff enter their daily attendance information into the system from their terminals.

[1389] Step 4:

[1390] The server automatically updates the attendance record with the received attendance information.

[1391] Step 5:

[1392] The teacher sends the contents of the educational materials to the server.

[1393] Step 6:

[1394] The generation AI applies formatting and checks the content of the educational materials sent.

[1395] Step 7:

[1396] The server returns the generated educational materials to the instructor and accepts corrections as necessary.

[1397] 5. Updating Information

[1398] Constantly updated

[1399] Step 1:

[1400] The server periodically collects educational updates and curriculum changes.

[1401] Step 2:

[1402] The generative AI analyzes new information and makes necessary updates.

[1403] Step 3:

[1404] The server updates the database and notifies education professionals.

[1405] Step 4:

[1406] Educational professionals can check the latest information on their devices and update learning and curriculum as needed.

[1407] Example 2

[1408] 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."

[1409] In today's educational environment, quickly and accurately finding educational professionals with the specialized skills required by educational institutions is a difficult challenge. In addition to simple skill matching, matching based on the personality and emotions of educational professionals is also required, but this is difficult to achieve with conventional systems. Furthermore, to improve the quality of education, it is important for educational professionals to have continuous access to the latest educational materials, but this process can also be cumbersome. A system that can efficiently solve these problems is needed.

[1410] 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.

[1411] In this invention, the server includes a means for registering the skill information and qualification information of educational experts, a means for inputting needs information from educational institutions, a generating artificial intelligence means for analyzing the needs information of educational experts and educational institutions to generate optimal matches, a means for notifying educational institutions and educational experts of the matching results, a means for collecting and analyzing emotional data to improve matching accuracy, a means for proposing interview dates and storing the selection results in a database, and a means for generating evaluation results for educational experts. This enables educational institutions to quickly and accurately find educational experts with the specialized skills and characteristics they require, enabling optimal matching with educational experts. Furthermore, since educational experts can easily access the latest educational materials, the quality of education can be expected to improve.

[1412] "Educational institution" refers to a school, university, college, or other organization that provides education or training to students.

[1413] "Educational professional" refers to an individual, such as a teacher, lecturer, or trainer, who has specialized knowledge and skills in a particular academic or technical field and is in a position to teach.

[1414] "Share Platform" refers to an information sharing and management tool that matches educational institutions and educational experts online.

[1415] "Generative AI" refers to AI technology that has the ability to analyze and judge input data and generate new information.

[1416] "Skills information" refers to data about the specific job functions and skills possessed by educational professionals.

[1417] "Credentials" refers to data about the certifications and licenses held by education professionals.

[1418] "Needs Information" refers to the requirements and requirements for education professionals, such as the specific skills and years of experience required by an educational institution.

[1419] "Emotional data" refers to emotional information based on the facial expressions and tone of voice of educational professionals collected through video interviews and audio analysis.

[1420] "Interview Schedule" refers to the plan and date and time for an interview with an educational professional at a specific date and time.

[1421] A "database" refers to a recording medium or platform for systematically storing and managing information.

[1422] "Evaluation results" refers to evaluation information regarding the skills and aptitude of educational professionals generated through analysis by generative artificial intelligence.

[1423] "Educational Materials" refers to learning materials and instructional content for use by educational institutions and educational professionals.

[1424] "Administrative tasks" refers to tasks such as information entry, attendance management, and preparation of educational materials that educational institutions and educational professionals perform on a daily basis.

[1425] The present invention is a sharing platform for effectively matching educational institutions with educational experts. This platform improves matching accuracy by using an emotion engine that collects and analyzes emotion data and generative AI. Specific embodiments of the platform are described below.

[1426] Registration and initial evaluation of educational professionals

[1427] User (educational professional) registration

[1428] Users (education professionals) access the sharing platform using their devices, then enter basic information (such as name, contact details, qualifications, skills, etc.) and upload resumes and certificate files. The server then stores this information in a database.

[1429] AI-based initial assessment

[1430] The server retrieves the newly saved information from the database and asks the generated AI to analyze it using the following prompt:

[1431] markdown

[1432] Please use the following information from educational experts to make your initial assessment.

[1433] Name: John Doe

[1434] Qualifications: Elementary school teacher's license, junior high school teacher's license (mathematics)

[1435] Skills: Programming (Python, JavaScript)

[1436] Years of experience: 10 years

[1437] Resume: [Resume file link]

[1438] When making your initial assessment, consider the type of qualifications, skill details, and years of experience.

[1439] The generation AI analyzes these data and generates an initial evaluation result, which the server stores in a database.

[1440] Interview and detailed evaluation

[1441] Arranging interview schedules

[1442] The server sends an email to the educational specialist proposing an interview date. The user (education specialist) selects a convenient date and time and responds from their terminal. The server confirms the selected interview date and time and saves it in the database. The server then notifies the interviewer of the interview schedule.

[1443] Interview and detailed evaluation

[1444] The interviewer will use a video interview tool to conduct an interview with the educational expert at the designated date and time. During the interview, the emotion engine will analyze the facial expressions and voice of the educational expert to collect emotional data in real time. The interviewer will then enter their evaluation of the interview content and the educational expert's skills and personality into the system. The emotion engine will analyze the collected emotional data and reflect it in the evaluation results. The server will store the entered evaluation and emotional data in a database, and the generation AI will generate the final evaluation.

[1445] Inputting and matching needs

[1446] Inputting school needs

[1447] The administrator of the educational institution logs in to the sharing platform using a terminal and inputs the requirements for the educational specialists they need. The server stores the input needs data in a database.

[1448] AI-based matching

[1449] The server searches for educational expert information in the database, and the generation AI matches the educational institution's needs with the educational expert's skill profile. The generation AI generates a list of optimal educational experts, and the server notifies the list to the educational institution's administrator.

[1450] Final selection and placement

[1451] The administrator of the educational institution selects suitable educational experts from the candidate list and, if necessary, selects the most suitable educational expert based on the emotional data. The server notifies the educational experts of the selection result and updates the database.

[1452] Support and Management

[1453] Provision of supplementary teaching materials

[1454] The server periodically checks the skill profiles of educational experts, and the generative AI selects the most suitable learning materials. The server then notifies the educational experts of the selected learning materials by email and provides them with a download link. The educational experts then download the learning materials using their devices and begin studying.

[1455] Automating administrative tasks

[1456] The server automates administrative tasks for educational professionals and institutions, including entering and updating teacher information, managing attendance, and creating educational materials. The server streamlines these tasks using generative AI and updates the database accordingly.

[1457] Information Update

[1458] The server regularly collects the latest educational information and changes in the curriculum, and the generative AI makes any necessary updates. The server then updates the database with this information and notifies educational experts. Educational experts can then check the new information on their devices and update their learning and curriculum as needed.

[1459] In this way, we provide a system that effectively matches educational institutions with educational experts. Furthermore, the combination of an emotion engine and generative AI improves matching accuracy and service quality.

[1460] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1461] Step 1: Register your education professional

[1462] input:

[1463] Basic information (name, contact details, qualifications, skills, etc.) entered by the user (educational specialist) on the device

[1464] Resume and certificate files to be uploaded

[1465] Specific behavior:

[1466] 1. The user (educational professional) accesses the sharing platform using a device.

[1467] 2. The user enters basic information into a web form.

[1468] 3. The user clicks the "Upload Resume" button and selects and uploads a resume file from the local file system.

[1469] Data processing:

[1470] The server receives the entered information and uploaded files and stores them as new records in the database.

[1471] output:

[1472] Educational professionals' basic information and resume files stored in the database

[1473] Step 2: Initial assessment by AI

[1474] input:

[1475] Basic information and resume files of educational professionals stored in a database

[1476] Specific behavior:

[1477] 1. The server retrieves the newly saved information and files from the database.

[1478] 2. The server sends the following prompt to the generating AI:

[1479] markdown

[1480] Please use the following information from educational experts to make your initial assessment.

[1481] Name: John Doe

[1482] Qualifications: Elementary school teacher's license, junior high school teacher's license (mathematics)

[1483] Skills: Programming (Python, JavaScript)

[1484] Years of experience: 10 years

[1485] Resume: [Resume file link]

[1486] When making your initial assessment, consider the type of qualifications, skill details, and years of experience.

[1487] Data processing:

[1488] The generative AI analyzes the information provided and makes an initial assessment of the educational professional's skills and aptitude.

[1489] output:

[1490] The generated initial evaluation results are saved in the database.

[1491] Step 3: Schedule an interview

[1492] input:

[1493] Basic information and initial evaluation results of educational experts stored in a database

[1494] Specific behavior:

[1495] 1. The server sends an email to the education professional proposing an interview date.

[1496] 2. The user (educational professional) clicks on the link in the email and selects a convenient date and time.

[1497] 3. The server confirms the selected date and time, saves it in the database, and notifies the interviewer of the interview schedule.

[1498] Data processing:

[1499] The server stores the selected date and time in a database and generates and sends a notification email.

[1500] output:

[1501] Interview schedule confirmed between educational experts and interviewers

[1502] Step 4: Interview and detailed assessment

[1503] input:

[1504] Scheduled interview date and time and basic information about the education professional

[1505] Specific behavior:

[1506] 1. The interviewer will conduct a video interview with the education professional using a video interviewing tool at the appointed date and time.

[1507] 2. During the interview, the emotion engine analyzes the educational expert's facial expressions and voice to collect emotional data in real time.

[1508] 3. The interviewer will enter their evaluation of the interview content and the educational professional's skills and personality.

[1509] Data processing:

[1510] The emotion engine analyzes the collected emotional data and reflects it in the evaluation results.

[1511] output:

[1512] The server stores the detailed evaluation and emotion data in a database, and the generation AI generates the final evaluation.

[1513] Step 5: Enter your school's needs

[1514] input:

[1515] Specific educational professional requirements entered by the educational institution administrator (e.g., specific skills or years of experience)

[1516] Specific behavior:

[1517] 1. The educational institution administrator logs in to the share platform using a device.

[1518] 2. The administrator enters the requirements for the educational specialists required in the "Needs Input" form.

[1519] Data processing:

[1520] The server stores the input needs information in a database.

[1521] output:

[1522] School needs data stored in a database

[1523] Step 6: AI matching

[1524] input:

[1525] Database of educational professional information and school needs data

[1526] Specific behavior:

[1527] 1. The server retrieves the educational professional's information from the database.

[1528] 2. The server uses the generative AI to match the needs of educational institutions with the skill profiles of educational professionals.

[1529] 3. Generative AI generates a list of the most suitable educational experts.

[1530] 4. The server notifies the institution's administrator of the list.

[1531] Data processing:

[1532] Generative AI uses a matching algorithm to select the most suitable educational expert.

[1533] output:

[1534] A list of the best education professionals to be notified to the educational institution's administrators

[1535] Step 7: Final selection and placement

[1536] input:

[1537] Notified Educational Specialist Candidate List

[1538] Specific behavior:

[1539] 1. The educational institution administrator selects the most suitable educational professional from the list of candidates.

[1540] 2. If necessary, select the most suitable educational expert based on the emotional data.

[1541] 3. The server notifies the educational specialist of the selection results and updates the assignment information in the database.

[1542] Data processing:

[1543] The server stores the selection results in a database and generates a notification email to send to the education specialist.

[1544] output:

[1545] Educational professionals are notified of placement decisions and the information is updated in the database.

[1546] Step 8: Providing supplementary materials

[1547] input:

[1548] Skill profiles of educational professionals stored in a database

[1549] Specific behavior:

[1550] 1. The server periodically checks the skill profile of the education professional.

[1551] 2. Generative AI collects the latest information from a database of online teaching materials and selects the materials that best suit the skills of educational professionals.

[1552] 3. The server will email the educational specialist a list of selected learning materials and provide a download link.

[1553] 4. The user (educational expert) downloads the learning materials from the download link and begins studying.

[1554] Data processing:

[1555] Generative AI selects the most appropriate educational materials to fill skill gaps and generates email notifications.

[1556] output:

[1557] A list of educational materials and download links provided by educational experts

[1558] Step 9: Automate administrative tasks

[1559] input:

[1560] Changes to faculty information, new attendance information, and draft educational materials

[1561] Specific behavior:

[1562] 1. The teacher logs in to the platform from their device and enters new information.

[1563] 2. The server verifies the entered information and updates the database.

[1564] 3. When a teacher uploads a draft of educational material, the server asks the generation AI to check the content and apply formatting.

[1565] 4. The generating AI checks and formats the materials, and the server returns the generated materials to the instructor.

[1566] Data processing:

[1567] The server immediately reflects the input information in the database, and the generating AI processes the educational materials.

[1568] output:

[1569] Updated faculty information, attendance data, and automatically generated teaching materials

[1570] Step 10: Update your information

[1571] input:

[1572] Educational updates and curriculum changes

[1573] Specific behavior:

[1574] 1. The server periodically collects educational updates and curriculum changes from online resources.

[1575] 2. The generation AI analyzes the collected information and generates the necessary updates.

[1576] 3. The server updates the database and notifies the education specialist.

[1577] 4. Educational professionals will be notified, review new information, and make learning and curriculum updates as needed.

[1578] Data processing:

[1579] The server and generating AI analyze new information and update the database accordingly.

[1580] output:

[1581] Updated latest education information and update notifications

[1582] (Application example 2)

[1583] 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."

[1584] Conventional systems for matching educational institutions with educational experts only matched experts based on their skills and qualifications, and were unable to consider users' emotions or aptitudes. As a result, the system was not well suited to actual educational settings, making it difficult to achieve a highly satisfying match. Furthermore, it was unable to generate appropriate advertisements or effectively promote to the target audience.

[1585] 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.

[1586] In this invention, the server includes a means for registering skill information and qualification information of educational experts, a means for inputting needs information from educational institutions, a means for analyzing user emotion data using an emotion engine, a means for generating advertisements based on the analysis results and notifying educational institutions and educational experts, and a means for the generating artificial intelligence to analyze the needs information of educational experts and educational institutions and generate optimal matches. This enables highly accurate matching that takes user emotion data into consideration, and enables the generation of effective targeted advertisements.

[1587] "Educational institution" is a general term for any organization that provides or manages educational activities.

[1588] An "educational expert" is an individual or organization with specialized knowledge and skills in a particular educational field.

[1589] A "share platform" is an online system that allows multiple users to share information and access each other's information.

[1590] "Skill information" is data about specific skills and knowledge that a user possesses.

[1591] "Credentials" means data relating to officially recognized abilities or qualifications held by a User.

[1592] "Needs information" is data that indicates the skills and qualifications of education professionals required by an educational institution.

[1593] "Emotion engine" is a general term for a software or hardware system that recognizes and analyzes a user's emotional state.

[1594] "Generative AI" is an AI system that has the ability to learn from large amounts of data and generate new information and analytical results.

[1595] "Matching" is the process of matching the needs of educational institutions with the skills and qualifications of educational professionals to find the best match.

[1596] "Ad generation" is the process of automatically creating advertising content for targeted users.

[1597] A "database" is a system for managing and storing large amounts of data, and has the ability to efficiently search for specific information.

[1598] The following system configuration is shown as an embodiment of the present invention.

[1599] System program generation

[1600] This system is a shared platform for effectively matching educational institutions with educational experts, and consists of the following elements:

[1601] A means of registering the skills and qualifications of education professionals.

[1602] A means of inputting needs information from educational institutions.

[1603] A means of analyzing user emotional data using an emotion engine.

[1604] A means of generating advertisements based on the analysis results and informing educational institutions and education professionals.

[1605] A means by which generative artificial intelligence analyzes the needs information of educational experts and educational institutions and generates optimal matches.

[1606] A server means to suggest interview dates and store the selection results in a database.

[1607] A means for human and generative artificial intelligence to evaluate the skills and credentials of educational professionals.

[1608] A means by which the emotion engine collects and analyzes the emotion data of educational professionals in real time.

[1609] A means of informing education professionals of selected educational materials and providing download links.

[1610] A server means to automate administrative tasks and update education-related information into a database.

[1611] A means of storing generated advertisements in a database and automating updates to advertisement content.

[1612] Hardware and software used

[1613] The following hardware and software are used in this system:

[1614] Server: A computer device that connects to a database and manages and processes data.

[1615] Terminal: A computer or smart device used by education professionals and institutions to access the system.

[1616] Emotion engine: Software for analyzing user emotion data.

[1617] Generative AI model: An artificial intelligence system that analyzes data from education experts and educational institutions to generate optimal matches and advertisements.

[1618] Database: A system for storing large amounts of data and efficiently retrieving needed information.

[1619] Data processing and calculation process

[1620] 1. Registration of Educational Professionals

[1621] Education professionals use terminals to access the system, enter their skills and qualifications, and upload their resumes, and the server stores this information in a database.

[1622] 2. Input your needs

[1623] The administrator of the educational institution logs in to the system using a terminal and inputs the requirements for the educational specialists required (e.g., specific skills, years of experience, etc.). The server stores the input needs data in a database.

[1624] 3. Emotion Data Analysis

[1625] The emotion engine analyzes the facial expressions and voice of education experts to generate real-time emotional data, which is then stored in a database for later use in the matching and ad generation process.

[1626] 4. Matching and Ad Generation

[1627] The server uses a generative artificial intelligence model to match the needs of educational institutions with the skill information of educational experts to generate the most suitable candidate list, and at the same time, it generates the most suitable advertising content taking into account the sentiment data and notifies the educational institutions and educational experts.

[1628] 5. Ad Updates and Delivery

[1629] The generated advertisements are stored in a database and updated as necessary, enabling effective promotions to be delivered to target users.

[1630] As a concrete example, the following prompt sentence is presented.

[1631] Prompt Sentence Examples

[1632] Educational institutions need: Professionals with experience in English language teaching

[1633] Sentiment data: Mostly positive feedback

[1634] Advertisement content: An educational institution specializing in English education in Tokyo is looking for new teachers. We are looking for professionals with extensive experience in English education.

[1635] In this way, by implementing the invention, the accuracy of matching educational institutions with educational experts is improved, and effective targeted advertisements are generated and delivered.

[1636] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1637] Step 1:

[1638] Register of Educational Professionals

[1639] Input: Education professionals use terminals to access the system, enter skill information, qualification information, and upload resumes.

[1640] Specific operations: Register information through an input form on the device and upload files to the server.

[1641] Data processing / calculation: The server receives this information, checks the format for consistency, and then stores it in the database.

[1642] Output: Educational expert information stored in a database.

[1643] Step 2:

[1644] Input your needs

[1645] Input: The administrator of the educational institution logs into the system using a terminal and inputs the required educational professional requirements.

[1646] Specific operation: Enter specific skills, years of experience, etc. into the input form on the terminal and send it to the server.

[1647] Data processing / calculation: The server stores the received needs information in a database and organizes it for use in future matching processes.

[1648] Output: Institutional needs information stored in a database.

[1649] Step 3:

[1650] Emotional Data Analysis

[1651] Input: Facial expression and speech data of educational experts.

[1652] Specific operation: The device sends facial expression and voice data collected during the interview and registration to the emotion engine.

[1653] Data processing / calculation: The emotion engine analyzes the data, quantifies the emotional state (positive or negative), and sends it to the server.

[1654] Output: Sentiment analysis results stored on the server.

[1655] Step 4:

[1656] Matching and Ad Generation

[1657] Input: educational institution needs information and education professionals' skill information and sentiment data.

[1658] Specific operation: The server calls the generation AI, compares the needs information with the skill information and emotion data, lists the most suitable education experts, and determines the content of the generated advertisement.

[1659] Data processing / calculation: Generative AI analyzes large amounts of data and generates optimal matching results and advertisements.

[1660] Output: Best match results and advertisements notified to educational institutions and education professionals.

[1661] Step 5:

[1662] Ad updates and delivery

[1663] Input: Generated ad content.

[1664] Specific operation: The server saves the generated advertisement in a database, updates the content as necessary, and delivers the advertisement to the target user.

[1665] Data processing / calculation: Refer to the database, monitor the effectiveness of the advertisement, and generate and deliver new advertisements if necessary.

[1666] Output: Updated advertisements delivered to educational institutions and education professionals.

[1667] This series of steps enables highly accurate matching that takes into account user emotional data, as well as the creation and delivery of effective targeted advertisements.

[1668] 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.

[1669] 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.

[1670] 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.

[1671] [Third embodiment]

[1672] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1673] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1674] 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).

[1675] 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.

[1676] 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.

[1677] 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).

[1678] 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.

[1679] 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.

[1680] 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.

[1681] 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.

[1682] 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.

[1683] 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."

[1684] The present invention is a "share platform" for effectively matching educational institutions with educational experts. Specific embodiments of the present invention will be described below.

[1685] 1. Registration and Initial Evaluation of Educational Professionals

[1686] User (educational professional) registration

[1687] Education professionals access the sharing platform using their devices, enter basic information (such as name, contact details, qualifications, and skills), and upload files such as resumes and certificates.

[1688] The server stores the information entered by the education specialist and the uploaded files in a database.

[1689] AI-based initial assessment

[1690] The server accesses the newly stored information and files.

[1691] The server calls the generation AI and has it analyze information about the qualifications and skills of educational professionals.

[1692] The generation AI performs an initial evaluation based on the analysis results and generates an evaluation result.

[1693] The server stores the initial evaluation results in a database.

[1694] 2. Interview and detailed evaluation

[1695] Arranging interview schedules

[1696] The server will send an email to the education professional suggesting an interview date.

[1697] The educational expert can choose a convenient date from the provided dates and times and respond from their device.

[1698] The server stores the selected interview dates in a database and notifies the interviewer of the interview schedule.

[1699] Interview and detailed evaluation

[1700] The interviewer will conduct the video interview at the appointed date and time.

[1701] Interviewers enter their evaluations into the system based on the interview content, the educational professional's skills, and their personality.

[1702] The server stores the entered ratings in a database and again uses the generation AI to generate the final rating.

[1703] 3. Inputting needs and matching

[1704] Inputting school needs

[1705] The educational institution administrator logs into the platform from a terminal and enters the requirements for the required educational specialist.

[1706] The server stores the school's needs data in a database.

[1707] AI-based matching

[1708] The server searches a database of registered education professionals.

[1709] The generative AI matches the input school needs with the skills of educational experts and generates a list of the most suitable educational experts.

[1710] The server notifies the educational institution administrator of the generated list.

[1711] Final selection and placement

[1712] The educational institution's administrator will select suitable educational professionals from the notified list of candidates and schedule additional interviews if necessary.

[1713] The server sends a notification of the placement decision to the selected education professional.

[1714] The server stores the final decision in a database and updates the educational professional's placement information.

[1715] 4. Support and Management

[1716] Provision of supplementary teaching materials

[1717] The server periodically checks the skill profiles of the education professionals.

[1718] Generative AI collects the latest educational material information and selects the most suitable materials to fill the skill gaps of educational professionals.

[1719] The server will email the educational specialist a list of selected learning materials and provide a download link.

[1720] Educational professionals use the devices to download learning materials and conduct their studies.

[1721] Automating administrative tasks

[1722] Entering and updating faculty information:

[1723] Teachers enter new information (e.g., contact information changes) on their terminals.

[1724] The server immediately updates the database.

[1725] Attendance Management:

[1726] Faculty and staff enter their daily attendance information on their terminals.

[1727] The server receives this and automatically updates the attendance record.

[1728] Creating educational materials:

[1729] When a teacher sends the contents of educational materials to the server, the generating AI automatically applies the format and checks the content.

[1730] The server returns the generated educational materials to the instructor and accepts corrections as necessary.

[1731] 5. Updating Information

[1732] Constantly updated

[1733] The server periodically collects educational updates and curriculum changes.

[1734] The generative AI analyzes this new information and makes any necessary updates.

[1735] The server updates the database and notifies education professionals.

[1736] Educational professionals can check the latest information on their devices and update learning and curriculum as needed.

[1737] Specific examples

[1738] As a concrete example, here is the process that a public school in Tokyo goes through when it is looking for an educational expert with programming knowledge.

[1739] 1. Registration and evaluation of educational professionals

[1740] An educational expert A who is knowledgeable in programming registers in the system, enters his / her skills and qualifications, and uploads his / her resume.

[1741] The server receives this, and the generation AI analyzes it to complete the initial evaluation.

[1742] 2. Interview

[1743] The server proposes an interview date to Educational Specialist A. Educational Specialist A selects a convenient date and time, and the server confirms the interview date.

[1744] The interviewer conducts the video interview and inputs the evaluation into the server.

[1745] 3. Matching

[1746] The school's administrator logs into the system and enters the needs of programming educators.

[1747] The server's generation AI will compare the skill information of Educational Expert A and add him to the list as the most suitable candidate.

[1748] 4. Selection and Assignment

[1749] The school administrator selects educational expert A, the server notifies educational expert A, and then the assignment is decided.

[1750] This series of processes provides a system that can quickly and efficiently connect educational professionals sought by schools with educational institutions that suit the professionals' qualifications.

[1751] The processing flow will be explained below.

[1752] 1. Registration and Initial Evaluation of Educational Professionals

[1753] User (educational professional) registration

[1754] Step 1:

[1755] The user accesses the sharing platform website using a device and proceeds to the login or new registration screen.

[1756] Step 2:

[1757] Users enter basic information such as name, contact details, email address, qualifications, and skills, and upload resume and certificate files.

[1758] Step 3:

[1759] Once the user has entered all the information, they click the "Submit" button.

[1760] Step 4:

[1761] The server receives the information entered by the user and the uploaded files and stores them in a database.

[1762] AI-based initial assessment

[1763] Step 1:

[1764] The server accesses the newly stored information and files.

[1765] Step 2:

[1766] The server calls the generation AI and has it analyze information about the qualifications and skills of educational professionals.

[1767] Step 3:

[1768] The generation AI performs an initial evaluation based on the analysis results and generates an evaluation result.

[1769] Step 4:

[1770] The server stores the generated initial evaluation results in a database.

[1771] 2. Interview and detailed evaluation

[1772] Arranging interview schedules

[1773] Step 1:

[1774] The server sends an email to the education professional containing a suggested interview date.

[1775] Step 2:

[1776] The user (educational specialist) receives the email and responds to the system from a terminal to select a convenient date from the presented dates and times.

[1777] Step 3:

[1778] The server confirms the interview date and time selected by the user and stores it in a database.

[1779] Step 4:

[1780] The server notifies the interviewer of the selected interview schedule.

[1781] Interview and detailed evaluation

[1782] Step 1:

[1783] The interviewer will conduct a video interview with the education professional using a video interviewing tool at the appointed date and time.

[1784] Step 2:

[1785] Interviewers enter their evaluations into the system based on the interview content and the educational professional's skills and personality.

[1786] Step 3:

[1787] The server stores the evaluations entered by the interviewers in a database.

[1788] Step 4:

[1789] The server then uses the generation AI again based on the saved detailed evaluation information to generate the final evaluation.

[1790] 3. Inputting needs and matching

[1791] Inputting school needs

[1792] Step 1:

[1793] The educational institution administrator logs in to the share platform using a device.

[1794] Step 2:

[1795] Administrators input the required educational professional requirements (e.g., specific skills, years of experience, etc.).

[1796] Step 3:

[1797] The server stores the school needs data entered by the administrator in a database.

[1798] AI-based matching

[1799] Step 1:

[1800] The server searches a database of registered education professionals.

[1801] Step 2:

[1802] The generative AI matches the input needs of schools with the skill profiles of educational professionals.

[1803] Step 3:

[1804] Generative AI generates a list of the best educational experts.

[1805] Step 4:

[1806] The server notifies the educational institution administrator of the generated list.

[1807] Final selection and placement

[1808] Step 1:

[1809] The educational institution's administrator will select a suitable educational professional from the notified list of candidates.

[1810] Step 2:

[1811] Administrators will schedule additional interviews through the system if necessary.

[1812] Step 3:

[1813] The server confirms the administrator's selection result and sends a notification of the placement decision to the selected educational expert.

[1814] Step 4:

[1815] The server stores the final decision in a database and updates the educational professional's placement information.

[1816] 4. Support and Management

[1817] Provision of supplementary teaching materials

[1818] Step 1:

[1819] The server periodically checks the skill profile of the education professional.

[1820] Step 2:

[1821] Generative AI collects the latest educational material information and selects the most suitable materials to fill the skill gaps of educational professionals.

[1822] Step 3:

[1823] The server will email the educational specialist a list of selected learning materials and provide a download link.

[1824] Step 4:

[1825] Educational professionals use the devices to download learning materials and conduct their studies.

[1826] Automating administrative tasks

[1827] Step 1:

[1828] The user (teacher) uses the terminal to enter new information (e.g., contact information change).

[1829] Step 2:

[1830] The server immediately stores and updates the database with the new information it receives.

[1831] Step 3:

[1832] Faculty and staff enter their daily attendance information into the system from their terminals.

[1833] Step 4:

[1834] The server automatically updates the attendance record with the received attendance information.

[1835] Step 5:

[1836] The teacher sends the contents of the educational materials to the server.

[1837] Step 6:

[1838] The generation AI applies formatting and checks the content of the educational materials sent.

[1839] Step 7:

[1840] The server returns the generated educational materials to the instructor and accepts corrections as necessary.

[1841] 5. Updating Information

[1842] Constantly updated

[1843] Step 1:

[1844] The server periodically collects educational updates and curriculum changes.

[1845] Step 2:

[1846] The generative AI analyzes new information and makes necessary updates.

[1847] Step 3:

[1848] The server updates the database and notifies education professionals.

[1849] Step 4:

[1850] Educational professionals can check the latest information on their devices and update learning and curriculum as needed.

[1851] Example 1

[1852] 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."

[1853] In today's educational environment, it is difficult for educational institutions to quickly and efficiently find educational professionals with the specialized knowledge and skills they require. As a result, it takes time for educational institutions to hire suitable educational professionals, making it difficult to maintain the quality of education. Furthermore, educational professionals lack the means to have their skills and qualifications properly evaluated, making it difficult to find suitable positions. Furthermore, the time and effort required to obtain the latest educational materials and information is a significant burden. There is a need to build an efficient matching system to solve these issues.

[1854] 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.

[1855] In this invention, the server includes a means for recording the experience and qualification information of educational experts, a means for inputting requirement information from educational institutions, and a generating AI means for analyzing the requirement information of educational experts and educational institutions to generate optimal matches. This enables educational institutions to quickly and efficiently find educational experts with the expertise and skills they require. The server also includes a means for periodically checking the skill profiles of educational experts and selecting appropriate learning materials using a generating AI model, and a means for notifying educational experts of the selected learning materials and providing download links. This allows educational experts to keep their skills up to date at all times.

[1856] "Educational institutions" refers to facilities and organizations that carry out educational activities, including elementary schools, junior high schools, high schools, universities, and other educational institutions.

[1857] "Educational professionals" refers to professionals who have the qualifications and experience to provide instruction and education in educational institutions, including teachers, lecturers, and special education coordinators.

[1858] A "share platform" refers to an online system that connects multiple educational institutions and educational experts.

[1859] "Experience" refers to the practical experience and skills acquired by an educational professional, including teaching experience in a particular subject or program.

[1860] "Credentials" refers to any official qualifications or certifications held by an education professional, including teaching licenses and professional certifications.

[1861] "Requirements Information" refers to the specific skills, qualifications, and experience requirements of educational professionals sought by an educational institution.

[1862] "Analysis" refers to the process of analyzing input information, understanding its content, and making an evaluation.

[1863] "Generative AI means" refers to artificial intelligence technology that analyzes and evaluates input information to generate optimal candidates and teaching materials.

[1864] "Notification" refers to the act of communicating important information from the system to educational professionals and institutions, primarily via email or in-system notifications.

[1865] A "skills profile" refers to information that records an overview of the skills and experience of an educational professional.

[1866] "Instructional Materials" refers to educational materials and reference documents used by educational professionals to improve their skills.

[1867] "Download link" refers to the URL that educational professionals can use to obtain educational materials via the Internet.

[1868] "Administrative tasks" refers to the day-to-day administrative tasks of education professionals and institutions, such as updating contact details and managing attendance.

[1869] "Storage" refers to the act of saving and storing data or information in a database.

[1870] The present invention provides a sharing platform for effectively matching educational institutions with educational experts. This system has the function of registering the skills and qualifications of educational experts, automating the process of matching them with the requirements of educational institutions, and providing the educational experts with the most suitable educational materials.

[1871] Hardware and software used

[1872] Server: The computer that performs the main processing of this system, managing the database and running the AI ​​model.

[1873] Device: A computer, tablet, smartphone, or other device used by education professionals and administrators to enter information and receive notifications.

[1874] Generative AI model: An artificial intelligence technology that performs information analysis and evaluation, evaluating the skills of educational experts, generating matching lists, and selecting optimal teaching materials.

[1875] Program processing overview

[1876] 1. Registration and Initial Evaluation of Educational Professionals

[1877] User (educational professional): Uses a terminal to access the sharing platform, enters basic information such as name, contact details, qualifications, skills, etc., and uploads resumes and certificates. After completing the entry, the server stores this information in a database and sends a confirmation email to the user.

[1878] Server: Inputs the saved information and files into the generative AI model, analyzes the qualifications and skills of the educational expert, and performs an initial evaluation. The results are saved in a database, and an email is sent to the educational expert to notify them of the completion of the initial evaluation.

[1879] Example of how it works: An educational expert inputs skills such as "Python" or "Java," and the server requests the generated AI model to analyze them and saves the results.

[1880] Example prompt sentence:

[1881] "Make an initial assessment based on the skills information this education professional has."

[1882] 2. Interview and detailed evaluation

[1883] User (educational specialist): Checks the interview dates and times suggested by the server on the terminal and selects a suitable date and time. The server saves the selected date and time in the database and notifies the interviewer.

[1884] Server: The interviewer conducts the video interview at the specified date and time, and saves the results and evaluation in the database. The generative AI model is used again to perform the final evaluation, and the results are saved.

[1885] Example of specific operation: The interviewer conducts the interview using a video conferencing tool, inputs the evaluation details, and analyzes them using the generative AI model.

[1886] Example prompt sentence:

[1887] "Generate a final grade based on the interview evaluation results."

[1888] 3. Input and matching of school needs

[1889] User (educational institution administrator): Logs in to the sharing platform from a terminal and enters the necessary information on educational professionals. The server stores this information in a database.

[1890] Server: Retrieves information about educational professionals from the database, compares it with the school's requirements using a generative AI model, and generates a list of the best candidates. The list is then sent to the educational institution's administrator.

[1891] Example of specific operation: An educational institution inputs conditions such as "5 or more years of programming experience," and the server generates a list of candidates using a generative AI model and notifies them.

[1892] Example prompt sentence:

[1893] "Generate a list of educational professionals who best fit the needs of this school."

[1894] 4. Final selection and assignment

[1895] User (educational institution administrator): Selects appropriate educational specialists from the notified candidate list and schedules additional interviews if necessary. The server stores the selection results in a database and notifies the educational specialists of the placement decision.

[1896] Example of specific operation: Select from the candidate list and press the "Decide" button. A notification is automatically sent to the educational expert and the database is updated.

[1897] Example prompt sentence:

[1898] "Please send notification of placement decision to the selected educational professional."

[1899] 5. Support and Management

[1900] Server: Regularly checks the skill profiles of education experts and selects the most suitable learning materials using a generative AI model. It notifies education experts of the list of selected learning materials and provides download links. It also automates administrative tasks and updates the database.

[1901] User (educational specialist): Uses the download link from the device to obtain the learning materials and proceed with the study.

[1902] Example of specific operation: The server queries the skill data of the educational expert, and the generative AI selects and notifies the optimal teaching materials. The educational expert downloads the materials from the link.

[1903] Example prompt sentence:

[1904] "Select the most appropriate educational materials for this educational professional."

[1905] The server-based system automates a series of processes to quickly and efficiently match educational institutions with educational experts. Utilizing generative AI models, it seamlessly performs everything from skill assessment to matching, selection, and assignment, as well as providing teaching materials and updating information.

[1906] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1907] Step 1:

[1908] Register of Educational Professionals

[1909] Input: The user (education professional) uses a device to access the share platform, enters basic information such as name, contact details, qualifications, and skills, and uploads files of resumes and certificates.

[1910] Data processing and calculation: The server receives the input information and files, performs an initial data format check, and verifies the accuracy and completeness of the information.

[1911] Output: The server stores the received data in a database and sends the user a confirmation email.

[1912] Specific action: A user enters information into a system form and clicks the "Submit" button.

[1913] Step 2:

[1914] Initial evaluation by educational professionals

[1915] Input: Saved education professional information and uploaded files.

[1916] Data processing and calculation: The server retrieves new registration information from the database and inputs it into the generative AI model. The generative AI model analyzes skills and qualifications and generates evaluation results.

[1917] Output: The generated evaluation results are returned to the server and stored in the database. The server then sends the user an email to complete the initial evaluation.

[1918] Specific operation: The server inputs the data into the AI ​​analysis and stores the evaluation results in a database.

[1919] Step 3:

[1920] Arranging interview schedules

[1921] Input: Multiple interview dates and times suggested by the server.

[1922] Data processing and calculation: The educational expert selects a convenient date and time and sends it back to the server. The server saves the selected date and time in the database and notifies the interviewer.

[1923] Output: The selected interview date and time are saved in the database and the interviewer is notified of the schedule.

[1924] Specific behavior: The user selects a convenient date and time from the calendar form and submits it.

[1925] Step 4:

[1926] Interview and detailed evaluation

[1927] Input: Interview content and evaluation from the interviewer's video conferencing tool.

[1928] Data processing and calculation: Interviewers input their evaluations into the system, and the server stores them in a database. The generative AI model is then used again to make the final evaluation.

[1929] Output: The interview evaluation results and final evaluation are saved in the database.

[1930] Specific action: The interviewer enters information into the evaluation form and clicks the "Submit" button.

[1931] Step 5:

[1932] Inputting school needs

[1933] Input: Institution requirement information (such as required skills and experience).

[1934] Data processing and calculation: The server stores the input requirements information in a database and prepares for matching.

[1935] Output: Requirement information is saved in the database.

[1936] Specific action: The educational institution administrator fills in the required requirements on the form and clicks the "Submit" button.

[1937] Step 6:

[1938] Match Generation

[1939] Input: Education professional information and school requirement information in the database.

[1940] Data processing and calculation: The server retrieves the information in the database, inputs it into the generative AI model for matching, and generates a list of optimal educational experts.

[1941] Output: The generated list is sent to the institution administrator.

[1942] Specific operation: The server inputs the data into AI analysis, generates a result report, and notifies the administrator by email.

[1943] Step 7:

[1944] Final selection and placement

[1945] Input: A list of candidates selected by the institution's administrators.

[1946] Data processing and calculation: The server sends a notification to the selected education specialist and updates the assignment information in the database.

[1947] Output: An assignment notification is sent to the education specialist and the assignment information is saved in the database.

[1948] Specific action: The administrator selects from the candidate list and clicks the "Decide" button.

[1949] Step 8:

[1950] Provision of supplementary teaching materials

[1951] Input: Skills profiles of education professionals and up-to-date educational material information.

[1952] Data processing and calculation: The server passes the skill profile to the generative AI model to generate the optimal teaching material list. The selected teaching material list is notified to the educational expert.

[1953] Output: A list of materials and a download link will be sent to the education specialist.

[1954] Specific operation: The server inputs skill data into AI analysis, generates a list of teaching materials, and notifies the user.

[1955] Step 9:

[1956] Automating administrative tasks

[1957] Input: Faculty new information or daily attendance information.

[1958] Data processing and calculation: The server immediately updates the database with the input information. If necessary, it automatically performs management tasks using a generative AI model.

[1959] Output: The database is updated with the latest information.

[1960] Specific action: Faculty enters new information into the form and clicks the "Submit" button.

[1961] Step 10:

[1962] Information Update

[1963] Input: Latest education-related information and curriculum changes.

[1964] Data processing and calculation: The server periodically collects this new information, analyzes it using the generative AI model, and updates the database accordingly.

[1965] Output: The latest information is updated in the database and the education specialist is notified.

[1966] Specific operation: The server uses APIs and RSS feeds to collect the latest information, performs AI analysis, saves the results in a database, and notifies the user.

[1967] (Application example 1)

[1968] 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."

[1969] The previous system did not efficiently match educational institutions with educational experts, and the registration and evaluation of expert skills and qualifications was cumbersome. There were also issues with scheduling interviews and notifying selection results smoothly, which meant that the alignment between the needs of educational institutions and the skills of experts was not fully ensured. Furthermore, there was insufficient automation of the provision and management of educational materials.

[1970] 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.

[1971] In this invention, the server includes a means for registering skill information and qualification information of educational professionals, a means for inputting needs information from educational institutions, a generating artificial intelligence means for analyzing the needs information of educational professionals and educational institutions and generating optimal matches, a means for notifying educational institutions and educational professionals of the matching results, a means for educational professionals to input and update information via a smart device, and a video call means for supporting interviews, meetings, and the sharing of educational materials. This enables efficient matching between educational professionals and educational institutions, smooth interview arrangements and notifications, and the automation of the provision and management of educational materials.

[1972] An "educational institution" is an organization that provides educational services, such as a school, university, or vocational school.

[1973] An "educational professional" is a professional who has the qualifications and skills to specialize in education.

[1974] The "Share Platform" is an online system for sharing information and matching between educational experts and educational institutions.

[1975] "Skills information" is information about the professional abilities and experience of educational professionals.

[1976] "Credentials" refers to information about the various certifications and credentials held by education professionals.

[1977] "Needs information" refers to information about the skills, qualifications, and assignment conditions of professionals required by educational institutions.

[1978] "Generative AI" is an AI technology that analyzes input data and generates the most suitable matches between educational experts and educational institutions.

[1979] A "smart device" is a multi-function terminal that can connect to the Internet, such as a smartphone, smart glasses, or a head-mounted display.

[1980] "Video communication means" refers to a means for real-time video and audio communication using the Internet.

[1981] A "server" is a computer system that stores and manages various data, and analyzes, notifies, and operates on information.

[1982] "Notification means" refers to email or application messaging functions used to notify relevant parties of various information and results.

[1983] "Educational materials" are any type of learning material used by educational professionals in teaching or training.

[1984] "Administrative work" refers to administrative tasks such as updating education-related information, managing attendance, and creating materials.

[1985] "Automation" means that tasks that were previously performed manually can be performed automatically by machines or software.

[1986] The present invention relates to a sharing platform for efficiently matching educational institutions with educational experts. This system enables educational experts to appropriately match the requirements of educational institutions and quickly find experts with the skills required by the educational institutions. Specific embodiments of the system are described below.

[1987] 1. Registration and Initial Evaluation of Educational Professionals

[1988] User (educational professional) registration

[1989] Educational professionals access the sharing platform using a smart device (smartphone, smart glasses, head-mounted display), enter basic information (name, contact details, qualifications, skills, etc.), and upload resumes and certificate files. The server stores the information entered by the educational professionals and the uploaded files in a database.

[1990] AI-based initial assessment

[1991] The server accesses the newly saved information and files, invokes a generative AI (such as OpenAI's GPT-3) and has it analyze the information about the educational expert's qualifications and skills. The generative AI performs an initial evaluation based on the analysis results and generates an evaluation result. The server stores the initial evaluation result in a database.

[1992] 2. Interview and detailed evaluation

[1993] Arranging interview schedules

[1994] The server sends a notification to the educational specialist suggesting an interview date to the smart device. The educational specialist selects a convenient date from the suggested dates and responds from the device. The server saves the selected interview date in the database and notifies the interviewer of the interview schedule.

[1995] Interview and detailed evaluation

[1996] The interviewer will conduct the interview via video call at the appointed date and time. The interviewer will enter their evaluation of the interview content, the skills of the educational expert, and their personality into the system. The server will store the entered evaluation in a database and use the generative AI again to generate the final evaluation.

[1997] 3. Inputting needs and matching

[1998] Inputting school needs

[1999] The administrator of the educational institution logs in to the platform from a terminal and inputs the requirements for the educational specialists they need. The server stores the school's needs data in a database.

[2000] AI-based matching

[2001] The server searches the database of registered educational experts. The generation AI matches the input school's needs with the skills of the educational experts and generates a list of the most suitable educational experts. The server notifies the educational institution's administrator of the generated list.

[2002] Final selection and placement

[2003] The educational institution administrator selects a suitable educational expert from the notified candidate list and schedules additional interviews if necessary. The server then sends a notification of the placement decision to the selected educational expert. The server then saves the final decision in the database and updates the placement information of the educational expert.

[2004] 4. Provision and management of educational materials

[2005] Provision of supplementary teaching materials

[2006] The server periodically checks the skill profiles of education experts. The generation AI collects the latest educational material information and selects the most suitable materials to fill the education expert's skill gaps. The server notifies the education expert of the list of selected materials and provides a download link. The education expert downloads the materials using their device and begins studying.

[2007] Automating administrative tasks

[2008] Entering and updating faculty information:

[2009] The server instantly updates the database when education professionals enter new information (e.g., contact changes) at their devices.

[2010] Attendance Management:

[2011] Faculty and staff enter their daily attendance information on their terminals, and the server receives this information and automatically updates the attendance records.

[2012] Creating educational materials:

[2013] When a teacher sends the contents of educational materials to the server, the generation AI automatically applies formatting and checks the content, then returns the generated educational materials to the teacher and accepts corrections as necessary.

[2014] Specific examples

[2015] As a concrete example, here is the process that a public school in Tokyo goes through when it is looking for an educational expert with programming knowledge.

[2016] 1. Registration and evaluation of educational professionals

[2017] An educational expert A who is familiar with programming registers with the system, enters skill information and qualifications, and uploads a resume. The server receives this, and the generation AI analyzes it to complete an initial evaluation.

[2018] 2. Interview

[2019] The server proposes an interview date to Educational Expert A. Educational Expert A selects a convenient date and time, and the server confirms the interview date. The interviewer conducts the interview via video call and enters the evaluation into the server.

[2020] 3. Matching

[2021] The school administrator logs into the system and inputs their needs for programming educators. The server's generation AI compares this with the skill information of Educational Expert A and adds him or her to the list as the most suitable candidate.

[2022] 4. Selection and Assignment

[2023] The school administrator selects educational expert A, the server notifies educational expert A, and then the assignment is decided.

[2024] Example prompts to input to the generative AI model

[2025] plain

[2026] "Please rate an educational professional with expertise in programming education. Please make an initial assessment based on the following information: Qualifications: {Qualifications}, Skills: {Skills}"

[2027] The system allows educational institutions to quickly and efficiently connect with the educational professionals they need.

[2028] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2029] Step 1:

[2030] Registration and initial evaluation of educational professionals

[2031] Users (education professionals) access the sharing platform using their smart devices, enter basic information (such as name, contact details, qualifications, and skills), and upload resume and certificate files. This information and files are then sent to the server, which stores the data in a database. The entered data includes the education professional's skills and qualifications.

[2032] Next, the server calls a generative AI model (e.g., OpenAI's GPT-3) to generate a prompt that analyzes the uploaded information. An example of a prompt is, "Please evaluate the educational expert based on the following information: Qualifications: {Qualifications}, Skills: {Skills}." The generative AI performs an initial evaluation based on the analysis results and sends the results back to the server, where they are stored in a database. This stores the educational expert's basic information and initial evaluation results in the database.

[2033] Step 2:

[2034] Arranging interview schedules

[2035] The server sends a notification to the educational expert proposing an interview date. The notification is sent to the smart device, and the educational expert selects a convenient date from the specified dates and times and responds through the device. The server saves the selected interview date in the database and simultaneously notifies the interviewer of the interview schedule. Through this process, the interview date is confirmed for both the educational expert and the interviewer.

[2036] Step 3:

[2037] Interview and detailed evaluation

[2038] The interviewer will conduct the interview via video call at the appointed date and time. For the video call, an appropriate video call tool (e.g., Zoom, Microsoft Teams) will be used. After the interview, the interviewer will enter their evaluation into the system regarding the interview content, the educational expert's skills, and their personality. The server will then store the entered evaluation data in a database. The server will then again use the generative AI to perform a final evaluation. This result will be stored in the database, and the final evaluation result will be confirmed.

[2039] Step 4:

[2040] Inputting and matching needs

[2041] The administrator of the educational institution logs in to the platform using a terminal and enters the requirements for the educational specialists required. This data is sent to the server, which stores it in a database. The server then invokes the generation AI to match the needs of the educational institution with the skill information of registered educational specialists and generate a list of the most suitable educational specialists. This matching involves selecting specialists with the appropriate skills and experience based on the educational institution's conditions and requirements. The generated list is then notified to the administrator of the educational institution.

[2042] Step 5:

[2043] Final selection and placement

[2044] The educational institution administrator selects a suitable educational expert from the notified candidate list and schedules additional interviews if necessary. The server then sends a notification of the placement decision to the selected educational expert. This notification is delivered to the educational expert via their smart device. The server then saves the final decision in the database and updates the placement information of the educational expert. This allows the educational institution and the educational expert to be appropriately linked.

[2045] Step 6:

[2046] Provision and management of educational materials

[2047] The server periodically checks the skill profiles of education experts and uses generative AI to collect the latest educational material information. The AI ​​selects the most suitable educational materials to fill the education expert's skill gaps and notifies the education expert of the list. The notification includes a download link, and the education expert can download the materials using their device and study.

[2048] The server also has the ability to automate administrative tasks, efficiently updating education-related information, managing attendance, creating educational materials, etc. This will greatly simplify the administrative work of educational institutions.

[2049] This allows educational institutions to quickly and efficiently connect with the education professionals they need, and for education professionals to seamlessly receive the information and materials they need.

[2050] 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.

[2051] The present invention is a sharing platform for effectively matching educational institutions with educational professionals. This platform is combined with an emotion engine that recognizes and analyzes user emotions to achieve more accurate matching and improved service. Specific embodiments of the platform are described below.

[2052] 1. Registration and Initial Evaluation of Educational Professionals

[2053] User (educational professional) registration

[2054] Education professionals use their devices to access the sharing platform, enter basic information (such as name, contact details, qualifications, skills, etc.), and upload files of their resumes and certificates.

[2055] The server stores the information entered by the education specialist and the uploaded files in a database.

[2056] AI-based initial assessment

[2057] The server accesses the newly stored information and files.

[2058] The server calls the generation AI and has it analyze information about the qualifications and skills of educational professionals.

[2059] The generation AI performs an initial evaluation based on the analysis results and generates an evaluation result.

[2060] The server stores the generated initial evaluation results in a database.

[2061] 2. Interview and detailed evaluation

[2062] Arranging interview schedules

[2063] The server sends an email to the education professional suggesting an interview date.

[2064] The educational expert can choose a convenient date from the provided dates and times and respond from their device.

[2065] The server verifies the selected interview date and time and stores it in a database.

[2066] The server notifies the interviewer of the selected interview schedule.

[2067] Interview and detailed evaluation

[2068] The interviewer will conduct a video interview with the education professional using a video interviewing tool at the appointed date and time.

[2069] During the interview, the emotion engine analyzes the educational professional's facial expressions and voice to collect emotional data in real time.

[2070] Interviewers enter their evaluations into the system based on the content of the interview and the educational professional's skills and personality.

[2071] The emotion engine analyzes the collected emotional data and reflects it in the evaluation results.

[2072] The server stores the input ratings and analysis results in a database, and the generation AI generates the final rating.

[2073] 3. Inputting needs and matching

[2074] Inputting school needs

[2075] The educational institution administrator logs in to the share platform using a device.

[2076] Administrators input the required educational professional requirements (e.g., specific skills, years of experience, etc.).

[2077] The server stores the school needs data entered by the administrator in a database.

[2078] AI-based matching

[2079] The server searches a database of registered education professionals.

[2080] The generative AI matches the input needs of schools with the skill profiles of educational professionals.

[2081] Generative AI generates a list of the best educational experts.

[2082] The server notifies the educational institution administrator of the generated list.

[2083] Final selection and placement

[2084] The educational institution's administrator will select a suitable educational professional from the notified list of candidates.

[2085] If necessary, educational institution administrators can use the emotion engine to select the most suitable educational expert based on the candidate's emotion data.

[2086] The server verifies the selection results and sends a notification of the placement decision to the education specialist.

[2087] The server stores the final decision in a database and updates the educational professional's placement information.

[2088] 4. Support and Management

[2089] Provision of supplementary teaching materials

[2090] The server periodically checks the skill profiles of the education professionals.

[2091] Generative AI collects the latest educational material information and selects the most suitable materials to fill the skill gaps of educational professionals.

[2092] The server will email the educational specialist a list of selected learning materials and provide a download link.

[2093] Educational professionals use the devices to download learning materials and conduct their studies.

[2094] Automating administrative tasks

[2095] Entering and updating faculty information:

[2096] Teachers enter new information (e.g., contact information changes) on their terminals.

[2097] The server immediately updates the database.

[2098] Attendance Management:

[2099] Faculty and staff enter their daily attendance information on their terminals.

[2100] The server receives this and automatically updates the attendance record.

[2101] Creating educational materials:

[2102] When a teacher sends the contents of educational materials to the server, the generating AI automatically applies the format and checks the content.

[2103] The server returns the generated educational materials to the instructor and accepts corrections as necessary.

[2104] 5. Updating Information

[2105] Constantly updated

[2106] The server periodically collects educational updates and curriculum changes.

[2107] The generative AI analyzes this new information and makes any necessary updates.

[2108] The server updates the database and notifies education professionals.

[2109] Educational professionals can check the latest information on their devices and update learning and curriculum as needed.

[2110] Specific examples

[2111] As a concrete example, here is the process that a public school in Tokyo goes through when it is looking for an educational expert with programming knowledge.

[2112] 1. Registration and evaluation of educational professionals

[2113] An educational expert A who is knowledgeable in programming registers in the system, enters his / her skills and qualifications, and uploads his / her resume.

[2114] The server receives this, and the generation AI analyzes it to complete the initial evaluation.

[2115] 2. Interview

[2116] The server proposes an interview date to Educational Specialist A. Educational Specialist A selects a convenient date and time, and the server confirms the interview date.

[2117] The interviewer conducts the video interview, and the emotion engine collects emotional data in real time. The server stores the interviewer's evaluation and emotional data in a database, and the generative AI makes the final evaluation.

[2118] 3. Matching

[2119] The school's administrator logs into the system and enters the needs of programming educators.

[2120] The server's generation AI compares educational expert A's skill information with his / her emotional data and adds him / her to the list as the most suitable candidate.

[2121] 4. Selection and Assignment

[2122] The school administrator selects Educational Expert A and confirms that he is the best fit based on the emotional data. The server then sends a notification of the assignment decision to Educational Expert A. The final decision information is stored in the database.

[2123] This series of processes provides a system that can quickly and efficiently connect educational experts needed by schools with educational institutions that match the experts' aptitudes. Furthermore, by utilizing an emotion engine, it is expected that matching accuracy and service quality will be further improved.

[2124] The processing flow will be explained below.

[2125] 1. Registration and Initial Evaluation of Educational Professionals

[2126] User (educational professional) registration

[2127] Step 1:

[2128] The user accesses the sharing platform website using a device and proceeds to the login or new registration screen.

[2129] Step 2:

[2130] Users enter basic information such as name, contact details, email address, qualifications, and skills, and upload resume and certificate files.

[2131] Step 3:

[2132] Once the user has entered all the information, they click the "Submit" button.

[2133] Step 4:

[2134] The server receives the information entered by the user and the uploaded files and stores them in a database.

[2135] AI-based initial assessment

[2136] Step 1:

[2137] The server accesses the newly stored information and files.

[2138] Step 2:

[2139] The server calls the generation AI and has it analyze information about the qualifications and skills of educational professionals.

[2140] Step 3:

[2141] The generation AI performs an initial evaluation based on the analysis results and generates an evaluation result.

[2142] Step 4:

[2143] The server stores the generated initial evaluation results in a database.

[2144] 2. Interview and detailed evaluation

[2145] Arranging interview schedules

[2146] Step 1:

[2147] The server sends an email to the education professional containing a suggested interview date.

[2148] Step 2:

[2149] The user (educational specialist) receives the email and responds to the system from a terminal to select a convenient date from the presented dates and times.

[2150] Step 3:

[2151] The server confirms the interview date and time selected by the user and stores it in a database.

[2152] Step 4:

[2153] The server notifies the interviewer of the selected interview schedule.

[2154] Interview and detailed evaluation

[2155] Step 1:

[2156] The interviewer will conduct a video interview with the education professional using a video interviewing tool at the appointed date and time.

[2157] Step 2:

[2158] During the interview, the emotion engine analyzes the educational professional's facial expressions and voice to collect emotional data in real time.

[2159] Step 3:

[2160] Interviewers enter their evaluations into the system based on the content of the interview and the educational professional's skills and personality.

[2161] Step 4:

[2162] The emotion engine analyzes the collected emotional data and reflects it in the evaluation results.

[2163] Step 5:

[2164] The server stores the input ratings and analysis results in a database, and the generation AI generates the final rating.

[2165] 3. Inputting needs and matching

[2166] Inputting school needs

[2167] Step 1:

[2168] The educational institution administrator logs in to the share platform using a device.

[2169] Step 2:

[2170] Administrators input the required educational professional requirements (e.g., specific skills, years of experience, etc.).

[2171] Step 3:

[2172] The server stores the school needs data entered by the administrator in a database.

[2173] AI-based matching

[2174] Step 1:

[2175] The server searches a database of registered education professionals.

[2176] Step 2:

[2177] The generative AI matches the input needs of schools with the skill profiles of educational professionals.

[2178] Step 3:

[2179] Generative AI generates a list of the best educational experts.

[2180] Step 4:

[2181] The server notifies the educational institution administrator of the generated list.

[2182] Final selection and placement

[2183] Step 1:

[2184] The educational institution's administrator will select a suitable educational professional from the notified list of candidates.

[2185] Step 2:

[2186] Administrators will schedule additional interviews through the system if necessary.

[2187] Step 3:

[2188] Use an emotion engine to collect and analyze emotional data from education professionals to identify suitable candidates.

[2189] Step 4:

[2190] The server confirms the administrator's selection result and sends a notification of the placement decision to the selected educational expert.

[2191] Step 5:

[2192] The server stores the final decision in a database and updates the educational professional's placement information.

[2193] 4. Support and Management

[2194] Provision of supplementary teaching materials

[2195] Step 1:

[2196] The server periodically checks the skill profiles of the education professionals.

[2197] Step 2:

[2198] Generative AI collects the latest educational material information and selects the most suitable materials to fill the skill gaps of educational professionals.

[2199] Step 3:

[2200] The server will email the educational specialist a list of selected learning materials and provide a download link.

[2201] Step 4:

[2202] Educational professionals use the devices to download learning materials and conduct their studies.

[2203] Automating administrative tasks

[2204] Step 1:

[2205] The user (teacher) uses the terminal to enter new information (e.g., contact information change).

[2206] Step 2:

[2207] The server immediately stores and updates the database with the new information it receives.

[2208] Step 3:

[2209] Faculty and staff enter their daily attendance information into the system from their terminals.

[2210] Step 4:

[2211] The server automatically updates the attendance record with the received attendance information.

[2212] Step 5:

[2213] The teacher sends the contents of the educational materials to the server.

[2214] Step 6:

[2215] The generation AI applies formatting and checks the content of the educational materials sent.

[2216] Step 7:

[2217] The server returns the generated educational materials to the instructor and accepts corrections as necessary.

[2218] 5. Updating Information

[2219] Constantly updated

[2220] Step 1:

[2221] The server periodically collects educational updates and curriculum changes.

[2222] Step 2:

[2223] The generative AI analyzes new information and makes necessary updates.

[2224] Step 3:

[2225] The server updates the database and notifies education professionals.

[2226] Step 4:

[2227] Educational professionals can check the latest information on their devices and update learning and curriculum as needed.

[2228] Example 2

[2229] 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."

[2230] In today's educational environment, quickly and accurately finding educational professionals with the specialized skills required by educational institutions is a difficult challenge. In addition to simple skill matching, matching based on the personality and emotions of educational professionals is also required, but this is difficult to achieve with conventional systems. Furthermore, to improve the quality of education, it is important for educational professionals to have continuous access to the latest educational materials, but this process can also be cumbersome. A system that can efficiently solve these problems is needed.

[2231] 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.

[2232] In this invention, the server includes a means for registering the skill information and qualification information of educational experts, a means for inputting needs information from educational institutions, a generating artificial intelligence means for analyzing the needs information of educational experts and educational institutions to generate optimal matches, a means for notifying educational institutions and educational experts of the matching results, a means for collecting and analyzing emotional data to improve matching accuracy, a means for proposing interview dates and storing the selection results in a database, and a means for generating evaluation results for educational experts. This enables educational institutions to quickly and accurately find educational experts with the specialized skills and characteristics they require, enabling optimal matching with educational experts. Furthermore, since educational experts can easily access the latest educational materials, the quality of education can be expected to improve.

[2233] "Educational institution" refers to a school, university, college, or other organization that provides education or training to students.

[2234] "Educational professional" refers to an individual, such as a teacher, lecturer, or trainer, who has specialized knowledge and skills in a particular academic or technical field and is in a position to teach.

[2235] "Share Platform" refers to an information sharing and management tool that matches educational institutions and educational experts online.

[2236] "Generative AI" refers to AI technology that has the ability to analyze and judge input data and generate new information.

[2237] "Skills information" refers to data about the specific job functions and skills possessed by educational professionals.

[2238] "Credentials" refers to data about the certifications and licenses held by education professionals.

[2239] "Needs Information" refers to the requirements and requirements for education professionals, such as the specific skills and years of experience required by an educational institution.

[2240] "Emotional data" refers to emotional information based on the facial expressions and tone of voice of educational professionals collected through video interviews and audio analysis.

[2241] "Interview Schedule" refers to the plan and date and time for an interview with an educational professional at a specific date and time.

[2242] A "database" refers to a recording medium or platform for systematically storing and managing information.

[2243] "Evaluation results" refers to evaluation information regarding the skills and aptitude of educational professionals generated through analysis by generative artificial intelligence.

[2244] "Educational Materials" refers to learning materials and instructional content for use by educational institutions and educational professionals.

[2245] "Administrative tasks" refers to tasks such as information entry, attendance management, and preparation of educational materials that educational institutions and educational professionals perform on a daily basis.

[2246] The present invention is a sharing platform for effectively matching educational institutions with educational experts. This platform improves matching accuracy by using an emotion engine that collects and analyzes emotion data and generative AI. Specific embodiments of the platform are described below.

[2247] Registration and initial evaluation of educational professionals

[2248] User (educational professional) registration

[2249] Users (education professionals) access the sharing platform using their devices, then enter basic information (such as name, contact details, qualifications, skills, etc.) and upload resumes and certificate files. The server then stores this information in a database.

[2250] AI-based initial assessment

[2251] The server retrieves the newly saved information from the database and asks the generated AI to analyze it using the following prompt:

[2252] markdown

[2253] Please use the following information from educational experts to make your initial assessment.

[2254] Name: John Doe

[2255] Qualifications: Elementary school teacher's license, junior high school teacher's license (mathematics)

[2256] Skills: Programming (Python, JavaScript)

[2257] Years of experience: 10 years

[2258] Resume: [Resume file link]

[2259] When making your initial assessment, consider the type of qualifications, skill details, and years of experience.

[2260] The generation AI analyzes these data and generates an initial evaluation result, which the server stores in a database.

[2261] Interview and detailed evaluation

[2262] Arranging interview schedules

[2263] The server sends an email to the educational specialist proposing an interview date. The user (education specialist) selects a convenient date and time and responds from their terminal. The server confirms the selected interview date and time and saves it in the database. The server then notifies the interviewer of the interview schedule.

[2264] Interview and detailed evaluation

[2265] The interviewer will use a video interview tool to conduct an interview with the educational expert at the designated date and time. During the interview, the emotion engine will analyze the facial expressions and voice of the educational expert to collect emotional data in real time. The interviewer will then enter their evaluation of the interview content and the educational expert's skills and personality into the system. The emotion engine will analyze the collected emotional data and reflect it in the evaluation results. The server will store the entered evaluation and emotional data in a database, and the generation AI will generate the final evaluation.

[2266] Inputting and matching needs

[2267] Inputting school needs

[2268] The administrator of the educational institution logs in to the sharing platform using a terminal and inputs the requirements for the educational specialists they need. The server stores the input needs data in a database.

[2269] AI-based matching

[2270] The server searches for educational expert information in the database, and the generation AI matches the educational institution's needs with the educational expert's skill profile. The generation AI generates a list of optimal educational experts, and the server notifies the list to the educational institution's administrator.

[2271] Final selection and placement

[2272] The administrator of the educational institution selects suitable educational experts from the candidate list and, if necessary, selects the most suitable educational expert based on the emotional data. The server notifies the educational experts of the selection result and updates the database.

[2273] Support and Management

[2274] Provision of supplementary teaching materials

[2275] The server periodically checks the skill profiles of educational experts, and the generative AI selects the most suitable learning materials. The server then notifies the educational experts of the selected learning materials by email and provides them with a download link. The educational experts then download the learning materials using their devices and begin studying.

[2276] Automating administrative tasks

[2277] The server automates administrative tasks for educational professionals and institutions, including entering and updating teacher information, managing attendance, and creating educational materials. The server streamlines these tasks using generative AI and updates the database accordingly.

[2278] Information Update

[2279] The server regularly collects the latest educational information and changes in the curriculum, and the generative AI makes any necessary updates. The server then updates the database with this information and notifies educational experts. Educational experts can then check the new information on their devices and update their learning and curriculum as needed.

[2280] In this way, we provide a system that effectively matches educational institutions with educational experts. Furthermore, the combination of an emotion engine and generative AI improves matching accuracy and service quality.

[2281] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2282] Step 1: Register your education professional

[2283] input:

[2284] Basic information (name, contact details, qualifications, skills, etc.) entered by the user (educational specialist) on the device

[2285] Resume and certificate files to be uploaded

[2286] Specific behavior:

[2287] 1. The user (educational professional) accesses the sharing platform using a device.

[2288] 2. The user enters basic information into a web form.

[2289] 3. The user clicks the "Upload Resume" button and selects and uploads a resume file from the local file system.

[2290] Data processing:

[2291] The server receives the entered information and uploaded files and stores them as new records in the database.

[2292] output:

[2293] Educational professionals' basic information and resume files stored in the database

[2294] Step 2: Initial assessment by AI

[2295] input:

[2296] Basic information and resume files of educational professionals stored in a database

[2297] Specific behavior:

[2298] 1. The server retrieves the newly saved information and files from the database.

[2299] 2. The server sends the following prompt to the generating AI:

[2300] markdown

[2301] Please use the following information from educational experts to make your initial assessment.

[2302] Name: John Doe

[2303] Qualifications: Elementary school teacher's license, junior high school teacher's license (mathematics)

[2304] Skills: Programming (Python, JavaScript)

[2305] Years of experience: 10 years

[2306] Resume: [Resume file link]

[2307] When making your initial assessment, consider the type of qualifications, skill details, and years of experience.

[2308] Data processing:

[2309] The generative AI analyzes the information provided and makes an initial assessment of the educational professional's skills and aptitude.

[2310] output:

[2311] The generated initial evaluation results are saved in the database.

[2312] Step 3: Schedule an interview

[2313] input:

[2314] Basic information and initial evaluation results of educational experts stored in a database

[2315] Specific behavior:

[2316] 1. The server sends an email to the education professional proposing an interview date.

[2317] 2. The user (educational professional) clicks on the link in the email and selects a convenient date and time.

[2318] 3. The server confirms the selected date and time, saves it in the database, and notifies the interviewer of the interview schedule.

[2319] Data processing:

[2320] The server stores the selected date and time in a database and generates and sends a notification email.

[2321] output:

[2322] Interview schedule confirmed between educational experts and interviewers

[2323] Step 4: Interview and detailed assessment

[2324] input:

[2325] Scheduled interview date and time and basic information about the education professional

[2326] Specific behavior:

[2327] 1. The interviewer will conduct a video interview with the education professional using a video interviewing tool at the appointed date and time.

[2328] 2. During the interview, the emotion engine analyzes the educational expert's facial expressions and voice to collect emotional data in real time.

[2329] 3. The interviewer will enter their evaluation of the interview content and the educational professional's skills and personality.

[2330] Data processing:

[2331] The emotion engine analyzes the collected emotional data and reflects it in the evaluation results.

[2332] output:

[2333] The server stores the detailed evaluation and emotion data in a database, and the generation AI generates the final evaluation.

[2334] Step 5: Enter your school's needs

[2335] input:

[2336] Specific educational professional requirements entered by the educational institution administrator (e.g., specific skills or years of experience)

[2337] Specific behavior:

[2338] 1. The educational institution administrator logs in to the share platform using a device.

[2339] 2. The administrator enters the requirements for the educational specialists required in the "Needs Input" form.

[2340] Data processing:

[2341] The server stores the input needs information in a database.

[2342] output:

[2343] School needs data stored in a database

[2344] Step 6: AI matching

[2345] input:

[2346] Database of educational professional information and school needs data

[2347] Specific behavior:

[2348] 1. The server retrieves the educational professional's information from the database.

[2349] 2. The server uses the generative AI to match the needs of educational institutions with the skill profiles of educational professionals.

[2350] 3. Generative AI generates a list of the most suitable educational experts.

[2351] 4. The server notifies the institution's administrator of the list.

[2352] Data processing:

[2353] Generative AI uses a matching algorithm to select the most suitable educational expert.

[2354] output:

[2355] A list of the best education professionals to be notified to the educational institution's administrators

[2356] Step 7: Final selection and placement

[2357] input:

[2358] Notified Educational Specialist Candidate List

[2359] Specific behavior:

[2360] 1. The educational institution administrator selects the most suitable educational professional from the list of candidates.

[2361] 2. If necessary, select the most suitable educational expert based on the emotional data.

[2362] 3. The server notifies the educational specialist of the selection results and updates the assignment information in the database.

[2363] Data processing:

[2364] The server stores the selection results in a database and generates a notification email to send to the education specialist.

[2365] output:

[2366] Educational professionals are notified of placement decisions and the information is updated in the database.

[2367] Step 8: Providing supplementary materials

[2368] input:

[2369] Skill profiles of educational professionals stored in a database

[2370] Specific behavior:

[2371] 1. The server periodically checks the skill profile of the education professional.

[2372] 2. Generative AI collects the latest information from a database of online teaching materials and selects the materials that best suit the skills of educational professionals.

[2373] 3. The server will email the educational specialist a list of selected learning materials and provide a download link.

[2374] 4. The user (educational expert) downloads the learning materials from the download link and begins studying.

[2375] Data processing:

[2376] Generative AI selects the most appropriate educational materials to fill skill gaps and generates email notifications.

[2377] output:

[2378] A list of educational materials and download links provided by educational experts

[2379] Step 9: Automate administrative tasks

[2380] input:

[2381] Changes to faculty information, new attendance information, and draft educational materials

[2382] Specific behavior:

[2383] 1. The teacher logs in to the platform from their device and enters new information.

[2384] 2. The server verifies the entered information and updates the database.

[2385] 3. When a teacher uploads a draft of educational material, the server asks the generation AI to check the content and apply formatting.

[2386] 4. The generating AI checks and formats the materials, and the server returns the generated materials to the instructor.

[2387] Data processing:

[2388] The server immediately reflects the input information in the database, and the generating AI processes the educational materials.

[2389] output:

[2390] Updated faculty information, attendance data, and automatically generated teaching materials

[2391] Step 10: Update your information

[2392] input:

[2393] Educational updates and curriculum changes

[2394] Specific behavior:

[2395] 1. The server periodically collects educational updates and curriculum changes from online resources.

[2396] 2. The generation AI analyzes the collected information and generates the necessary updates.

[2397] 3. The server updates the database and notifies the education specialist.

[2398] 4. Educational professionals will be notified, review new information, and make learning and curriculum updates as needed.

[2399] Data processing:

[2400] The server and generating AI analyze new information and update the database accordingly.

[2401] output:

[2402] Updated latest education information and update notifications

[2403] (Application example 2)

[2404] 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."

[2405] Conventional systems for matching educational institutions with educational experts only matched experts based on their skills and qualifications, and were unable to consider users' emotions or aptitudes. As a result, the system was not well suited to actual educational settings, making it difficult to achieve a highly satisfying match. Furthermore, it was unable to generate appropriate advertisements or effectively promote to the target audience.

[2406] 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.

[2407] In this invention, the server includes a means for registering skill information and qualification information of educational experts, a means for inputting needs information from educational institutions, a means for analyzing user emotion data using an emotion engine, a means for generating advertisements based on the analysis results and notifying educational institutions and educational experts, and a means for the generating artificial intelligence to analyze the needs information of educational experts and educational institutions and generate optimal matches. This enables highly accurate matching that takes user emotion data into consideration, and enables the generation of effective targeted advertisements.

[2408] "Educational institution" is a general term for any organization that provides or manages educational activities.

[2409] An "educational expert" is an individual or organization with specialized knowledge and skills in a particular educational field.

[2410] A "share platform" is an online system that allows multiple users to share information and access each other's information.

[2411] "Skill information" is data about specific skills and knowledge that a user possesses.

[2412] "Credentials" means data relating to officially recognized abilities or qualifications held by a User.

[2413] "Needs information" is data that indicates the skills and qualifications of education professionals required by an educational institution.

[2414] "Emotion engine" is a general term for a software or hardware system that recognizes and analyzes a user's emotional state.

[2415] "Generative AI" is an AI system that has the ability to learn from large amounts of data and generate new information and analytical results.

[2416] "Matching" is the process of matching the needs of educational institutions with the skills and qualifications of educational professionals to find the best match.

[2417] "Ad generation" is the process of automatically creating advertising content for targeted users.

[2418] A "database" is a system for managing and storing large amounts of data, and has the ability to efficiently search for specific information.

[2419] The following system configuration is shown as an embodiment of the present invention.

[2420] System program generation

[2421] This system is a shared platform for effectively matching educational institutions with educational experts, and consists of the following elements:

[2422] A means of registering the skills and qualifications of education professionals.

[2423] A means of inputting needs information from educational institutions.

[2424] A means of analyzing user emotional data using an emotion engine.

[2425] A means of generating advertisements based on the analysis results and informing educational institutions and education professionals.

[2426] A means by which generative artificial intelligence analyzes the needs information of educational experts and educational institutions and generates optimal matches.

[2427] A server means to suggest interview dates and store the selection results in a database.

[2428] A means for human and generative artificial intelligence to evaluate the skills and credentials of educational professionals.

[2429] A means by which the emotion engine collects and analyzes the emotion data of educational professionals in real time.

[2430] A means of informing education professionals of selected educational materials and providing download links.

[2431] A server means to automate administrative tasks and update education-related information into a database.

[2432] A means of storing generated advertisements in a database and automating updates to advertisement content.

[2433] Hardware and software used

[2434] The following hardware and software are used in this system:

[2435] Server: A computer device that connects to a database and manages and processes data.

[2436] Terminal: A computer or smart device used by education professionals and institutions to access the system.

[2437] Emotion engine: Software for analyzing user emotion data.

[2438] Generative AI model: An artificial intelligence system that analyzes data from education experts and educational institutions to generate optimal matches and advertisements.

[2439] Database: A system for storing large amounts of data and efficiently retrieving needed information.

[2440] Data processing and calculation process

[2441] 1. Registration of Educational Professionals

[2442] Education professionals use terminals to access the system, enter their skills and qualifications, and upload their resumes, and the server stores this information in a database.

[2443] 2. Input your needs

[2444] The administrator of the educational institution logs in to the system using a terminal and inputs the requirements for the educational specialists required (e.g., specific skills, years of experience, etc.). The server stores the input needs data in a database.

[2445] 3. Emotion Data Analysis

[2446] The emotion engine analyzes the facial expressions and voice of education experts to generate real-time emotional data, which is then stored in a database for later use in the matching and ad generation process.

[2447] 4. Matching and Ad Generation

[2448] The server uses a generative artificial intelligence model to match the needs of educational institutions with the skill information of educational experts to generate the most suitable candidate list, and at the same time, it generates the most suitable advertising content taking into account the sentiment data and notifies the educational institutions and educational experts.

[2449] 5. Ad Updates and Delivery

[2450] The generated advertisements are stored in a database and updated as necessary, enabling effective promotions to be delivered to target users.

[2451] As a concrete example, the following prompt sentence is presented.

[2452] Prompt Sentence Examples

[2453] Educational institutions need: Professionals with experience in English language teaching

[2454] Sentiment data: Mostly positive feedback

[2455] Advertisement content: An educational institution specializing in English education in Tokyo is looking for new teachers. We are looking for professionals with extensive experience in English education.

[2456] In this way, by implementing the invention, the accuracy of matching educational institutions with educational experts is improved, and effective targeted advertisements are generated and delivered.

[2457] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2458] Step 1:

[2459] Register of Educational Professionals

[2460] Input: Education professionals use terminals to access the system, enter skill information, qualification information, and upload resumes.

[2461] Specific operations: Register information through an input form on the device and upload files to the server.

[2462] Data processing / calculation: The server receives this information, checks the format for consistency, and then stores it in the database.

[2463] Output: Educational expert information stored in a database.

[2464] Step 2:

[2465] Input your needs

[2466] Input: The administrator of the educational institution logs into the system using a terminal and inputs the required educational professional requirements.

[2467] Specific operation: Enter specific skills, years of experience, etc. into the input form on the terminal and send it to the server.

[2468] Data processing / calculation: The server stores the received needs information in a database and organizes it for use in future matching processes.

[2469] Output: Institutional needs information stored in a database.

[2470] Step 3:

[2471] Emotional Data Analysis

[2472] Input: Facial expression and speech data of educational experts.

[2473] Specific operation: The device sends facial expression and voice data collected during the interview and registration to the emotion engine.

[2474] Data processing / calculation: The emotion engine analyzes the data, quantifies the emotional state (positive or negative), and sends it to the server.

[2475] Output: Sentiment analysis results stored on the server.

[2476] Step 4:

[2477] Matching and Ad Generation

[2478] Input: educational institution needs information and education professionals' skill information and sentiment data.

[2479] Specific operation: The server calls the generation AI, compares the needs information with the skill information and emotion data, lists the most suitable education experts, and determines the content of the generated advertisement.

[2480] Data processing / calculation: Generative AI analyzes large amounts of data and generates optimal matching results and advertisements.

[2481] Output: Best match results and advertisements notified to educational institutions and education professionals.

[2482] Step 5:

[2483] Ad updates and delivery

[2484] Input: Generated ad content.

[2485] Specific operation: The server saves the generated advertisement in a database, updates the content as necessary, and delivers the advertisement to the target user.

[2486] Data processing / calculation: Refer to the database, monitor the effectiveness of the advertisement, and generate and deliver new advertisements if necessary.

[2487] Output: Updated advertisements delivered to educational institutions and education professionals.

[2488] This series of steps enables highly accurate matching that takes into account user emotional data, as well as the creation and delivery of effective targeted advertisements.

[2489] 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.

[2490] 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.

[2491] 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.

[2492] [Fourth embodiment]

[2493] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[2494] 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.

[2495] 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).

[2496] 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.

[2497] 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.

[2498] Camera 42 is a small digital camera equipped with an optical system includ...

Claims

1. A sharing platform to properly match educational institutions with educational experts. a means for registering the skills and qualifications of educational professionals; a means for inputting needs information from educational institutions; A generative artificial intelligence means for analyzing the needs information of educational experts and educational institutions to generate optimal matches; a means of communicating the match results to educational institutions and education professionals; A system including:

2. a server means for proposing interview dates and storing the selection results in a database; A means for human and artificial intelligence to evaluate the skills and qualifications of educational professionals; The system of claim 1 further comprising:

3. A means for selecting optimal educational materials provided by the generative artificial intelligence based on requests from educational institutions; a means for informing educational professionals of the selected educational materials and providing download links; a server means for automating administrative tasks and updating education-related information into a database; The system of claim 1 further comprising:

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