System

Abstract

A system is provided.SOLUTION: A system comprising: input means for inputting a theme of a lesson, a target grade, and necessary materials; reception means for receiving data input by the input means; generation means for automatically generating content of the lesson based on the data received by the reception means; and display means for displaying the content generated by the generation means.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] In today's educational environment, educators spend a lot of time preparing lessons and dealing with parents, leaving them with insufficient time to interact with students. This has led to a decline in the quality of education, leading to educational disparities and declining student academic performance. The purpose of this invention is to improve the quality of education by reducing the workload of educators and increasing the time they spend communicating with students. [Means for solving the problem]

[0005] The present invention provides a system including an input means for inputting the lesson theme, target grade, and necessary materials, a receiving means for receiving the data input by the input means, a generating means for automatically generating lesson content based on the data received by the receiving means, and a display means for displaying the content generated by the generating means. The system also provides an input means for inputting inquiries from parents, a receiving means for receiving the inquiries input by the input means, a generating means for analyzing the inquiries received by the receiving means and generating appropriate answers, and a display means for displaying the answers generated by the generating means, thereby reducing the workload of teachers and improving the efficiency and quality of education. Furthermore, the receiving means is located on a server and the display means is located on the teacher's terminal, thereby achieving efficient and intuitive operation.

[0006] "Input means" refers to a device or interface that allows a user to input into the system the topic of the lesson, the target grade, necessary materials, or inquiries from parents.

[0007] The "receiving means" is a device or function for receiving data input by the input means on the server side.

[0008] The "generation means" refers to an algorithm or program for automatically generating lesson content and responses to parents based on the data received by the reception means.

[0009] The "display means" is a device or interface for visually displaying to the user the content and answers generated by the generation means.

[0010] "Class theme" refers to the specific topics or content covered in the class.

[0011] "Target grade" refers to the grade or educational level of students taking the class.

[0012] "Necessary materials" refers to materials and information needed to prepare for and conduct a lesson.

[0013] "Inquiry content" refers to the content of questions or inquiries that parents make to teachers. [Brief explanation of the drawings]

[0014] [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

[0015] 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.

[0016] First, the terms used in the following description will be explained.

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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."

[0022] [First embodiment]

[0023] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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."

[0035] The present invention provides a system for reducing the workload of educators and improving the quality of education. This system supports lesson preparation and parental support. Specific embodiments of the system are described below.

[0036] Class preparation support

[0037] Examples:

[0038] The user (teacher) uses a terminal to input the lesson theme, target grade, and required materials. For example, "Mathematics lesson for second-year junior high school students, theme is simultaneous equations, required materials are practice problems and slides." The terminal then sends this information to the server.

[0039] The server analyzes the received data and calls a generative AI to automatically generate content for related lessons. Specifically, it generates exercises, sample answers, and slides related to simultaneous equations. The generated content is sent from the server to the device, which displays it to the user. The user can then edit and modify the displayed content.

[0040] Support for parental interaction

[0041] Examples:

[0042] The user (teacher) uses the device to input the parent's inquiry. For example, they might input "Inquiry about this week's lesson content." The device then sends this information to the server.

[0043] The server analyzes the received inquiry and generates an appropriate answer using generative AI. Specifically, it generates an answer such as, "In this week's class, we learned about simultaneous equations and their applications. To check your child's understanding, please try solving the following review problem together." The generated answer is sent from the server to the device, which displays it to the user. The user can then edit and revise the displayed answer and send it to their parent.

[0044] System configuration

[0045] 1. Input Method

[0046] A device or interface that allows users to input lesson topics, target grades, required materials, or parental inquiries.

[0047] 2. Receiving Method

[0048] A device or function that allows a terminal to send input data or inquiry content to a server, which then receives it.

[0049] 3. Generation means

[0050] Algorithms and programs that automatically generate lesson content and responses to parents based on the data received by the server.

[0051] 4. Display means

[0052] A device or interface for visually displaying generated content and answers to the user.

[0053] With the above configuration, the present invention can reduce the workload of educators and increase the time they have to communicate with students, thereby improving the quality of education.

[0054] The processing flow will be explained below.

[0055] Class preparation support

[0056] Step 1:

[0057] The user uses the terminal to input the lesson topic, target grade, and necessary materials.

[0058] Step 2:

[0059] The terminal transmits the input data to the server.

[0060] Step 3:

[0061] The server parses the data it receives.

[0062] Step 4:

[0063] The server calls the generative AI and automatically generates lesson content.

[0064] Specifically, it generates relevant exercises, sample answers, slides, etc. based on the lesson theme, target grade, and type of material.

[0065] Step 5:

[0066] The server transmits the generated content to the terminal.

[0067] Step 6:

[0068] The terminal displays the generated content to the user.

[0069] The user can view the displayed content and edit or modify it as necessary.

[0070] Support for parental interaction

[0071] Step 1:

[0072] The user uses the terminal to input the inquiry from the parent.

[0073] Step 2:

[0074] The terminal transmits the input inquiry to the server.

[0075] Step 3:

[0076] The server analyzes the query received.

[0077] Specifically, it uses natural language processing (NLP) to understand the query and extract information to generate an appropriate answer.

[0078] Step 4:

[0079] The server calls a generative AI and automatically generates an appropriate response for the parent.

[0080] Specifically, it generates a response based on the inquiry and also suggests providing additional information if necessary.

[0081] Step 5:

[0082] The server sends the generated response to the terminal.

[0083] Step 6:

[0084] The terminal displays the generated answer to the user.

[0085] The user can review the displayed answers, edit or correct them as necessary, and then send the final answers to the parents.

[0086] Through these steps, the system reduces the workload of educators and enables them to provide education and respond to parents efficiently.

[0087] Example 1

[0088] 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."

[0089] In recent years, the increasing workload of teachers has become a problem in the educational field. In particular, the time required for lesson preparation and parental support is significant, raising concerns that this could result in a decline in the quality of education. Furthermore, due to a lack of support for providing appropriate lesson content and prompt, useful responses to parents, teachers expend a great deal of effort on these tasks. The present invention aims to solve these problems by providing a system that efficiently supports lesson preparation and parental support.

[0090] 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.

[0091] In this invention, the server includes an input means for inputting the lesson theme, target grade, and necessary materials, a receiving means for receiving the data input by the input means, a data analysis means for analyzing the received data, a prompt generation means for generating a prompt sentence to be sent to the generative AI model, a generation means for automatically generating lesson content based on the generated prompt sentence, and a display means for displaying the generated content. This enables teachers to quickly and efficiently prepare for lessons and respond to parents.

[0092] "Input means" refers to a device or interface that allows a user to input information.

[0093] The "receiving means" is a device or function for receiving data input by the input means.

[0094] The "data analysis means" refers to an algorithm or program for analyzing the data received by the receiving means.

[0095] The "prompt generation means" is a mechanism by which the data analysis means generates a prompt sentence to be sent to the generative AI model.

[0096] A "generation means" is an algorithm or program for automatically generating lesson content and answers based on a prompt.

[0097] The "display means" is a device or interface for visually displaying to the user the content and answers generated by the generation means.

[0098] A "generative AI model" is a model that automatically generates specific content or answers based on a prompt.

[0099] A "server" is a computer system that receives and analyzes data, operates generation means, and so on.

[0100] "Terminal" means a device operated by a user to display and edit data sent from a server.

[0101] "Class content" refers to educational materials such as exercises, sample answers, and slides that are generated based on the theme of the class.

[0102] "Inquiry content" refers to information regarding questions or requests from parents.

[0103] A "response" is an appropriate response message to the parent's inquiry.

[0104] The present invention is a system for reducing the workload of educators and improving the quality of education. This system supports lesson preparation and parental support, and a specific embodiment thereof is described below.

[0105] System configuration

[0106] The system includes the following hardware and software:

[0107] 1. Input Method

[0108] It is a device or interface that allows users (teachers) to input lesson topics, target grades, necessary materials, or inquiries from parents.

[0109] Examples: keyboards, touchscreens, voice input devices

[0110] 2. Receiving Method

[0111] This is a device or function that allows the terminal to send input data and inquiry contents to the server, and the server to receive them.

[0112] Examples: Internet connection, API communication interface

[0113] 3. Data Analysis Methods

[0114] The server contains algorithms and programs that analyze the data it receives.

[0115] Example: Data analysis program

[0116] 4. Prompt Generation Methods

[0117] The server is a mechanism for generating prompt sentences to send to the generative AI model.

[0118] Examples: text generation programs, natural language processing algorithms

[0119] 5. Generation means

[0120] The server is an algorithm or program that automatically generates lesson content and responses to parents based on prompts.

[0121] Example: Generative AI models (e.g., OpenAI's GPT-4)

[0122] 6. Display means

[0123] It is a device or interface for visually displaying generated content and answers to the user.

[0124] Examples: monitors, tablet screens, smartphone screens

[0125] Class preparation support

[0126] The user (teacher) uses a device to input the lesson theme, target grade, and necessary materials. For example, they might input "Math class for second-year junior high school students, theme is simultaneous equations, necessary materials are practice problems and slides." The device then sends this input information to the server. The server analyzes the received data and, based on the analysis results, creates a prompt to send to a generative AI model (for example, OpenAI's GPT-4). The generated prompt is "Create lesson materials for a 2nd-year junior high school math class. The topic is simultaneous equations. Generate practice problems and slides." The generative AI model generates lesson content based on this prompt; specifically, practice problems related to simultaneous equations, sample answers, and slides are generated. The generated content is sent from the server to the device, which then displays it to the teacher. The teacher can view and edit this generated content.

[0127] Support for parental interaction

[0128] The user (teacher) uses the device to input the parent's inquiry. For example, they might input "Inquiry about this week's class content." The device then sends this information to the server. The server analyzes the received inquiry and, based on the analysis results, creates a prompt to send to a generative AI model (e.g., OpenAI's GPT-4). The generated prompt is "Provide a detailed response to a parent's inquiry about this week's class content. The class covered simultaneous equations and their applications. Include a suggestion for reviewing the material with their child." The generative AI model then generates an answer based on this prompt, specifically, "In this week's class, we learned about simultaneous equations and their applications. To check your child's understanding, please solve the following review problem together." The generated answer is sent from the server to the device, where it is displayed to the teacher. The teacher can view, edit, or modify the answer and then send it to the parent.

[0129] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0130] Class preparation support

[0131] Processing Steps

[0132] Step 1:

[0133] The user inputs the lesson topic, target grade, and necessary materials into the terminal.

[0134] Input: "8th grade math class, topic: simultaneous equations, required materials: practice problems and slides"

[0135] Output: The device holds this input data.

[0136] Step 2:

[0137] The terminal transmits the input data to the server.

[0138] Specific operation: The device uses the API to send data to the server as an HTTP request.

[0139] Input: Data entered by the user

[0140] Output: The server receives the data.

[0141] Step 3:

[0142] The server parses the received data.

[0143] Specific operation: The server launches a data analysis program and extracts keywords such as "simultaneous equations" and "second-year junior high school student."

[0144] Input: Data received from the terminal

[0145] Output: Extracted keyword list

[0146] Step 4:

[0147] The server generates a prompt to send to the generative AI model.

[0148] Specific operation: The server uses a text generator to create the following prompt: "Create lesson materials for a 2nd-year junior high school math class. The topic is simultaneous equations. Generate practice problems and slides."

[0149] Input: Extracted keyword list

[0150] Output: Generated prompt statement

[0151] Step 5:

[0152] A generative AI model generates lesson content.

[0153] How it works: Based on the prompt, the generative AI model generates practice problems, sample answers, and slides related to simultaneous equations.

[0154] Input: Generated prompt statement

[0155] Output: Generated lesson content (exercises, sample answers, slides)

[0156] Step 6:

[0157] The server transmits the generated content to the terminal.

[0158] Specific operation: The server sends the generated lesson content to the terminal as an HTTP response.

[0159] Input: Generated lesson content

[0160] Output: The device receives the lesson content.

[0161] Step 7:

[0162] The terminal displays the generated content to the user.

[0163] Specific operation: The device launches a program to visually display the data received, allowing the user to confirm the displayed content.

[0164] Input: Lesson content received from the server

[0165] Output: The content that is displayed to the user

[0166] Support for parental interaction

[0167] Processing Steps

[0168] Step 1:

[0169] The user inputs the parent's inquiry into the terminal.

[0170] Input: "Inquiry about this week's class content"

[0171] Output: The device holds this input data.

[0172] Step 2:

[0173] The terminal transmits the input inquiry to the server.

[0174] Specific operation: The device uses the API to send the inquiry to the server as an HTTP request.

[0175] Input: The query entered by the user

[0176] Output: The server receives the query.

[0177] Step 3:

[0178] The server analyzes the query.

[0179] Specific operation: The server launches a data analysis program and extracts keywords such as "class content" and "inquiry."

[0180] Input: Inquiry received from the device

[0181] Output: Extracted keyword list

[0182] Step 4:

[0183] The server generates a prompt to send to the generative AI model.

[0184] What it does: The server uses a text generator to create the following prompt: "Provide a detailed response to a parent's inquiry about this week's class content. The class covered simultaneous equations and their applications. Include a suggestion for reviewing the material with their child."

[0185] Input: Extracted keyword list

[0186] Output: Generated prompt statement

[0187] Step 5:

[0188] A generative AI model generates the answer.

[0189] Specific behavior: The generative AI model generates an appropriate answer based on the prompt.

[0190] Input: Generated prompt statement

[0191] Output: Generated answer (Example: This week in class we learned about simultaneous equations and their applications. To check your child's understanding, try working through these review questions together.)

[0192] Step 6:

[0193] The server sends the generated response to the terminal.

[0194] Specific operation: The server sends the generated answer to the device as an HTTP response.

[0195] Input: Generated answer

[0196] Output: The device receives the answer.

[0197] Step 7:

[0198] The terminal displays the generated answer to the user.

[0199] Specific operation: The device launches a program to visually display the data received, allowing the user to confirm the displayed answer.

[0200] Input: Answer received from the server

[0201] Output: The answer that is displayed to the user

[0202] (Application example 1)

[0203] 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."

[0204] In conventional education systems, teachers have to spend a lot of time preparing lessons and responding to parents, limiting the room for improving the quality of education. It is also difficult for teachers to quickly obtain necessary materials and content or efficiently respond to inquiries from parents. This increases the workload of teachers and reduces the time they have to communicate with students. The purpose of this invention is to solve these problems, reduce the workload of educators, and improve the quality of education.

[0205] 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.

[0206] In this invention, the server includes an input means for inputting the lesson theme, target grade, and necessary materials, a receiving means for receiving the data input by the input means, and a generating means for automatically generating lesson content based on the data received by the receiving means. This makes it possible to display content generated based on prompt sentences on the display of the smart glasses. Furthermore, by including an input means for inputting inquiries from parents, a receiving means for receiving the inquiries input by the input means, and a generating means for analyzing the inquiries received by the receiving means and generating appropriate answers, it is possible to display answers generated based on prompt sentences on the display of the smart glasses. This reduces the workload of educators and improves the quality of education.

[0207] Key Word Definitions

[0208] A "lesson topic" is a specific content or topic that an educator teaches.

[0209] "Target grade" refers to the grade of students taking the class.

[0210] "Necessary materials" refers to teaching materials and reference materials needed to conduct the lesson.

[0211] "Input means" refers to a device or interface that allows a user to input data or inquiries.

[0212] The "receiving means" refers to a device or function for receiving data or inquiry content input by the input means.

[0213] The "generation means" refers to an algorithm or program that automatically generates content or answers based on the data received by the reception means.

[0214] "Display means" refers to a device or interface for visually displaying generated content and answers to the user.

[0215] A "prompt sentence" is a specific input sentence that instructs the generative AI on what content to generate.

[0216] "Smart glasses" are eyeglass-type devices with computer functions that can provide users with visual information in real time.

[0217] "Form for carrying out the invention" of the specification

[0218] The present invention relates to a system for reducing the workload of educators and improving the quality of education. This system is designed to support lesson preparation and parental support. Specific embodiments of the present invention will be described below.

[0219] (Class preparation support)

[0220] Consider the example of a teacher using smart glasses. First, the teacher inputs the lesson topic, target grade, and necessary materials into the smart glasses via voice input or a touch interface, such as "Mathematics class for second-year junior high school students, the topic is simultaneous equations, and the necessary materials are practice problems and slides." This input information is then sent from the device to the server.

[0221] The server analyzes the received information and automatically generates appropriate lesson content using a generative AI model. Specifically, practice problems, sample solutions, and slides related to simultaneous equations are automatically generated. The generated content is sent from the server to the smart glasses in real time, where teachers can review it and immediately edit or revise it if necessary.

[0222] (Support for parents)

[0223] Smart glasses are also useful for teachers when communicating with parents. For example, teachers can input questions from parents, such as "questions about this week's lesson content," using voice input or a touch interface. This information is also sent from the device to the server.

[0224] The server analyzes the received inquiry and automatically generates an appropriate answer using a generative AI model. Specifically, it might generate an answer such as, "In this week's class, we learned about simultaneous equations and their applications. To check your child's understanding, please try solving the following review problem together." The generated answer is sent from the server to the smart glasses in real time, where the teacher can review it and, if necessary, instantly edit or revise it before sending it to the parent.

[0225] (Hardware and software used)

[0226] The following hardware and software are used in implementing the present invention.

[0227] Hardware:

[0228] Smart glasses (display information and accept voice and touch input)

[0229] Smartphone (linked to smart glasses and communicating with the server)

[0230] Cloud server (receives, analyzes, generates, and transmits data)

[0231] software:

[0232] OpenAI API (provides generative AI models)

[0233] Python (a programming language for writing programs to receive, analyze, and process data)

[0234] (Example)

[0235] Example of lesson preparation:

[0236] When a teacher enters "Mathematics class for second-year junior high school students, topic is simultaneous equations, required materials are practice problems and slides" into the input field on the smart glasses, the generation AI uses this information to generate appropriate practice problems, sample answers, and slides, which are then displayed on the smart glasses.

[0237] Examples of parental interactions:

[0238] When a teacher types "Inquiry about this week's lesson content" into the input field on the smart glasses, the generative AI generates an appropriate response to the inquiry, which the teacher confirms and then sends to the parent.

[0239] In this way, the present invention saves educators time and effort and provides a higher quality education.

[0240] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0241] Program processing flow

[0242] Class preparation support

[0243] Step 1:

[0244] The user (teacher) inputs the lesson topic, target grade, and necessary materials into the smart glasses.

[0245] Input: 8th grade math class, topic is simultaneous equations, required materials are practice problems and slides.

[0246] Output: Send input data from smart glasses to the device.

[0247] Step 2:

[0248] The terminal transmits the data entered by the user to the server.

[0249] Input: Lesson topic, target grade, and required materials information entered by the teacher.

[0250] Output: Sends input data to the server.

[0251] Step 3:

[0252] The server analyzes the received data and calls a generative AI model to create a prompt.

[0253] Input: Teacher input data.

[0254] Data processing: Prompt generation. For example, "Generate exercises and slides for a simultaneous equations class for eighth graders."

[0255] Output: The generated prompt statement.

[0256] Step 4:

[0257] The server generates lesson content using the generative AI model.

[0258] Input: The generated prompt statement.

[0259] Data Calculation: Generate simultaneous equation practice problems, sample answers, and slides based on generated prompts.

[0260] Output: The generated lesson content.

[0261] Step 5:

[0262] The server transmits the generated content to the terminal.

[0263] Input: Generated lesson content.

[0264] Output: Send lesson content to the device.

[0265] Step 6:

[0266] The lesson content received by the device is displayed on the smart glasses.

[0267] Input: Lesson content sent from the server.

[0268] Output: Display content on the smart glasses display.

[0269] Support for parental interaction

[0270] Step 1:

[0271] The user (teacher) inputs the parent's inquiry into the smart glasses.

[0272] Input: "Inquiry about this week's class content"

[0273] Output: Send input data from smart glasses to the device.

[0274] Step 2:

[0275] The terminal transmits the inquiry content input by the user to the server.

[0276] Input: The inquiry entered by the instructor.

[0277] Output: Sends input data to the server.

[0278] Step 3:

[0279] The server analyzes the received query and calls a generative AI model to create a prompt.

[0280] Input: Teacher input data.

[0281] Data processing: Generate prompt sentences. For example, "Parental inquiry: Please respond appropriately to the inquiry about this week's lesson content."

[0282] Output: The generated prompt statement.

[0283] Step 4:

[0284] The server uses the generative AI model to generate answers for the parents.

[0285] Input: The generated prompt statement.

[0286] Data Calculation: Generates appropriate answers to queries based on generated prompts. For example, "In class this week, we learned about simultaneous equations and their applications."

[0287] Output: The generated answer.

[0288] Step 5:

[0289] The server sends the generated response to the terminal.

[0290] Input: The generated answer.

[0291] Output: Sends the answer to the terminal.

[0292] Step 6:

[0293] The answer received by the device is displayed on the smart glasses.

[0294] Input: The answer sent by the server.

[0295] Output: Show the answer on the smart glasses display.

[0296] 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.

[0297] The present invention provides a system for reducing the workload of educators and improving the quality of education. This system supports lesson preparation and parental support, and also includes an emotion engine for recognizing the emotions of users (teachers). Specific embodiments of the system are described below.

[0298] Class preparation support

[0299] Examples:

[0300] The user uses the device to input the lesson topic, target grade, and required materials. For example, they might input "math class for second-year junior high school students, topic is simultaneous equations, required materials are practice problems and slides." The device then sends this information to the server.

[0301] The server analyzes the received data and calls the generative AI and emotion engine. The emotion engine recognizes the emotion expressed by the user when inputting and customizes the lesson content based on that emotion. For example, if the user is feeling stressed, it generates simple content to ease the stress. The generative AI generates practice problems, sample answers, and slides related to simultaneous equations.

[0302] The server sends the generated content to the terminal, which displays it to the user, who can then view the displayed content and edit or modify it as needed.

[0303] Support for parental interaction

[0304] Examples:

[0305] The user uses the device to input the parent's inquiry. For example, the user inputs "Inquiry about this week's lesson content." The device then sends this information to the server.

[0306] The server analyzes the received inquiry and generates an appropriate answer using an emotion engine and generative AI. The emotion engine recognizes the user's emotion when typing and customizes the answer based on that emotion. For example, if the user is tired, it generates a quick and concise answer. The generated answer might be something like, "In this week's class, we learned about simultaneous equations and their applications. To check your child's understanding, try solving the following review problem together."

[0307] The server sends the generated answers to the device, which displays them to the user. The user can check the displayed answers, edit or correct them as necessary, and send the final answers to their parents.

[0308] System configuration

[0309] 1. Input Method

[0310] A device or interface that allows users to input lesson topics, target grades, required materials, or parental inquiries.

[0311] 2. Receiving Method

[0312] A device or function that allows a terminal to send input data or inquiry content to a server, which then receives it.

[0313] 3. Generation means

[0314] Algorithms and programs that automatically generate lesson content and responses to parents based on the data received by the server.

[0315] 4. Display means

[0316] A device or interface for visually displaying generated content and answers to the user.

[0317] 5. Emotion Engine

[0318] An engine that recognizes the emotions of users as they type and customizes lesson content and responses based on those emotions.

[0319] With the above configuration, the present invention reduces the workload of educators and increases the time they spend communicating with students, thereby improving the quality of education. Furthermore, the inclusion of an emotion engine allows for flexible support based on the user's emotions.

[0320] The processing flow will be explained below.

[0321] Class preparation support

[0322] Step 1:

[0323] The user uses the terminal to input the lesson topic, target grade, and necessary materials.

[0324] Step 2:

[0325] The terminal transmits the input data to the server.

[0326] Step 3:

[0327] The server parses the data it receives.

[0328] Step 4:

[0329] The server invokes the emotion engine to recognize the emotion of the user's input.

[0330] For example, if the user is feeling stressed, that emotion is recognized.

[0331] Step 5:

[0332] Based on the recognized emotions, the server calls a generative AI to generate customized lesson content.

[0333] Specifically, if the user is feeling stressed, simple and less burdensome content is generated.

[0334] Examples of generated content include simultaneous equation exercises, sample solutions, and slides.

[0335] Step 6:

[0336] The server transmits the generated content to the terminal.

[0337] Step 7:

[0338] The terminal displays the generated content to the user.

[0339] The user can view the displayed content and edit or modify it as necessary.

[0340] Support for parental interaction

[0341] Step 1:

[0342] The user uses the terminal to input the inquiry from the parent.

[0343] Step 2:

[0344] The terminal transmits the input inquiry to the server.

[0345] Step 3:

[0346] The server analyzes the query received.

[0347] Step 4:

[0348] The server invokes the emotion engine to recognize the emotion of the user's input.

[0349] For example, if the user is tired, it recognizes that emotion.

[0350] Step 5:

[0351] The server uses generative AI to generate appropriate answers based on the recognized emotions.

[0352] Specifically, if the user is tired, a quick and concise response is generated.

[0353] An example of a generated answer might be, "In class this week we learned about simultaneous equations and their applications. To make sure your child understands, try working through the review questions below together."

[0354] Step 6:

[0355] The server sends the generated response to the terminal.

[0356] Step 7:

[0357] The terminal displays the generated answer to the user.

[0358] The user can review the displayed answers, edit or correct them as necessary, and then send the final answers to the parents.

[0359] Through these steps, the system can recognize the user's emotions and support them in preparing lessons and responding to parents accordingly.

[0360] Example 2

[0361] 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."

[0362] In recent years, the workload of educators has increased, with a large amount of time and effort being spent on lesson preparation and parental interactions. This has led to concerns about increased stress among educators and a decline in the quality of education. Furthermore, because it is difficult to respond flexibly to the emotions of each individual educator, efficient and effective educational support is required. Therefore, a system is needed to reduce educators' workload and improve the quality of education.

[0363] 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.

[0364] In this invention, the server includes input means for inputting the lesson theme, target grade, and necessary materials, receiving means for receiving the data input by the input means, processing means having an emotion engine for analyzing the data received by the receiving means and recognizing emotions, generation means for customizing and automatically generating lesson content based on the emotions recognized by the emotion engine, and display means for displaying the content generated by the generation means. This makes it possible to generate customized lesson content according to the emotional state of the educator, and to respond quickly and appropriately to parents.

[0365] An "input means" is a device or interface through which a user inputs information.

[0366] The "receiving means" is a function or device that acquires data input by the input means.

[0367] An "emotion engine" is software or algorithms for recognizing and analyzing a user's emotions.

[0368] A "generator" is an algorithm or program for automatically generating content or responses based on received data and recognized sentiment.

[0369] A "display means" is a device or interface for visually presenting generated content and answers to a user.

[0370] A "server" is a computer system responsible for receiving, processing, and transmitting data over a network.

[0371] "Terminal" means a device such as a computer, tablet, or smartphone that a user uses to input and display information.

[0372] "Content" refers to educational materials created according to the lesson theme and target grade.

[0373] A "response" is a text reply generated in response to an inquiry from a parent.

[0374] This system aims to reduce the workload of educators and enable flexible responses according to their emotions. This system provides two main functions: support for lesson preparation and support for parental interaction.

[0375] Class preparation support

[0376] The user inputs the lesson topic, target grade, and required materials using the device, and the information is sent to the server. For example, if a user inputs "math class for second-year junior high school students, topic is simultaneous equations, required materials are practice problems and slides," the device encrypts this information and sends it to the server. The server analyzes the received data and calls the emotion engine and generative AI.

[0377] The emotion engine analyzes the user's emotions when they input information and recognizes their stress level and fatigue. Based on the analysis results, the generative AI automatically generates appropriate lesson content (practice questions, sample answers, slides, etc.). For example, if the user is feeling stressed, simple and easy-to-understand content is generated. The generated content is sent from the server to the device, where the user can review it and edit or modify it as necessary.

[0378] Support for parental interaction

[0379] When a user uses the device to input a parent's inquiry, the device encrypts the information and sends it to the server. For example, if a user inputs "Inquiry about this week's lesson content," the server analyzes the information and calls the emotion engine and generative AI.

[0380] The emotion engine analyzes the user's emotions when they input information and recognizes their fatigue and stress levels. Based on the analysis results, the generative AI automatically generates an appropriate answer. For example, if the user is tired, a short and concise answer will be generated. The generated answer is sent from the server to the device, where the user can review it, make corrections if necessary, and then send the final answer to their guardian.

[0381] Hardware and software used

[0382] Hardware: Devices (PCs, tablets, smartphones), servers

[0383] Software: Emotion engine, generative AI

[0384] Examples of concrete examples and prompts

[0385] Examples of lesson preparation:

[0386] The user types:

[0387] "Mathematics class for second-year junior high school students, the topic is simultaneous equations, and the necessary materials are practice problems and slides."

[0388] Examples of parental interactions:

[0389] The user types:

[0390] "Inquiry about this week's class content"

[0391] This allows appropriate data analysis and content generation at each processing step, reducing the workload of educators and improving the quality of education.

[0392] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0393] Class preparation support

[0394] Step 1:

[0395] The user uses the device to input the lesson topic, target grade, and necessary materials. Specifically, they launch a dedicated application and input "math lesson for second-year junior high school students, topic is simultaneous equations, necessary materials are practice problems and slides."

[0396] Input: lesson topic, target grade, required materials

[0397] Output: Input data

[0398] Step 2:

[0399] The terminal sends the entered data to the server, where it is encrypted and sent securely.

[0400] Input: Data entered by the user

[0401] Output: Encrypted data

[0402] Step 3:

[0403] The server analyzes the data it receives and verifies that the input is accurate and includes all required fields.

[0404] Input: Encrypted data

[0405] Output: Analysis results

[0406] Step 4:

[0407] The server calls the emotion engine to analyze the emotions entered by the user, which then recognizes the level of stress or fatigue.

[0408] Input: Analysis results and input data

[0409] Output: User's emotional state

[0410] Step 5:

[0411] The server calls the generative AI, which generates lesson content based on the received data and the recognized emotions. For example, if the user is feeling stressed, the generative AI will create simple and easy-to-understand exercises, sample answers, and slides.

[0412] Input: User's emotional state and input data

[0413] Output: Generated lesson content

[0414] Step 6:

[0415] The server re-encrypts the generated content data and transmits it to the terminal.

[0416] Input: Generated lesson content

[0417] Output: Encrypted lesson content

[0418] Step 7:

[0419] The device decodes the received data and visually displays it to the user, who can then review the displayed content and make edits or corrections as necessary.

[0420] Input: Encrypted lesson content

[0421] Output: Displayed lesson content

[0422] Support for parental interaction

[0423] Step 1:

[0424] The user uses the device to input the parent's inquiry. Specifically, the user launches a dedicated application and inputs "Inquiry about this week's lesson content."

[0425] Input: Parental inquiry

[0426] Output: Input data

[0427] Step 2:

[0428] The device sends the entered inquiry to the server, where the data is encrypted and sent securely.

[0429] Input: The query entered by the user

[0430] Output: Encrypted data

[0431] Step 3:

[0432] The server analyzes the data it receives to ensure that the input is accurate and that all required information is included.

[0433] Input: Encrypted data

[0434] Output: Analysis results

[0435] Step 4:

[0436] The server calls the emotion engine, which analyzes the emotions entered by the user and recognizes the level of fatigue and stress.

[0437] Input: Analysis results and input data

[0438] Output: User's emotional state

[0439] Step 5:

[0440] The server calls the generative AI, which generates an appropriate response based on the received data and the perceived emotion. For example, if the user is tired, the generative AI will create a quick and concise response.

[0441] Input: User's emotional state and input data

[0442] Output: The generated answer

[0443] Step 6:

[0444] The server re-encrypts the generated response data and transmits it to the terminal.

[0445] Input: Generated answer

[0446] Output: Encrypted answer

[0447] Step 7:

[0448] The device decrypts the received data and visually displays it to the user, who can then review the displayed answers, make corrections if necessary, and send the final answers to the parent.

[0449] Input: Encrypted answer

[0450] Output: The displayed answer

[0451] (Application example 2)

[0452] 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."

[0453] In conventional educational support systems and parental support systems, content and responses are generated without taking into account the feelings of educators, which can easily increase stress for educators and lead to a decline in the quality of education and parental support.In addition, due to a lack of flexible support based on user feelings, the user experience is uniform and unable to respond to individual needs.

[0454] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes input means for inputting the lesson theme, target grade, and necessary materials, receiving means for receiving the data input by the input means, generation means for automatically generating lesson content based on the data received by the receiving means, display means for displaying the content generated by the generation means, an emotion engine for recognizing emotions from the user's input content, and adjustment means for customizing the content generated based on the emotion data recognized by the emotion engine. This makes it possible to generate content and answers customized according to the user's emotions, reducing the workload of educators and improving the quality of education and parental support.

[0455] "Class theme" refers to the specific content or subject matter that educators deal with in class.

[0456] "Target grade" refers to the grade of students who are eligible to take the class.

[0457] "Necessary materials" refers to teaching materials and related materials used to smoothly conduct classes.

[0458] "Input means" refers to a device or interface that allows a user to input information into a system.

[0459] The "receiving means" refers to a device or function for receiving data transmitted from the input means.

[0460] "Generation means" refers to an algorithm or program for automatically generating content or answers based on data received by the receiving means.

[0461] "Display means" means a device or interface for visually displaying generated content or answers to a user.

[0462] "Emotion engine" refers to a system or software for recognizing emotions from user input and extracting that emotion data.

[0463] "Adjustment means" refers to a function or program for customizing the content or answers generated based on the emotional data recognized by the emotion engine.

[0464] MODE FOR CARRYING OUT THE INVENTION

[0465] The present invention provides a system for reducing the workload of educators and users of online shopping sites and improving quality. Specific embodiments of the system will be described below.

[0466] 1. Educational Support System

[0467] 1.1. Class preparation support

[0468] Examples:

[0469] The user uses a smartphone or tablet device to input the lesson topic, target grade, and required materials. For example, this information might be "a math class for second-year junior high school students, the topic is simultaneous equations, and the required materials are practice problems and slides." The device then sends this information to the server.

[0470] The server analyzes the received data and activates the emotion engine. The emotion engine recognizes the emotion expressed by the user when inputting the data and customizes the lesson content based on that emotion data. For example, if the user is feeling stressed, it generates simple content to ease their stress.

[0471] Next, the generative AI model generates practice problems, sample solutions, and slides related to simultaneous equations. The server sends the generated content to the device, which displays it to the user. The user can review the displayed content and edit or modify it as needed.

[0472] 2. Implementation of a personalized shopping assistant for an online shopping site

[0473] Shopping Assistant

[0474] Examples:

[0475] A user uses a smartphone to type, "I'm looking for the latest smartphone, but I don't know how to choose one." The device sends this information to the server.

[0476] The server analyzes the received data and activates the emotion engine, which recognizes the user's emotions when inputting and customizes product recommendations based on the emotion data. For example, if the user is tired, it generates a list of recommendations that emphasizes easy-to-use products.

[0477] Next, the generative AI model generates a product recommendation list based on the user's needs and emotions. The server sends the generated recommendation list to the device, which displays it to the user. The user then reviews the displayed recommendation list and selects suitable products.

[0478] Hardware and software used

[0479] Hardware:

[0480] 1. Smartphone

[0481] 2. Tablet devices

[0482] 3. Server

[0483] software:

[0484] 1. Emotion Engine: Software for recognizing emotions from user input

[0485] 2. Generative AI model: Software for automatically generating lesson content and product lists

[0486] Adding specific examples

[0487] Prompt Sentence Examples

[0488] Prompt: "I'm looking for the latest smartphone. I'm interested in its features and performance, but I'm a beginner and don't know how to choose one. I've been busy lately and I'm tired."

[0489] Product recommendations provided:

[0490] Product name: Smartphone Model X, Price: 100,000 yen, Features: High-performance camera, long-lasting battery

[0491] Product name: Smartphone Model Y, Price: ¥80,000, Features: Large screen display, easy-to-use UI

[0492] Product name: Smartphone Model Z, Price: 60,000 yen, Features: Waterproof, large storage capacity

[0493] Reason for recommendation: Because the user is feeling stressed or tired, we recommend products that are easy to use.

[0494] This enables the system to generate customized content and answers based on the user's emotions, reducing the workload of educators and online shopping site users and improving quality.

[0495] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0496] Program processing steps

[0497] Shopping assistant system

[0498] Step 1:

[0499] A user uses a smartphone to enter purchasing interests, such as "I'm looking for the latest smartphone, but I don't know how to choose one."

[0500] Input: Text data about purchases entered by the user

[0501] Output: Text data received by the server

[0502] Step 2:

[0503] The terminal sends the user's input to the server, where it can be processed.

[0504] Input: Text data entered by the user

[0505] Output: Text data sent to the server

[0506] Step 3:

[0507] The server analyzes the received text data and activates an emotion engine to recognize the user's emotions.

[0508] Input: Text data sent from the terminal

[0509] Data processing: Analysis of text data, emotion recognition using emotion engine

[0510] Output: Recognized emotion data

[0511] Step 4:

[0512] The server customizes product recommendations based on the recognized emotion data and generates product lists using a generative AI model.

[0513] Input: Recognized emotion data, user input text data

[0514] Data Computation: Customize product recommendations based on sentiment data, generate product lists using generative AI models

[0515] Output: A customized product recommendation list

[0516] Step 5:

[0517] The server sends the generated product recommendation list to the terminal, and the user receives the recommended product list.

[0518] Input: A customized product recommendation list

[0519] Output: Product recommendation list sent to the device

[0520] Step 6:

[0521] The device displays a customized product recommendation list to the user, who then reviews the displayed recommended products and selects the appropriate product.

[0522] Input: Product list sent from the server

[0523] Output: A visual list of products displayed to the user

[0524] Prompt Sentence Examples

[0525] Prompt: "I'm looking for the latest smartphone. I'm interested in its features and performance, but I'm a beginner and don't know how to choose one. I've been busy lately and I'm tired."

[0526] Product recommendations provided:

[0527] Product name: Smartphone Model X, Price: 100,000 yen, Features: High-performance camera, long-lasting battery

[0528] Product name: Smartphone Model Y, Price: ¥80,000, Features: Large screen display, easy-to-use UI

[0529] Product name: Smartphone Model Z, Price: 60,000 yen, Features: Waterproof, large storage capacity

[0530] Reason for recommendation: Because the user is feeling stressed or tired, we recommend products that are easy to use.

[0531]

[0532] 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.

[0533] 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.

[0534] 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.

[0535] [Second embodiment]

[0536] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0537] 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.

[0538] 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).

[0539] 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.

[0540] 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.

[0541] 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).

[0542] 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. 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.

[0543] 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.

[0544] 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.

[0545] 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.

[0546] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0547] 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."

[0548] The present invention provides a system for reducing the workload of educators and improving the quality of education. This system supports lesson preparation and parental support. Specific embodiments of the system are described below.

[0549] Class preparation support

[0550] Examples:

[0551] The user (teacher) uses a terminal to input the lesson theme, target grade, and required materials. For example, "Mathematics lesson for second-year junior high school students, theme is simultaneous equations, required materials are practice problems and slides." The terminal then sends this information to the server.

[0552] The server analyzes the received data and calls a generative AI to automatically generate content for related lessons. Specifically, it generates exercises, sample answers, and slides related to simultaneous equations. The generated content is sent from the server to the device, which displays it to the user. The user can then edit and modify the displayed content.

[0553] Support for parental interaction

[0554] Examples:

[0555] The user (teacher) uses the device to input the parent's inquiry. For example, they might input "Inquiry about this week's lesson content." The device then sends this information to the server.

[0556] The server analyzes the received inquiry and generates an appropriate answer using generative AI. Specifically, it generates an answer such as, "In this week's class, we learned about simultaneous equations and their applications. To check your child's understanding, please try solving the following review problem together." The generated answer is sent from the server to the device, which displays it to the user. The user can then edit and revise the displayed answer and send it to their parent.

[0557] System configuration

[0558] 1. Input Method

[0559] A device or interface that allows users to input lesson topics, target grades, required materials, or parental inquiries.

[0560] 2. Receiving Method

[0561] A device or function that allows a terminal to send input data or inquiry content to a server, which then receives it.

[0562] 3. Generation means

[0563] Algorithms and programs that automatically generate lesson content and responses to parents based on the data received by the server.

[0564] 4. Display means

[0565] A device or interface for visually displaying generated content and answers to the user.

[0566] With the above configuration, the present invention can reduce the workload of educators and increase the time they have to communicate with students, thereby improving the quality of education.

[0567] The processing flow will be explained below.

[0568] Class preparation support

[0569] Step 1:

[0570] The user uses the terminal to input the lesson topic, target grade, and necessary materials.

[0571] Step 2:

[0572] The terminal transmits the input data to the server.

[0573] Step 3:

[0574] The server parses the data it receives.

[0575] Step 4:

[0576] The server calls the generative AI and automatically generates lesson content.

[0577] Specifically, it generates relevant exercises, sample answers, slides, etc. based on the lesson theme, target grade, and type of material.

[0578] Step 5:

[0579] The server transmits the generated content to the terminal.

[0580] Step 6:

[0581] The terminal displays the generated content to the user.

[0582] The user can view the displayed content and edit or modify it as necessary.

[0583] Support for parental interaction

[0584] Step 1:

[0585] The user uses the terminal to input the inquiry from the parent.

[0586] Step 2:

[0587] The terminal transmits the input inquiry to the server.

[0588] Step 3:

[0589] The server analyzes the query received.

[0590] Specifically, it uses natural language processing (NLP) to understand the query and extract information to generate an appropriate answer.

[0591] Step 4:

[0592] The server calls a generative AI and automatically generates an appropriate response for the parent.

[0593] Specifically, it generates a response based on the inquiry and also suggests providing additional information if necessary.

[0594] Step 5:

[0595] The server sends the generated response to the terminal.

[0596] Step 6:

[0597] The terminal displays the generated answer to the user.

[0598] The user can review the displayed answers, edit or correct them as necessary, and then send the final answers to the parents.

[0599] Through these steps, the system reduces the workload of educators and enables them to provide education and respond to parents efficiently.

[0600] Example 1

[0601] 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."

[0602] In recent years, the increasing workload of teachers has become a problem in the educational field. In particular, the time required for lesson preparation and parental support is significant, raising concerns that this could result in a decline in the quality of education. Furthermore, due to a lack of support for providing appropriate lesson content and prompt, useful responses to parents, teachers expend a great deal of effort on these tasks. The present invention aims to solve these problems by providing a system that efficiently supports lesson preparation and parental support.

[0603] 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.

[0604] In this invention, the server includes an input means for inputting the lesson theme, target grade, and necessary materials, a receiving means for receiving the data input by the input means, a data analysis means for analyzing the received data, a prompt generation means for generating a prompt sentence to be sent to the generative AI model, a generation means for automatically generating lesson content based on the generated prompt sentence, and a display means for displaying the generated content. This enables teachers to quickly and efficiently prepare for lessons and respond to parents.

[0605] "Input means" refers to a device or interface that allows a user to input information.

[0606] The "receiving means" is a device or function for receiving data input by the input means.

[0607] The "data analysis means" refers to an algorithm or program for analyzing the data received by the receiving means.

[0608] The "prompt generation means" is a mechanism by which the data analysis means generates a prompt sentence to be sent to the generative AI model.

[0609] A "generation means" is an algorithm or program for automatically generating lesson content and answers based on a prompt.

[0610] The "display means" is a device or interface for visually displaying to the user the content and answers generated by the generation means.

[0611] A "generative AI model" is a model that automatically generates specific content or answers based on a prompt.

[0612] A "server" is a computer system that receives and analyzes data, operates generation means, and so on.

[0613] "Terminal" means a device operated by a user to display and edit data sent from a server.

[0614] "Class content" refers to educational materials such as exercises, sample answers, and slides that are generated based on the theme of the class.

[0615] "Inquiry content" refers to information regarding questions or requests from parents.

[0616] A "response" is an appropriate response message to the parent's inquiry.

[0617] The present invention is a system for reducing the workload of educators and improving the quality of education. This system supports lesson preparation and parental support, and a specific embodiment thereof is described below.

[0618] System configuration

[0619] The system includes the following hardware and software:

[0620] 1. Input Method

[0621] It is a device or interface that allows users (teachers) to input lesson topics, target grades, necessary materials, or inquiries from parents.

[0622] Examples: keyboards, touchscreens, voice input devices

[0623] 2. Receiving Method

[0624] This is a device or function that allows the terminal to send input data and inquiry contents to the server, and the server to receive them.

[0625] Examples: Internet connection, API communication interface

[0626] 3. Data Analysis Methods

[0627] The server contains algorithms and programs that analyze the data it receives.

[0628] Example: Data analysis program

[0629] 4. Prompt Generation Methods

[0630] The server is a mechanism for generating prompt sentences to send to the generative AI model.

[0631] Examples: text generation programs, natural language processing algorithms

[0632] 5. Generation means

[0633] The server is an algorithm or program that automatically generates lesson content and responses to parents based on prompts.

[0634] Example: Generative AI models (e.g., OpenAI's GPT-4)

[0635] 6. Display means

[0636] It is a device or interface for visually displaying generated content and answers to the user.

[0637] Examples: monitors, tablet screens, smartphone screens

[0638] Class preparation support

[0639] The user (teacher) uses a device to input the lesson theme, target grade, and necessary materials. For example, they might input "Math class for second-year junior high school students, theme is simultaneous equations, necessary materials are practice problems and slides." The device then sends this input information to the server. The server analyzes the received data and, based on the analysis results, creates a prompt to send to a generative AI model (for example, OpenAI's GPT-4). The generated prompt is "Create lesson materials for a 2nd-year junior high school math class. The topic is simultaneous equations. Generate practice problems and slides." The generative AI model generates lesson content based on this prompt; specifically, practice problems related to simultaneous equations, sample answers, and slides are generated. The generated content is sent from the server to the device, which then displays it to the teacher. The teacher can view and edit this generated content.

[0640] Support for parental interaction

[0641] The user (teacher) uses the device to input the parent's inquiry. For example, they might input "Inquiry about this week's class content." The device then sends this information to the server. The server analyzes the received inquiry and, based on the analysis results, creates a prompt to send to a generative AI model (e.g., OpenAI's GPT-4). The generated prompt is "Provide a detailed response to a parent's inquiry about this week's class content. The class covered simultaneous equations and their applications. Include a suggestion for reviewing the material with their child." The generative AI model then generates an answer based on this prompt, specifically, "In this week's class, we learned about simultaneous equations and their applications. To check your child's understanding, please solve the following review problem together." The generated answer is sent from the server to the device, where it is displayed to the teacher. The teacher can view, edit, or modify the answer and then send it to the parent.

[0642] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0643] Class preparation support

[0644] Processing Steps

[0645] Step 1:

[0646] The user inputs the lesson topic, target grade, and necessary materials into the terminal.

[0647] Input: "8th grade math class, topic: simultaneous equations, required materials: practice problems and slides"

[0648] Output: The device holds this input data.

[0649] Step 2:

[0650] The terminal transmits the input data to the server.

[0651] Specific operation: The device uses the API to send data to the server as an HTTP request.

[0652] Input: Data entered by the user

[0653] Output: The server receives the data.

[0654] Step 3:

[0655] The server parses the received data.

[0656] Specific operation: The server launches a data analysis program and extracts keywords such as "simultaneous equations" and "second-year junior high school student."

[0657] Input: Data received from the terminal

[0658] Output: Extracted keyword list

[0659] Step 4:

[0660] The server generates a prompt to send to the generative AI model.

[0661] Specific operation: The server uses a text generator to create the following prompt: "Create lesson materials for a 2nd-year junior high school math class. The topic is simultaneous equations. Generate practice problems and slides."

[0662] Input: Extracted keyword list

[0663] Output: Generated prompt statement

[0664] Step 5:

[0665] A generative AI model generates lesson content.

[0666] How it works: Based on the prompt, the generative AI model generates practice problems, sample answers, and slides related to simultaneous equations.

[0667] Input: Generated prompt statement

[0668] Output: Generated lesson content (exercises, sample answers, slides)

[0669] Step 6:

[0670] The server transmits the generated content to the terminal.

[0671] Specific operation: The server sends the generated lesson content to the terminal as an HTTP response.

[0672] Input: Generated lesson content

[0673] Output: The device receives the lesson content.

[0674] Step 7:

[0675] The terminal displays the generated content to the user.

[0676] Specific operation: The device launches a program to visually display the data received, allowing the user to confirm the displayed content.

[0677] Input: Lesson content received from the server

[0678] Output: The content that is displayed to the user

[0679] Support for parental interaction

[0680] Processing Steps

[0681] Step 1:

[0682] The user inputs the parent's inquiry into the terminal.

[0683] Input: "Inquiry about this week's class content"

[0684] Output: The device holds this input data.

[0685] Step 2:

[0686] The terminal transmits the input inquiry to the server.

[0687] Specific operation: The device uses the API to send the inquiry to the server as an HTTP request.

[0688] Input: The query entered by the user

[0689] Output: The server receives the query.

[0690] Step 3:

[0691] The server analyzes the query.

[0692] Specific operation: The server launches a data analysis program and extracts keywords such as "class content" and "inquiry."

[0693] Input: Inquiry received from the device

[0694] Output: Extracted keyword list

[0695] Step 4:

[0696] The server generates a prompt to send to the generative AI model.

[0697] What it does: The server uses a text generator to create the following prompt: "Provide a detailed response to a parent's inquiry about this week's class content. The class covered simultaneous equations and their applications. Include a suggestion for reviewing the material with their child."

[0698] Input: Extracted keyword list

[0699] Output: Generated prompt statement

[0700] Step 5:

[0701] A generative AI model generates the answer.

[0702] Specific behavior: The generative AI model generates an appropriate answer based on the prompt.

[0703] Input: Generated prompt statement

[0704] Output: Generated answer (Example: This week in class we learned about simultaneous equations and their applications. To check your child's understanding, try working through these review questions together.)

[0705] Step 6:

[0706] The server sends the generated response to the terminal.

[0707] Specific operation: The server sends the generated answer to the device as an HTTP response.

[0708] Input: Generated answer

[0709] Output: The device receives the answer.

[0710] Step 7:

[0711] The terminal displays the generated answer to the user.

[0712] Specific operation: The device launches a program to visually display the data received, allowing the user to confirm the displayed answer.

[0713] Input: Answer received from the server

[0714] Output: The answer that is displayed to the user

[0715] (Application example 1)

[0716] 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."

[0717] In conventional education systems, teachers have to spend a lot of time preparing lessons and responding to parents, limiting the room for improving the quality of education. It is also difficult for teachers to quickly obtain necessary materials and content or efficiently respond to inquiries from parents. This increases the workload of teachers and reduces the time they have to communicate with students. The purpose of this invention is to solve these problems, reduce the workload of educators, and improve the quality of education.

[0718] 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.

[0719] In this invention, the server includes an input means for inputting the lesson theme, target grade, and necessary materials, a receiving means for receiving the data input by the input means, and a generating means for automatically generating lesson content based on the data received by the receiving means. This makes it possible to display content generated based on prompt sentences on the display of the smart glasses. Furthermore, by including an input means for inputting inquiries from parents, a receiving means for receiving the inquiries input by the input means, and a generating means for analyzing the inquiries received by the receiving means and generating appropriate answers, it is possible to display answers generated based on prompt sentences on the display of the smart glasses. This reduces the workload of educators and improves the quality of education.

[0720] Key Word Definitions

[0721] A "lesson topic" is a specific content or topic that an educator teaches.

[0722] "Target grade" refers to the grade of students taking the class.

[0723] "Necessary materials" refers to teaching materials and reference materials needed to conduct the lesson.

[0724] "Input means" refers to a device or interface that allows a user to input data or inquiries.

[0725] The "receiving means" refers to a device or function for receiving data or inquiry content input by the input means.

[0726] The "generation means" refers to an algorithm or program that automatically generates content or answers based on the data received by the reception means.

[0727] "Display means" refers to a device or interface for visually displaying generated content and answers to the user.

[0728] A "prompt sentence" is a specific input sentence that instructs the generative AI on what content to generate.

[0729] "Smart glasses" are eyeglass-type devices with computer functions that can provide users with visual information in real time.

[0730] "Form for carrying out the invention" of the specification

[0731] The present invention relates to a system for reducing the workload of educators and improving the quality of education. This system is designed to support lesson preparation and parental support. Specific embodiments of the present invention will be described below.

[0732] (Class preparation support)

[0733] Consider the example of a teacher using smart glasses. First, the teacher inputs the lesson topic, target grade, and necessary materials into the smart glasses via voice input or a touch interface, such as "Mathematics class for second-year junior high school students, the topic is simultaneous equations, and the necessary materials are practice problems and slides." This input information is then sent from the device to the server.

[0734] The server analyzes the received information and automatically generates appropriate lesson content using a generative AI model. Specifically, practice problems, sample solutions, and slides related to simultaneous equations are automatically generated. The generated content is sent from the server to the smart glasses in real time, where teachers can review it and immediately edit or revise it if necessary.

[0735] (Support for parents)

[0736] Smart glasses are also useful for teachers when communicating with parents. For example, teachers can input questions from parents, such as "questions about this week's lesson content," using voice input or a touch interface. This information is also sent from the device to the server.

[0737] The server analyzes the received inquiry and automatically generates an appropriate answer using a generative AI model. Specifically, it might generate an answer such as, "In this week's class, we learned about simultaneous equations and their applications. To check your child's understanding, please try solving the following review problem together." The generated answer is sent from the server to the smart glasses in real time, where the teacher can review it and, if necessary, instantly edit or revise it before sending it to the parent.

[0738] (Hardware and software used)

[0739] The following hardware and software are used in implementing the present invention.

[0740] Hardware:

[0741] Smart glasses (display information and accept voice and touch input)

[0742] Smartphone (linked to smart glasses and communicating with the server)

[0743] Cloud server (receives, analyzes, generates, and transmits data)

[0744] software:

[0745] OpenAI API (provides generative AI models)

[0746] Python (a programming language for writing programs to receive, analyze, and process data)

[0747] (Example)

[0748] Example of lesson preparation:

[0749] When a teacher enters "Mathematics class for second-year junior high school students, topic is simultaneous equations, required materials are practice problems and slides" into the input field on the smart glasses, the generation AI uses this information to generate appropriate practice problems, sample answers, and slides, which are then displayed on the smart glasses.

[0750] Examples of parental interactions:

[0751] When a teacher types "Inquiry about this week's lesson content" into the input field on the smart glasses, the generative AI generates an appropriate response to the inquiry, which the teacher confirms and then sends to the parent.

[0752] In this way, the present invention saves educators time and effort and provides a higher quality education.

[0753] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0754] Program processing flow

[0755] Class preparation support

[0756] Step 1:

[0757] The user (teacher) inputs the lesson topic, target grade, and necessary materials into the smart glasses.

[0758] Input: 8th grade math class, topic is simultaneous equations, required materials are practice problems and slides.

[0759] Output: Send input data from smart glasses to the device.

[0760] Step 2:

[0761] The terminal transmits the data entered by the user to the server.

[0762] Input: Lesson topic, target grade, and required materials information entered by the teacher.

[0763] Output: Sends input data to the server.

[0764] Step 3:

[0765] The server analyzes the received data and calls a generative AI model to create a prompt.

[0766] Input: Teacher input data.

[0767] Data processing: Prompt generation. For example, "Generate exercises and slides for a simultaneous equations class for eighth graders."

[0768] Output: The generated prompt statement.

[0769] Step 4:

[0770] The server generates lesson content using the generative AI model.

[0771] Input: The generated prompt statement.

[0772] Data Calculation: Generate simultaneous equation practice problems, sample answers, and slides based on generated prompts.

[0773] Output: The generated lesson content.

[0774] Step 5:

[0775] The server transmits the generated content to the terminal.

[0776] Input: Generated lesson content.

[0777] Output: Send lesson content to the device.

[0778] Step 6:

[0779] The lesson content received by the device is displayed on the smart glasses.

[0780] Input: Lesson content sent from the server.

[0781] Output: Display content on the smart glasses display.

[0782] Support for parental interaction

[0783] Step 1:

[0784] The user (teacher) inputs the parent's inquiry into the smart glasses.

[0785] Input: "Inquiry about this week's class content"

[0786] Output: Send input data from smart glasses to the device.

[0787] Step 2:

[0788] The terminal transmits the inquiry content input by the user to the server.

[0789] Input: The inquiry entered by the instructor.

[0790] Output: Sends input data to the server.

[0791] Step 3:

[0792] The server analyzes the received query and calls a generative AI model to create a prompt.

[0793] Input: Teacher input data.

[0794] Data processing: Generate prompt sentences. For example, "Parental inquiry: Please respond appropriately to the inquiry about this week's lesson content."

[0795] Output: The generated prompt statement.

[0796] Step 4:

[0797] The server uses the generative AI model to generate answers for the parents.

[0798] Input: The generated prompt statement.

[0799] Data Calculation: Generates appropriate answers to queries based on generated prompts. For example, "In class this week, we learned about simultaneous equations and their applications."

[0800] Output: The generated answer.

[0801] Step 5:

[0802] The server sends the generated response to the terminal.

[0803] Input: The generated answer.

[0804] Output: Sends the answer to the terminal.

[0805] Step 6:

[0806] The answer received by the device is displayed on the smart glasses.

[0807] Input: The answer sent by the server.

[0808] Output: Show the answer on the smart glasses display.

[0809] 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.

[0810] The present invention provides a system for reducing the workload of educators and improving the quality of education. This system supports lesson preparation and parental support, and also includes an emotion engine for recognizing the emotions of users (teachers). Specific embodiments of the system are described below.

[0811] Class preparation support

[0812] Examples:

[0813] The user uses the device to input the lesson topic, target grade, and required materials. For example, they might input "math class for second-year junior high school students, topic is simultaneous equations, required materials are practice problems and slides." The device then sends this information to the server.

[0814] The server analyzes the received data and calls the generative AI and emotion engine. The emotion engine recognizes the emotion expressed by the user when inputting and customizes the lesson content based on that emotion. For example, if the user is feeling stressed, it generates simple content to ease the stress. The generative AI generates practice problems, sample answers, and slides related to simultaneous equations.

[0815] The server sends the generated content to the terminal, which displays it to the user, who can then view the displayed content and edit or modify it as needed.

[0816] Support for parental interaction

[0817] Examples:

[0818] The user uses the device to input the parent's inquiry. For example, the user inputs "Inquiry about this week's lesson content." The device then sends this information to the server.

[0819] The server analyzes the received inquiry and generates an appropriate answer using an emotion engine and generative AI. The emotion engine recognizes the user's emotion when typing and customizes the answer based on that emotion. For example, if the user is tired, it generates a quick and concise answer. The generated answer might be something like, "In this week's class, we learned about simultaneous equations and their applications. To check your child's understanding, try solving the following review problem together."

[0820] The server sends the generated answers to the device, which displays them to the user. The user can check the displayed answers, edit or correct them as necessary, and send the final answers to their parents.

[0821] System configuration

[0822] 1. Input Method

[0823] A device or interface that allows users to input lesson topics, target grades, required materials, or parental inquiries.

[0824] 2. Receiving Method

[0825] A device or function that allows a terminal to send input data or inquiry content to a server, which then receives it.

[0826] 3. Generation means

[0827] Algorithms and programs that automatically generate lesson content and responses to parents based on the data received by the server.

[0828] 4. Display means

[0829] A device or interface for visually displaying generated content and answers to the user.

[0830] 5. Emotion Engine

[0831] An engine that recognizes the emotions of users as they type and customizes lesson content and responses based on those emotions.

[0832] With the above configuration, the present invention reduces the workload of educators and increases the time they spend communicating with students, thereby improving the quality of education. Furthermore, the inclusion of an emotion engine allows for flexible support based on the user's emotions.

[0833] The processing flow will be explained below.

[0834] Class preparation support

[0835] Step 1:

[0836] The user uses the terminal to input the lesson topic, target grade, and necessary materials.

[0837] Step 2:

[0838] The terminal transmits the input data to the server.

[0839] Step 3:

[0840] The server parses the data it receives.

[0841] Step 4:

[0842] The server invokes the emotion engine to recognize the emotion of the user's input.

[0843] For example, if the user is feeling stressed, that emotion is recognized.

[0844] Step 5:

[0845] Based on the recognized emotions, the server calls a generative AI to generate customized lesson content.

[0846] Specifically, if the user is feeling stressed, simple and less burdensome content is generated.

[0847] Examples of generated content include simultaneous equation exercises, sample solutions, and slides.

[0848] Step 6:

[0849] The server transmits the generated content to the terminal.

[0850] Step 7:

[0851] The terminal displays the generated content to the user.

[0852] The user can view the displayed content and edit or modify it as necessary.

[0853] Support for parental interaction

[0854] Step 1:

[0855] The user uses the terminal to input the inquiry from the parent.

[0856] Step 2:

[0857] The terminal transmits the input inquiry to the server.

[0858] Step 3:

[0859] The server analyzes the query received.

[0860] Step 4:

[0861] The server invokes the emotion engine to recognize the emotion of the user's input.

[0862] For example, if the user is tired, it recognizes that emotion.

[0863] Step 5:

[0864] The server uses generative AI to generate appropriate answers based on the recognized emotions.

[0865] Specifically, if the user is tired, a quick and concise response is generated.

[0866] An example of a generated answer might be, "In class this week we learned about simultaneous equations and their applications. To make sure your child understands, try working through the review questions below together."

[0867] Step 6:

[0868] The server sends the generated response to the terminal.

[0869] Step 7:

[0870] The terminal displays the generated answer to the user.

[0871] The user can review the displayed answers, edit or correct them as necessary, and then send the final answers to the parents.

[0872] Through these steps, the system can recognize the user's emotions and support them in preparing lessons and responding to parents accordingly.

[0873] Example 2

[0874] 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."

[0875] In recent years, the workload of educators has increased, with a large amount of time and effort being spent on lesson preparation and parental interactions. This has led to concerns about increased stress among educators and a decline in the quality of education. Furthermore, because it is difficult to respond flexibly to the emotions of each individual educator, efficient and effective educational support is required. Therefore, a system is needed to reduce educators' workload and improve the quality of education.

[0876] 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.

[0877] In this invention, the server includes input means for inputting the lesson theme, target grade, and necessary materials, receiving means for receiving the data input by the input means, processing means having an emotion engine for analyzing the data received by the receiving means and recognizing emotions, generation means for customizing and automatically generating lesson content based on the emotions recognized by the emotion engine, and display means for displaying the content generated by the generation means. This makes it possible to generate customized lesson content according to the emotional state of the educator, and to respond quickly and appropriately to parents.

[0878] An "input means" is a device or interface through which a user inputs information.

[0879] The "receiving means" is a function or device that acquires data input by the input means.

[0880] An "emotion engine" is software or algorithms for recognizing and analyzing a user's emotions.

[0881] A "generator" is an algorithm or program for automatically generating content or responses based on received data and recognized sentiment.

[0882] A "display means" is a device or interface for visually presenting generated content and answers to a user.

[0883] A "server" is a computer system responsible for receiving, processing, and transmitting data over a network.

[0884] "Terminal" means a device such as a computer, tablet, or smartphone that a user uses to input and display information.

[0885] "Content" refers to educational materials created according to the lesson theme and target grade.

[0886] A "response" is a text reply generated in response to an inquiry from a parent.

[0887] This system aims to reduce the workload of educators and enable flexible responses according to their emotions. This system provides two main functions: support for lesson preparation and support for parental interaction.

[0888] Class preparation support

[0889] The user inputs the lesson topic, target grade, and required materials using the device, and the information is sent to the server. For example, if a user inputs "math class for second-year junior high school students, topic is simultaneous equations, required materials are practice problems and slides," the device encrypts this information and sends it to the server. The server analyzes the received data and calls the emotion engine and generative AI.

[0890] The emotion engine analyzes the user's emotions when they input information and recognizes their stress level and fatigue. Based on the analysis results, the generative AI automatically generates appropriate lesson content (practice questions, sample answers, slides, etc.). For example, if the user is feeling stressed, simple and easy-to-understand content is generated. The generated content is sent from the server to the device, where the user can review it and edit or modify it as necessary.

[0891] Support for parental interaction

[0892] When a user uses the device to input a parent's inquiry, the device encrypts the information and sends it to the server. For example, if a user inputs "Inquiry about this week's lesson content," the server analyzes the information and calls the emotion engine and generative AI.

[0893] The emotion engine analyzes the user's emotions when they input information and recognizes their fatigue and stress levels. Based on the analysis results, the generative AI automatically generates an appropriate answer. For example, if the user is tired, a short and concise answer will be generated. The generated answer is sent from the server to the device, where the user can review it, make corrections if necessary, and then send the final answer to their guardian.

[0894] Hardware and software used

[0895] Hardware: Devices (PCs, tablets, smartphones), servers

[0896] Software: Emotion engine, generative AI

[0897] Examples of concrete examples and prompts

[0898] Examples of lesson preparation:

[0899] The user types:

[0900] "Mathematics class for second-year junior high school students, the topic is simultaneous equations, and the necessary materials are practice problems and slides."

[0901] Examples of parental interactions:

[0902] The user types:

[0903] "Inquiry about this week's class content"

[0904] This allows appropriate data analysis and content generation at each processing step, reducing the workload of educators and improving the quality of education.

[0905] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0906] Class preparation support

[0907] Step 1:

[0908] The user uses the device to input the lesson topic, target grade, and necessary materials. Specifically, they launch a dedicated application and input "math lesson for second-year junior high school students, topic is simultaneous equations, necessary materials are practice problems and slides."

[0909] Input: lesson topic, target grade, required materials

[0910] Output: Input data

[0911] Step 2:

[0912] The terminal sends the entered data to the server, where it is encrypted and sent securely.

[0913] Input: Data entered by the user

[0914] Output: Encrypted data

[0915] Step 3:

[0916] The server analyzes the data it receives and verifies that the input is accurate and includes all required fields.

[0917] Input: Encrypted data

[0918] Output: Analysis results

[0919] Step 4:

[0920] The server calls the emotion engine to analyze the emotions entered by the user, which then recognizes the level of stress or fatigue.

[0921] Input: Analysis results and input data

[0922] Output: User's emotional state

[0923] Step 5:

[0924] The server calls the generative AI, which generates lesson content based on the received data and the recognized emotions. For example, if the user is feeling stressed, the generative AI will create simple and easy-to-understand exercises, sample answers, and slides.

[0925] Input: User's emotional state and input data

[0926] Output: Generated lesson content

[0927] Step 6:

[0928] The server re-encrypts the generated content data and transmits it to the terminal.

[0929] Input: Generated lesson content

[0930] Output: Encrypted lesson content

[0931] Step 7:

[0932] The device decodes the received data and visually displays it to the user, who can then review the displayed content and make edits or corrections as necessary.

[0933] Input: Encrypted lesson content

[0934] Output: Displayed lesson content

[0935] Support for parental interaction

[0936] Step 1:

[0937] The user uses the device to input the parent's inquiry. Specifically, the user launches a dedicated application and inputs "Inquiry about this week's lesson content."

[0938] Input: Parental inquiry

[0939] Output: Input data

[0940] Step 2:

[0941] The device sends the entered inquiry to the server, where the data is encrypted and sent securely.

[0942] Input: The query entered by the user

[0943] Output: Encrypted data

[0944] Step 3:

[0945] The server analyzes the data it receives to ensure that the input is accurate and that all required information is included.

[0946] Input: Encrypted data

[0947] Output: Analysis results

[0948] Step 4:

[0949] The server calls the emotion engine, which analyzes the emotions entered by the user and recognizes the level of fatigue and stress.

[0950] Input: Analysis results and input data

[0951] Output: User's emotional state

[0952] Step 5:

[0953] The server calls the generative AI, which generates an appropriate response based on the received data and the perceived emotion. For example, if the user is tired, the generative AI will create a quick and concise response.

[0954] Input: User's emotional state and input data

[0955] Output: The generated answer

[0956] Step 6:

[0957] The server re-encrypts the generated response data and transmits it to the terminal.

[0958] Input: Generated answer

[0959] Output: Encrypted answer

[0960] Step 7:

[0961] The device decrypts the received data and visually displays it to the user, who can then review the displayed answers, make corrections if necessary, and send the final answers to the parent.

[0962] Input: Encrypted answer

[0963] Output: The displayed answer

[0964] (Application example 2)

[0965] 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."

[0966] In conventional educational support systems and parental support systems, content and responses are generated without taking into account the feelings of educators, which can easily increase stress for educators and lead to a decline in the quality of education and parental support.In addition, due to a lack of flexible support based on user feelings, the user experience is uniform and unable to respond to individual needs.

[0967] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes input means for inputting the lesson theme, target grade, and necessary materials, receiving means for receiving the data input by the input means, generation means for automatically generating lesson content based on the data received by the receiving means, display means for displaying the content generated by the generation means, an emotion engine for recognizing emotions from the user's input content, and adjustment means for customizing the content generated based on the emotion data recognized by the emotion engine. This makes it possible to generate content and answers customized according to the user's emotions, reducing the workload of educators and improving the quality of education and parental support.

[0968] "Class theme" refers to the specific content or subject matter that educators deal with in class.

[0969] "Target grade" refers to the grade of students who are eligible to take the class.

[0970] "Necessary materials" refers to teaching materials and related materials used to smoothly conduct classes.

[0971] "Input means" refers to a device or interface that allows a user to input information into a system.

[0972] The "receiving means" refers to a device or function for receiving data transmitted from the input means.

[0973] "Generation means" refers to an algorithm or program for automatically generating content or answers based on data received by the receiving means.

[0974] "Display means" means a device or interface for visually displaying generated content or answers to a user.

[0975] "Emotion engine" refers to a system or software for recognizing emotions from user input and extracting that emotion data.

[0976] "Adjustment means" refers to a function or program for customizing the content or answers generated based on the emotional data recognized by the emotion engine.

[0977] MODE FOR CARRYING OUT THE INVENTION

[0978] The present invention provides a system for reducing the workload of educators and users of online shopping sites and improving quality. Specific embodiments of the system will be described below.

[0979] 1. Educational Support System

[0980] 1.1. Class preparation support

[0981] Examples:

[0982] The user uses a smartphone or tablet device to input the lesson topic, target grade, and required materials. For example, this information might be "a math class for second-year junior high school students, the topic is simultaneous equations, and the required materials are practice problems and slides." The device then sends this information to the server.

[0983] The server analyzes the received data and activates the emotion engine. The emotion engine recognizes the emotion expressed by the user when inputting the data and customizes the lesson content based on that emotion data. For example, if the user is feeling stressed, it generates simple content to ease their stress.

[0984] Next, the generative AI model generates practice problems, sample solutions, and slides related to simultaneous equations. The server sends the generated content to the device, which displays it to the user. The user can review the displayed content and edit or modify it as needed.

[0985] 2. Implementation of a personalized shopping assistant for an online shopping site

[0986] Shopping Assistant

[0987] Examples:

[0988] A user uses a smartphone to type, "I'm looking for the latest smartphone, but I don't know how to choose one." The device sends this information to the server.

[0989] The server analyzes the received data and activates the emotion engine, which recognizes the user's emotions when inputting and customizes product recommendations based on the emotion data. For example, if the user is tired, it generates a list of recommendations that emphasizes easy-to-use products.

[0990] Next, the generative AI model generates a product recommendation list based on the user's needs and emotions. The server sends the generated recommendation list to the device, which displays it to the user. The user then reviews the displayed recommendation list and selects suitable products.

[0991] Hardware and software used

[0992] Hardware:

[0993] 1. Smartphone

[0994] 2. Tablet devices

[0995] 3. Server

[0996] software:

[0997] 1. Emotion Engine: Software for recognizing emotions from user input

[0998] 2. Generative AI model: Software for automatically generating lesson content and product lists

[0999] Adding specific examples

[1000] Prompt Sentence Examples

[1001] Prompt: "I'm looking for the latest smartphone. I'm interested in its features and performance, but I'm a beginner and don't know how to choose one. I've been busy lately and I'm tired."

[1002] Product recommendations provided:

[1003] Product name: Smartphone Model X, Price: 100,000 yen, Features: High-performance camera, long-lasting battery

[1004] Product name: Smartphone Model Y, Price: ¥80,000, Features: Large screen display, easy-to-use UI

[1005] Product name: Smartphone Model Z, Price: 60,000 yen, Features: Waterproof, large storage capacity

[1006] Reason for recommendation: Because the user is feeling stressed or tired, we recommend products that are easy to use.

[1007] This enables the system to generate customized content and answers based on the user's emotions, reducing the workload of educators and online shopping site users and improving quality.

[1008] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1009] Program processing steps

[1010] Shopping assistant system

[1011] Step 1:

[1012] A user uses a smartphone to enter purchasing interests, such as "I'm looking for the latest smartphone, but I don't know how to choose one."

[1013] Input: Text data about purchases entered by the user

[1014] Output: Text data received by the server

[1015] Step 2:

[1016] The terminal sends the user's input to the server, where it can be processed.

[1017] Input: Text data entered by the user

[1018] Output: Text data sent to the server

[1019] Step 3:

[1020] The server analyzes the received text data and activates an emotion engine to recognize the user's emotions.

[1021] Input: Text data sent from the terminal

[1022] Data processing: Analysis of text data, emotion recognition using emotion engine

[1023] Output: Recognized emotion data

[1024] Step 4:

[1025] The server customizes product recommendations based on the recognized emotion data and generates product lists using a generative AI model.

[1026] Input: Recognized emotion data, user input text data

[1027] Data Computation: Customize product recommendations based on sentiment data, generate product lists using generative AI models

[1028] Output: A customized product recommendation list

[1029] Step 5:

[1030] The server sends the generated product recommendation list to the terminal, and the user receives the recommended product list.

[1031] Input: A customized product recommendation list

[1032] Output: Product recommendation list sent to the device

[1033] Step 6:

[1034] The device displays a customized product recommendation list to the user, who then reviews the displayed recommended products and selects the appropriate product.

[1035] Input: Product list sent from the server

[1036] Output: A visual list of products displayed to the user

[1037] Prompt Sentence Examples

[1038] Prompt: "I'm looking for the latest smartphone. I'm interested in its features and performance, but I'm a beginner and don't know how to choose one. I've been busy lately and I'm tired."

[1039] Product recommendations provided:

[1040] Product name: Smartphone Model X, Price: 100,000 yen, Features: High-performance camera, long-lasting battery

[1041] Product name: Smartphone Model Y, Price: ¥80,000, Features: Large screen display, easy-to-use UI

[1042] Product name: Smartphone Model Z, Price: 60,000 yen, Features: Waterproof, large storage capacity

[1043] Reason for recommendation: Because the user is feeling stressed or tired, we recommend products that are easy to use.

[1044]

[1045] 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.

[1046] 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.

[1047] 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.

[1048] [Third embodiment]

[1049] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1050] 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.

[1051] 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).

[1052] 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.

[1053] 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.

[1054] 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).

[1055] 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. 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.

[1056] 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.

[1057] 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.

[1058] 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.

[1059] 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.

[1060] 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."

[1061] The present invention provides a system for reducing the workload of educators and improving the quality of education. This system supports lesson preparation and parental support. Specific embodiments of the system are described below.

[1062] Class preparation support

[1063] Examples:

[1064] The user (teacher) uses a terminal to input the lesson theme, target grade, and required materials. For example, "Mathematics lesson for second-year junior high school students, theme is simultaneous equations, required materials are practice problems and slides." The terminal then sends this information to the server.

[1065] The server analyzes the received data and calls a generative AI to automatically generate content for related lessons. Specifically, it generates exercises, sample answers, and slides related to simultaneous equations. The generated content is sent from the server to the device, which displays it to the user. The user can then edit and modify the displayed content.

[1066] Support for parental interaction

[1067] Examples:

[1068] The user (teacher) uses the device to input the parent's inquiry. For example, they might input "Inquiry about this week's lesson content." The device then sends this information to the server.

[1069] The server analyzes the received inquiry and generates an appropriate answer using generative AI. Specifically, it generates an answer such as, "In this week's class, we learned about simultaneous equations and their applications. To check your child's understanding, please try solving the following review problem together." The generated answer is sent from the server to the device, which displays it to the user. The user can then edit and revise the displayed answer and send it to their parent.

[1070] System configuration

[1071] 1. Input Method

[1072] A device or interface that allows users to input lesson topics, target grades, required materials, or parental inquiries.

[1073] 2. Receiving Method

[1074] A device or function that allows a terminal to send input data or inquiry content to a server, which then receives it.

[1075] 3. Generation means

[1076] Algorithms and programs that automatically generate lesson content and responses to parents based on the data received by the server.

[1077] 4. Display means

[1078] A device or interface for visually displaying generated content and answers to the user.

[1079] With the above configuration, the present invention can reduce the workload of educators and increase the time they have to communicate with students, thereby improving the quality of education.

[1080] The processing flow will be explained below.

[1081] Class preparation support

[1082] Step 1:

[1083] The user uses the terminal to input the lesson topic, target grade, and necessary materials.

[1084] Step 2:

[1085] The terminal transmits the input data to the server.

[1086] Step 3:

[1087] The server parses the data it receives.

[1088] Step 4:

[1089] The server calls the generative AI and automatically generates lesson content.

[1090] Specifically, it generates relevant exercises, sample answers, slides, etc. based on the lesson theme, target grade, and type of material.

[1091] Step 5:

[1092] The server transmits the generated content to the terminal.

[1093] Step 6:

[1094] The terminal displays the generated content to the user.

[1095] The user can view the displayed content and edit or modify it as necessary.

[1096] Support for parental interaction

[1097] Step 1:

[1098] The user uses the terminal to input the inquiry from the parent.

[1099] Step 2:

[1100] The terminal transmits the input inquiry to the server.

[1101] Step 3:

[1102] The server analyzes the query received.

[1103] Specifically, it uses natural language processing (NLP) to understand the query and extract information to generate an appropriate answer.

[1104] Step 4:

[1105] The server calls a generative AI and automatically generates an appropriate response for the parent.

[1106] Specifically, it generates a response based on the inquiry and also suggests providing additional information if necessary.

[1107] Step 5:

[1108] The server sends the generated response to the terminal.

[1109] Step 6:

[1110] The terminal displays the generated answer to the user.

[1111] The user can review the displayed answers, edit or correct them as necessary, and then send the final answers to the parents.

[1112] Through these steps, the system reduces the workload of educators and enables them to provide education and respond to parents efficiently.

[1113] Example 1

[1114] 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."

[1115] In recent years, the increasing workload of teachers has become a problem in the educational field. In particular, the time required for lesson preparation and parental support is significant, raising concerns that this could result in a decline in the quality of education. Furthermore, due to a lack of support for providing appropriate lesson content and prompt, useful responses to parents, teachers expend a great deal of effort on these tasks. The present invention aims to solve these problems by providing a system that efficiently supports lesson preparation and parental support.

[1116] 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.

[1117] In this invention, the server includes an input means for inputting the lesson theme, target grade, and necessary materials, a receiving means for receiving the data input by the input means, a data analysis means for analyzing the received data, a prompt generation means for generating a prompt sentence to be sent to the generative AI model, a generation means for automatically generating lesson content based on the generated prompt sentence, and a display means for displaying the generated content. This enables teachers to quickly and efficiently prepare for lessons and respond to parents.

[1118] "Input means" refers to a device or interface that allows a user to input information.

[1119] The "receiving means" is a device or function for receiving data input by the input means.

[1120] The "data analysis means" refers to an algorithm or program for analyzing the data received by the receiving means.

[1121] The "prompt generation means" is a mechanism by which the data analysis means generates a prompt sentence to be sent to the generative AI model.

[1122] A "generation means" is an algorithm or program for automatically generating lesson content and answers based on a prompt.

[1123] The "display means" is a device or interface for visually displaying to the user the content and answers generated by the generation means.

[1124] A "generative AI model" is a model that automatically generates specific content or answers based on a prompt.

[1125] A "server" is a computer system that receives and analyzes data, operates generation means, and so on.

[1126] "Terminal" means a device operated by a user to display and edit data sent from a server.

[1127] "Class content" refers to educational materials such as exercises, sample answers, and slides that are generated based on the theme of the class.

[1128] "Inquiry content" refers to information regarding questions or requests from parents.

[1129] A "response" is an appropriate response message to the parent's inquiry.

[1130] The present invention is a system for reducing the workload of educators and improving the quality of education. This system supports lesson preparation and parental support, and a specific embodiment thereof is described below.

[1131] System configuration

[1132] The system includes the following hardware and software:

[1133] 1. Input Method

[1134] It is a device or interface that allows users (teachers) to input lesson topics, target grades, necessary materials, or inquiries from parents.

[1135] Examples: keyboards, touchscreens, voice input devices

[1136] 2. Receiving Method

[1137] This is a device or function that allows the terminal to send input data and inquiry contents to the server, and the server to receive them.

[1138] Examples: Internet connection, API communication interface

[1139] 3. Data Analysis Methods

[1140] The server contains algorithms and programs that analyze the data it receives.

[1141] Example: Data analysis program

[1142] 4. Prompt Generation Methods

[1143] The server is a mechanism for generating prompt sentences to send to the generative AI model.

[1144] Examples: text generation programs, natural language processing algorithms

[1145] 5. Generation means

[1146] The server is an algorithm or program that automatically generates lesson content and responses to parents based on prompts.

[1147] Example: Generative AI models (e.g., OpenAI's GPT-4)

[1148] 6. Display means

[1149] It is a device or interface for visually displaying generated content and answers to the user.

[1150] Examples: monitors, tablet screens, smartphone screens

[1151] Class preparation support

[1152] The user (teacher) uses a device to input the lesson theme, target grade, and necessary materials. For example, they might input "Math class for second-year junior high school students, theme is simultaneous equations, necessary materials are practice problems and slides." The device then sends this input information to the server. The server analyzes the received data and, based on the analysis results, creates a prompt to send to a generative AI model (for example, OpenAI's GPT-4). The generated prompt is "Create lesson materials for a 2nd-year junior high school math class. The topic is simultaneous equations. Generate practice problems and slides." The generative AI model generates lesson content based on this prompt; specifically, practice problems related to simultaneous equations, sample answers, and slides are generated. The generated content is sent from the server to the device, which then displays it to the teacher. The teacher can view and edit this generated content.

[1153] Support for parental interaction

[1154] The user (teacher) uses the device to input the parent's inquiry. For example, they might input "Inquiry about this week's class content." The device then sends this information to the server. The server analyzes the received inquiry and, based on the analysis results, creates a prompt to send to a generative AI model (e.g., OpenAI's GPT-4). The generated prompt is "Provide a detailed response to a parent's inquiry about this week's class content. The class covered simultaneous equations and their applications. Include a suggestion for reviewing the material with their child." The generative AI model then generates an answer based on this prompt, specifically, "In this week's class, we learned about simultaneous equations and their applications. To check your child's understanding, please solve the following review problem together." The generated answer is sent from the server to the device, where it is displayed to the teacher. The teacher can view, edit, or modify the answer and then send it to the parent.

[1155] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1156] Class preparation support

[1157] Processing Steps

[1158] Step 1:

[1159] The user inputs the lesson topic, target grade, and necessary materials into the terminal.

[1160] Input: "8th grade math class, topic: simultaneous equations, required materials: practice problems and slides"

[1161] Output: The device holds this input data.

[1162] Step 2:

[1163] The terminal transmits the input data to the server.

[1164] Specific operation: The device uses the API to send data to the server as an HTTP request.

[1165] Input: Data entered by the user

[1166] Output: The server receives the data.

[1167] Step 3:

[1168] The server parses the received data.

[1169] Specific operation: The server launches a data analysis program and extracts keywords such as "simultaneous equations" and "second-year junior high school student."

[1170] Input: Data received from the terminal

[1171] Output: Extracted keyword list

[1172] Step 4:

[1173] The server generates a prompt to send to the generative AI model.

[1174] Specific operation: The server uses a text generator to create the following prompt: "Create lesson materials for a 2nd-year junior high school math class. The topic is simultaneous equations. Generate practice problems and slides."

[1175] Input: Extracted keyword list

[1176] Output: Generated prompt statement

[1177] Step 5:

[1178] A generative AI model generates lesson content.

[1179] How it works: Based on the prompt, the generative AI model generates practice problems, sample answers, and slides related to simultaneous equations.

[1180] Input: Generated prompt statement

[1181] Output: Generated lesson content (exercises, sample answers, slides)

[1182] Step 6:

[1183] The server transmits the generated content to the terminal.

[1184] Specific operation: The server sends the generated lesson content to the terminal as an HTTP response.

[1185] Input: Generated lesson content

[1186] Output: The device receives the lesson content.

[1187] Step 7:

[1188] The terminal displays the generated content to the user.

[1189] Specific operation: The device launches a program to visually display the data received, allowing the user to confirm the displayed content.

[1190] Input: Lesson content received from the server

[1191] Output: The content that is displayed to the user

[1192] Support for parental interaction

[1193] Processing Steps

[1194] Step 1:

[1195] The user inputs the parent's inquiry into the terminal.

[1196] Input: "Inquiry about this week's class content"

[1197] Output: The device holds this input data.

[1198] Step 2:

[1199] The terminal transmits the input inquiry to the server.

[1200] Specific operation: The device uses the API to send the inquiry to the server as an HTTP request.

[1201] Input: The query entered by the user

[1202] Output: The server receives the query.

[1203] Step 3:

[1204] The server analyzes the query.

[1205] Specific operation: The server launches a data analysis program and extracts keywords such as "class content" and "inquiry."

[1206] Input: Inquiry received from the device

[1207] Output: Extracted keyword list

[1208] Step 4:

[1209] The server generates a prompt to send to the generative AI model.

[1210] What it does: The server uses a text generator to create the following prompt: "Provide a detailed response to a parent's inquiry about this week's class content. The class covered simultaneous equations and their applications. Include a suggestion for reviewing the material with their child."

[1211] Input: Extracted keyword list

[1212] Output: Generated prompt statement

[1213] Step 5:

[1214] A generative AI model generates the answer.

[1215] Specific behavior: The generative AI model generates an appropriate answer based on the prompt.

[1216] Input: Generated prompt statement

[1217] Output: Generated answer (Example: This week in class we learned about simultaneous equations and their applications. To check your child's understanding, try working through these review questions together.)

[1218] Step 6:

[1219] The server sends the generated response to the terminal.

[1220] Specific operation: The server sends the generated answer to the device as an HTTP response.

[1221] Input: Generated answer

[1222] Output: The device receives the answer.

[1223] Step 7:

[1224] The terminal displays the generated answer to the user.

[1225] Specific operation: The device launches a program to visually display the data received, allowing the user to confirm the displayed answer.

[1226] Input: Answer received from the server

[1227] Output: The answer that is displayed to the user

[1228] (Application example 1)

[1229] 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."

[1230] In conventional education systems, teachers have to spend a lot of time preparing lessons and responding to parents, limiting the room for improving the quality of education. It is also difficult for teachers to quickly obtain necessary materials and content or efficiently respond to inquiries from parents. This increases the workload of teachers and reduces the time they have to communicate with students. The purpose of this invention is to solve these problems, reduce the workload of educators, and improve the quality of education.

[1231] 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.

[1232] In this invention, the server includes an input means for inputting the lesson theme, target grade, and necessary materials, a receiving means for receiving the data input by the input means, and a generating means for automatically generating lesson content based on the data received by the receiving means. This makes it possible to display content generated based on prompt sentences on the display of the smart glasses. Furthermore, by including an input means for inputting inquiries from parents, a receiving means for receiving the inquiries input by the input means, and a generating means for analyzing the inquiries received by the receiving means and generating appropriate answers, it is possible to display answers generated based on prompt sentences on the display of the smart glasses. This reduces the workload of educators and improves the quality of education.

[1233] Key Word Definitions

[1234] A "lesson topic" is a specific content or topic that an educator teaches.

[1235] "Target grade" refers to the grade of students taking the class.

[1236] "Necessary materials" refers to teaching materials and reference materials needed to conduct the lesson.

[1237] "Input means" refers to a device or interface that allows a user to input data or inquiries.

[1238] The "receiving means" refers to a device or function for receiving data or inquiry content input by the input means.

[1239] The "generation means" refers to an algorithm or program that automatically generates content or answers based on the data received by the reception means.

[1240] "Display means" refers to a device or interface for visually displaying generated content and answers to the user.

[1241] A "prompt sentence" is a specific input sentence that instructs the generative AI on what content to generate.

[1242] "Smart glasses" are eyeglass-type devices with computer functions that can provide users with visual information in real time.

[1243] "Form for carrying out the invention" of the specification

[1244] The present invention relates to a system for reducing the workload of educators and improving the quality of education. This system is designed to support lesson preparation and parental support. Specific embodiments of the present invention will be described below.

[1245] (Class preparation support)

[1246] Consider the example of a teacher using smart glasses. First, the teacher inputs the lesson topic, target grade, and necessary materials into the smart glasses via voice input or a touch interface, such as "Mathematics class for second-year junior high school students, the topic is simultaneous equations, and the necessary materials are practice problems and slides." This input information is then sent from the device to the server.

[1247] The server analyzes the received information and automatically generates appropriate lesson content using a generative AI model. Specifically, practice problems, sample solutions, and slides related to simultaneous equations are automatically generated. The generated content is sent from the server to the smart glasses in real time, where teachers can review it and immediately edit or revise it if necessary.

[1248] (Support for parents)

[1249] Smart glasses are also useful for teachers when communicating with parents. For example, teachers can input questions from parents, such as "questions about this week's lesson content," using voice input or a touch interface. This information is also sent from the device to the server.

[1250] The server analyzes the received inquiry and automatically generates an appropriate answer using a generative AI model. Specifically, it might generate an answer such as, "In this week's class, we learned about simultaneous equations and their applications. To check your child's understanding, please try solving the following review problem together." The generated answer is sent from the server to the smart glasses in real time, where the teacher can review it and, if necessary, instantly edit or revise it before sending it to the parent.

[1251] (Hardware and software used)

[1252] The following hardware and software are used in implementing the present invention.

[1253] Hardware:

[1254] Smart glasses (display information and accept voice and touch input)

[1255] Smartphone (linked to smart glasses and communicating with the server)

[1256] Cloud server (receives, analyzes, generates, and transmits data)

[1257] software:

[1258] OpenAI API (provides generative AI models)

[1259] Python (a programming language for writing programs to receive, analyze, and process data)

[1260] (Example)

[1261] Example of lesson preparation:

[1262] When a teacher enters "Mathematics class for second-year junior high school students, topic is simultaneous equations, required materials are practice problems and slides" into the input field on the smart glasses, the generation AI uses this information to generate appropriate practice problems, sample answers, and slides, which are then displayed on the smart glasses.

[1263] Examples of parental interactions:

[1264] When a teacher types "Inquiry about this week's lesson content" into the input field on the smart glasses, the generative AI generates an appropriate response to the inquiry, which the teacher confirms and then sends to the parent.

[1265] In this way, the present invention saves educators time and effort and provides a higher quality education.

[1266] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1267] Program processing flow

[1268] Class preparation support

[1269] Step 1:

[1270] The user (teacher) inputs the lesson topic, target grade, and necessary materials into the smart glasses.

[1271] Input: 8th grade math class, topic is simultaneous equations, required materials are practice problems and slides.

[1272] Output: Send input data from smart glasses to the device.

[1273] Step 2:

[1274] The terminal transmits the data entered by the user to the server.

[1275] Input: Lesson topic, target grade, and required materials information entered by the teacher.

[1276] Output: Sends input data to the server.

[1277] Step 3:

[1278] The server analyzes the received data and calls a generative AI model to create a prompt.

[1279] Input: Teacher input data.

[1280] Data processing: Prompt generation. For example, "Generate exercises and slides for a simultaneous equations class for eighth graders."

[1281] Output: The generated prompt statement.

[1282] Step 4:

[1283] The server generates lesson content using the generative AI model.

[1284] Input: The generated prompt statement.

[1285] Data Calculation: Generate simultaneous equation practice problems, sample answers, and slides based on generated prompts.

[1286] Output: The generated lesson content.

[1287] Step 5:

[1288] The server transmits the generated content to the terminal.

[1289] Input: Generated lesson content.

[1290] Output: Send lesson content to the device.

[1291] Step 6:

[1292] The lesson content received by the device is displayed on the smart glasses.

[1293] Input: Lesson content sent from the server.

[1294] Output: Display content on the smart glasses display.

[1295] Support for parental interaction

[1296] Step 1:

[1297] The user (teacher) inputs the parent's inquiry into the smart glasses.

[1298] Input: "Inquiry about this week's class content"

[1299] Output: Send input data from smart glasses to the device.

[1300] Step 2:

[1301] The terminal transmits the inquiry content input by the user to the server.

[1302] Input: The inquiry entered by the instructor.

[1303] Output: Sends input data to the server.

[1304] Step 3:

[1305] The server analyzes the received query and calls a generative AI model to create a prompt.

[1306] Input: Teacher input data.

[1307] Data processing: Generate prompt sentences. For example, "Parental inquiry: Please respond appropriately to the inquiry about this week's lesson content."

[1308] Output: The generated prompt statement.

[1309] Step 4:

[1310] The server uses the generative AI model to generate answers for the parents.

[1311] Input: The generated prompt statement.

[1312] Data Calculation: Generates appropriate answers to queries based on generated prompts. For example, "In class this week, we learned about simultaneous equations and their applications."

[1313] Output: The generated answer.

[1314] Step 5:

[1315] The server sends the generated response to the terminal.

[1316] Input: The generated answer.

[1317] Output: Sends the answer to the terminal.

[1318] Step 6:

[1319] The answer received by the device is displayed on the smart glasses.

[1320] Input: The answer sent by the server.

[1321] Output: Show the answer on the smart glasses display.

[1322] 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.

[1323] The present invention provides a system for reducing the workload of educators and improving the quality of education. This system supports lesson preparation and parental support, and also includes an emotion engine for recognizing the emotions of users (teachers). Specific embodiments of the system are described below.

[1324] Class preparation support

[1325] Examples:

[1326] The user uses the device to input the lesson topic, target grade, and required materials. For example, they might input "math class for second-year junior high school students, topic is simultaneous equations, required materials are practice problems and slides." The device then sends this information to the server.

[1327] The server analyzes the received data and calls the generative AI and emotion engine. The emotion engine recognizes the emotion expressed by the user when inputting and customizes the lesson content based on that emotion. For example, if the user is feeling stressed, it generates simple content to ease the stress. The generative AI generates practice problems, sample answers, and slides related to simultaneous equations.

[1328] The server sends the generated content to the terminal, which displays it to the user, who can then view the displayed content and edit or modify it as needed.

[1329] Support for parental interaction

[1330] Examples:

[1331] The user uses the device to input the parent's inquiry. For example, the user inputs "Inquiry about this week's lesson content." The device then sends this information to the server.

[1332] The server analyzes the received inquiry and generates an appropriate answer using an emotion engine and generative AI. The emotion engine recognizes the user's emotion when typing and customizes the answer based on that emotion. For example, if the user is tired, it generates a quick and concise answer. The generated answer might be something like, "In this week's class, we learned about simultaneous equations and their applications. To check your child's understanding, try solving the following review problem together."

[1333] The server sends the generated answers to the device, which displays them to the user. The user can check the displayed answers, edit or correct them as necessary, and send the final answers to their parents.

[1334] System configuration

[1335] 1. Input Method

[1336] A device or interface that allows users to input lesson topics, target grades, required materials, or parental inquiries.

[1337] 2. Receiving Method

[1338] A device or function that allows a terminal to send input data or inquiry content to a server, which then receives it.

[1339] 3. Generation means

[1340] Algorithms and programs that automatically generate lesson content and responses to parents based on the data received by the server.

[1341] 4. Display means

[1342] A device or interface for visually displaying generated content and answers to the user.

[1343] 5. Emotion Engine

[1344] An engine that recognizes the emotions of users as they type and customizes lesson content and responses based on those emotions.

[1345] With the above configuration, the present invention reduces the workload of educators and increases the time they spend communicating with students, thereby improving the quality of education. Furthermore, the inclusion of an emotion engine allows for flexible support based on the user's emotions.

[1346] The processing flow will be explained below.

[1347] Class preparation support

[1348] Step 1:

[1349] The user uses the terminal to input the lesson topic, target grade, and necessary materials.

[1350] Step 2:

[1351] The terminal transmits the input data to the server.

[1352] Step 3:

[1353] The server parses the data it receives.

[1354] Step 4:

[1355] The server invokes the emotion engine to recognize the emotion of the user's input.

[1356] For example, if the user is feeling stressed, that emotion is recognized.

[1357] Step 5:

[1358] Based on the recognized emotions, the server calls a generative AI to generate customized lesson content.

[1359] Specifically, if the user is feeling stressed, simple and less burdensome content is generated.

[1360] Examples of generated content include simultaneous equation exercises, sample solutions, and slides.

[1361] Step 6:

[1362] The server transmits the generated content to the terminal.

[1363] Step 7:

[1364] The terminal displays the generated content to the user.

[1365] The user can view the displayed content and edit or modify it as necessary.

[1366] Support for parental interaction

[1367] Step 1:

[1368] The user uses the terminal to input the inquiry from the parent.

[1369] Step 2:

[1370] The terminal transmits the input inquiry to the server.

[1371] Step 3:

[1372] The server analyzes the query received.

[1373] Step 4:

[1374] The server invokes the emotion engine to recognize the emotion of the user's input.

[1375] For example, if the user is tired, it recognizes that emotion.

[1376] Step 5:

[1377] The server uses generative AI to generate appropriate answers based on the recognized emotions.

[1378] Specifically, if the user is tired, a quick and concise response is generated.

[1379] An example of a generated answer might be, "In class this week we learned about simultaneous equations and their applications. To make sure your child understands, try working through the review questions below together."

[1380] Step 6:

[1381] The server sends the generated response to the terminal.

[1382] Step 7:

[1383] The terminal displays the generated answer to the user.

[1384] The user can review the displayed answers, edit or correct them as necessary, and then send the final answers to the parents.

[1385] Through these steps, the system can recognize the user's emotions and support them in preparing lessons and responding to parents accordingly.

[1386] Example 2

[1387] 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."

[1388] In recent years, the workload of educators has increased, with a large amount of time and effort being spent on lesson preparation and parental interactions. This has led to concerns about increased stress among educators and a decline in the quality of education. Furthermore, because it is difficult to respond flexibly to the emotions of each individual educator, efficient and effective educational support is required. Therefore, a system is needed to reduce educators' workload and improve the quality of education.

[1389] 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.

[1390] In this invention, the server includes input means for inputting the lesson theme, target grade, and necessary materials, receiving means for receiving the data input by the input means, processing means having an emotion engine for analyzing the data received by the receiving means and recognizing emotions, generation means for customizing and automatically generating lesson content based on the emotions recognized by the emotion engine, and display means for displaying the content generated by the generation means. This makes it possible to generate customized lesson content according to the emotional state of the educator, and to respond quickly and appropriately to parents.

[1391] An "input means" is a device or interface through which a user inputs information.

[1392] The "receiving means" is a function or device that acquires data input by the input means.

[1393] An "emotion engine" is software or algorithms for recognizing and analyzing a user's emotions.

[1394] A "generator" is an algorithm or program for automatically generating content or responses based on received data and recognized sentiment.

[1395] A "display means" is a device or interface for visually presenting generated content and answers to a user.

[1396] A "server" is a computer system responsible for receiving, processing, and transmitting data over a network.

[1397] "Terminal" means a device such as a computer, tablet, or smartphone that a user uses to input and display information.

[1398] "Content" refers to educational materials created according to the lesson theme and target grade.

[1399] A "response" is a text reply generated in response to an inquiry from a parent.

[1400] This system aims to reduce the workload of educators and enable flexible responses according to their emotions. This system provides two main functions: support for lesson preparation and support for parental interaction.

[1401] Class preparation support

[1402] The user inputs the lesson topic, target grade, and required materials using the device, and the information is sent to the server. For example, if a user inputs "math class for second-year junior high school students, topic is simultaneous equations, required materials are practice problems and slides," the device encrypts this information and sends it to the server. The server analyzes the received data and calls the emotion engine and generative AI.

[1403] The emotion engine analyzes the user's emotions when they input information and recognizes their stress level and fatigue. Based on the analysis results, the generative AI automatically generates appropriate lesson content (practice questions, sample answers, slides, etc.). For example, if the user is feeling stressed, simple and easy-to-understand content is generated. The generated content is sent from the server to the device, where the user can review it and edit or modify it as necessary.

[1404] Support for parental interaction

[1405] When a user uses the device to input a parent's inquiry, the device encrypts the information and sends it to the server. For example, if a user inputs "Inquiry about this week's lesson content," the server analyzes the information and calls the emotion engine and generative AI.

[1406] The emotion engine analyzes the user's emotions when they input information and recognizes their fatigue and stress levels. Based on the analysis results, the generative AI automatically generates an appropriate answer. For example, if the user is tired, a short and concise answer will be generated. The generated answer is sent from the server to the device, where the user can review it, make corrections if necessary, and then send the final answer to their guardian.

[1407] Hardware and software used

[1408] Hardware: Devices (PCs, tablets, smartphones), servers

[1409] Software: Emotion engine, generative AI

[1410] Examples of concrete examples and prompts

[1411] Examples of lesson preparation:

[1412] The user types:

[1413] "Mathematics class for second-year junior high school students, the topic is simultaneous equations, and the necessary materials are practice problems and slides."

[1414] Examples of parental interactions:

[1415] The user types:

[1416] "Inquiry about this week's class content"

[1417] This allows appropriate data analysis and content generation at each processing step, reducing the workload of educators and improving the quality of education.

[1418] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1419] Class preparation support

[1420] Step 1:

[1421] The user uses the device to input the lesson topic, target grade, and necessary materials. Specifically, they launch a dedicated application and input "math lesson for second-year junior high school students, topic is simultaneous equations, necessary materials are practice problems and slides."

[1422] Input: lesson topic, target grade, required materials

[1423] Output: Input data

[1424] Step 2:

[1425] The terminal sends the entered data to the server, where it is encrypted and sent securely.

[1426] Input: Data entered by the user

[1427] Output: Encrypted data

[1428] Step 3:

[1429] The server analyzes the data it receives and verifies that the input is accurate and includes all required fields.

[1430] Input: Encrypted data

[1431] Output: Analysis results

[1432] Step 4:

[1433] The server calls the emotion engine to analyze the emotions entered by the user, which then recognizes the level of stress or fatigue.

[1434] Input: Analysis results and input data

[1435] Output: User's emotional state

[1436] Step 5:

[1437] The server calls the generative AI, which generates lesson content based on the received data and the recognized emotions. For example, if the user is feeling stressed, the generative AI will create simple and easy-to-understand exercises, sample answers, and slides.

[1438] Input: User's emotional state and input data

[1439] Output: Generated lesson content

[1440] Step 6:

[1441] The server re-encrypts the generated content data and transmits it to the terminal.

[1442] Input: Generated lesson content

[1443] Output: Encrypted lesson content

[1444] Step 7:

[1445] The device decodes the received data and visually displays it to the user, who can then review the displayed content and make edits or corrections as necessary.

[1446] Input: Encrypted lesson content

[1447] Output: Displayed lesson content

[1448] Support for parental interaction

[1449] Step 1:

[1450] The user uses the device to input the parent's inquiry. Specifically, the user launches a dedicated application and inputs "Inquiry about this week's lesson content."

[1451] Input: Parental inquiry

[1452] Output: Input data

[1453] Step 2:

[1454] The device sends the entered inquiry to the server, where the data is encrypted and sent securely.

[1455] Input: The query entered by the user

[1456] Output: Encrypted data

[1457] Step 3:

[1458] The server analyzes the data it receives to ensure that the input is accurate and that all required information is included.

[1459] Input: Encrypted data

[1460] Output: Analysis results

[1461] Step 4:

[1462] The server calls the emotion engine, which analyzes the emotions entered by the user and recognizes the level of fatigue and stress.

[1463] Input: Analysis results and input data

[1464] Output: User's emotional state

[1465] Step 5:

[1466] The server calls the generative AI, which generates an appropriate response based on the received data and the perceived emotion. For example, if the user is tired, the generative AI will create a quick and concise response.

[1467] Input: User's emotional state and input data

[1468] Output: The generated answer

[1469] Step 6:

[1470] The server re-encrypts the generated response data and transmits it to the terminal.

[1471] Input: Generated answer

[1472] Output: Encrypted answer

[1473] Step 7:

[1474] The device decrypts the received data and visually displays it to the user, who can then review the displayed answers, make corrections if necessary, and send the final answers to the parent.

[1475] Input: Encrypted answer

[1476] Output: The displayed answer

[1477] (Application example 2)

[1478] 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."

[1479] In conventional educational support systems and parental support systems, content and responses are generated without taking into account the feelings of educators, which can easily increase stress for educators and lead to a decline in the quality of education and parental support.In addition, due to a lack of flexible support based on user feelings, the user experience is uniform and unable to respond to individual needs.

[1480] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes input means for inputting the lesson theme, target grade, and necessary materials, receiving means for receiving the data input by the input means, generation means for automatically generating lesson content based on the data received by the receiving means, display means for displaying the content generated by the generation means, an emotion engine for recognizing emotions from the user's input content, and adjustment means for customizing the content generated based on the emotion data recognized by the emotion engine. This makes it possible to generate content and answers customized according to the user's emotions, reducing the workload of educators and improving the quality of education and parental support.

[1481] "Class theme" refers to the specific content or subject matter that educators deal with in class.

[1482] "Target grade" refers to the grade of students who are eligible to take the class.

[1483] "Necessary materials" refers to teaching materials and related materials used to smoothly conduct classes.

[1484] "Input means" refers to a device or interface that allows a user to input information into a system.

[1485] The "receiving means" refers to a device or function for receiving data transmitted from the input means.

[1486] "Generation means" refers to an algorithm or program for automatically generating content or answers based on data received by the receiving means.

[1487] "Display means" means a device or interface for visually displaying generated content or answers to a user.

[1488] "Emotion engine" refers to a system or software for recognizing emotions from user input and extracting that emotion data.

[1489] "Adjustment means" refers to a function or program for customizing the content or answers generated based on the emotional data recognized by the emotion engine.

[1490] MODE FOR CARRYING OUT THE INVENTION

[1491] The present invention provides a system for reducing the workload of educators and users of online shopping sites and improving quality. Specific embodiments of the system will be described below.

[1492] 1. Educational Support System

[1493] 1.1. Class preparation support

[1494] Examples:

[1495] The user uses a smartphone or tablet device to input the lesson topic, target grade, and required materials. For example, this information might be "a math class for second-year junior high school students, the topic is simultaneous equations, and the required materials are practice problems and slides." The device then sends this information to the server.

[1496] The server analyzes the received data and activates the emotion engine. The emotion engine recognizes the emotion expressed by the user when inputting the data and customizes the lesson content based on that emotion data. For example, if the user is feeling stressed, it generates simple content to ease their stress.

[1497] Next, the generative AI model generates practice problems, sample solutions, and slides related to simultaneous equations. The server sends the generated content to the device, which displays it to the user. The user can review the displayed content and edit or modify it as needed.

[1498] 2. Implementation of a personalized shopping assistant for an online shopping site

[1499] Shopping Assistant

[1500] Examples:

[1501] A user uses a smartphone to type, "I'm looking for the latest smartphone, but I don't know how to choose one." The device sends this information to the server.

[1502] The server analyzes the received data and activates the emotion engine, which recognizes the user's emotions when inputting and customizes product recommendations based on the emotion data. For example, if the user is tired, it generates a list of recommendations that emphasizes easy-to-use products.

[1503] Next, the generative AI model generates a product recommendation list based on the user's needs and emotions. The server sends the generated recommendation list to the device, which displays it to the user. The user then reviews the displayed recommendation list and selects suitable products.

[1504] Hardware and software used

[1505] Hardware:

[1506] 1. Smartphone

[1507] 2. Tablet devices

[1508] 3. Server

[1509] software:

[1510] 1. Emotion Engine: Software for recognizing emotions from user input

[1511] 2. Generative AI model: Software for automatically generating lesson content and product lists

[1512] Adding specific examples

[1513] Prompt Sentence Examples

[1514] Prompt: "I'm looking for the latest smartphone. I'm interested in its features and performance, but I'm a beginner and don't know how to choose one. I've been busy lately and I'm tired."

[1515] Product recommendations provided:

[1516] Product name: Smartphone Model X, Price: 100,000 yen, Features: High-performance camera, long-lasting battery

[1517] Product name: Smartphone Model Y, Price: ¥80,000, Features: Large screen display, easy-to-use UI

[1518] Product name: Smartphone Model Z, Price: 60,000 yen, Features: Waterproof, large storage capacity

[1519] Reason for recommendation: Because the user is feeling stressed or tired, we recommend products that are easy to use.

[1520] This enables the system to generate customized content and answers based on the user's emotions, reducing the workload of educators and online shopping site users and improving quality.

[1521] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1522] Program processing steps

[1523] Shopping assistant system

[1524] Step 1:

[1525] A user uses a smartphone to enter purchasing interests, such as "I'm looking for the latest smartphone, but I don't know how to choose one."

[1526] Input: Text data about purchases entered by the user

[1527] Output: Text data received by the server

[1528] Step 2:

[1529] The terminal sends the user's input to the server, where it can be processed.

[1530] Input: Text data entered by the user

[1531] Output: Text data sent to the server

[1532] Step 3:

[1533] The server analyzes the received text data and activates an emotion engine to recognize the user's emotions.

[1534] Input: Text data sent from the terminal

[1535] Data processing: Analysis of text data, emotion recognition using emotion engine

[1536] Output: Recognized emotion data

[1537] Step 4:

[1538] The server customizes product recommendations based on the recognized emotion data and generates product lists using a generative AI model.

[1539] Input: Recognized emotion data, user input text data

[1540] Data Computation: Customize product recommendations based on sentiment data, generate product lists using generative AI models

[1541] Output: A customized product recommendation list

[1542] Step 5:

[1543] The server sends the generated product recommendation list to the terminal, and the user receives the recommended product list.

[1544] Input: A customized product recommendation list

[1545] Output: Product recommendation list sent to the device

[1546] Step 6:

[1547] The device displays a customized product recommendation list to the user, who then reviews the displayed recommended products and selects the appropriate product.

[1548] Input: Product list sent from the server

[1549] Output: A visual list of products displayed to the user

[1550] Prompt Sentence Examples

[1551] Prompt: "I'm looking for the latest smartphone. I'm interested in its features and performance, but I'm a beginner and don't know how to choose one. I've been busy lately and I'm tired."

[1552] Product recommendations provided:

[1553] Product name: Smartphone Model X, Price: 100,000 yen, Features: High-performance camera, long-lasting battery

[1554] Product name: Smartphone Model Y, Price: ¥80,000, Features: Large screen display, easy-to-use UI

[1555] Product name: Smartphone Model Z, Price: 60,000 yen, Features: Waterproof, large storage capacity

[1556] Reason for recommendation: Because the user is feeling stressed or tired, we recommend products that are easy to use.

[1557]

[1558] 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.

[1559] 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.

[1560] 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.

[1561] [Fourth embodiment]

[1562] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1563] 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.

[1564] 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).

[1565] 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.

[1566] 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.

[1567] 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).

[1568] 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. 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.

[1569] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1570] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1571] 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.

[1572] 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.

[1573] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1574] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1575] The present invention provides a system for reducing the workload of educators and improving the quality of education. This system supports lesson preparation and parental support. Specific embodiments of the system are described below.

[1576] Class preparation support

[1577] Examples:

[1578] The user (teacher) uses a terminal to input the lesson theme, target grade, and required materials. For example, "Mathematics lesson for second-year junior high school students, theme is simultaneous equations, required materials are practice problems and slides." The terminal then sends this information to the server.

[1579] The server analyzes the received data and calls a generative AI to automatically generate content for related lessons. Specifically, it generates exercises, sample answers, and slides related to simultaneous equations. The generated content is sent from the server to the device, which displays it to the user. The user can then edit and modify the displayed content.

[1580] Support for parental interaction

[1581] Examples:

[1582] The user (teacher) uses the device to input the parent's inquiry. For example, they might input "Inquiry about this week's lesson content." The device then sends this information to the server.

[1583] The server analyzes the received inquiry and generates an appropriate answer using generative AI. Specifically, it generates an answer such as, "In this week's class, we learned about simultaneous equations and their applications. To check your child's understanding, please try solving the following review problem together." The generated answer is sent from the server to the device, which displays it to the user. The user can then edit and revise the displayed answer and send it to their parent.

[1584] System configuration

[1585] 1. Input Method

[1586] A device or interface that allows users to input lesson topics, target grades, required materials, or parental inquiries.

[1587] 2. Receiving Method

[1588] A device or function that allows a terminal to send input data or inquiry content to a server, which then receives it.

[1589] 3. Generation means

[1590] Algorithms and programs that automatically generate lesson content and responses to parents based on the data received by the server.

[1591] 4. Display means

[1592] A device or interface for visually displaying generated content and answers to the user.

[1593] With the above configuration, the present invention can reduce the workload of educators and increase the time they have to communicate with students, thereby improving the quality of education.

[1594] The processing flow will be explained below.

[1595] Class preparation support

[1596] Step 1:

[1597] The user uses the terminal to input the lesson topic, target grade, and necessary materials.

[1598] Step 2:

[1599] The terminal transmits the input data to the server.

[1600] Step 3:

[1601] The server parses the data it receives.

[1602] Step 4:

[1603] The server calls the generative AI and automatically generates lesson content.

[1604] Specifically, it generates relevant exercises, sample answers, slides, etc. based on the lesson theme, target grade, and type of material.

[1605] Step 5:

[1606] The server transmits the generated content to the terminal.

[1607] Step 6:

[1608] The terminal displays the generated content to the user.

[1609] The user can view the displayed content and edit or modify it as necessary.

[1610] Support for parental interaction

[1611] Step 1:

[1612] The user uses the terminal to input the inquiry from the parent.

[1613] Step 2:

[1614] The terminal transmits the input inquiry to the server.

[1615] Step 3:

[1616] The server analyzes the query received.

[1617] Specifically, it uses natural language processing (NLP) to understand the query and extract information to generate an appropriate answer.

[1618] Step 4:

[1619] The server calls a generative AI and automatically generates an appropriate response for the parent.

[1620] Specifically, it generates a response based on the inquiry and also suggests providing additional information if necessary.

[1621] Step 5:

[1622] The server sends the generated response to the terminal.

[1623] Step 6:

[1624] The terminal displays the generated answer to the user.

[1625] The user can review the displayed answers, edit or correct them as necessary, and then send the final answers to the parents.

[1626] Through these steps, the system reduces the workload of educators and enables them to provide education and respond to parents efficiently.

[1627] Example 1

[1628] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1629] In recent years, the increasing workload of teachers has become a problem in the educational field. In particular, the time required for lesson preparation and parental support is significant, raising concerns that this could result in a decline in the quality of education. Furthermore, due to a lack of support for providing appropriate lesson content and prompt, useful responses to parents, teachers expend a great deal of effort on these tasks. The present invention aims to solve these problems by providing a system that efficiently supports lesson preparation and parental support.

[1630] 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.

[1631] In this invention, the server includes an input means for inputting the lesson theme, target grade, and necessary materials, a receiving means for receiving the data input by the input means, a data analysis means for analyzing the received data, a prompt generation means for generating a prompt sentence to be sent to the generative AI model, a generation means for automatically generating lesson content based on the generated prompt sentence, and a display means for displaying the generated content. This enables teachers to quickly and efficiently prepare for lessons and respond to parents.

[1632] "Input means" refers to a device or interface that allows a user to input information.

[1633] The "receiving means" is a device or function for receiving data input by the input means.

[1634] The "data analysis means" refers to an algorithm or program for analyzing the data received by the receiving means.

[1635] The "prompt generation means" is a mechanism by which the data analysis means generates a prompt sentence to be sent to the generative AI model.

[1636] A "generation means" is an algorithm or program for automatically generating lesson content and answers based on a prompt.

[1637] The "display means" is a device or interface for visually displaying to the user the content and answers generated by the generation means.

[1638] A "generative AI model" is a model that automatically generates specific content or answers based on a prompt.

[1639] A "server" is a computer system that receives and analyzes data, operates generation means, and so on.

[1640] "Terminal" means a device operated by a user to display and edit data sent from a server.

[1641] "Class content" refers to educational materials such as exercises, sample answers, and slides that are generated based on the theme of the class.

[1642] "Inquiry content" refers to information regarding questions or requests from parents.

[1643] A "response" is an appropriate response message to the parent's inquiry.

[1644] The present invention is a system for reducing the workload of educators and improving the quality of education. This system supports lesson preparation and parental support, and a specific embodiment thereof is described below.

[1645] System configuration

[1646] The system includes the following hardware and software:

[1647] 1. Input Method

[1648] It is a device or interface that allows users (teachers) to input lesson topics, target grades, necessary materials, or inquiries from parents.

[1649] Examples: keyboards, touchscreens, voice input devices

[1650] 2. Receiving Method

[1651] This is a device or function that allows the terminal to send input data and inquiry contents to the server, and the server to receive them.

[1652] Examples: Internet connection, API communication interface

[1653] 3. Data Analysis Methods

[1654] The server contains algorithms and programs that analyze the data it receives.

[1655] Example: Data analysis program

[1656] 4. Prompt Generation Methods

[1657] The server is a mechanism for generating prompt sentences to send to the generative AI model.

[1658] Examples: text generation programs, natural language processing algorithms

[1659] 5. Generation means

[1660] The server is an algorithm or program that automatically generates lesson content and responses to parents based on prompts.

[1661] Example: Generative AI models (e.g., OpenAI's GPT-4)

[1662] 6. Display means

[1663] It is a device or interface for visually displaying generated content and answers to the user.

[1664] Examples: monitors, tablet screens, smartphone screens

[1665] Class preparation support

[1666] The user (teacher) uses a device to input the lesson theme, target grade, and necessary materials. For example, they might input "Math class for second-year junior high school students, theme is simultaneous equations, necessary materials are practice problems and slides." The device then sends this input information to the server. The server analyzes the received data and, based on the analysis results, creates a prompt to send to a generative AI model (for example, OpenAI's GPT-4). The generated prompt is "Create lesson materials for a 2nd-year junior high school math class. The topic is simultaneous equations. Generate practice problems and slides." The generative AI model generates lesson content based on this prompt; specifically, practice problems related to simultaneous equations, sample answers, and slides are generated. The generated content is sent from the server to the device, which then displays it to the teacher. The teacher can view and edit this generated content.

[1667] Support for parental interaction

[1668] The user (teacher) uses the device to input the parent's inquiry. For example, they might input "Inquiry about this week's class content." The device then sends this information to the server. The server analyzes the received inquiry and, based on the analysis results, creates a prompt to send to a generative AI model (e.g., OpenAI's GPT-4). The generated prompt is "Provide a detailed response to a parent's inquiry about this week's class content. The class covered simultaneous equations and their applications. Include a suggestion for reviewing the material with their child." The generative AI model then generates an answer based on this prompt, specifically, "In this week's class, we learned about simultaneous equations and their applications. To check your child's understanding, please solve the following review problem together." The generated answer is sent from the server to the device, where it is displayed to the teacher. The teacher can view, edit, or modify the answer and then send it to the parent.

[1669] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1670] Class preparation support

[1671] Processing Steps

[1672] Step 1:

[1673] The user inputs the lesson topic, target grade, and necessary materials into the terminal.

[1674] Input: "8th grade math class, topic: simultaneous equations, required materials: practice problems and slides"

[1675] Output: The device holds this input data.

[1676] Step 2:

[1677] The terminal transmits the input data to the server.

[1678] Specific operation: The device uses the API to send data to the server as an HTTP request.

[1679] Input: Data entered by the user

[1680] Output: The server receives the data.

[1681] Step 3:

[1682] The server parses the received data.

[1683] Specific operation: The server launches a data analysis program and extracts keywords such as "simultaneous equations" and "second-year junior high school student."

[1684] Input: Data received from the terminal

[1685] Output: Extracted keyword list

[1686] Step 4:

[1687] The server generates a prompt to send to the generative AI model.

[1688] Specific operation: The server uses a text generator to create the following prompt: "Create lesson materials for a 2nd-year junior high school math class. The topic is simultaneous equations. Generate practice problems and slides."

[1689] Input: Extracted keyword list

[1690] Output: Generated prompt statement

[1691] Step 5:

[1692] A generative AI model generates lesson content.

[1693] How it works: Based on the prompt, the generative AI model generates practice problems, sample answers, and slides related to simultaneous equations.

[1694] Input: Generated prompt statement

[1695] Output: Generated lesson content (exercises, sample answers, slides)

[1696] Step 6:

[1697] The server transmits the generated content to the terminal.

[1698] Specific operation: The server sends the generated lesson content to the terminal as an HTTP response.

[1699] Input: Generated lesson content

[1700] Output: The device receives the lesson content.

[1701] Step 7:

[1702] The terminal displays the generated content to the user.

[1703] Specific operation: The device launches a program to visually display the data received, allowing the user to confirm the displayed content.

[1704] Input: Lesson content received from the server

[1705] Output: The content that is displayed to the user

[1706] Support for parental interaction

[1707] Processing Steps

[1708] Step 1:

[1709] The user inputs the parent's inquiry into the terminal.

[1710] Input: "Inquiry about this week's class content"

[1711] Output: The device holds this input data.

[1712] Step 2:

[1713] The terminal transmits the input inquiry to the server.

[1714] Specific operation: The device uses the API to send the inquiry to the server as an HTTP request.

[1715] Input: The query entered by the user

[1716] Output: The server receives the query.

[1717] Step 3:

[1718] The server analyzes the query.

[1719] Specific operation: The server launches a data analysis program and extracts keywords such as "class content" and "inquiry."

[1720] Input: Inquiry received from the device

[1721] Output: Extracted keyword list

[1722] Step 4:

[1723] The server generates a prompt to send to the generative AI model.

[1724] What it does: The server uses a text generator to create the following prompt: "Provide a detailed response to a parent's inquiry about this week's class content. The class covered simultaneous equations and their applications. Include a suggestion for reviewing the material with their child."

[1725] Input: Extracted keyword list

[1726] Output: Generated prompt statement

[1727] Step 5:

[1728] A generative AI model generates the answer.

[1729] Specific behavior: The generative AI model generates an appropriate answer based on the prompt.

[1730] Input: Generated prompt statement

[1731] Output: Generated answer (Example: This week in class we learned about simultaneous equations and their applications. To check your child's understanding, try working through these review questions together.)

[1732] Step 6:

[1733] The server sends the generated response to the terminal.

[1734] Specific operation: The server sends the generated answer to the device as an HTTP response.

[1735] Input: Generated answer

[1736] Output: The device receives the answer.

[1737] Step 7:

[1738] The terminal displays the generated answer to the user.

[1739] Specific operation: The device launches a program to visually display the data received, allowing the user to confirm the displayed answer.

[1740] Input: Answer received from the server

[1741] Output: The answer that is displayed to the user

[1742] (Application example 1)

[1743] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1744] In conventional education systems, teachers have to spend a lot of time preparing lessons and responding to parents, limiting the room for improving the quality of education. It is also difficult for teachers to quickly obtain necessary materials and content or efficiently respond to inquiries from parents. This increases the workload of teachers and reduces the time they have to communicate with students. The purpose of this invention is to solve these problems, reduce the workload of educators, and improve the quality of education.

[1745] 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.

[1746] In this invention, the server includes an input means for inputting the lesson theme, target grade, and necessary materials, a receiving means for receiving the data input by the input means, and a generating means for automatically generating lesson content based on the data received by the receiving means. This makes it possible to display content generated based on prompt sentences on the display of the smart glasses. Furthermore, by including an input means for inputting inquiries from parents, a receiving means for receiving the inquiries input by the input means, and a generating means for analyzing the inquiries received by the receiving means and generating appropriate answers, it is possible to display answers generated based on prompt sentences on the display of the smart glasses. This reduces the workload of educators and improves the quality of education.

[1747] Key Word Definitions

[1748] A "lesson topic" is a specific content or topic that an educator teaches.

[1749] "Target grade" refers to the grade of students taking the class.

[1750] "Necessary materials" refers to teaching materials and reference materials needed to conduct the lesson.

[1751] "Input means" refers to a device or interface that allows a user to input data or inquiries.

[1752] The "receiving means" refers to a device or function for receiving data or inquiry content input by the input means.

[1753] The "generation means" refers to an algorithm or program that automatically generates content or answers based on the data received by the reception means.

[1754] "Display means" refers to a device or interface for visually displaying generated content and answers to the user.

[1755] A "prompt sentence" is a specific input sentence that instructs the generative AI on what content to generate.

[1756] "Smart glasses" are eyeglass-type devices with computer functions that can provide users with visual information in real time.

[1757] "Form for carrying out the invention" of the specification

[1758] The present invention relates to a system for reducing the workload of educators and improving the quality of education. This system is designed to support lesson preparation and parental support. Specific embodiments of the present invention will be described below.

[1759] (Class preparation support)

[1760] Consider the example of a teacher using smart glasses. First, the teacher inputs the lesson topic, target grade, and necessary materials into the smart glasses via voice input or a touch interface, such as "Mathematics class for second-year junior high school students, the topic is simultaneous equations, and the necessary materials are practice problems and slides." This input information is then sent from the device to the server.

[1761] The server analyzes the received information and automatically generates appropriate lesson content using a generative AI model. Specifically, practice problems, sample solutions, and slides related to simultaneous equations are automatically generated. The generated content is sent from the server to the smart glasses in real time, where teachers can review it and immediately edit or revise it if necessary.

[1762] (Support for parents)

[1763] Smart glasses are also useful for teachers when communicating with parents. For example, teachers can input questions from parents, such as "questions about this week's lesson content," using voice input or a touch interface. This information is also sent from the device to the server.

[1764] The server analyzes the received inquiry and automatically generates an appropriate answer using a generative AI model. Specifically, it might generate an answer such as, "In this week's class, we learned about simultaneous equations and their applications. To check your child's understanding, please try solving the following review problem together." The generated answer is sent from the server to the smart glasses in real time, where the teacher can review it and, if necessary, instantly edit or revise it before sending it to the parent.

[1765] (Hardware and software used)

[1766] The following hardware and software are used in implementing the present invention.

[1767] Hardware:

[1768] Smart glasses (display information and accept voice and touch input)

[1769] Smartphone (linked to smart glasses and communicating with the server)

[1770] Cloud server (receives, analyzes, generates, and transmits data)

[1771] software:

[1772] OpenAI API (provides generative AI models)

[1773] Python (a programming language for writing programs to receive, analyze, and process data)

[1774] (Example)

[1775] Example of lesson preparation:

[1776] When a teacher enters "Mathematics class for second-year junior high school students, topic is simultaneous equations, required materials are practice problems and slides" into the input field on the smart glasses, the generation AI uses this information to generate appropriate practice problems, sample answers, and slides, which are then displayed on the smart glasses.

[1777] Examples of parental interactions:

[1778] When a teacher types "Inquiry about this week's lesson content" into the input field on the smart glasses, the generative AI generates an appropriate response to the inquiry, which the teacher confirms and then sends to the parent.

[1779] In this way, the present invention saves educators time and effort and provides a higher quality education.

[1780] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1781] Program processing flow

[1782] Class preparation support

[1783] Step 1:

[1784] The user (teacher) inputs the lesson topic, target grade, and necessary materials into the smart glasses.

[1785] Input: 8th grade math class, topic is simultaneous equations, required materials are practice problems and slides.

[1786] Output: Send input data from smart glasses to the device.

[1787] Step 2:

[1788] The terminal transmits the data entered by the user to the server.

[1789] Input: Lesson topic, target grade, and required materials information entered by the teacher.

[1790] Output: Sends input data to the server.

[1791] Step 3:

[1792] The server analyzes the received data and calls a generative AI model to create a prompt.

[1793] Input: Teacher input data.

[1794] Data processing: Prompt generation. For example, "Generate exercises and slides for a simultaneous equations class for eighth graders."

[1795] Output: The generated prompt statement.

[1796] Step 4:

[1797] The server generates lesson content using the generative AI model.

[1798] Input: The generated prompt statement.

[1799] Data Calculation: Generate simultaneous equation practice problems, sample answers, and slides based on generated prompts.

[1800] Output: The generated lesson content.

[1801] Step 5:

[1802] The server transmits the generated content to the terminal.

[1803] Input: Generated lesson content.

[1804] Output: Send lesson content to the device.

[1805] Step 6:

[1806] The lesson content received by the device is displayed on the smart glasses.

[1807] Input: Lesson content sent from the server.

[1808] Output: Display content on the smart glasses display.

[1809] Support for parental interaction

[1810] Step 1:

[1811] The user (teacher) inputs the parent's inquiry into the smart glasses.

[1812] Input: "Inquiry about this week's class content"

[1813] Output: Send input data from smart glasses to the device.

[1814] Step 2:

[1815] The terminal transmits the inquiry content input by the user to the server.

[1816] Input: The inquiry entered by the instructor.

[1817] Output: Sends input data to the server.

[1818] Step 3:

[1819] The server analyzes the received query and calls a generative AI model to create a prompt.

[1820] Input: Teacher input data.

[1821] Data processing: Generate prompt sentences. For example, "Parental inquiry: Please respond appropriately to the inquiry about this week's lesson content."

[1822] Output: The generated prompt statement.

[1823] Step 4:

[1824] The server uses the generative AI model to generate answers for the parents.

[1825] Input: The generated prompt statement.

[1826] Data Calculation: Generates appropriate answers to queries based on generated prompts. For example, "In class this week, we learned about simultaneous equations and their applications."

[1827] Output: The generated answer.

[1828] Step 5:

[1829] The server sends the generated response to the terminal.

[1830] Input: The generated answer.

[1831] Output: Sends the answer to the terminal.

[1832] Step 6:

[1833] The answer received by the device is displayed on the smart glasses.

[1834] Input: The answer sent by the server.

[1835] Output: Show the answer on the smart glasses display.

[1836] 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.

[1837] The present invention provides a system for reducing the workload of educators and improving the quality of education. This system supports lesson preparation and parental support, and also includes an emotion engine for recognizing the emotions of users (teachers). Specific embodiments of the system are described below.

[1838] Class preparation support

[1839] Examples:

[1840] The user uses the device to input the lesson topic, target grade, and required materials. For example, they might input "math class for second-year junior high school students, topic is simultaneous equations, required materials are practice problems and slides." The device then sends this information to the server.

[1841] The server analyzes the received data and calls the generative AI and emotion engine. The emotion engine recognizes the emotion expressed by the user when inputting and customizes the lesson content based on that emotion. For example, if the user is feeling stressed, it generates simple content to ease the stress. The generative AI generates practice problems, sample answers, and slides related to simultaneous equations.

[1842] The server sends the generated content to the terminal, which displays it to the user, who can then view the displayed content and edit or modify it as needed.

[1843] Support for parental interaction

[1844] Examples:

[1845] The user uses the device to input the parent's inquiry. For example, the user inputs "Inquiry about this week's lesson content." The device then sends this information to the server.

[1846] The server analyzes the received inquiry and generates an appropriate answer using an emotion engine and generative AI. The emotion engine recognizes the user's emotion when typing and customizes the answer based on that emotion. For example, if the user is tired, it generates a quick and concise answer. The generated answer might be something like, "In this week's class, we learned about simultaneous equations and their applications. To check your child's understanding, try solving the following review problem together."

[1847] The server sends the generated answers to the device, which displays them to the user. The user can check the displayed answers, edit or correct them as necessary, and send the final answers to their parents.

[1848] System configuration

[1849] 1. Input Method

[1850] A device or interface that allows users to input lesson topics, target grades, required materials, or parental inquiries.

[1851] 2. Receiving Method

[1852] A device or function that allows a terminal to send input data or inquiry content to a server, which then receives it.

[1853] 3. Generation means

[1854] Algorithms and programs that automatically generate lesson content and responses to parents based on the data received by the server.

[1855] 4. Display means

[1856] A device or interface for visually displaying generated content and answers to the user.

[1857] 5. Emotion Engine

[1858] An engine that recognizes the emotions of users as they type and customizes lesson content and responses based on those emotions.

[1859] With the above configuration, the present invention reduces the workload of educators and increases the time they spend communicating with students, thereby improving the quality of education. Furthermore, the inclusion of an emotion engine allows for flexible support based on the user's emotions.

[1860] The processing flow will be explained below.

[1861] Class preparation support

[1862] Step 1:

[1863] The user uses the terminal to input the lesson topic, target grade, and necessary materials.

[1864] Step 2:

[1865] The terminal transmits the input data to the server.

[1866] Step 3:

[1867] The server parses the data it receives.

[1868] Step 4:

[1869] The server invokes the emotion engine to recognize the emotion of the user's input.

[1870] For example, if the user is feeling stressed, that emotion is recognized.

[1871] Step 5:

[1872] Based on the recognized emotions, the server calls a generative AI to generate customized lesson content.

[1873] Specifically, if the user is feeling stressed, simple and less burdensome content is generated.

[1874] Examples of generated content include simultaneous equation exercises, sample solutions, and slides.

[1875] Step 6:

[1876] The server transmits the generated content to the terminal.

[1877] Step 7:

[1878] The terminal displays the generated content to the user.

[1879] The user can view the displayed content and edit or modify it as necessary.

[1880] Support for parental interaction

[1881] Step 1:

[1882] The user uses the terminal to input the inquiry from the parent.

[1883] Step 2:

[1884] The terminal transmits the input inquiry to the server.

[1885] Step 3:

[1886] The server analyzes the query received.

[1887] Step 4:

[1888] The server invokes the emotion engine to recognize the emotion of the user's input.

[1889] For example, if the user is tired, it recognizes that emotion.

[1890] Step 5:

[1891] The server uses generative AI to generate appropriate answers based on the recognized emotions.

[1892] Specifically, if the user is tired, a quick and concise response is generated.

[1893] An example of a generated answer might be, "In class this week we learned about simultaneous equations and their applications. To make sure your child understands, try working through the review questions below together."

[1894] Step 6:

[1895] The server sends the generated response to the terminal.

[1896] Step 7:

[1897] The terminal displays the generated answer to the user.

[1898] The user can review the displayed answers, edit or correct them as necessary, and then send the final answers to the parents.

[1899] Through these steps, the system can recognize the user's emotions and support them in preparing lessons and responding to parents accordingly.

[1900] Example 2

[1901] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1902] In recent years, the workload of educators has increased, with a large amount of time and effort being spent on lesson preparation and parental interactions. This has led to concerns about increased stress among educators and a decline in the quality of education. Furthermore, because it is difficult to respond flexibly to the emotions of each individual educator, efficient and effective educational support is required. Therefore, a system is needed to reduce educators' workload and improve the quality of education.

[1903] 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.

[1904] In this invention, the server includes input means for inputting the lesson theme, target grade, and necessary materials, receiving means for receiving the data input by the input means, processing means having an emotion engine for analyzing the data received by the receiving means and recognizing emotions, generation means for customizing and automatically generating lesson content based on the emotions recognized by the emotion engine, and display means for displaying the content generated by the generation means. This makes it possible to generate customized lesson content according to the emotional state of the educator, and to respond quickly and appropriately to parents.

[1905] An "input means" is a device or interface through which a user inputs information.

[1906] The "receiving means" is a function or device that acquires data input by the input means.

[1907] An "emotion engine" is software or algorithms for recognizing and analyzing a user's emotions.

[1908] A "generator" is an algorithm or program for automatically generating content or responses based on received data and recognized sentiment.

[1909] A "display means" is a device or interface for visually presenting generated content and answers to a user.

[1910] A "server" is a computer system responsible for receiving, processing, and transmitting data over a network.

[1911] "Terminal" means a device such as a computer, tablet, or smartphone that a user uses to input and display information.

[1912] "Content" refers to educational materials created according to the lesson theme and target grade.

[1913] A "response" is a text reply generated in response to an inquiry from a parent.

[1914] This system aims to reduce the workload of educators and enable flexible responses according to their emotions. This system provides two main functions: support for lesson preparation and support for parental interaction.

[1915] Class preparation support

[1916] The user inputs the lesson topic, target grade, and required materials using the device, and the information is sent to the server. For example, if a user inputs "math class for second-year junior high school students, topic is simultaneous equations, required materials are practice problems and slides," the device encrypts this information and sends it to the server. The server analyzes the received data and calls the emotion engine and generative AI.

[1917] The emotion engine analyzes the user's emotions when they input information and recognizes their stress level and fatigue. Based on the analysis results, the generative AI automatically generates appropriate lesson content (practice questions, sample answers, slides, etc.). For example, if the user is feeling stressed, simple and easy-to-understand content is generated. The generated content is sent from the server to the device, where the user can review it and edit or modify it as necessary.

[1918] Support for parental interaction

[1919] When a user uses the device to input a parent's inquiry, the device encrypts the information and sends it to the server. For example, if a user inputs "Inquiry about this week's lesson content," the server analyzes the information and calls the emotion engine and generative AI.

[1920] The emotion engine analyzes the user's emotions when they input information and recognizes their fatigue and stress levels. Based on the analysis results, the generative AI automatically generates an appropriate answer. For example, if the user is tired, a short and concise answer will be generated. The generated answer is sent from the server to the device, where the user can review it, make corrections if necessary, and then send the final answer to their guardian.

[1921] Hardware and software used

[1922] Hardware: Devices (PCs, tablets, smartphones), servers

[1923] Software: Emotion engine, generative AI

[1924] Examples of concrete examples and prompts

[1925] Examples of lesson preparation:

[1926] The user types:

[1927] "Mathematics class for second-year junior high school students, the topic is simultaneous equations, and the necessary materials are practice problems and slides."

[1928] Examples of parental interactions:

[1929] The user types:

[1930] "Inquiry about this week's class content"

[1931] This allows appropriate data analysis and content generation at each processing step, reducing the workload of educators and improving the quality of education.

[1932] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1933] Class preparation support

[1934] Step 1:

[1935] The user uses the device to input the lesson topic, target grade, and necessary materials. Specifically, they launch a dedicated application and input "math lesson for second-year junior high school students, topic is simultaneous equations, necessary materials are practice problems and slides."

[1936] Input: lesson topic, target grade, required materials

[1937] Output: Input data

[1938] Step 2:

[1939] The terminal sends the entered data to the server, where it is encrypted and sent securely.

[1940] Input: Data entered by the user

[1941] Output: Encrypted data

[1942] Step 3:

[1943] The server analyzes the data it receives and verifies that the input is accurate and includes all required fields.

[1944] Input: Encrypted data

[1945] Output: Analysis results

[1946] Step 4:

[1947] The server calls the emotion engine to analyze the emotions entered by the user, which then recognizes the level of stress or fatigue.

[1948] Input: Analysis results and input data

[1949] Output: User's emotional state

[1950] Step 5:

[1951] The server calls the generative AI, which generates lesson content based on the received data and the recognized emotions. For example, if the user is feeling stressed, the generative AI will create simple and easy-to-understand exercises, sample answers, and slides.

[1952] Input: User's emotional state and input data

[1953] Output: Generated lesson content

[1954] Step 6:

[1955] The server re-encrypts the generated content data and transmits it to the terminal.

[1956] Input: Generated lesson content

[1957] Output: Encrypted lesson content

[1958] Step 7:

[1959] The device decodes the received data and visually displays it to the user, who can then review the displayed content and make edits or corrections as necessary.

[1960] Input: Encrypted lesson content

[1961] Output: Displayed lesson content

[1962] Support for parental interaction

[1963] Step 1:

[1964] The user uses the device to input the parent's inquiry. Specifically, the user launches a dedicated application and inputs "Inquiry about this week's lesson content."

[1965] Input: Parental inquiry

[1966] Output: Input data

[1967] Step 2:

[1968] The device sends the entered inquiry to the server, where the data is encrypted and sent securely.

[1969] Input: The query entered by the user

[1970] Output: Encrypted data

[1971] Step 3:

[1972] The server analyzes the data it receives to ensure that the input is accurate and that all required information is included.

[1973] Input: Encrypted data

[1974] Output: Analysis results

[1975] Step 4:

[1976] The server calls the emotion engine, which analyzes the emotions entered by the user and recognizes the level of fatigue and stress.

[1977] Input: Analysis results and input data

[1978] Output: User's emotional state

[1979] Step 5:

[1980] The server calls the generative AI, which generates an appropriate response based on the received data and the perceived emotion. For example, if the user is tired, the generative AI will create a quick and concise response.

[1981] Input: User's emotional state and input data

[1982] Output: The generated answer

[1983] Step 6:

[1984] The server re-encrypts the generated response data and transmits it to the terminal.

[1985] Input: Generated answer

[1986] Output: Encrypted answer

[1987] Step 7:

[1988] The device decrypts the received data and visually displays it to the user, who can then review the displayed answers, make corrections if necessary, and send the final answers to the parent.

[1989] Input: Encrypted answer

[1990] Output: The displayed answer

[1991] (Application example 2)

[1992] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1993] In conventional educational support systems and parental support systems, content and responses are generated without taking into account the feelings of educators, which can easily increase stress for educators and lead to a decline in the quality of education and parental support.In addition, due to a lack of flexible support based on user feelings, the user experience is uniform and unable to respond to individual needs.

[1994] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes input means for inputting the lesson theme, target grade, and necessary materials, receiving means for receiving the data input by the input means, generation means for automatically generating lesson content based on the data received by the receiving means, display means for displaying the content generated by the generation means, an emotion engine for recognizing emotions from the user's input content, and adjustment means for customizing the content generated based on the emotion data recognized by the emotion engine. This makes it possible to generate content and answers customized according to the user's emotions, reducing the workload of educators and improving the quality of education and parental support.

[1995] "Class theme" refers to the specific content or subject matter that educators deal with in class.

[1996] "Target grade" refers to the grade of students who are eligible to take the class.

[1997] "Necessary materials" refers to teaching materials and related materials used to smoothly conduct classes.

[1998] "Input means" refers to a device or interface that allows a user to input information into a system.

[1999] The "receiving means" refers to a device or function for receiving data transmitted from the input means.

[2000] "Generation means" refers to an algorithm or program for automatically generating content or answers based on data received by the receiving means.

[2001] "Display means" means a device or interface for visually displaying generated content or answers to a user.

[2002] "Emotion engine" refers to a system or software for recognizing emotions from user input and extracting that emotion data.

[2003] "Adjustment means" refers to a function or program for customizing the content or answers generated based on the emotional data recognized by the emotion engine.

[2004] MODE FOR CARRYING OUT THE INVENTION

[2005] The present invention provides a system for reducing the workload of educators and users of online shopping sites and improving quality. Specific embodiments of the system will be described below.

[2006] 1. Educational Support System

[2007] 1.1. Class preparation support

[2008] Examples:

[2009] The user uses a smartphone or tablet device to input the lesson topic, target grade, and required materials. For example, this information might be "a math class for second-year junior high school students, the topic is simultaneous equations, and the required materials are practice problems and slides." The device then sends this information to the server.

[2010] The server analyzes the received data and activates the emotion engine. The emotion engine recognizes the emotion expressed by the user when inputting the data and customizes the lesson content based on that emotion data. For example, if the user is feeling stressed, it generates simple content to ease their stress.

[2011] Next, the generative AI model generates practice problems, sample solutions, and slides related to simultaneous equations. The server sends the generated content to the device, which displays it to the user. The user can review the displayed content and edit or modify it as needed.

[2012] 2. Implementation of a personalized shopping assistant for an online shopping site

[2013] Shopping Assistant

[2014] Examples:

[2015] A user uses a smartphone to type, "I'm looking for the latest smartphone, but I don't know how to choose one." The device sends this information to the server.

[2016] The server analyzes the received data and activates the emotion engine, which recognizes the user's emotions when inputting and customizes product recommendations based on the emotion data. For example, if the user is tired, it generates a list of recommendations that emphasizes easy-to-use products.

[2017] Next, the generative AI model generates a product recommendation list based on the user's needs and emotions. The server sends the generated recommendation list to the device, which displays it to the user. The user then reviews the displayed recommendation list and selects suitable products.

[2018] Hardware and software used

[2019] Hardware:

[2020] 1. Smartphone

[2021] 2. Tablet devices

[2022] 3. Server

[2023] software:

[2024] 1. Emotion Engine: Software for recognizing emotions from user input

[2025] 2. Generative AI model: Software for automatically generating lesson content and product lists

[2026] Adding specific examples

[2027] Prompt Sentence Examples

[2028] Prompt: "I'm looking for the latest smartphone. I'm interested in its features and performance, but I'm a beginner and don't know how to choose one. I've been busy lately and I'm tired."

[2029] Product recommendations provided:

[2030] Product name: Smartphone Model X, Price: 100,000 yen, Features: High-performance camera, long-lasting battery

[2031] Product name: Smartphone Model Y, Price: ¥80,000, Features: Large screen display, easy-to-use UI

[2032] Product name: Smartphone Model Z, Price: 60,000 yen, Features: Waterproof, large storage capacity

[2033] Reason for recommendation: Because the user is feeling stressed or tired, we recommend products that are easy to use.

[2034] This enables the system to generate customized content and answers based on the user's emotions, reducing the workload of educators and online shopping site users and improving quality.

[2035] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2036] Program processing steps

[2037] Shopping assistant system

[2038] Step 1:

[2039] A user uses a smartphone to enter purchasing interests, such as "I'm looking for the latest smartphone, but I don't know how to choose one."

[2040] Input: Text data about purchases entered by the user

[2041] Output: Text data received by the server

[2042] Step 2:

[2043] The terminal sends the user's input to the server, where it can be processed.

[2044] Input: Text data entered by the user

[2045] Output: Text data sent to the server

[2046] Step 3:

[2047] The server analyzes the received text data and activates an emotion engine to recognize the user's emotions.

[2048] Input: Text data sent from the terminal

[2049] Data processing: Analysis of text data, emotion recognition using emotion engine

[2050] Output: Recognized emotion data

[2051] Step 4:

[2052] The server customizes product recommendations based on the recognized emotion data and generates product lists using a generative AI model.

[2053] Input: Recognized emotion data, user input text data

[2054] Data Computation: Customize product recommendations based on sentiment data, generate product lists using generative AI models

[2055] Output: A customized product recommendation list

[2056] Step 5:

[2057] The server sends the generated product recommendation list to the terminal, and the user receives the recommended product list.

[2058] Input: A customized product recommendation list

[2059] Output: Product recommendation list sent to the device

[2060] Step 6:

[2061] The device displays a customized product recommendation list to the user, who then reviews the displayed recommended products and selects the appropriate product.

[2062] Input: Product list sent from the server

[2063] Output: A visual list of products displayed to the user

[2064] Prompt Sentence Examples

[2065] Prompt: "I'm looking for the latest smartphone. I'm interested in its features and performance, but I'm a beginner and don't know how to choose one. I've been busy lately and I'm tired."

[2066] Product recommendations provided:

[2067] Product name: Smartphone Model X, Price: 100,000 yen, Features: High-performance camera, long-lasting battery

[2068] Product name: Smartphone Model Y, Price: ¥80,000, Features: Large screen display, easy-to-use UI

[2069] Product name: Smartphone Model Z, Price: 60,000 yen, Features: Waterproof, large storage capacity

[2070] Reason for recommendation: Because the user is feeling stressed or tired, we recommend products that are easy to use.

[2071]

[2072] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2073] 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.

[2074] 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 robot 414.

[2075] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2076] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2077] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2078] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2079] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2080] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2081] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2082] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2083] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2084] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2085] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[2086] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2087] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2088] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2089] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2090] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2091] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[2092] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[2093] The following is further disclosed regarding the above embodiment.

[2094] (Claim 1)

[2095] An input method for inputting the lesson theme, target grade, and necessary materials;

[2096] receiving means for receiving data input by the input means;

[2097] a generating means for automatically generating lesson content based on the data received by the receiving means;

[2098] a display means for displaying the content generated by the generation means;

[2099] A system including:

[2100] (Claim 2)

[2101] an input means for inputting the contents of an inquiry from a parent;

[2102] receiving means for receiving the inquiry content input by the input means;

[2103] generating means for analyzing the content of the inquiry received by said receiving means and generating an appropriate response;

[2104] a display means for displaying the answer generated by the generation means;

[2105] A system including:

[2106] (Claim 3)

[2107] 3. The system according to claim 1, wherein the receiving means is located on a server;

[2108] The system is characterized in that the display means is arranged on a teacher's terminal.

[2109] "Example 1"

[2110] (Claim 1)

[2111] An input method for inputting the lesson theme, target grade, and necessary materials;

[2112] receiving means for receiving data input by the input means;

[2113] the receiving means is arranged on a server, and data analysis means for analyzing the received data;

[2114] a prompt generation means for generating a prompt sentence to be sent to the generative AI model by the data analysis means;

[2115] a generation means for automatically generating lesson content based on the prompt sentence generated by the prompt generation means;

[2116] a display means for displaying the content generated by the generation means;

[2117] the display means is arranged on a teacher's terminal;

[2118] A system including:

[2119] (Claim 2)

[2120] an input means for inputting the contents of an inquiry from a parent;

[2121] receiving means for receiving the inquiry content input by the input means;

[2122] data analysis means arranged on the server for analyzing the received inquiry;

[2123] a prompt generation means for generating a prompt sentence to be sent to the generative AI model by the data analysis means;

[2124] a generating means for automatically generating an appropriate answer based on the prompt sentence generated by the prompt generating means;

[2125] a display means for displaying the answer generated by the generation means;

[2126] The system is characterized in that the display means is arranged on a teacher's terminal.

[2127] (Claim 3)

[2128] The system described in claim 1, characterized in that the generative AI model transmits the generated lesson content and answers to the teacher's terminal via a server.

[2129] "Application Example 1"

[2130] New Claims

[2131] (Claim 1)

[2132] An input method for inputting the lesson theme, target grade, and necessary materials;

[2133] receiving means for receiving data input by the input means;

[2134] a generating means for automatically generating lesson content based on the data received by the receiving means;

[2135] a display means for displaying the content generated by the generation means;

[2136] display means for displaying content generated based on the prompt sentence on a display of the smart glasses;

[2137] A system including:

[2138] (Claim 2)

[2139] an input means for inputting the contents of an inquiry from a parent;

[2140] receiving means for receiving the inquiry content input by the input means;

[2141] generating means for analyzing the content of the inquiry received by said receiving means and generating an appropriate response;

[2142] a display means for displaying the answer generated by the generation means;

[2143] display means for displaying the generated answer based on the prompt sentence on a display of the smart glasses;

[2144] 10. The system of claim 1, comprising:

[2145] (Claim 3)

[2146] The receiving means is located on a server,

[2147] 2. The system according to claim 1, wherein the display means is disposed on a teacher's terminal.

[2148] "Example 2: Combining Emotion Engines"

[2149] (Claim 1)

[2150] An input method for inputting the lesson theme, target grade, and necessary materials;

[2151] receiving means for receiving data input by the input means;

[2152] a processing means having an emotion engine for analyzing the data received by said receiving means and recognizing emotions;

[2153] a generation means for automatically generating customized lesson content based on the emotions recognized by the emotion engine;

[2154] a display means for displaying the content generated by the generation means;

[2155] A system including:

[2156] (Claim 2)

[2157] an input means for inputting the contents of an inquiry from a parent;

[2158] receiving means for receiving the inquiry content input by the input means;

[2159] a processing means having an emotion engine for analyzing the inquiry content received by the receiving means and recognizing emotions;

[2160] generating means for customizing and generating an appropriate response based on the emotion recognized by the emotion engine;

[2161] a display means for displaying the answer generated by the generation means;

[2162] A system including:

[2163] (Claim 3)

[2164] 2. The system according to claim 1, wherein the receiving means is located on a server, and the display means is located on a terminal.

[2165] "Application example 2 when combining emotion engines"

[2166] Claims

[2167] (Claim 1)

[2168] An input method for inputting the lesson theme, target grade, and necessary materials;

[2169] receiving means for receiving data input by the input means;

[2170] a generating means for automatically generating lesson content based on the data received by the receiving means;

[2171] a display means for displaying the content generated by the generation means;

[2172] an emotion engine for recognizing emotions from user input;

[2173] an adjustment means for customizing content generated based on emotion data recognized by the emotion engine;

[2174] A system including:

[2175] (Claim 2)

[2176] an input means for inputting the contents of an inquiry from a parent;

[2177] receiving means for receiving the inquiry content input by the input means;

[2178] generating means for analyzing the content of the inquiry received by said receiving means and generating an appropriate response;

[2179] a display means for displaying the answer generated by the generation means;

[2180] an emotion engine for recognizing the emotion of a user when entering an inquiry;

[2181] an adjustment means for customizing answers generated based on emotion data recognized by the emotion engine;

[2182] A system including:

[2183] (Claim 3)

[2184] The receiving means is located on a server,

[2185] 2. The system of claim 1, wherein the display means is located on a user terminal. [Explanation of symbols]

[2186] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. An input method for inputting the lesson theme, target grade, and necessary materials; receiving means for receiving data input by the input means; a generating means for automatically generating lesson content based on the data received by the receiving means; a display means for displaying the content generated by the generation means; A system including:

2. an input means for inputting the contents of an inquiry from a parent; receiving means for receiving the inquiry content input by the input means; generating means for analyzing the content of the inquiry received by said receiving means and generating an appropriate response; a display means for displaying the answer generated by the generation means; A system including:

3. 3. The system according to claim 1, wherein the receiving means is located on a server, The system is characterized in that the display means is arranged on a teacher's terminal.

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