System

Abstract

To provide a system that proposes commodities in a timely manner in accordance with a life event unique to students.SOLUTION: A system includes: means that sets in advance a user's grade or school information; means that interacts with the user by using a generative AI, and acquires difficult points or targets in learning through the interaction with the user; means that collects information on a life event that is before a test or before submission of reports through the interaction with the user; and means that, on the basis of the difficult points or targets in learning, and the information on the life event, proposes commodities that are textbooks, notes, or online courses to the user, by using a prompt sentence instructing proposing the commodities and the generative AI.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 a description and related instruction sentence regarding 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] JP 2022-180282 A Summary of the Invention [Problem to be solved by the invention]

[0004] When proposing learning materials and gadgets that meet the learning needs of students, it is necessary to accurately understand the difficulties and goals of each student. It is also necessary to make timely product proposals that match the life events unique to each student. [Means for solving the problem]

[0005] The present invention provides the following means for suggesting learning materials and gadgets that match the learning needs of students. The learning situation of the user is grasped by a means for setting the user's grade and school information in advance. Suggestions are made that match individual needs by a means for understanding the student's difficulties and goals through dialogue with the user using generative AI. Timely product suggestions are made by a means for collecting information on the user's life events. More effective learning support is realized by making accurate suggestions that match the student's learning needs and responding to life events unique to students.

[0006] "Learning needs" refers to the content and methods that students require or want to learn.

[0007] "Instructional Materials" refers to books, textbooks, reference materials, and other study materials used to support learning.

[0008] A "gadget" refers to an electronic device or tool that has functions or equipment that are useful for learning.

[0009] A "data generation model" is an artificial intelligence model that can conduct dialogue using natural language processing technology, and is used to collect information through dialogue with users and make appropriate suggestions. One example of a data generation model is generative AI.

[0010] "Life events" refers to specific events or periods that students experience in their school life, such as commuting to school, taking exams, submitting papers, etc. These events may create special needs or demands in learning. [Brief description of the drawings]

[0011] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Diagram 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. FIG. [Diagram 3]FIG. 11 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Diagram 5] FIG. 13 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. 13 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 13 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] 4 is a sequence diagram showing a process flow of the data processing system according to the first embodiment. FIG. [Figure 12] 11 is a sequence diagram showing a process flow of the data processing system in application example 1. FIG. [Figure 13] FIG. 11 is a sequence diagram showing the flow of processing of the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 11 is a sequence diagram showing the flow of processing in the data processing system in application example 2 when combined with an emotion engine. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0013] First, the terms used in the following description will be explained.

[0014] In the following embodiments, a signed processor (hereinafter simply referred to as a "processor") may be one arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be one 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), or an APU (Accelerated Processing Unit).

[0015] In the following embodiments, a signed RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by the processor.

[0016] 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.

[0017] In the following embodiments, a communication I / F (Interface) with a code is an interface including a communication processor and an antenna. The communication I / F controls communication between multiple computers. An example of a communication standard applied to the communication I / F is a wireless communication standard including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0018] 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. In addition, in this specification, the same idea as "A and / or B" is also applied when three or more things are expressed by connecting them with "and / or."

[0019] [First embodiment]

[0020] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0021] 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.

[0022] 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 wide area network (WAN) and / or a local area network (LAN).

[0023] 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.

[0024] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (e.g., a pen or a finger) to receive user input by the touch of the pointer. 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.

[0025] 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 (e.g., voice and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs voice according to instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a Complementary Metal-Oxide-Semiconductor (CMOS) image sensor or a Charge Coupled Device (CCD) image sensor.

[0026] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54.

[0027] FIG. 2 shows an example of main functions of the data processing device 12 and the smart device 14.

[0028] As shown in Fig. 2, 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. The specific process program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific process program 56 from the storage 32, and executes the read specific process 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 process program 56 executed on the RAM 30.

[0029] 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.

[0030] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores a reception output program 60. The reception output program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads out the reception output program 60 from the storage 50, and executes the read reception output program 60 on the RAM 48. The reception output processing 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.

[0031] Next, a description will be given of the specific processing 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".

[0032] 1. The server has the function of receiving the user's grade and school information and storing it in a database.

[0033] 2. The server will utilize generative AI to engage in dialogue with users and understand their learning difficulties and goals.

[0034] 3. The server has the function of searching the database and suggesting products such as textbooks, notebooks, and online courses according to the user's learning needs.

[0035] 4. The server will have the ability to use generative AI to collect information about student-specific life events, such as before exams or before submitting reports, through dialogue with users.

[0036] 5. The server has the function of searching the database for timely products that match the user's life events and making suggestions.

[0037] 6. The server has the function of processing the purchase of the product selected by the user and sending a notification to the user that the purchase has been completed.

[0038] This allows the server to understand the user's learning needs and recommend appropriate learning materials and gadgets. It also makes timely product suggestions that match the life events specific to the student. The user selects a suggested product, and the server processes the purchase and sends the user a notification of purchase completion.

[0039] As a specific example, a user starts the app and enters their grade and school information. The server understands the user's learning difficulties and goals through dialogue with the user. When the user mentions their weaknesses in mathematics, the server searches the database for mathematics textbooks, notes, and online courses to suggest them. When the user mentions that they need to make a study plan before an exam, the server suggests past exam guidebooks and study plan creation applications. The user selects a suggested product, and the server processes the purchase and sends the user a notification of purchase completion.

[0040] In this way, a system that effectively provides learning support is realized by carrying out product suggestions tailored to the user's learning needs, information collection on life events, and purchasing processing via the server.

[0041] For example, if a user is having difficulty with math, the generative AI will identify the cause through dialogue with the user and suggest products such as math textbooks and online courses. In addition, when a user experiences student-specific life events such as before an exam or before submitting a paper, the generative AI will collect that information and make timely product recommendations.

[0042] For example, if a user tells the AI ​​that they have a university exam coming up, the AI ​​can use their past learning data and other users' exam preparation information to suggest effective study materials and notes for the exam. Also, if a user tells the AI ​​that they have a paper to submit, the AI ​​can suggest books and online resources related to that topic.

[0043] In this way, the system understands the learning needs and life events of the user through dialogue, and suggests suitable learning materials and gadgets. Users can obtain products that are tailored to their learning needs, enabling them to study more effectively.

[0044] The process flow of each embodiment will be described below.

[0045] Step 1: The user launches the app on the device. For example, the user launches the app and enters grade and school information.

[0046] Step 2: The server receives the user's information and stores it in a database. For example, the server receives the grade and school information entered by the user and stores it in a database.

[0047] Step 3: The server uses generative AI to initiate a dialogue with the user. For example, the server uses generative AI to initiate a dialogue with the user. The server generates questions about the user’s learning needs, difficulties, and goals, and receives the user’s answers.

[0048] Step 4: The server analyzes the user's answers and identifies the elements and trends of learning. For example, the server analyzes the user's answers and identifies the elements and trends of learning. When the user tells the server about their weaknesses in math, the server suggests products such as math textbooks, notebooks, and online courses.

[0049] Step 5: The server continues to dialogue with the user using generative AI to collect information about life events. For example, the server uses generative AI to continue dialogue with the user and collect information about student-specific life events, such as before an exam or before submitting a report. If the user mentions that they need to make a study plan before an exam, the server suggests past exam guides and a study plan creation app.

[0050] Step 6: The server processes the product selected by the user. For example, the server processes the product selected by the user from the products proposed. The server processes the purchase of the product selected by the user and notifies the user that the purchase is completed.

[0051] As described above, after a user starts the app and enters their grade and school information, the server interacts with the user to understand their learning needs and life events, and suggests appropriate products. The user selects a suggested product, and the server processes the purchase and sends the user a notification that the purchase has been completed. This realizes a system that supports the user's learning experience.

[0052] Example 1

[0053] Next, a description will be given of Example 1. In the following description, the data processing device 12 is referred to as a "server" and the smart device 14 is referred to as a "terminal."

[0054] Conventional learning support systems lack effective product suggestions tailored to the user's learning needs and life events. In addition, since there is no system that consistently supports the process from product selection to purchase, it is difficult for users to efficiently obtain the learning materials and gadgets they need. Furthermore, detailed understanding of needs through dialogue with users using generative AI models is insufficient.

[0055] 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.

[0056] In this invention, the server includes a means for setting the grade or school information of the user in advance, a means for acquiring learning difficulties or goals through dialogue with the user using a generative AI model, and a means for proposing products such as textbooks, notebooks, or online courses according to the learning difficulties or goals. This makes it possible to propose products with high accuracy according to the learning needs of the user.

[0057] "Grade" is information indicating the academic grade in which the user is currently enrolled.

[0058] "School information" is information about the educational institution that the user attends.

[0059] A "generative AI model" is an artificial intelligence algorithm that generates appropriate responses or suggestions based on human input.

[0060] "Difficult points in learning" refers to areas or issues that the user finds particularly difficult in learning.

[0061] "Goal" refers to the specific purpose or outcome that a user wants to achieve through learning.

[0062] "Instructional Materials" are learning resources such as books, notes, online courses, etc. that are used to assist the user in their learning.

[0063] "Gadgets" refers to electronic devices and tools that aid in learning.

[0064] "Products" refers collectively to all learning materials and gadgets proposed to aid learning.

[0065] A "life event" refers to an important event that a user experiences at a particular time, such as before an exam or before submitting a report.

[0066] The "purchase process" refers to a series of procedures including payments and other procedures required to purchase the product selected by the user.

[0067] A "notification" is information or a message sent from the server to the user.

[0068] To implement the present invention, information is exchanged between the server, the terminal, and the user. The necessary hardware and software, as well as specific operation examples, are described below.

[0069] Hardware used

[0070] Server (a server equipped with a high-performance CPU and large-capacity memory)

[0071] Database server (e.g. MySQL (registered trademark), PostgreSQL (registered trademark))

[0072] User's device (smartphone, PC, etc.)

[0073] Software used

[0074] Generative AI models (e.g. OpenAI ChatGPT)

[0075] Database management systems (e.g. MySQL, PostgreSQL)

[0076] Web application frameworks (e.g. Django(R), Flask(R))

[0077] Network communication protocol (e.g. HTTP / HTTPS)

[0078] Working Example

[0079] 1. User input operations

[0080] The user starts up a dedicated application on their smartphone or computer, enters their grade and school information into the form displayed on the application screen, and clicks the "Submit" button.

[0081] 2. Receiving and storing data on the server side

[0082] The server receives the grade and school information entered by the user as an HTTP request and saves it as a new entry in the database.

[0083] 3. Dialogue using generative AI

[0084] The server starts the generative AI model and starts a dialogue with the user. For example, it asks, "Hello. What are you having trouble with in the learning you are currently doing?" It analyzes the user's response and understands the learning difficulties and goals.

[0085] 4. Product proposal

[0086] Based on the acquired learning difficulties and goals, the server searches a database for appropriate learning materials and gadgets (e.g., mathematics textbooks and online courses) and suggests them to the user.

[0087] 5. Ongoing dialogue and information gathering

[0088] The server uses a generative AI to ask the user, "Is there anything else you're having trouble with studying or schoolwork?" and, if it gets a response like, "I have an important math exam next week," it records this information.

[0089] 6. Product re-proposal based on life events

[0090] Based on the collected life events, the server re-searches the database for related products (e.g., exam preparation notes and manuals) and suggests them to the user.

[0091] 7. Purchase Processing and Notifications

[0092] When the user selects a product, the server receives the purchase request, communicates with the payment system, and executes the purchase process. When the purchase is complete, the server sends a "purchase completed" notification to the user.

[0093] Examples of prompt statements

[0094] "I'm in the third year of middle school and I'm not good at math. I have exams coming up. Can you tell me some effective study methods and useful study materials?"

[0095] Using these prompts, the generative AI model can understand the user's specific learning needs and difficulties and suggest suitable learning materials and online courses from its database, allowing users to receive effective learning support tailored to their grade level and learning goals.

[0096] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0097] Step 1:

[0098] The user enters grade and school information from the terminal. The user starts the application, enters their grade and school information in the form on the screen, and clicks the "Submit" button. The input data is the user's grade and school information. This is sent to the server.

[0099] Step 2:

[0100] The server receives the input information and saves it in the database. The server parses the user's grade and school information received as an HTTP request and saves it as a new record in the database (e.g. MySQL, PostgreSQL). During this process, a database insert operation is performed and a confirmation message is generated if successful.

[0101] Step 3:

[0102] The server uses a generative AI model to start a dialogue with the user and understands the learning difficulties and goals. The server starts a generative AI model (e.g., ChatGPT by OpenAI) and asks the user, "Hello. What are you having particular difficulty with in the learning you are currently working on?" The server analyzes the text data received as the user's response and extracts the learning difficulties and goals.

[0103] Step 4:

[0104] The server searches the database for products that meet the user's learning needs and suggests them. The server searches the database for related textbooks, notes, or online courses based on the extracted learning difficulties and goals. The server sends the product list obtained as the search result to the user in the form of a suggestion message.

[0105] Step 5:

[0106] The server continues to use the generative AI model to continue the dialogue with the user, collecting information about life events such as before an exam or before submitting a report. The server asks, "Is there anything else you're having trouble with regarding your studies or schoolwork?" If the user responds, "I have an important math exam next week," the server analyzes the text data and records it as life event information.

[0107] Step 6:

[0108] The server re-searches the database for products that match the user's life event and suggests them. The server again searches the database for related products (e.g., exam preparation notes and manuals) based on the collected life event information. The search results are sent to the user in the form of a suggestion message.

[0109] Step 7:

[0110] The user selects a product. The user checks the list of products suggested by the server and selects the product he or she wants to purchase by clicking the "Purchase" button. The selection information is sent to the server.

[0111] Step 8:

[0112] The server processes the purchase of the selected item and sends a notification of purchase completion to the user. The server receives the purchase request, communicates with the payment system to perform the appropriate payment processing, and if the payment is successful, generates a notification message of purchase completion and sends it to the user.

[0113] (Application example 1)

[0114] 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."

[0115] Conventional learning support systems have difficulty in timely proposing appropriate learning materials and products that match the individual learning needs and life events of learners. In addition, it has been difficult to grasp specific difficulties and goals through dialogue with learners and provide optimal resources accordingly. This has made it difficult to maximize the learning effect of learners.

[0116] 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.

[0117] In this invention, the server includes a means for setting the user's grade or school information in advance, a means for acquiring learning difficulties or goals through dialogue with the user using a generative AI model, a means for proposing products such as textbooks, notes, or online courses according to the learning difficulties or goals, a means for collecting the user's life events (e.g., before an exam, before submitting a report) and proposing timely products, a means for processing the purchase of the product selected by the user and notifying the user of the completion of the purchase, and a means for generating prompt sentences for dialogue using a generative AI model. This makes it possible to propose and purchase appropriate resources according to the user's learning needs and life events.

[0118] The "means for setting the user's grade or school information in advance" refers to a method for inputting and registering information about the grade or school the user belongs to in advance into the system.

[0119] A "generative AI model" is an artificial intelligence model that uses machine learning algorithms to interact with users and generate data.

[0120] The "means for acquiring learning difficulties or goals" refers to a method for identifying, through dialogue with users, which learning content they are having difficulty with or which learning goals they want to achieve.

[0121] A "means for suggesting products that are textbooks, notes, or online courses" is a method for selecting and recommending suitable learning materials or online educational resources to a user based on learning difficulties and goals.

[0122] The "means for collecting user's life events" is a method by which a user collects information about a specific event, such as before an exam or before submitting a report.

[0123] The "means for proposing timely products" is a method for proposing the most useful product to the user at that time based on collected life event information.

[0124] The "means for carrying out the purchasing process for the product selected by the user and notifying the user of the completion of the purchase" refers to a method for carrying out the purchasing process for the product selected by the user and notifying the user of the completion of the purchase.

[0125] A "means for generating prompts for dialogue using a generative AI model" is a method for automatically generating questions or instructions for effective dialogue with a user using a generative AI model.

[0126] This invention is an embodiment of a system that suggests learning materials and gadgets that match the user's learning needs and life events, and supports the purchase procedure. The system includes the following components.

[0127] Hardware Configuration

[0128] server:

[0129] Amazon Web Services (AWS®), Google® Cloud, or Azure®

[0130] User device:

[0131] Smartphone (iOS(R) or ANDROID(R))

[0132] Software configuration and processing

[0133] The server has the following software and functions:

[0134] Database:

[0135] Relational databases such as MySQL and PostgreSQL

[0136] Stores user information, product information, and life event information

[0137] Generative AI models:

[0138] Advanced conversational AI models such as OpenAI ChatGPT

[0139] Through dialogue with the user, the system understands the learning difficulties and goals and generates prompts

[0140] Purchase Processing System:

[0141] Integrate payment processors like Stripe and PayPal

[0142] Implementation Procedure

[0143] 1. User Registration:

[0144] A user launches the app and enters grade or school information, which is then stored in a database on the server.

[0145] 2. Interactive learning support:

[0146] When a user inquires about a particular learning difficulty or goal, the generative AI model on the server collects detailed information through dialogue. For example, if a user asks, "I don't understand mathematical functions," the generative AI model generates a prompt such as, "What learning materials can help me understand?"

[0147] 3. Study material suggestions:

[0148] Based on the collected information, the server searches its database for appropriate learning materials (textbooks, notes, online courses, etc.) and suggests them to the user.

[0149] 4. Life Event Support:

[0150] When a user provides information about a life event, such as before an exam or before submitting a report, the generative AI model suggests timely products that match that event.

[0151] 5. Product Purchase:

[0152] The user selects the suggested product and completes the purchase procedure. The server processes the purchase and issues a purchase completion notification.

[0153] Examples

[0154] For example, if a user is having difficulty learning about mathematical functions, the difficulty is identified through the dialogue function of the smartphone app. The generative AI model generates a prompt, "What kind of study materials do you need about mathematical functions?" and suggests appropriate study materials from a past database. When the user selects, "I want exam preparation notes," the purchase procedure is completed through the payment system, and a notification that "purchase has been completed" is sent to the user.

[0155] Examples of prompt statements

[0156] If a user asks, "I don't understand a mathematical function":

[0157] "What teaching materials can help me understand math functions?"

[0158] Example of the answer generated:

[0159] "There are books and online courses that explain mathematical functions. I can suggest these products. Would you be interested?"

[0160] In this way, a system is constructed that can efficiently suggest and purchase appropriate resources according to the user's learning needs and life events.

[0161] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0162] Step 1:

[0163] User Registration:

[0164] A user starts the smartphone app and registers their grade and school information. The input is provided by the user, and the server receives this input and stores it in a database. This organizes the user's basic information and uses it for subsequent customized suggestions.

[0165] Input: Grade, School Information

[0166] Output: User information stored in the database

[0167] Step 2:

[0168] Interacting with generative AI models:

[0169] The user asks questions about their learning difficulties and goals through the app. The conversational bot using the generative AI model analyzes the user's input, generates appropriate prompts, and continues the conversation. For example, if the user types, "Mathematical functions are difficult," the generative AI model responds, "Which part specifically is difficult?"

[0170] Input: User question

[0171] Output: Response prompts from a generative AI model

[0172] Step 3:

[0173] Identifying learning challenges and goals:

[0174] Through dialogue with the generative AI model, the server identifies the user's learning difficulties and goals. If the user specifically answers, for example, "I don't understand how to draw a graph of a function," that information is sent to the server and stored.

[0175] Input: User interaction

[0176] Output: Identified learning difficulties and goals

[0177] Step 4:

[0178] Suggested teaching materials:

[0179] Based on the identified learning difficulties and goals, the server searches the database for appropriate learning materials (textbooks, notes, online courses, etc.) and suggests them to the user. For example, learning materials for "how to draw a graph of a function" are suggested.

[0180] Input: Learning difficulties and goals

[0181] Output: A list of suggested materials

[0182] Step 5:

[0183] Collecting life event information:

[0184] When a user provides information about a life event, such as before an exam or before submitting a report, the server collects that information and the generative AI model suggests timely products to meet the user's needs. For example, when a user says, "I have a math exam next week," a notebook for exam preparation is suggested.

[0185] Input: Life event information

[0186] Output: Product suggestions based on life events

[0187] Step 6:

[0188] Checkout:

[0189] The user selects the suggested learning materials and completes the purchase procedure. The server processes the payment and sends the user a notification that the purchase is complete. Payment services such as Stripe (registered trademark) and PayPal (registered trademark) are used for the payment process.

[0190] Input: User's purchase selection

[0191] Output: Purchase completion notification

[0192] Step 7:

[0193] Post-purchase notice:

[0194] After the purchase procedure is completed, the server sends a notification of purchase completion to the user, so that the user can confirm that the purchase process was completed successfully.

[0195] Input: Purchase completion data

[0196] Output: Notification to user that purchase is complete

[0197] The above are the specific process steps for carrying out the invention.

[0198] Furthermore, an emotion engine that estimates the emotion of the user may be combined. That is, the identification processing unit 290 may estimate the emotion of the user using the emotion identification model 59, and perform identification processing using the emotion of the user.

[0199] In this case, the system includes the following elements:

[0200] 1. The server has the function of receiving the user's grade and school information and storing it in a database.

[0201] 2. The server will utilize generative AI to engage in dialogue with users and understand their learning difficulties and goals.

[0202] 3. The server has the function of searching the database and suggesting products such as textbooks, notebooks, and online courses according to the user's learning needs.

[0203] 4. The server will have the ability to utilize generative AI to continue dialogue with the user and collect information about life events.

[0204] 5. The server is equipped with an emotion engine that recognizes the user's emotions and has the ability to analyze the user's emotional state.

[0205] 6. The server will have the ability to customize learning support and product suggestions according to the user's emotional state.

[0206] This allows the server to understand the user's learning needs and recommend appropriate learning materials and gadgets. It can also recognize the user's emotional state and customize learning support and product suggestions to match the user's emotions.

[0207] As a concrete example, a user starts the app and inputs their grade and school information. The server understands the user's learning difficulties and goals through dialogue with the user. When the user tells the server what they are weak at in math, the server searches the database for math textbooks, notes, and online courses and suggests them. At the same time, the server uses an emotion engine to analyze the user's emotional state, and if it determines that the user is feeling anxious or stressed, it suggests appropriate study support and relaxation methods.

[0208] In this way, product suggestions tailored to the user's learning needs and emotional support are provided via the server, providing a more personalized learning experience.

[0209] The process flow will be explained below.

[0210] Step 1: The user launches the app on the device. For example, the user launches the app and enters grade and school information.

[0211] Step 2: The server receives the user's information and stores it in a database. For example, the server receives the grade and school information entered by the user and stores it in a database.

[0212] Step 3: The server uses generative AI to initiate a dialogue with the user. For example, the server uses generative AI to initiate a dialogue with the user. The server generates questions about the user’s learning needs, difficulties, and goals, and receives the user’s answers.

[0213] Step 4: The server analyzes the user's answers and identifies the elements and trends of learning. For example, the server analyzes the user's answers and identifies the elements and trends of learning. When the user tells the server about their weaknesses in math, the server suggests products such as math textbooks, notebooks, and online courses.

[0214] Step 5: The server continues to dialogue with the user using generative AI to collect information about life events. For example, the server uses generative AI to continue dialogue with the user and collect information about student-specific life events, such as before an exam or before submitting a paper. If the user mentions that they need to make a study plan before an exam, the server suggests past exam guides and a study plan creation application.

[0215] Step 6: The server combines an emotion engine that recognizes the user's emotions and analyzes the user's emotional state. For example, the server uses the emotion engine to analyze information such as the user's speech and facial expressions to recognize the user's emotional state. If the server determines that the user is feeling anxious or stressed, it will provide appropriate study support or suggest ways to relax.

[0216] Step 7: The server customizes learning support and product suggestions based on the user's emotional state. For example, the server customizes learning support and product suggestions based on the user's emotional state. If the server determines that the user needs relaxation, it suggests relaxing music or a meditation application.

[0217] That's it. After the user starts the app and enters their grade and school information, the server will understand information about the user's learning needs and life events through dialogue with the user and suggest appropriate products. At the same time, the server will use an emotion engine to analyze the user's emotional state and provide support and suggestions tailored to the user's emotions. This makes it possible to more individually customize the user's learning experience and provide support based on emotions.

[0218] Example 2

[0219] Next, a description will be given of Example 2. In the following description, the data processing device 12 is referred to as a "server" and the smart device 14 is referred to as a "terminal."

[0220] Conventional learning support systems can provide learning materials and learning resources according to the user's learning needs, but it is difficult to provide personalized support that takes into account the user's emotional state. In addition, there is a lack of flexible learning material suggestions that respond to the user's life events and changes in daily life. This makes it difficult to provide an optimal learning experience for each individual user.

[0221] 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.

[0222] In this invention, the server includes a means for setting the grade or school information of the user in advance, a means for acquiring learning difficulties or goals through dialogue with the user using a generative AI model, a means for proposing products, which are teaching materials or online courses, according to the learning difficulties or goals, a means for combining an emotion engine for analyzing the emotional state of the user, and a means for customizing the suggesting means according to the emotional state of the user. This enables flexible teaching material suggestions that take into account the user's emotions and life events, and personalized learning support.

[0223] "User" refers to an individual who receives learning support using this system.

[0224] The "grade" is information indicating the educational stage of the educational institution in which the user is currently enrolled.

[0225] "School information" is information that includes details such as the name and location of the educational institution that the user attends.

[0226] A "generative AI model" is a type of artificial intelligence (AI) that uses natural language processing to interact with users and generate answers to their input and questions.

[0227] "Difficulties in learning" refers to subjects or content that the user finds particularly difficult to understand in learning.

[0228] "Goal" is information indicating the purpose or goal of learning that the user wishes to achieve.

[0229] "Instructional Materials" refers to educational materials such as textbooks, notes, online courses, etc. that a User uses to study.

[0230] "Means of suggestion" refers to a mechanism by which the server presents appropriate learning materials and products according to the user's learning needs.

[0231] An "emotion engine" refers to an algorithm or software that analyzes a user's language expressions and dialogue content to determine their emotional state (e.g., anxiety, stress, joy, etc.).

[0232] "Emotional state" refers to the psychological state that a user is feeling at a given moment, and includes factors such as motivation for learning, anxiety, and stress.

[0233] "Life events" refer to major events that occur in the user's daily life (e.g. exams, submitting reports, entering higher education, etc.).

[0234] The "means for carrying out purchase processing" refers to a mechanism for carrying out the procedure for purchasing the product selected by the user online or offline.

[0235] "Means for notifying the user of the completion of purchase" refers to a mechanism for executing a procedure to notify the user that the purchase of the product selected by the user has been completed.

[0236] This invention is a system that suggests learning materials and gadgets according to the user's learning needs and further personalizes support based on the user's emotional state. This system is composed of three main elements: a server, a terminal, and a user.

[0237] 1. Enter and save user information

[0238] server:

[0239] When a user launches an application on a terminal and enters grade and school information, that information is sent to the server. The server stores the user information received from the application in a database (e.g., MySQL or PostgreSQL). This stored information is used to provide a personalized learning experience for each user.

[0240] Examples:

[0241] The user enters "second year high school student" and "XX High School" into the application's input form. This information is sent to the server and saved in the database.

[0242] 2. Understanding learning difficulties through dialogue with users

[0243] server:

[0244] The server uses a generative AI model (e.g., ChatGPT by OpenAI) to converse with the user. Through the dialogue, the server understands the user's learning difficulties and goals, and uses that information to prepare to suggest appropriate learning materials.

[0245] Examples:

[0246] The user enters, "I'm not good at math," and the generative AI model asks, "Which part is difficult for you?" The user answers, "Calculus is difficult."

[0247] 3. Product suggestions based on learning needs

[0248] server:

[0249] The server searches a database for appropriate learning materials (e.g., mathematics textbooks, notes, online courses) and suggests them based on the user's learning difficulties and goals.

[0250] Examples:

[0251] If a user says that they are having difficulty with "calculus," the server will search the database for related learning materials and suggest, "We recommend these textbooks and online courses." A list of candidates will be displayed to the user on the terminal.

[0252] 4. Collecting life events through user interaction

[0253] server:

[0254] Generative AI models are used to collect information about users' life events (e.g. exams and paper submissions) to further customize learning support.

[0255] Examples:

[0256] When a user says, "I'm taking the university entrance exam next year," the generative AI model asks, "Which university and faculty are you aiming for?" to which the user answers, "The Faculty of Engineering at XX University."

[0257] 5. Emotion Analysis Using an Emotion Engine

[0258] server:

[0259] The server uses an emotion engine (e.g. IBM Watson's Tone Analyzer) to analyze the user's emotional state from their input and dialogue, and based on this information, determines whether the user is feeling anxious or stressed.

[0260] Examples:

[0261] When a user types, "I'm very anxious about studying math," the emotion engine recognizes the emotion "anxiety."

[0262] 6. Providing emotional support

[0263] server:

[0264] Based on the analyzed emotional state, the system customizes the suggestions to the user, and for users who feel anxious or stressed, it provides advice on how to relax or increase motivation.

[0265] Examples:

[0266] If the emotion engine recognizes the user as "anxious," the server will suggest, "Try taking some deep breaths to relax," and again provide appropriate learning resources.

[0267] Examples of Prompt Statements

[0268] 1. User Information Collection:

[0269] Please enter your grade and school information.

[0270] "What year are you in? What is the name of the school you go to?"

[0271] 2. Understanding learning difficulties:

[0272] "What are you having difficulty with in your studies?"

[0273] Which specific subjects or units are difficult for you?

[0274] 3. Suggested teaching materials:

[0275] "We'll suggest materials that fit your learning needs. Would you prefer a textbook, notes, or an online course?"

[0276] "I understand that you are looking for materials on calculus. I recommend the following products."

[0277] 4. Emotional state analysis:

[0278] “What emotions have you been feeling as a result of your recent learning?”

[0279] "If you have any anxiety or stress about your studies, please tell us the specifics."

[0280] By following this format, it is possible to realize a system that can provide flexible learning material suggestions based on the user's emotions and life events, and individualized learning support.

[0281] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0282] Step 1:

[0283] Entering and saving user information

[0284] A user starts the application on a terminal and inputs grade and school information. The input information (grade, school name) is sent to the server. The server stores the received information in a database (e.g. MySQL or PostgreSQL). This makes it possible to provide support tailored to the individual learning needs of each user.

[0285] Specific behavior:

[0286] The user enters their grade as "second year high school student" and the name of their school as "XX High School" in the app's input form.

[0287] The input information is sent to the server, which stores it in a database.

[0288] input:

[0289] Grade: "2nd year high school student"

[0290] School name: "XX High School"

[0291] output:

[0292] The grade and school name are stored in a database.

[0293] Step 2:

[0294] Understanding learning difficulties through dialogue with users

[0295] The server uses a generative AI model (e.g., ChatGPT by OpenAI) to initiate a dialogue with the user. Through the dialogue, the server understands the user's learning difficulties and goals. The user's answers are sent to the server, and the understood content is stored.

[0296] Specific behavior:

[0297] User types, "I'm not good at math."

[0298] The server uses a generative AI model to ask, "What part specifically is difficult?"

[0299] A user answered, "Differential and integral calculus is difficult."

[0300] input:

[0301] User answers: "I'm not good at math," "Calculus is difficult"

[0302] output:

[0303] Learning difficulty: "Calculus" is stored in the database.

[0304] Step 3:

[0305] Product suggestions based on learning needs

[0306] The server searches the database for appropriate learning materials based on the user's learning difficulties and goals, and suggests them to the user. The suggested learning materials are sent to the user's terminal and displayed.

[0307] Specific behavior:

[0308] The server searches a database for learning materials (e.g., textbooks, notes, online courses) related to "Calculus."

[0309] The search results are presented to the user.

[0310] input:

[0311] Difficulty in learning: "Calculus"

[0312] output:

[0313] A list of suggested teaching materials is displayed on the user's terminal.

[0314] Step 4:

[0315] Collecting information about life events

[0316] The server uses the generative AI model to collect information about life events (e.g. exams and report submissions) from interactions with the user. The collected information is sent to the server and stored.

[0317] Specific behavior:

[0318] The user says, "I have to take the university entrance exam next year."

[0319] The generative AI model asks, "Which university and department are you aiming for?"

[0320] The user answers, "XX University, Faculty of Engineering."

[0321] input:

[0322] User's life event information: "I have to take the university entrance exam next year", "XX University's Engineering Department"

[0323] output:

[0324] Life event information is stored in a database.

[0325] Step 5:

[0326] Emotion analysis using emotion engine

[0327] The server uses an emotion engine (e.g., IBM Watson's Tone Analyzer) to analyze the user's emotional state from their input and dialogue. The analyzed emotion information is stored on the server.

[0328] Specific behavior:

[0329] A user types, "I'm really anxious about studying math."

[0330] The emotion engine recognizes the emotion of "anxiety."

[0331] input:

[0332] User says: "I'm really anxious about studying math."

[0333] output:

[0334] The recognized emotion: "anxiety" is stored in the database.

[0335] Step 6:

[0336] Providing emotional support

[0337] The server customizes the content of suggestions to the user based on the analyzed emotional state, and learning support and advice appropriate to the emotional state are sent to the user's device and displayed.

[0338] Specific behavior:

[0339] If the server detects that you are "anxious," it will suggest relaxation techniques and learning resources.

[0340] The user is presented with a message such as "Try taking a deep breath to relax" and learning resources.

[0341] input:

[0342] Recognized emotion: "Anxiety"

[0343] output:

[0344] The customized suggestions are displayed on the user's device.

[0345] (Application example 2)

[0346] 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."

[0347] Conventional learning support systems were unable to adequately respond to the individual needs of users and were limited to providing uniform learning materials and support. In addition, the system did not make suggestions that took into account the user's emotional state, which could result in a decrease in learning effectiveness. Furthermore, there was a lack of suggestions that were tailored to important life events such as exams and report submissions. There is a need for a system that can solve these problems and provide a personalized learning experience.

[0348] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means. In this invention, the server includes a means for setting the grade or school information of the user in advance, a means for using a generative AI to have a dialogue with the user and acquiring learning difficulties or goals through the dialogue with the user, a means for collecting information on a life event before an exam or before submitting a report through the dialogue with the user, a prompt sentence for instructing to suggest a product, which is a textbook, a notebook, or an online course, based on the learning difficulties or goals and information on the life event, a means for suggesting the product to the user using the generative AI, a means for analyzing the emotional state of the user using an emotion analysis engine, a prompt sentence for instructing to suggest learning support or a relaxation method based on the emotional state of the user, a means for suggesting the learning support or relaxation method to the user using the generative AI, a means for accepting the selection of the proposed product, a means for purchasing the product selected by the user, and a means for notifying the user of the completion of the purchase. This makes it possible to suggest educational materials tailored to the individual needs of each user and provide support tailored to their emotions.

[0349] "User" refers to an individual who uses the learning support system.

[0350] "Grade" means the stage at which students advance in their school education.

[0351] "School information" refers to information about the educational institution to which the user belongs.

[0352] "Data generation model" refers to an algorithm that uses generative AI technology to interact with users and generate information.

[0353] "Difficulty points in learning" refers to areas or issues that users find difficult to understand in their studies.

[0354] A "goal" refers to a specific learning objective that a user wishes to achieve.

[0355] "Teaching materials" means study materials such as textbooks and notebooks used for study.

[0356] "Online Course" refers to a program of study delivered via the Internet.

[0357] "Products" refers to suggested educational materials and online courses to assist users in their learning.

[0358] "Emotion Analysis Engine" means technology for recognizing and analyzing a user's emotional state.

[0359] "Learning support" refers to specific assistance and help to help users learn.

[0360] "Relaxation methods" refers to suggestions and methods for the user to reduce stress.

[0361] The term "system" refers to a configuration in which multiple means are combined to achieve a series of functions.

[0362] The present invention provides a system for providing appropriate learning materials and support according to a user's learning needs. Specifically, the system includes means including the following elements.

[0363] 1. Hardware and Software Configuration

[0364] Hardware: Mainly smartphones are used. Users use learning support applications on their smartphones.

[0365] software:

[0366] Front-end: Use a front-end framework such as React Native (registered trademark).

[0367] Backend: Uses technologies such as Node.js (registered trademark) and Express (registered trademark).

[0368] Database: Use database technologies such as MongoDB® or MySQL.

[0369] Sentiment analysis engine: Uses sentiment analysis technologies such as Amazon Rekognition(registered trademark).

[0370] Generative AI models: Use generative AI models such as OpenAI's GPT.

[0371] 2. Management of User Information

[0372] The server receives basic information such as grade and school information entered by the user and stores it in a database. This information is the basis for the system to understand the user's learning difficulties and goals and make appropriate suggestions.

[0373] 3. User Dialogue Using Generative AI Models

[0374] The user launches the app and begins a dialogue with the generative AI. The generative AI uses natural language processing technology to gain a detailed understanding of the user's learning difficulties and goals. Based on the information obtained from this dialogue, the server uses the generative AI and a prompt sentence to suggest products such as textbooks, notes, or online courses based on the user's learning difficulties or goals to search the database and suggest learning materials (textbooks, notes, online courses, etc.) suitable for the user.

[0375] 4. Emotional state analysis and customization suggestions

[0376] The emotion analysis engine analyzes the user's emotional state from facial expressions, voice, etc. For example, if the user is feeling stressed or anxious, the server uses a prompt to suggest learning support or relaxation methods appropriate to the user's state, and generative AI to suggest learning support or relaxation methods. In this way, customized support is provided according to the user's emotional state.

[0377] 5. Collecting and suggesting life events according to context

[0378] The server collects information about life events, such as before an exam or before submitting a report, through dialogue with the generative AI. Based on the information obtained from the dialogue, the server uses the generative AI and a prompt to suggest products, such as textbooks, notes, or online courses, based on the learning difficulties or goals and the information about the life events, to search the database and provide timely educational materials and support to the user.

[0379] Examples:

[0380] When a second-year junior high school student uses this system, he or she first inputs their grade and school information. Then, through dialogue with the generative AI, it becomes clear that the student has difficulty with geometry problems in mathematics. It also becomes clear that the student has a mathematics exam next week. Based on this information, the server suggests related online courses and exercise books. Also, if the system detects through the emotion analysis engine that the user is feeling stressed, it suggests light exercise videos as a way to relax.

[0381] Example prompts for suggesting products: "A user in the 8th grade is having difficulty with geometry problems in mathematics. Next week, there will be an exam on geometry problems in mathematics. Please suggest some related learning materials or courses." An example prompt to suggest relaxation techniques: "I've noticed that I've been feeling stressed lately, so please provide me with some relaxation and motivational content."

[0382] In this way, the system of the present invention provides personalized support according to the user's learning needs and emotional state, resulting in a more effective learning experience.

[0383] The flow of the specific process in the application example 2 will be described with reference to FIG.

[0384] Step 1:

[0385] The user launches the smartphone app and enters grade and school information. The entered information is sent to the server and saved in the database. In this step, grade and school information is received as input data, and the process of saving this in the database is carried out. Specifically, the user enters their information into the form and presses the "Submit" button, which sends the data to the server.

[0386] Step 2:

[0387] The server uses the generative AI model to initiate a dialogue with the user. As the user continues the dialogue on the app, the generative AI analyzes the text input to understand the user's learning difficulties and goals. During this process, the user's input data is sent to the generative AI model and analyzed using natural language processing. The user's learning difficulties and goals are obtained as output. Information about life events is also obtained.

[0388] Step 3:

[0389] Based on the analyzed learning difficulties, goals, and information on life events, the server uses a generative AI and a prompt sentence instructing the server to suggest products such as textbooks, notes, or online courses from a database and suggests them to the user. In this step, the learning difficulties and goals are input data, and the suggested learning materials or courses are obtained as output. In specific operations, the server uses the generative AI to execute a database query and displays the results on the user's app screen.

[0390] Step 4:

[0391] The server uses an emotion analysis engine to analyze the user's emotional state. The user's facial expressions and voice data are input and processed by the emotion analysis engine. The output is the emotional state the user is feeling (stress, anxiety, etc.). Specifically, the server uses the smartphone's camera and microphone to collect the user's facial expressions and voice and transmits them to the analysis server.

[0392] Step 5:

[0393] The server uses a generative AI and a prompt sentence that instructs the server to suggest learning support or relaxation methods based on the analyzed emotional state, to suggest learning support or relaxation methods to the user. In this step, the emotional state is used as input data, and the suggested learning support or relaxation methods are obtained as output. In concrete terms, the server searches for and displays appropriate relaxation content or support guides based on the results of the emotion analysis.

[0394] Step 6:

[0395] The server accepts the user's selection of suggested teaching materials and support content, and processes the purchase of the selected product. In this step, the selected product information is input, and the server outputs the purchase process and a notification of purchase completion. In concrete terms, when the user presses the "Purchase" button, the server executes the purchase process and payment process for the selected product, and sends a completion notification to the user.

[0396] In this way, the system of the present invention uses a generative AI model and sentiment analysis engine based on user input data to execute a series of processes that suggest optimal learning materials and support to the user.

[0397] 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 a voice indicating a user input for the result of the specific processing. The control unit 46A transmits the voice 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 voice data.

[0398] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search<url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data according to 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.

[0399] In the above embodiment, an example was given in which the specific process was performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0400] [Second embodiment]

[0401] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0402] 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.

[0403] 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 wide area network (WAN) and / or a local area network (LAN).

[0404] 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.

[0405] 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 the voice according to instructions from the processor 46.

[0406] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a 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 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[0407] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54. The transmission and reception of various types of information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[0408] Fig. 4 shows an example of 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.

[0409] 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.

[0410] 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.

[0411] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50, and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0412] 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 a "server" and the smart glasses 214 will be referred to as a "terminal".

[0413] 1. The server has the function of receiving the user's grade and school information and storing it in a database.

[0414] 2. The server will utilize generative AI to engage in dialogue with users and understand their learning difficulties and goals.

[0415] 3. The server has the function of searching the database and suggesting products such as textbooks, notebooks, and online courses according to the user's learning needs.

[0416] 4. The server will have the ability to use generative AI to collect information about student-specific life events, such as before exams or before submitting reports, through dialogue with users.

[0417] 5. The server has the function of searching the database for timely products that match the user's life events and suggesting them.

[0418] 6. The server has the function of processing the purchase of the product selected by the user and sending a notification of purchase completion to the user.

[0419] This allows the server to understand the user's learning needs and recommend appropriate learning materials and gadgets. It also makes timely product suggestions that match the life events specific to the student. The user selects a suggested product, and the server processes the purchase and sends the user a notification of purchase completion.

[0420] As a specific example, a user starts the app and enters their grade and school information. The server understands the user's learning difficulties and goals through dialogue with the user. When the user mentions their weaknesses in mathematics, the server searches the database for mathematics textbooks, notes, and online courses to suggest them. When the user mentions that they need to make a study plan before an exam, the server suggests past exam guidebooks and study plan creation applications. The user selects a suggested product, and the server processes the purchase and sends the user a notification of purchase completion.

[0421] In this way, a system that effectively provides learning support is realized by carrying out product suggestions tailored to the user's learning needs, information collection on life events, and purchasing processing via the server.

[0422] For example, if a user is having difficulty with math, the generative AI will identify the cause through dialogue with the user and suggest products such as math textbooks and online courses. In addition, when a user experiences student-specific life events such as before an exam or before submitting a paper, the generative AI will collect that information and make timely product recommendations.

[0423] For example, if a user tells the system that they have an upcoming university exam, the generative AI can use past learning data and information about other users' exam preparation to suggest effective exam preparation materials and notes.

[0424] Additionally, when a user indicates that they have not yet submitted a paper, the generative AI can suggest books and online resources related to the topic.

[0425] In this way, the system understands the learning needs and life events of the user through dialogue, and suggests suitable learning materials and gadgets. Users can obtain products that are tailored to their learning needs, enabling them to study more effectively.

[0426] The process flow of each embodiment will be described below.

[0427] Step 1: The user launches the app on the device. For example, the user launches the app and enters grade and school information.

[0428] Step 2: The server receives the user's information and stores it in a database. For example, the server receives the grade and school information entered by the user and stores it in a database.

[0429] Step 3: The server uses generative AI to initiate a dialogue with the user. For example, the server uses generative AI to initiate a dialogue with the user. The server generates questions about the user’s learning needs, difficulties, and goals, and receives the user’s answers.

[0430] Step 4: The server analyzes the user's answers and identifies the elements and trends of learning. For example, the server analyzes the user's answers and identifies the elements and trends of learning. When the user tells the server about their weaknesses in math, the server suggests products such as math textbooks, notebooks, and online courses.

[0431] Step 5: The server continues to dialogue with the user using generative AI to collect information about life events. For example, the server uses generative AI to continue dialogue with the user and collect information about student-specific life events, such as before an exam or before submitting a report. If the user mentions that they need to make a study plan before an exam, the server suggests past exam guides and a study plan creation app.

[0432] Step 6: The server processes the product selected by the user. For example, the server processes the product selected by the user from the products proposed. The server processes the purchase of the product selected by the user and notifies the user that the purchase is completed.

[0433] As described above, after a user starts the app and enters their grade and school information, the server interacts with the user to understand their learning needs and life events, and suggests appropriate products. The user selects a suggested product, and the server processes the purchase and sends the user a notification that the purchase has been completed. This realizes a system that supports the user's learning experience.

[0434] Example 1

[0435] Next, a description will be given of Example 1. In the following description, the data processing device 12 is referred to as a "server" and the smart glasses 214 are referred to as a "terminal".

[0436] Conventional learning support systems lack effective product suggestions tailored to the user's learning needs and life events. In addition, since there is no system that consistently supports the process from product selection to purchase, it is difficult for users to efficiently obtain the learning materials and gadgets they need. Furthermore, detailed understanding of needs through dialogue with users using generative AI models is insufficient.

[0437] 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.

[0438] In this invention, the server includes a means for setting the grade or school information of the user in advance, a means for acquiring learning difficulties or goals through dialogue with the user using a generative AI model, and a means for proposing products such as textbooks, notebooks, or online courses according to the learning difficulties or goals. This makes it possible to propose products with high accuracy according to the learning needs of the user.

[0439] "Grade" is information indicating the academic grade in which the user is currently enrolled.

[0440] "School information" is information about the educational institution that the user attends.

[0441] A "generative AI model" is an artificial intelligence algorithm that generates appropriate responses or suggestions based on human input.

[0442] "Difficult points in learning" refers to areas or issues that the user finds particularly difficult in learning.

[0443] "Goal" refers to the specific purpose or outcome that a user wants to achieve through learning.

[0444] "Instructional Materials" are learning resources such as books, notes, online courses, etc. that are used to assist the user in their learning.

[0445] "Gadgets" refers to electronic devices and tools that aid in learning.

[0446] "Products" refers collectively to all learning materials and gadgets proposed to aid learning.

[0447] A "life event" refers to an important event that a user experiences at a particular time, such as before an exam or before submitting a report.

[0448] The "purchase process" refers to a series of procedures including payments and other procedures required to purchase the product selected by the user.

[0449] A "notification" is information or a message sent from the server to the user.

[0450] To implement the present invention, information is exchanged between the server, the terminal, and the user. The necessary hardware and software, as well as specific operation examples, are described below.

[0451] Hardware used

[0452] Server (a server equipped with a high-performance CPU and large-capacity memory)

[0453] Database server (e.g. MySQL, PostgreSQL)

[0454] User's device (smartphone, PC, etc.)

[0455] Software used

[0456] Generative AI models (e.g. OpenAI ChatGPT)

[0457] Database management systems (e.g. MySQL, PostgreSQL)

[0458] Web application frameworks (e.g. Django, Flask)

[0459] Network communication protocol (e.g. HTTP / HTTPS)

[0460] Working Example

[0461] 1. User input operations

[0462] The user starts up a dedicated application on their smartphone or computer, enters their grade and school information into the form displayed on the application screen, and clicks the "Submit" button.

[0463] 2. Receiving and storing data on the server side

[0464] The server receives the grade and school information entered by the user as an HTTP request and saves it as a new entry in the database.

[0465] 3. Dialogue using generative AI

[0466] The server starts the generative AI model and starts a dialogue with the user. For example, it asks, "Hello. What are you having trouble with in the learning you are currently doing?" It analyzes the user's response and understands the learning difficulties and goals.

[0467] 4. Product proposal

[0468] Based on the acquired learning difficulties and goals, the server searches a database for appropriate learning materials and gadgets (e.g., mathematics textbooks and online courses) and suggests them to the user.

[0469] 5. Ongoing dialogue and information gathering

[0470] The server uses a generative AI to ask the user, "Is there anything else you're having trouble with studying or schoolwork?" and, if it gets a response like, "I have an important math exam next week," it records this information.

[0471] 6. Product re-proposal based on life events

[0472] Based on the collected life events, the server re-searches the database for related products (e.g., exam preparation notes and manuals) and suggests them to the user.

[0473] 7. Purchase Processing and Notifications

[0474] When the user selects a product, the server receives the purchase request, communicates with the payment system, and executes the purchase process. When the purchase is complete, the server sends a "purchase completed" notification to the user.

[0475] Examples of prompt statements

[0476] "I'm in the third year of middle school and I'm not good at math. I have exams coming up. Can you tell me some effective study methods and useful study materials?"

[0477] Using these prompts, the generative AI model can understand the user's specific learning needs and difficulties and suggest suitable learning materials and online courses from its database, allowing users to receive effective learning support tailored to their grade level and learning goals.

[0478] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0479] Step 1:

[0480] The user enters grade and school information from the terminal. The user starts the application, enters their grade and school information in the form on the screen, and clicks the "Submit" button. The input data is the user's grade and school information. This is sent to the server.

[0481] Step 2:

[0482] The server receives the input information and saves it in the database. The server parses the user's grade and school information received as an HTTP request and saves it as a new record in the database (e.g. MySQL, PostgreSQL). During this process, a database insert operation is performed and a confirmation message is generated if successful.

[0483] Step 3:

[0484] The server uses a generative AI model to start a dialogue with the user and understands the learning difficulties and goals. The server starts a generative AI model (e.g., ChatGPT by OpenAI) and asks the user, "Hello. What are you having particular difficulty with in the learning you are currently working on?" The server analyzes the text data received as the user's response and extracts the learning difficulties and goals.

[0485] Step 4:

[0486] The server searches the database for products that meet the user's learning needs and suggests them. The server searches the database for related textbooks, notes, or online courses based on the extracted learning difficulties and goals. The server sends the product list obtained as the search result to the user in the form of a suggestion message.

[0487] Step 5:

[0488] The server continues to use the generative AI model to continue the dialogue with the user, collecting information about life events such as before an exam or before submitting a report. The server asks, "Is there anything else you're having trouble with regarding your studies or schoolwork?" If the user responds, "I have an important math exam next week," the server analyzes the text data and records it as life event information.

[0489] Step 6:

[0490] The server re-searches the database for products that match the user's life event and suggests them. The server again searches the database for related products (e.g., exam preparation notes and manuals) based on the collected life event information. The search results are sent to the user in the form of a suggestion message.

[0491] Step 7:

[0492] The user selects a product. The user checks the list of products suggested by the server and selects the product he or she wants to purchase by clicking the "Purchase" button. The selection information is sent to the server.

[0493] Step 8:

[0494] The server processes the purchase of the selected item and sends a notification of purchase completion to the user. The server receives the purchase request, communicates with the payment system to perform the appropriate payment processing, and if the payment is successful, generates a notification message of purchase completion and sends it to the user.

[0495] (Application example 1)

[0496] 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".

[0497] Conventional learning support systems have difficulty in timely proposing appropriate learning materials and products that match the individual learning needs and life events of learners. In addition, it has been difficult to grasp specific difficulties and goals through dialogue with learners and provide optimal resources accordingly. This has made it difficult to maximize the learning effect of learners.

[0498] 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.

[0499] In this invention, the server includes a means for setting the user's grade or school information in advance, a means for acquiring learning difficulties or goals through dialogue with the user using a generative AI model, a means for proposing products such as textbooks, notes, or online courses according to the learning difficulties or goals, a means for collecting the user's life events (e.g., before an exam, before submitting a report) and proposing timely products, a means for processing the purchase of the product selected by the user and notifying the user of the completion of the purchase, and a means for generating prompt sentences for dialogue using a generative AI model. This makes it possible to propose and purchase appropriate resources according to the user's learning needs and life events.

[0500] The "means for setting the user's grade or school information in advance" refers to a method for inputting and registering information about the grade or school the user belongs to in advance into the system.

[0501] A "generative AI model" is an artificial intelligence model that uses machine learning algorithms to interact with users and generate data.

[0502] The "means for acquiring learning difficulties or goals" refers to a method for identifying, through dialogue with users, which learning content they are having difficulty with or which learning goals they want to achieve.

[0503] A "means for suggesting products that are textbooks, notes, or online courses" is a method for selecting and recommending suitable learning materials or online educational resources to a user based on learning difficulties and goals.

[0504] The "means for collecting user's life events" is a method by which a user collects information about a specific event, such as before an exam or before submitting a report.

[0505] The "means for proposing timely products" is a method for proposing the most useful product to the user at that time based on collected life event information.

[0506] The "means for carrying out the purchasing process for the product selected by the user and notifying the user of the completion of the purchase" refers to a method for carrying out the purchasing process for the product selected by the user and notifying the user of the completion of the purchase.

[0507] A "means for generating prompts for dialogue using a generative AI model" is a method for automatically generating questions or instructions for effective dialogue with a user using a generative AI model.

[0508] This invention is an embodiment of a system that suggests learning materials and gadgets that match the user's learning needs and life events, and supports the purchase procedure. The system includes the following components.

[0509] Hardware Configuration

[0510] server:

[0511] Amazon Web Services (AWS), Google Cloud, or Azure

[0512] User device:

[0513] Smartphone (iOS or Android)

[0514] Software configuration and processing

[0515] The server has the following software and functions:

[0516] Database:

[0517] Relational databases such as MySQL and PostgreSQL

[0518] Stores user information, product information, and life event information

[0519] Generative AI models:

[0520] Advanced conversational AI models such as OpenAI ChatGPT

[0521] Through dialogue with the user, the system understands the learning difficulties and goals and generates prompts

[0522] Purchase Processing System:

[0523] Integrate payment processors like Stripe and PayPal

[0524] Implementation Procedure

[0525] 1. User Registration:

[0526] A user launches the app and enters grade or school information, which is then stored in a database on the server.

[0527] 2. Interactive learning support:

[0528] When a user inquires about a particular learning difficulty or goal, the generative AI model on the server collects detailed information through dialogue. For example, if a user asks, "I don't understand mathematical functions," the generative AI model generates a prompt such as, "What learning materials can help me understand?"

[0529] 3. Study material suggestions:

[0530] Based on the collected information, the server searches its database for appropriate learning materials (textbooks, notes, online courses, etc.) and suggests them to the user.

[0531] 4. Life Event Support:

[0532] When a user provides information about a life event, such as before an exam or before submitting a report, the generative AI model suggests timely products that match that event.

[0533] 5. Product Purchase:

[0534] The user selects the suggested product and completes the purchase procedure. The server processes the purchase and issues a purchase completion notification.

[0535] Examples

[0536] For example, if a user is having difficulty learning about mathematical functions, the difficulty is identified through the dialogue function of the smartphone app. The generative AI model generates a prompt, "What kind of study materials do you need about mathematical functions?" and suggests appropriate study materials from a past database. When the user selects, "I want exam preparation notes," the purchase procedure is completed through the payment system, and a notification that "purchase has been completed" is sent to the user.

[0537] Examples of prompt statements

[0538] If a user asks, "I don't understand a mathematical function":

[0539] "What teaching materials can help me understand math functions?"

[0540] Example of the answer generated:

[0541] "There are books and online courses that explain mathematical functions. I can suggest these products. Would you be interested?"

[0542] In this way, a system is constructed that can efficiently suggest and purchase appropriate resources according to the user's learning needs and life events.

[0543] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0544] Step 1:

[0545] User Registration:

[0546] A user starts the smartphone app and registers their grade and school information. The input is provided by the user, and the server receives this input and stores it in a database. This organizes the user's basic information and uses it for subsequent customized suggestions.

[0547] Input: Grade, School Information

[0548] Output: User information stored in the database

[0549] Step 2:

[0550] Interacting with generative AI models:

[0551] The user asks questions about their learning difficulties and goals through the app. The conversational bot using the generative AI model analyzes the user's input, generates appropriate prompts, and continues the conversation. For example, if the user types, "Mathematical functions are difficult," the generative AI model responds, "Which part specifically is difficult?"

[0552] Input: User question

[0553] Output: Response prompts from a generative AI model

[0554] Step 3:

[0555] Identifying learning challenges and goals:

[0556] Through dialogue with the generative AI model, the server identifies the user's learning difficulties and goals. If the user specifically answers, for example, "I don't understand how to draw a graph of a function," that information is sent to the server and stored.

[0557] Input: User interaction

[0558] Output: Identified learning difficulties and goals

[0559] Step 4:

[0560] Suggested teaching materials:

[0561] Based on the identified learning difficulties and goals, the server searches the database for appropriate learning materials (textbooks, notes, online courses, etc.) and suggests them to the user. For example, learning materials for "how to draw a graph of a function" are suggested.

[0562] Input: Learning difficulties and goals

[0563] Output: A list of suggested materials

[0564] Step 5:

[0565] Collecting life event information:

[0566] When a user provides information about a life event, such as before an exam or before submitting a report, the server collects that information and the generative AI model suggests timely products to meet the user's needs. For example, when a user says, "I have a math exam next week," a notebook for exam preparation is suggested.

[0567] Input: Life event information

[0568] Output: Product suggestions based on life events

[0569] Step 6:

[0570] Checkout:

[0571] The user selects the suggested learning materials and completes the purchase procedure. The server processes the payment and sends the user a notification that the purchase is complete. Payment is processed using a payment service such as Stripe or PayPal.

[0572] Input: User's purchase selection

[0573] Output: Purchase completion notification

[0574] Step 7:

[0575] Post-purchase notice:

[0576] After the purchase procedure is completed, the server sends a notification of purchase completion to the user, so that the user can confirm that the purchase process was completed successfully.

[0577] Input: Purchase completion data

[0578] Output: Notification to user that purchase is complete

[0579] The above are the specific process steps for carrying out the invention.

[0580] Furthermore, an emotion engine that estimates the emotion of the user may be combined. That is, the identification processing unit 290 may estimate the emotion of the user using the emotion identification model 59, and perform identification processing using the emotion of the user.

[0581] In this case, the system includes the following elements:

[0582] 1. The server has the function of receiving the user's grade and school information and storing it in a database.

[0583] 2. The server will utilize generative AI to engage in dialogue with users and understand their learning difficulties and goals.

[0584] 3. The server has the function of searching the database and suggesting products such as textbooks, notebooks, and online courses according to the user's learning needs.

[0585] 4. The server will have the ability to utilize generative AI to continue dialogue with the user and collect information about life events.

[0586] 5. The server is equipped with an emotion engine that recognizes the user's emotions and has the ability to analyze the user's emotional state.

[0587] 6. The server will have the ability to customize learning support and product suggestions according to the user's emotional state.

[0588] This allows the server to understand the user's learning needs and recommend appropriate learning materials and gadgets. It can also recognize the user's emotional state and customize learning support and product suggestions to match the user's emotions.

[0589] As a concrete example, a user starts the app and inputs their grade and school information. The server understands the user's learning difficulties and goals through dialogue with the user. When the user tells the server what they are weak at in math, the server searches the database for math textbooks, notes, and online courses and suggests them. At the same time, the server uses an emotion engine to analyze the user's emotional state, and if it determines that the user is feeling anxious or stressed, it suggests appropriate study support and relaxation methods.

[0590] In this way, product suggestions tailored to the user's learning needs and emotional support are provided via the server, providing a more personalized learning experience.

[0591] The process flow will be explained below.

[0592] Step 1: The user launches the app on the device. For example, the user launches the app and enters grade and school information.

[0593] Step 2: The server receives the user's information and stores it in a database. For example, the server receives the grade and school information entered by the user and stores it in a database.

[0594] Step 3: The server uses generative AI to initiate a dialogue with the user. For example, the server uses generative AI to initiate a dialogue with the user. The server generates questions about the user’s learning needs, difficulties, and goals, and receives the user’s answers.

[0595] Step 4: The server analyzes the user's answers and identifies the elements and trends of learning. For example, the server analyzes the user's answers and identifies the elements and trends of learning. When the user tells the server about their weaknesses in math, the server suggests products such as math textbooks, notebooks, and online courses.

[0596] Step 5: The server continues to dialogue with the user using generative AI to collect information about life events. For example, the server uses generative AI to continue dialogue with the user and collect information about student-specific life events, such as before an exam or before submitting a paper. If the user mentions that they need to make a study plan before an exam, the server suggests past exam guides and a study plan creation application.

[0597] Step 6: The server combines an emotion engine that recognizes the user's emotions and analyzes the user's emotional state. For example, the server uses the emotion engine to analyze information such as the user's speech and facial expressions to recognize the user's emotional state. If the server determines that the user is feeling anxious or stressed, it will provide appropriate study support or suggest ways to relax.

[0598] Step 7: The server customizes learning support and product suggestions based on the user's emotional state. For example, the server customizes learning support and product suggestions based on the user's emotional state. If the server determines that the user needs relaxation, it suggests relaxing music or a meditation application.

[0599] That's it. After the user starts the app and enters their grade and school information, the server will understand information about the user's learning needs and life events through dialogue with the user and suggest appropriate products. At the same time, the server will use an emotion engine to analyze the user's emotional state and provide support and suggestions tailored to the user's emotions. This makes it possible to more individually customize the user's learning experience and provide support based on emotions.

[0600] Example 2

[0601] Next, a description will be given of Example 2. In the following description, the data processing device 12 is referred to as a "server" and the smart glasses 214 are referred to as a "terminal".

[0602] Conventional learning support systems can provide learning materials and learning resources according to the user's learning needs, but it is difficult to provide personalized support that takes into account the user's emotional state. In addition, there is a lack of flexible learning material suggestions that respond to the user's life events and changes in daily life. This makes it difficult to provide an optimal learning experience for each individual user.

[0603] 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.

[0604] In this invention, the server includes a means for setting the grade or school information of the user in advance, a means for acquiring learning difficulties or goals through dialogue with the user using a generative AI model, a means for proposing products, which are teaching materials or online courses, according to the learning difficulties or goals, a means for combining an emotion engine for analyzing the emotional state of the user, and a means for customizing the suggesting means according to the emotional state of the user. This enables flexible teaching material suggestions that take into account the user's emotions and life events, and personalized learning support.

[0605] "User" refers to an individual who receives learning support using this system.

[0606] The "grade" is information indicating the educational stage of the educational institution in which the user is currently enrolled.

[0607] "School information" is information that includes details such as the name and location of the educational institution that the user attends.

[0608] A "generative AI model" is a type of artificial intelligence (AI) that uses natural language processing to interact with users and generate answers to their input and questions.

[0609] "Difficulties in learning" refers to subjects or content that the user finds particularly difficult to understand in learning.

[0610] "Goal" is information indicating the purpose or goal of learning that the user wishes to achieve.

[0611] "Instructional Materials" refers to educational materials such as textbooks, notes, online courses, etc. that a User uses to study.

[0612] "Means of suggestion" refers to a mechanism by which the server presents appropriate learning materials and products according to the user's learning needs.

[0613] An "emotion engine" refers to an algorithm or software that analyzes a user's language expressions and dialogue content to determine their emotional state (e.g., anxiety, stress, joy, etc.).

[0614] "Emotional state" refers to the psychological state that a user is feeling at a given moment, and includes factors such as motivation for learning, anxiety, and stress.

[0615] "Life events" refer to major events that occur in the user's daily life (e.g. exams, submitting reports, entering higher education, etc.).

[0616] The "means for carrying out purchase processing" refers to a mechanism for carrying out the procedure for purchasing the product selected by the user online or offline.

[0617] "Means for notifying the user of the completion of purchase" refers to a mechanism for executing a procedure to notify the user that the purchase of the product selected by the user has been completed.

[0618] This invention is a system that suggests learning materials and gadgets according to the user's learning needs and further personalizes support based on the user's emotional state. This system is composed of three main elements: a server, a terminal, and a user.

[0619] 1. Enter and save user information

[0620] server:

[0621] When a user launches an application on a terminal and enters grade and school information, that information is sent to the server. The server stores the user information received from the application in a database (e.g., MySQL or PostgreSQL). This stored information is used to provide a personalized learning experience for each user.

[0622] Examples:

[0623] The user enters "second year high school student" and "XX High School" into the application's input form. This information is sent to the server and saved in the database.

[0624] 2. Understanding learning difficulties through dialogue with users

[0625] server:

[0626] The server uses a generative AI model (e.g., ChatGPT by OpenAI) to converse with the user. Through the dialogue, the server understands the user's learning difficulties and goals, and uses that information to prepare to suggest appropriate learning materials.

[0627] Examples:

[0628] The user enters, "I'm not good at math," and the generative AI model asks, "Which part is difficult for you?" The user answers, "Calculus is difficult."

[0629] 3. Product suggestions based on learning needs

[0630] server:

[0631] The server searches a database for appropriate learning materials (e.g., mathematics textbooks, notes, online courses) and suggests them based on the user's learning difficulties and goals.

[0632] Examples:

[0633] If a user says that they are having difficulty with "calculus," the server will search the database for related learning materials and suggest, "We recommend these textbooks and online courses." A list of candidates will be displayed to the user on the terminal.

[0634] 4. Collecting life events through user interaction

[0635] server:

[0636] Generative AI models are used to collect information about users' life events (e.g. exams and paper submissions) to further customize learning support.

[0637] Examples:

[0638] When a user says, "I'm taking the university entrance exam next year," the generative AI model asks, "Which university and faculty are you aiming for?" to which the user answers, "The Faculty of Engineering at XX University."

[0639] 5. Emotion Analysis Using an Emotion Engine

[0640] server:

[0641] The server uses an emotion engine (e.g. IBM Watson's Tone Analyzer) to analyze the user's emotional state from their input and dialogue, and based on this information, determines whether the user is feeling anxious or stressed.

[0642] Examples:

[0643] When a user types, "I'm very anxious about studying math," the emotion engine recognizes the emotion "anxiety."

[0644] 6. Providing emotional support

[0645] server:

[0646] Based on the analyzed emotional state, the system customizes the suggestions to the user, and for users who feel anxious or stressed, it provides advice on how to relax or increase motivation.

[0647] Examples:

[0648] If the emotion engine recognizes the user as "anxious," the server will suggest, "Try taking some deep breaths to relax," and again provide appropriate learning resources.

[0649] Examples of Prompt Statements

[0650] 1. User Information Collection:

[0651] Please enter your grade and school information.

[0652] "What year are you in? What is the name of the school you go to?"

[0653] 2. Understanding learning difficulties:

[0654] "What are you having difficulty with in your studies?"

[0655] Which specific subjects or units are difficult for you?

[0656] 3. Suggested teaching materials:

[0657] "We'll suggest materials that fit your learning needs. Would you prefer a textbook, notes, or an online course?"

[0658] "I understand that you are looking for materials on calculus. I recommend the following products."

[0659] 4. Emotional state analysis:

[0660] “What emotions have you been feeling as a result of your recent learning?”

[0661] "If you have any anxiety or stress about your studies, please tell us the specifics."

[0662] By following this format, it is possible to realize a system that can provide flexible learning material suggestions based on the user's emotions and life events, and individualized learning support.

[0663] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0664] Step 1:

[0665] Entering and saving user information

[0666] A user starts the application on a terminal and inputs grade and school information. The input information (grade, school name) is sent to the server. The server stores the received information in a database (e.g. MySQL or PostgreSQL). This makes it possible to provide support tailored to the individual learning needs of each user.

[0667] Specific behavior:

[0668] The user enters their grade as "second year high school student" and the name of their school as "XX High School" in the app's input form.

[0669] The input information is sent to the server, which stores it in a database.

[0670] input:

[0671] Grade: "2nd year high school student"

[0672] School name: "XX High School"

[0673] output:

[0674] The grade and school name are stored in a database.

[0675] Step 2:

[0676] Understanding learning difficulties through dialogue with users

[0677] The server uses a generative AI model (e.g., ChatGPT by OpenAI) to initiate a dialogue with the user. Through the dialogue, the server understands the user's learning difficulties and goals. The user's answers are sent to the server, and the understood content is stored.

[0678] Specific behavior:

[0679] User types, "I'm not good at math."

[0680] The server uses a generative AI model to ask, "What part specifically is difficult?"

[0681] A user answered, "Differential and integral calculus is difficult."

[0682] input:

[0683] User answers: "I'm not good at math," "Calculus is difficult"

[0684] output:

[0685] Learning difficulty: "Calculus" is stored in the database.

[0686] Step 3:

[0687] Product suggestions based on learning needs

[0688] The server searches the database for appropriate learning materials based on the user's learning difficulties and goals, and suggests them to the user. The suggested learning materials are sent to the user's terminal and displayed.

[0689] Specific behavior:

[0690] The server searches a database for learning materials (e.g., textbooks, notes, online courses) related to "Calculus."

[0691] The search results are presented to the user.

[0692] input:

[0693] Difficulty in learning: "Calculus"

[0694] output:

[0695] A list of suggested teaching materials is displayed on the user's terminal.

[0696] Step 4:

[0697] Collecting information about life events

[0698] The server uses the generative AI model to collect information about life events (e.g. exams and report submissions) from interactions with the user. The collected information is sent to the server and stored.

[0699] Specific behavior:

[0700] The user says, "I have to take the university entrance exam next year."

[0701] The generative AI model asks, "Which university and department are you aiming for?"

[0702] The user answers, "XX University, Faculty of Engineering."

[0703] input:

[0704] User's life event information: "I have to take the university entrance exam next year", "XX University's Engineering Department"

[0705] output:

[0706] Life event information is stored in a database.

[0707] Step 5:

[0708] Emotion analysis using emotion engine

[0709] The server uses an emotion engine (e.g., IBM Watson's Tone Analyzer) to analyze the user's emotional state from their input and dialogue. The analyzed emotion information is stored on the server.

[0710] Specific behavior:

[0711] A user types, "I'm really anxious about studying math."

[0712] The emotion engine recognizes the emotion of "anxiety."

[0713] input:

[0714] User says: "I'm really anxious about studying math."

[0715] output:

[0716] The recognized emotion: "anxiety" is stored in the database.

[0717] Step 6:

[0718] Providing emotional support

[0719] The server customizes the content of suggestions to the user based on the analyzed emotional state, and learning support and advice appropriate to the emotional state are sent to and displayed on the user's device.

[0720] Specific behavior:

[0721] If the server detects that you are "anxious," it will suggest relaxation techniques and learning resources.

[0722] The user is presented with a message such as "Try taking a deep breath to relax" and learning resources.

[0723] input:

[0724] Recognized emotion: "Anxiety"

[0725] output:

[0726] The customized suggestions are displayed on the user's device.

[0727] (Application example 2)

[0728] 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".

[0729] Conventional learning support systems were unable to adequately respond to the individual needs of users and were limited to providing uniform learning materials and support. In addition, the system did not make suggestions that took into account the user's emotional state, which could result in a decrease in learning effectiveness. Furthermore, there was a lack of suggestions that were tailored to important life events such as exams and report submissions. There is a need for a system that can solve these problems and provide a personalized learning experience.

[0730] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means. In this invention, the server includes a means for setting the grade or school information of the user in advance, a means for using a generative AI to have a dialogue with the user and acquiring learning difficulties or goals through the dialogue with the user, a means for collecting information on a life event before an exam or before submitting a report through the dialogue with the user, a prompt sentence for instructing to suggest a product, which is a textbook, a notebook, or an online course, based on the learning difficulties or goals and information on the life event, a means for suggesting the product to the user using the generative AI, a means for analyzing the emotional state of the user using an emotion analysis engine, a prompt sentence for instructing to suggest learning support or a relaxation method based on the emotional state of the user, a means for suggesting the learning support or relaxation method to the user using the generative AI, a means for accepting the selection of the proposed product, a means for purchasing the product selected by the user, and a means for notifying the user of the completion of the purchase. This makes it possible to suggest educational materials tailored to the individual needs of each user and provide support tailored to their emotions.

[0731] "User" refers to an individual who uses the learning support system.

[0732] "Grade" means the stage at which students advance in their school education.

[0733] "School information" refers to information about the educational institution to which the user belongs.

[0734] "Data generation model" refers to an algorithm that uses generative AI technology to interact with users and generate information.

[0735] "Difficulty points in learning" refers to areas or issues that users find difficult to understand in their studies.

[0736] A "goal" refers to a specific learning objective that a user wishes to achieve.

[0737] "Teaching materials" means study materials such as textbooks and notebooks used for study.

[0738] "Online Course" refers to a program of study delivered via the Internet.

[0739] "Products" refers to suggested educational materials and online courses to assist users in their learning.

[0740] "Emotion Analysis Engine" means technology for recognizing and analyzing a user's emotional state.

[0741] "Learning support" refers to specific assistance and help to help users learn.

[0742] "Relaxation methods" refers to suggestions and methods for the user to reduce stress.

[0743] The term "system" refers to a configuration in which multiple means are combined to achieve a series of functions.

[0744] The present invention provides a system for providing appropriate learning materials and support according to a user's learning needs. Specifically, the system includes means including the following elements.

[0745] 1. Hardware and Software Configuration

[0746] Hardware: Mainly smartphones are used. Users use learning support applications on their smartphones.

[0747] software:

[0748] Front-end: Use a front-end framework such as React Native.

[0749] Backend: Uses technologies such as Node.js or Express.

[0750] Database: Use a database technology such as MongoDB or MySQL.

[0751] Sentiment analysis engine: Use sentiment analysis technologies such as Amazon Rekognition.

[0752] Generative AI models: Use generative AI models such as OpenAI's GPT.

[0753] 2. Management of User Information

[0754] The server receives basic information such as grade and school information entered by the user and stores it in a database. This information is the basis for the system to understand the user's learning difficulties and goals and make appropriate suggestions.

[0755] 3. User Dialogue Using Generative AI Models

[0756] The user launches the app and begins a dialogue with the generative AI. The generative AI uses natural language processing technology to gain a detailed understanding of the user's learning difficulties and goals. Based on the information obtained from this dialogue, the server uses the generative AI and a prompt sentence to suggest products such as textbooks, notes, or online courses based on the user's learning difficulties or goals to search the database and suggest learning materials (textbooks, notes, online courses, etc.) suitable for the user.

[0757] 4. Emotional state analysis and customization suggestions

[0758] The emotion analysis engine analyzes the user's emotional state from facial expressions, voice, etc. For example, if the user is feeling stressed or anxious, the server uses a prompt to suggest learning support or relaxation methods appropriate to the user's state, and generative AI to suggest learning support or relaxation methods. In this way, customized support is provided according to the user's emotional state.

[0759] 5. Collecting and suggesting life events according to context

[0760] The server collects information about life events, such as before an exam or before submitting a report, through dialogue with the generative AI. Based on the information obtained from the dialogue, the server uses the generative AI and a prompt to suggest products, such as textbooks, notes, or online courses, based on the learning difficulties or goals and the information about the life events, to search the database and provide timely educational materials and support to the user.

[0761] Examples:

[0762] When a second-year junior high school student uses this system, he or she first inputs their grade and school information. Then, through dialogue with the generative AI, it becomes clear that the student has difficulty with geometry problems in mathematics. It also becomes clear that the student has a mathematics exam next week. Based on this information, the server suggests related online courses and exercise books. Also, if the system detects through the emotion analysis engine that the user is feeling stressed, it suggests light exercise videos as a way to relax.

[0763] Example prompts for suggesting products: "A user in the 8th grade is having difficulty with geometry problems in mathematics. Next week, there will be an exam on geometry problems in mathematics. Please suggest some related learning materials or courses." An example prompt to suggest relaxation techniques: "I've noticed that I've been feeling stressed lately, so please provide me with some relaxation and motivational content."

[0764] In this way, the system of the present invention provides personalized support according to the user's learning needs and emotional state, resulting in a more effective learning experience.

[0765] The flow of the specific process in the application example 2 will be described with reference to FIG.

[0766] Step 1:

[0767] The user launches the smartphone app and enters grade and school information. The entered information is sent to the server and saved in the database. In this step, grade and school information is received as input data, and the process of saving this in the database is carried out. Specifically, the user enters their information into the form and presses the "Submit" button, which sends the data to the server.

[0768] Step 2:

[0769] The server uses the generative AI model to initiate a dialogue with the user. As the user continues the dialogue on the app, the generative AI analyzes the text input to understand the user's learning difficulties and goals. During this process, the user's input data is sent to the generative AI model and analyzed using natural language processing. The user's learning difficulties and goals are obtained as output. Information about life events is also obtained.

[0770] Step 3:

[0771] Based on the analyzed learning difficulties, goals, and information on life events, the server uses a generative AI and a prompt sentence instructing the server to suggest products such as textbooks, notes, or online courses from a database and suggests them to the user. In this step, the learning difficulties and goals are input data, and the suggested learning materials or courses are obtained as output. In specific operations, the server uses the generative AI to execute a database query and displays the results on the user's app screen.

[0772] Step 4:

[0773] The server uses an emotion analysis engine to analyze the user's emotional state. The user's facial expressions and voice data are input and processed by the emotion analysis engine. The output is the emotional state the user is feeling (stress, anxiety, etc.). Specifically, the server uses the smartphone's camera and microphone to collect the user's facial expressions and voice and transmits them to the analysis server.

[0774] Step 5:

[0775] The server uses a generative AI and a prompt sentence that instructs the server to suggest learning support or relaxation methods based on the analyzed emotional state, to suggest learning support or relaxation methods to the user. In this step, the emotional state is used as input data, and the suggested learning support or relaxation methods are obtained as output. In concrete terms, the server searches for and displays appropriate relaxation content or support guides based on the results of the emotion analysis.

[0776] Step 6:

[0777] The server accepts the user's selection of suggested teaching materials and support content, and processes the purchase of the selected product. In this step, the selected product information is input, and the server outputs the purchase process and a notification of purchase completion. In concrete terms, when the user presses the "Purchase" button, the server executes the purchase process and payment process for the selected product, and sends a completion notification to the user.

[0778] In this way, the system of the present invention uses a generative AI model and sentiment analysis engine based on user input data to execute a series of processes that suggest optimal learning materials and support to the user.

[0779] 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 a voice indicating a user input for the result of the specific processing. The control unit 46A transmits the 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.

[0780] 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 making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data according to 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.

[0781] 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 smart glasses 214.

[0782] [Third embodiment]

[0783] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0784] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0785] 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 wide area network (WAN) and / or a local area network (LAN).

[0786] 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.

[0787] 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 the voice according to instructions from the processor 46.

[0788] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a 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 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[0789] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54. The transmission and reception of various types of information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[0790] Fig. 6 shows an example of 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.

[0791] 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.

[0792] 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.

[0793] In the headset type terminal 314, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50, and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0794] 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".

[0795] 1. The server has the function of receiving the user's grade and school information and storing it in a database.

[0796] 2. The server will utilize generative AI to engage in dialogue with users and understand their learning difficulties and goals.

[0797] 3. The server has the function of searching the database and suggesting products such as textbooks, notebooks, and online courses according to the user's learning needs.

[0798] 4. The server will have the ability to use generative AI to collect information about student-specific life events, such as before exams or before submitting reports, through dialogue with users.

[0799] 5. The server has the function of searching the database for timely products that match the user's life events and suggesting them.

[0800] 6. The server has the function of processing the purchase of the product selected by the user and sending a notification of purchase completion to the user.

[0801] This allows the server to understand the user's learning needs and recommend appropriate learning materials and gadgets. It also makes timely product suggestions that match the life events specific to the student. The user selects a suggested product, and the server processes the purchase and sends the user a notification of purchase completion.

[0802] As a specific example, a user starts the app and enters their grade and school information. The server understands the user's learning difficulties and goals through dialogue with the user. When the user mentions their weaknesses in mathematics, the server searches the database for mathematics textbooks, notes, and online courses to suggest them. When the user mentions that they need to make a study plan before an exam, the server suggests past exam guidebooks and study plan creation applications. The user selects a suggested product, and the server processes the purchase and sends the user a notification of purchase completion.

[0803] In this way, a system that effectively provides learning support is realized by carrying out product suggestions tailored to the user's learning needs, information collection on life events, and purchasing processing via the server.

[0804] For example, if a user is having difficulty with math, the generative AI will identify the cause through dialogue with the user and suggest products such as math textbooks and online courses. In addition, when a user experiences student-specific life events such as before an exam or before submitting a paper, the generative AI will collect that information and make timely product recommendations.

[0805] For example, if a user tells the AI ​​that they have a university exam coming up, the AI ​​can use their past learning data and other users' exam preparation information to suggest effective study materials and notes for the exam. Also, if a user tells the AI ​​that they have a paper to submit, the AI ​​can suggest books and online resources related to that topic.

[0806] In this way, the system understands the learning needs and life events of the user through dialogue, and suggests suitable learning materials and gadgets. Users can obtain products that are tailored to their learning needs, enabling them to study more effectively.

[0807] The process flow of each embodiment will be described below.

[0808] Step 1: The user launches the app on the device. For example, the user launches the app and enters grade and school information.

[0809] Step 2: The server receives the user's information and stores it in a database. For example, the server receives the grade and school information entered by the user and stores it in a database.

[0810] Step 3: The server uses generative AI to initiate a dialogue with the user. For example, the server uses generative AI to initiate a dialogue with the user. The server generates questions about the user’s learning needs, difficulties, and goals, and receives the user’s answers.

[0811] Step 4: The server analyzes the user's answers and identifies the elements and trends of learning. For example, the server analyzes the user's answers and identifies the elements and trends of learning. When the user tells the server about their weaknesses in math, the server suggests products such as math textbooks, notebooks, and online courses.

[0812] Step 5: The server continues to dialogue with the user using generative AI to collect information about life events. For example, the server uses generative AI to continue dialogue with the user and collect information about student-specific life events, such as before an exam or before submitting a report. If the user mentions that they need to make a study plan before an exam, the server suggests past exam guides and a study plan creation app.

[0813] Step 6: The server processes the product selected by the user. For example, the server processes the product selected by the user from the products proposed. The server processes the purchase of the product selected by the user and notifies the user that the purchase is completed.

[0814] As described above, after a user starts the app and enters their grade and school information, the server interacts with the user to understand their learning needs and life events, and suggests appropriate products. The user selects a suggested product, and the server processes the purchase and sends the user a notification that the purchase has been completed. This realizes a system that supports the user's learning experience.

[0815] Example 1

[0816] 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".

[0817] Conventional learning support systems lack effective product suggestions tailored to the user's learning needs and life events. In addition, since there is no system that consistently supports the process from product selection to purchase, it is difficult for users to efficiently obtain the learning materials and gadgets they need. Furthermore, detailed understanding of needs through dialogue with users using generative AI models is insufficient.

[0818] 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.

[0819] In this invention, the server includes a means for setting the grade or school information of the user in advance, a means for acquiring learning difficulties or goals through dialogue with the user using a generative AI model, and a means for proposing products such as textbooks, notebooks, or online courses according to the learning difficulties or goals. This makes it possible to propose products with high accuracy according to the learning needs of the user.

[0820] "Grade" is information indicating the academic grade in which the user is currently enrolled.

[0821] "School information" is information about the educational institution that the user attends.

[0822] A "generative AI model" is an artificial intelligence algorithm that generates appropriate responses or suggestions based on human input.

[0823] "Difficult points in learning" refers to areas or issues that the user finds particularly difficult in learning.

[0824] "Goal" refers to the specific purpose or outcome that a user wants to achieve through learning.

[0825] "Instructional Materials" are learning resources such as books, notes, online courses, etc. that are used to assist the user in their learning.

[0826] "Gadgets" refers to electronic devices and tools that aid in learning.

[0827] "Products" refers collectively to all learning materials and gadgets proposed to aid learning.

[0828] A "life event" refers to an important event that a user experiences at a particular time, such as before an exam or before submitting a report.

[0829] The "purchase process" refers to a series of procedures including payments and other procedures required to purchase the product selected by the user.

[0830] A "notification" is information or a message sent from the server to the user.

[0831] To implement the present invention, information is exchanged between the server, the terminal, and the user. The necessary hardware and software, as well as specific operation examples, are described below.

[0832] Hardware used

[0833] Server (a server equipped with a high-performance CPU and large-capacity memory)

[0834] Database server (e.g. MySQL, PostgreSQL)

[0835] User's device (smartphone, PC, etc.)

[0836] Software used

[0837] Generative AI models (e.g. OpenAI ChatGPT)

[0838] Database management systems (e.g. MySQL, PostgreSQL)

[0839] Web application frameworks (e.g. Django, Flask)

[0840] Network communication protocol (e.g. HTTP / HTTPS)

[0841] Working Example

[0842] 1. User input operations

[0843] The user starts up a dedicated application on their smartphone or computer, enters their grade and school information into the form displayed on the application screen, and clicks the "Submit" button.

[0844] 2. Receiving and storing data on the server side

[0845] The server receives the grade and school information entered by the user as an HTTP request and saves it as a new entry in the database.

[0846] 3. Dialogue using generative AI

[0847] The server starts the generative AI model and starts a dialogue with the user. For example, it asks, "Hello. What are you having trouble with in the learning you are currently doing?" It analyzes the user's response and understands the learning difficulties and goals.

[0848] 4. Product proposal

[0849] Based on the acquired learning difficulties and goals, the server searches a database for appropriate learning materials and gadgets (e.g., mathematics textbooks and online courses) and suggests them to the user.

[0850] 5. Ongoing dialogue and information gathering

[0851] The server uses a generative AI to ask the user, "Is there anything else you're having trouble with studying or schoolwork?" and, if it gets a response like, "I have an important math exam next week," it records this information.

[0852] 6. Product re-proposal based on life events

[0853] Based on the collected life events, the server re-searches the database for related products (e.g., exam preparation notes and manuals) and suggests them to the user.

[0854] 7. Purchase Processing and Notifications

[0855] When the user selects a product, the server receives the purchase request, communicates with the payment system, and executes the purchase process. When the purchase is complete, the server sends a "purchase completed" notification to the user.

[0856] Examples of prompt statements

[0857] "I'm in the third year of middle school and I'm not good at math. I have exams coming up. Can you tell me some effective study methods and useful study materials?"

[0858] Using these prompts, the generative AI model can understand the user's specific learning needs and difficulties and suggest suitable learning materials and online courses from its database, allowing users to receive effective learning support tailored to their grade level and learning goals.

[0859] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0860] Step 1:

[0861] The user enters grade and school information from the terminal. The user starts the application, enters their grade and school information in the form on the screen, and clicks the "Submit" button. The input data is the user's grade and school information. This is sent to the server.

[0862] Step 2:

[0863] The server receives the input information and saves it in the database. The server parses the user's grade and school information received as an HTTP request and saves it as a new record in the database (e.g. MySQL, PostgreSQL). During this process, a database insert operation is performed and a confirmation message is generated if successful.

[0864] Step 3:

[0865] The server uses a generative AI model to start a dialogue with the user and understands the learning difficulties and goals. The server starts a generative AI model (e.g., ChatGPT by OpenAI) and asks the user, "Hello. What are you having particular difficulty with in the learning you are currently working on?" The server analyzes the text data received as the user's response and extracts the learning difficulties and goals.

[0866] Step 4:

[0867] The server searches the database for products that meet the user's learning needs and suggests them. The server searches the database for related textbooks, notes, or online courses based on the extracted learning difficulties and goals. The server sends the product list obtained as the search result to the user in the form of a suggestion message.

[0868] Step 5:

[0869] The server continues to use the generative AI model to continue the dialogue with the user, collecting information about life events such as before an exam or before submitting a report. The server asks, "Is there anything else you're having trouble with regarding your studies or schoolwork?" If the user responds, "I have an important math exam next week," the server analyzes the text data and records it as life event information.

[0870] Step 6:

[0871] The server re-searches the database for products that match the user's life event and suggests them. The server again searches the database for related products (e.g., exam preparation notes and manuals) based on the collected life event information. The search results are sent to the user in the form of a suggestion message.

[0872] Step 7:

[0873] The user selects a product. The user checks the list of products suggested by the server and selects the product he or she wants to purchase by clicking the "Purchase" button. The selection information is sent to the server.

[0874] Step 8:

[0875] The server processes the purchase of the selected item and sends a notification of purchase completion to the user. The server receives the purchase request, communicates with the payment system to perform the appropriate payment processing, and if the payment is successful, generates a notification message of purchase completion and sends it to the user.

[0876] (Application example 1)

[0877] 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."

[0878] Conventional learning support systems have difficulty in timely proposing appropriate learning materials and products that match the individual learning needs and life events of learners. In addition, it has been difficult to grasp specific difficulties and goals through dialogue with learners and provide optimal resources accordingly. This has made it difficult to maximize the learning effect of learners.

[0879] 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.

[0880] In this invention, the server includes a means for setting the user's grade or school information in advance, a means for acquiring learning difficulties or goals through dialogue with the user using a generative AI model, a means for proposing products such as textbooks, notes, or online courses according to the learning difficulties or goals, a means for collecting the user's life events (e.g., before an exam, before submitting a report) and proposing timely products, a means for processing the purchase of the product selected by the user and notifying the user of the completion of the purchase, and a means for generating prompt sentences for dialogue using a generative AI model. This makes it possible to propose and purchase appropriate resources according to the user's learning needs and life events.

[0881] The "means for setting the user's grade or school information in advance" refers to a method for inputting and registering information about the grade or school the user belongs to in advance into the system.

[0882] A "generative AI model" is an artificial intelligence model that uses machine learning algorithms to interact with users and generate data.

[0883] The "means for acquiring learning difficulties or goals" refers to a method for identifying, through dialogue with users, which learning content they are having difficulty with or which learning goals they want to achieve.

[0884] A "means for suggesting products that are textbooks, notes, or online courses" is a method for selecting and recommending suitable learning materials or online educational resources to a user based on learning difficulties and goals.

[0885] The "means for collecting user's life events" is a method by which a user collects information about a specific event, such as before an exam or before submitting a report.

[0886] The "means for proposing timely products" is a method for proposing the most useful product to the user at that time based on collected life event information.

[0887] The "means for carrying out the purchasing process for the product selected by the user and notifying the user of the completion of the purchase" refers to a method for carrying out the purchasing process for the product selected by the user and notifying the user of the completion of the purchase.

[0888] A "means for generating prompts for dialogue using a generative AI model" is a method for automatically generating questions or instructions for effective dialogue with a user using a generative AI model.

[0889] This invention is an embodiment of a system that suggests learning materials and gadgets that match the user's learning needs and life events, and supports the purchase procedure. The system includes the following components.

[0890] Hardware Configuration

[0891] server:

[0892] Amazon Web Services (AWS), Google Cloud, or Azure

[0893] User device:

[0894] Smartphone (iOS or Android)

[0895] Software configuration and processing

[0896] The server has the following software and functions:

[0897] Database:

[0898] Relational databases such as MySQL and PostgreSQL

[0899] Stores user information, product information, and life event information

[0900] Generative AI models:

[0901] Advanced conversational AI models such as OpenAI ChatGPT

[0902] Through dialogue with the user, the system understands the learning difficulties and goals and generates prompts

[0903] Purchase Processing System:

[0904] Integrate payment processors like Stripe and PayPal

[0905] Implementation Procedure

[0906] 1. User Registration:

[0907] A user launches the app and enters grade or school information, which is then stored in a database on the server.

[0908] 2. Interactive learning support:

[0909] When a user inquires about a particular learning difficulty or goal, the generative AI model on the server collects detailed information through dialogue. For example, if a user asks, "I don't understand mathematical functions," the generative AI model generates a prompt such as, "What learning materials can help me understand?"

[0910] 3. Study material suggestions:

[0911] Based on the collected information, the server searches its database for appropriate learning materials (textbooks, notes, online courses, etc.) and suggests them to the user.

[0912] 4. Life Event Support:

[0913] When a user provides information about a life event, such as before an exam or before submitting a report, the generative AI model suggests timely products that match that event.

[0914] 5. Product Purchase:

[0915] The user selects the suggested product and completes the purchase procedure. The server processes the purchase and issues a purchase completion notification.

[0916] Examples

[0917] For example, if a user is having difficulty learning about mathematical functions, the difficulty is identified through the dialogue function of the smartphone app. The generative AI model generates a prompt, "What kind of study materials do you need about mathematical functions?" and suggests appropriate study materials from a past database. When the user selects, "I want exam preparation notes," the purchase procedure is completed through the payment system, and a notification that "purchase has been completed" is sent to the user.

[0918] Examples of prompt statements

[0919] If a user asks, "I don't understand a mathematical function":

[0920] "What teaching materials can help me understand math functions?"

[0921] Example of the answer generated:

[0922] "There are books and online courses that explain mathematical functions. I can suggest these products. Would you be interested?"

[0923] In this way, a system is constructed that can efficiently suggest and purchase appropriate resources according to the user's learning needs and life events.

[0924] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0925] Step 1:

[0926] User Registration:

[0927] A user starts the smartphone app and registers their grade and school information. The input is provided by the user, and the server receives this input and stores it in a database. This organizes the user's basic information and uses it for subsequent customized suggestions.

[0928] Input: Grade, School Information

[0929] Output: User information stored in the database

[0930] Step 2:

[0931] Interacting with generative AI models:

[0932] The user asks questions about their learning difficulties and goals through the app. The conversational bot using the generative AI model analyzes the user's input, generates appropriate prompts, and continues the conversation. For example, if the user types, "Mathematical functions are difficult," the generative AI model responds, "Which part specifically is difficult?"

[0933] Input: User question

[0934] Output: Response prompts from a generative AI model

[0935] Step 3:

[0936] Identifying learning challenges and goals:

[0937] Through dialogue with the generative AI model, the server identifies the user's learning difficulties and goals. If the user specifically answers, for example, "I don't understand how to draw a graph of a function," that information is sent to the server and stored.

[0938] Input: User interaction

[0939] Output: Identified learning difficulties and goals

[0940] Step 4:

[0941] Suggested teaching materials:

[0942] Based on the identified learning difficulties and goals, the server searches the database for appropriate learning materials (textbooks, notes, online courses, etc.) and suggests them to the user. For example, learning materials for "how to draw a graph of a function" are suggested.

[0943] Input: Learning difficulties and goals

[0944] Output: A list of suggested materials

[0945] Step 5:

[0946] Collecting life event information:

[0947] When a user provides information about a life event, such as before an exam or before submitting a report, the server collects that information and the generative AI model suggests timely products to meet the user's needs. For example, when a user says, "I have a math exam next week," a notebook for exam preparation is suggested.

[0948] Input: Life event information

[0949] Output: Product suggestions based on life events

[0950] Step 6:

[0951] Checkout:

[0952] The user selects the suggested learning materials and completes the purchase procedure. The server processes the payment and sends the user a notification that the purchase is complete. Payment is processed using a payment service such as Stripe or PayPal.

[0953] Input: User's purchase selection

[0954] Output: Purchase completion notification

[0955] Step 7:

[0956] Post-purchase notice:

[0957] After the purchase procedure is completed, the server sends a notification of purchase completion to the user, so that the user can confirm that the purchase process was completed successfully.

[0958] Input: Purchase completion data

[0959] Output: Notification to user that purchase is complete

[0960] The above are the specific process steps for carrying out the invention.

[0961] Furthermore, an emotion engine that estimates the emotion of the user may be combined. That is, the identification processing unit 290 may estimate the emotion of the user using the emotion identification model 59, and perform identification processing using the emotion of the user.

[0962] In this case, the system includes the following elements:

[0963] 1. The server has the function of receiving the user's grade and school information and storing it in a database.

[0964] 2. The server will utilize generative AI to engage in dialogue with users and understand their learning difficulties and goals.

[0965] 3. The server has the function of searching the database and suggesting products such as textbooks, notebooks, and online courses according to the user's learning needs.

[0966] 4. The server will have the ability to utilize generative AI to continue dialogue with the user and collect information about life events.

[0967] 5. The server is equipped with an emotion engine that recognizes the user's emotions and has the ability to analyze the user's emotional state.

[0968] 6. The server will have the ability to customize learning support and product suggestions according to the user's emotional state.

[0969] This allows the server to understand the user's learning needs and recommend appropriate learning materials and gadgets. It can also recognize the user's emotional state and customize learning support and product suggestions to match the user's emotions.

[0970] As a concrete example, a user starts the app and inputs their grade and school information. The server understands the user's learning difficulties and goals through dialogue with the user. When the user tells the server what they are weak at in math, the server searches the database for math textbooks, notes, and online courses and suggests them. At the same time, the server uses an emotion engine to analyze the user's emotional state, and if it determines that the user is feeling anxious or stressed, it suggests appropriate study support and relaxation methods.

[0971] In this way, product suggestions tailored to the user's learning needs and emotional support are provided via the server, providing a more personalized learning experience.

[0972] The process flow will be explained below.

[0973] Step 1: The user launches the app on the device. For example, the user launches the app and enters grade and school information.

[0974] Step 2: The server receives the user's information and stores it in a database. For example, the server receives the grade and school information entered by the user and stores it in a database.

[0975] Step 3: The server uses generative AI to initiate a dialogue with the user. For example, the server uses generative AI to initiate a dialogue with the user. The server generates questions about the user’s learning needs, difficulties, and goals, and receives the user’s answers.

[0976] Step 4: The server analyzes the user's answers and identifies the elements and trends of learning. For example, the server analyzes the user's answers and identifies the elements and trends of learning. When the user tells the server about their weaknesses in math, the server suggests products such as math textbooks, notebooks, and online courses.

[0977] Step 5: The server continues to dialogue with the user using generative AI to collect information about life events. For example, the server uses generative AI to continue dialogue with the user and collect information about student-specific life events, such as before an exam or before submitting a paper. If the user mentions that they need to make a study plan before an exam, the server suggests past exam guides and a study plan creation application.

[0978] Step 6: The server combines an emotion engine that recognizes the user's emotions and analyzes the user's emotional state. For example, the server uses the emotion engine to analyze information such as the user's speech and facial expressions to recognize the user's emotional state. If the server determines that the user is feeling anxious or stressed, it will provide appropriate study support or suggest ways to relax.

[0979] Step 7: The server customizes learning support and product suggestions based on the user's emotional state. For example, the server customizes learning support and product suggestions based on the user's emotional state. If the server determines that the user needs relaxation, it suggests relaxing music or a meditation application.

[0980] That's it. After the user starts the app and enters their grade and school information, the server will understand information about the user's learning needs and life events through dialogue with the user and suggest appropriate products. At the same time, the server will use an emotion engine to analyze the user's emotional state and provide support and suggestions tailored to the user's emotions. This makes it possible to more individually customize the user's learning experience and provide support based on emotions.

[0981] Example 2

[0982] 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".

[0983] Conventional learning support systems can provide learning materials and learning resources according to the user's learning needs, but it is difficult to provide personalized support that takes into account the user's emotional state. In addition, there is a lack of flexible learning material suggestions that respond to the user's life events and changes in daily life. This makes it difficult to provide an optimal learning experience for each individual user.

[0984] 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.

[0985] In this invention, the server includes a means for setting the grade or school information of the user in advance, a means for acquiring learning difficulties or goals through dialogue with the user using a generative AI model, a means for proposing products, which are teaching materials or online courses, according to the learning difficulties or goals, a means for combining an emotion engine for analyzing the emotional state of the user, and a means for customizing the suggesting means according to the emotional state of the user. This enables flexible teaching material suggestions that take into account the user's emotions and life events, and personalized learning support.

[0986] "User" refers to an individual who receives learning support using this system.

[0987] The "grade" is information indicating the educational stage of the educational institution in which the user is currently enrolled.

[0988] "School information" is information that includes details such as the name and location of the educational institution that the user attends.

[0989] A "generative AI model" is a type of artificial intelligence (AI) that uses natural language processing to interact with users and generate answers to their input and questions.

[0990] "Difficulties in learning" refers to subjects or content that the user finds particularly difficult to understand in learning.

[0991] "Goal" is information indicating the purpose or goal of learning that the user wishes to achieve.

[0992] "Instructional Materials" refers to educational materials such as textbooks, notes, online courses, etc. that a User uses to study.

[0993] "Means of suggestion" refers to a mechanism by which the server presents appropriate learning materials and products according to the user's learning needs.

[0994] An "emotion engine" refers to an algorithm or software that analyzes a user's language expressions and dialogue content to determine their emotional state (e.g., anxiety, stress, joy, etc.).

[0995] "Emotional state" refers to the psychological state that a user is feeling at a given moment, and includes factors such as motivation for learning, anxiety, and stress.

[0996] "Life events" refer to major events that occur in the user's daily life (e.g. exams, submitting reports, entering higher education, etc.).

[0997] The "means for carrying out purchase processing" refers to a mechanism for carrying out the procedure for purchasing the product selected by the user online or offline.

[0998] "Means for notifying the user of the completion of purchase" refers to a mechanism for executing a procedure to notify the user that the purchase of the product selected by the user has been completed.

[0999] This invention is a system that suggests learning materials and gadgets according to the user's learning needs and further personalizes support based on the user's emotional state. This system is composed of three main elements: a server, a terminal, and a user.

[1000] 1. Enter and save user information

[1001] server:

[1002] When a user launches an application on a terminal and enters grade and school information, that information is sent to the server. The server stores the user information received from the application in a database (e.g., MySQL or PostgreSQL). This stored information is used to provide a personalized learning experience for each user.

[1003] Examples:

[1004] The user enters "second year high school student" and "XX High School" into the application's input form. This information is sent to the server and saved in the database.

[1005] 2. Understanding learning difficulties through dialogue with users

[1006] server:

[1007] The server uses a generative AI model (e.g., ChatGPT by OpenAI) to converse with the user. Through the dialogue, the server understands the user's learning difficulties and goals, and uses that information to prepare to suggest appropriate learning materials.

[1008] Examples:

[1009] The user enters, "I'm not good at math," and the generative AI model asks, "Which part is difficult for you?" The user answers, "Calculus is difficult."

[1010] 3. Product suggestions based on learning needs

[1011] server:

[1012] The server searches a database for appropriate learning materials (e.g., mathematics textbooks, notes, online courses) and suggests them based on the user's learning difficulties and goals.

[1013] Examples:

[1014] If a user says that they are having difficulty with "calculus," the server will search the database for related learning materials and suggest, "We recommend these textbooks and online courses." A list of candidates will be displayed to the user on the terminal.

[1015] 4. Collecting life events through user interaction

[1016] server:

[1017] Generative AI models are used to collect information about users' life events (e.g. exams and paper submissions) to further customize learning support.

[1018] Examples:

[1019] When a user says, "I'm taking the university entrance exam next year," the generative AI model asks, "Which university and faculty are you aiming for?" to which the user answers, "The Faculty of Engineering at XX University."

[1020] 5. Emotion Analysis Using an Emotion Engine

[1021] server:

[1022] The server uses an emotion engine (e.g. IBM Watson's Tone Analyzer) to analyze the user's emotional state from their input and dialogue, and based on this information, determines whether the user is feeling anxious or stressed.

[1023] Examples:

[1024] When a user types, "I'm very anxious about studying math," the emotion engine recognizes the emotion "anxiety."

[1025] 6. Providing emotional support

[1026] server:

[1027] Based on the analyzed emotional state, the system customizes the suggestions to the user, and for users who feel anxious or stressed, it provides advice on how to relax or increase motivation.

[1028] Examples:

[1029] If the emotion engine recognizes the user as "anxious," the server will suggest, "Try taking some deep breaths to relax," and again provide appropriate learning resources.

[1030] Examples of Prompt Statements

[1031] 1. User Information Collection:

[1032] Please enter your grade and school information.

[1033] "What year are you in? What is the name of the school you go to?"

[1034] 2. Understanding learning difficulties:

[1035] "What are you having difficulty with in your studies?"

[1036] Which specific subjects or units are difficult for you?

[1037] 3. Suggested teaching materials:

[1038] "We'll suggest materials that fit your learning needs. Would you prefer a textbook, notes, or an online course?"

[1039] "I understand that you are looking for materials on calculus. I recommend the following products."

[1040] 4. Emotional state analysis:

[1041] “What emotions have you been feeling as a result of your recent learning?”

[1042] "If you have any anxiety or stress about your studies, please tell us the specifics."

[1043] By following this format, it is possible to realize a system that can provide flexible learning material suggestions based on the user's emotions and life events, and individualized learning support.

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

[1045] Step 1:

[1046] Entering and saving user information

[1047] A user starts the application on a terminal and inputs grade and school information. The input information (grade, school name) is sent to the server. The server stores the received information in a database (e.g. MySQL or PostgreSQL). This makes it possible to provide support tailored to the individual learning needs of each user.

[1048] Specific behavior:

[1049] The user enters their grade as "second year high school student" and the name of their school as "XX High School" in the app's input form.

[1050] The input information is sent to the server, which stores it in a database.

[1051] input:

[1052] Grade: "2nd year high school student"

[1053] School name: "XX High School"

[1054] output:

[1055] The grade and school name are stored in a database.

[1056] Step 2:

[1057] Understanding learning difficulties through dialogue with users

[1058] The server uses a generative AI model (e.g., ChatGPT by OpenAI) to initiate a dialogue with the user. Through the dialogue, the server understands the user's learning difficulties and goals. The user's answers are sent to the server, and the understood content is stored.

[1059] Specific behavior:

[1060] User types, "I'm not good at math."

[1061] The server uses a generative AI model to ask, "What part specifically is difficult?"

[1062] A user answered, "Differential and integral calculus is difficult."

[1063] input:

[1064] User answers: "I'm not good at math," "Calculus is difficult"

[1065] output:

[1066] Learning difficulty: "Calculus" is stored in the database.

[1067] Step 3:

[1068] Product suggestions based on learning needs

[1069] The server searches the database for appropriate learning materials based on the user's learning difficulties and goals, and suggests them to the user. The suggested learning materials are sent to the user's terminal and displayed.

[1070] Specific behavior:

[1071] The server searches a database for learning materials (e.g., textbooks, notes, online courses) related to "Calculus."

[1072] The search results are presented to the user.

[1073] input:

[1074] Difficulty in learning: "Calculus"

[1075] output:

[1076] A list of suggested teaching materials is displayed on the user's terminal.

[1077] Step 4:

[1078] Collecting information about life events

[1079] The server uses the generative AI model to collect information about life events (e.g. exams and report submissions) from interactions with the user. The collected information is sent to the server and stored.

[1080] Specific behavior:

[1081] The user says, "I have to take the university entrance exam next year."

[1082] The generative AI model asks, "Which university and department are you aiming for?"

[1083] The user answers, "XX University, Faculty of Engineering."

[1084] input:

[1085] User's life event information: "I have to take the university entrance exam next year", "XX University's Engineering Department"

[1086] output:

[1087] Life event information is stored in a database.

[1088] Step 5:

[1089] Emotion analysis using emotion engine

[1090] The server uses an emotion engine (e.g., IBM Watson's Tone Analyzer) to analyze the user's emotional state from their input and dialogue. The analyzed emotion information is stored on the server.

[1091] Specific behavior:

[1092] A user types, "I'm really anxious about studying math."

[1093] The emotion engine recognizes the emotion of "anxiety."

[1094] input:

[1095] User says: "I'm really anxious about studying math."

[1096] output:

[1097] The recognized emotion: "anxiety" is stored in the database.

[1098] Step 6:

[1099] Providing emotional support

[1100] The server customizes the content of suggestions to the user based on the analyzed emotional state, and learning support and advice appropriate to the emotional state are sent to and displayed on the user's device.

[1101] Specific behavior:

[1102] If the server detects that you are "anxious," it will suggest relaxation techniques and learning resources.

[1103] The user is presented with a message such as "Try taking a deep breath to relax" and learning resources.

[1104] input:

[1105] Recognized emotion: "Anxiety"

[1106] output:

[1107] The customized suggestions are displayed on the user's device.

[1108] (Application example 2)

[1109] 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".

[1110] Conventional learning support systems were unable to adequately respond to the individual needs of users and were limited to providing uniform learning materials and support. In addition, the system did not make suggestions that took into account the user's emotional state, which could result in a decrease in learning effectiveness. Furthermore, there was a lack of suggestions that were tailored to important life events such as exams and report submissions. There is a need for a system that can solve these problems and provide a personalized learning experience.

[1111] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means. In this invention, the server includes a means for setting the grade or school information of the user in advance, a means for using a generative AI to have a dialogue with the user and acquiring learning difficulties or goals through the dialogue with the user, a means for collecting information on a life event before an exam or before submitting a report through the dialogue with the user, a prompt sentence for instructing to suggest a product, which is a textbook, a notebook, or an online course, based on the learning difficulties or goals and information on the life event, a means for suggesting the product to the user using the generative AI, a means for analyzing the emotional state of the user using an emotion analysis engine, a prompt sentence for instructing to suggest learning support or a relaxation method based on the emotional state of the user, a means for suggesting the learning support or relaxation method to the user using the generative AI, a means for accepting the selection of the proposed product, a means for purchasing the product selected by the user, and a means for notifying the user of the completion of the purchase. This makes it possible to suggest educational materials tailored to the individual needs of each user and provide support tailored to their emotions.

[1112] "User" refers to an individual who uses the learning support system.

[1113] "Grade" means the stage at which students advance in their school education.

[1114] "School information" refers to information about the educational institution to which the user belongs.

[1115] "Data generation model" refers to an algorithm that uses generative AI technology to interact with users and generate information.

[1116] "Difficulty points in learning" refers to areas or issues that users find difficult to understand in their studies.

[1117] A "goal" refers to a specific learning objective that a user wishes to achieve.

[1118] "Teaching materials" means study materials such as textbooks and notebooks used for study.

[1119] "Online Course" refers to a program of study delivered via the Internet.

[1120] "Products" refers to suggested educational materials and online courses to assist users in their learning.

[1121] "Emotion Analysis Engine" means technology for recognizing and analyzing a user's emotional state.

[1122] "Learning support" refers to specific assistance and help to help users learn.

[1123] "Relaxation methods" refers to suggestions and methods for the user to reduce stress.

[1124] The term "system" refers to a configuration in which multiple means are combined to achieve a series of functions.

[1125] The present invention provides a system for providing appropriate learning materials and support according to a user's learning needs. Specifically, the system includes means including the following elements.

[1126] 1. Hardware and Software Configuration

[1127] Hardware: Mainly smartphones are used. Users use learning support applications on their smartphones.

[1128] software:

[1129] Front-end: Use a front-end framework such as React Native.

[1130] Backend: Uses technologies such as Node.js or Express.

[1131] Database: Use a database technology such as MongoDB or MySQL.

[1132] Sentiment analysis engine: Use sentiment analysis technologies such as Amazon Rekognition.

[1133] Generative AI models: Use generative AI models such as OpenAI's GPT.

[1134] 2. Management of User Information

[1135] The server receives basic information such as grade and school information entered by the user and stores it in a database. This information is the basis for the system to understand the user's learning difficulties and goals and make appropriate suggestions.

[1136] 3. User Dialogue Using Generative AI Models

[1137] The user launches the app and begins a dialogue with the generative AI. The generative AI uses natural language processing technology to gain a detailed understanding of the user's learning difficulties and goals. Based on the information obtained from this dialogue, the server uses the generative AI and a prompt sentence to suggest products such as textbooks, notes, or online courses based on the user's learning difficulties or goals to search the database and suggest learning materials (textbooks, notes, online courses, etc.) suitable for the user.

[1138] 4. Emotional state analysis and customization suggestions

[1139] The emotion analysis engine analyzes the user's emotional state from facial expressions, voice, etc. For example, if the user is feeling stressed or anxious, the server uses a prompt to suggest learning support or relaxation methods appropriate to the user's state, and generative AI to suggest learning support or relaxation methods. In this way, customized support is provided according to the user's emotional state.

[1140] 5. Collecting and suggesting life events according to context

[1141] The server collects information about life events, such as before an exam or before submitting a report, through dialogue with the generative AI. Based on the information obtained from the dialogue, the server uses the generative AI and a prompt to suggest products, such as textbooks, notes, or online courses, based on the learning difficulties or goals and the information about the life events, to search the database and provide timely educational materials and support to the user.

[1142] Examples:

[1143] When a second-year junior high school student uses this system, he or she first inputs their grade and school information. Then, through dialogue with the generative AI, it becomes clear that the student has difficulty with geometry problems in mathematics. It also becomes clear that the student has a mathematics exam next week. Based on this information, the server suggests related online courses and exercise books. Also, if the system detects through the emotion analysis engine that the user is feeling stressed, it suggests light exercise videos as a way to relax.

[1144] Example prompts for suggesting products: "A user in the 8th grade is having difficulty with geometry problems in mathematics. Next week, there will be an exam on geometry problems in mathematics. Please suggest some related learning materials or courses." An example prompt to suggest relaxation techniques: "I've noticed that I've been feeling stressed lately, so please provide me with some relaxation and motivational content."

[1145] In this way, the system of the present invention provides personalized support according to the user's learning needs and emotional state, resulting in a more effective learning experience.

[1146] The flow of the specific process in the application example 2 will be described with reference to FIG.

[1147] Step 1:

[1148] The user launches the smartphone app and enters grade and school information. The entered information is sent to the server and saved in the database. In this step, grade and school information is received as input data, and the process of saving this in the database is carried out. Specifically, the user enters their information into the form and presses the "Submit" button, which sends the data to the server.

[1149] Step 2:

[1150] The server uses the generative AI model to initiate a dialogue with the user. As the user continues the dialogue on the app, the generative AI analyzes the text input to understand the user's learning difficulties and goals. During this process, the user's input data is sent to the generative AI model and analyzed using natural language processing. The user's learning difficulties and goals are obtained as output. Information about life events is also obtained.

[1151] Step 3:

[1152] Based on the analyzed learning difficulties, goals, and information on life events, the server uses a generative AI and a prompt sentence instructing the server to suggest products such as textbooks, notes, or online courses from a database and suggests them to the user. In this step, the learning difficulties and goals are input data, and the suggested learning materials or courses are obtained as output. In specific operations, the server uses the generative AI to execute a database query and displays the results on the user's app screen.

[1153] Step 4:

[1154] The server uses an emotion analysis engine to analyze the user's emotional state. The user's facial expressions and voice data are input and processed by the emotion analysis engine. The output is the emotional state the user is feeling (stress, anxiety, etc.). Specifically, the server uses the smartphone's camera and microphone to collect the user's facial expressions and voice and transmits them to the analysis server.

[1155] Step 5:

[1156] The server uses a generative AI and a prompt sentence that instructs the server to suggest learning support or relaxation methods based on the analyzed emotional state, to suggest learning support or relaxation methods to the user. In this step, the emotional state is used as input data, and the suggested learning support or relaxation methods are obtained as output. In concrete terms, the server searches for and displays appropriate relaxation content or support guides based on the results of the emotion analysis.

[1157] Step 6:

[1158] The server accepts the user's selection of suggested teaching materials and support content, and processes the purchase of the selected product. In this step, the selected product information is input, and the server outputs the purchase process and a notification of purchase completion. In concrete terms, when the user presses the "Purchase" button, the server executes the purchase process and payment process for the selected product, and sends a completion notification to the user.

[1159] In this way, the system of the present invention uses a generative AI model and sentiment analysis engine based on user input data to execute a series of processes that suggest optimal learning materials and support to the user.

[1160] 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 voice indicating a user input for 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.

[1161] 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 making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data according to 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.

[1162] 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.

[1163] [Fourth embodiment]

[1164] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1165] 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.

[1166] 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 wide area network (WAN) and / or a local area network (LAN).

[1167] 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. In addition, the microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1168] 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 the voice according to instructions from the processor 46.

[1169] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a 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 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[1170] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54. The transmission and reception of various types of information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[1171] The control target 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, legs, etc. The posture and behavior of the robot 414 are controlled by controlling the motors of the arms, hands, legs, etc. 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.

[1172] Fig. 8 shows an example of 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.

[1173] 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.

[1174] 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.

[1175] In the robot 414, the reception and output process is performed by the processor 46. A reception and output program 60 is stored in the storage 50. The processor 46 reads the reception and output program 60 from the storage 50, and executes the read reception and output program 60 on the RAM 48. The reception and output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception and output program 60 executed on the RAM 48.

[1176] Next, a description will be given of the specific processing 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".

[1177] 1. The server has the function of receiving the user's grade and school information and storing it in a database.

[1178] 2. The server will utilize generative AI to engage in dialogue with users and understand their learning difficulties and goals.

[1179] 3. The server has the function of searching the database and suggesting products such as textbooks, notebooks, and online courses according to the user's learning needs.

[1180] 4. The server will have the ability to use generative AI to collect information about student-specific life events, such as before exams or before submitting reports, through dialogue with users.

[1181] 5. The server has the function of searching the database for timely products that match the user's life events and making suggestions.

[1182] 6. The server has the function of processing the purchase of the product selected by the user and sending a notification to the user that the purchase has been completed.

[1183] This allows the server to understand the user's learning needs and recommend appropriate learning materials and gadgets. It also makes timely product suggestions that match the life events specific to the student. The user selects a suggested product, and the server processes the purchase and sends the user a notification of purchase completion.

[1184] As a specific example, a user starts the app and enters their grade and school information. The server understands the user's learning difficulties and goals through dialogue with the user. When the user mentions their weaknesses in mathematics, the server searches the database for mathematics textbooks, notes, and online courses to suggest them. When the user mentions that they need to make a study plan before an exam, the server suggests past exam guidebooks and study plan creation applications. The user selects a suggested product, and the server processes the purchase and sends the user a notification of purchase completion.

[1185] In this way, a system that effectively provides learning support is realized by carrying out product suggestions tailored to the user's learning needs, information collection on life events, and purchasing processing via the server.

[1186] For example, if a user is having difficulty with math, the generative AI will identify the cause through dialogue with the user and suggest products such as math textbooks and online courses. In addition, when a user experiences student-specific life events such as before an exam or before submitting a paper, the generative AI will collect that information and make timely product recommendations.

[1187] For example, if a user tells the AI ​​that they have a university exam coming up, the AI ​​can use their past learning data and other users' exam preparation information to suggest effective study materials and notes for the exam. Also, if a user tells the AI ​​that they have a paper to submit, the AI ​​can suggest books and online resources related to that topic.

[1188] In this way, the system understands the learning needs and life events of the user through dialogue, and suggests suitable learning materials and gadgets. Users can obtain products that are tailored to their learning needs, enabling them to study more effectively.

[1189] The process flow of each embodiment will be described below.

[1190] Step 1: The user launches the app on the device. For example, the user launches the app and enters grade and school information.

[1191] Step 2: The server receives the user's information and stores it in a database. For example, the server receives the grade and school information entered by the user and stores it in a database.

[1192] Step 3: The server uses generative AI to initiate a dialogue with the user. For example, the server uses generative AI to initiate a dialogue with the user. The server generates questions about the user’s learning needs, difficulties, and goals, and receives the user’s answers.

[1193] Step 4: The server analyzes the user's answers and identifies the elements and trends of learning. For example, the server analyzes the user's answers and identifies the elements and trends of learning. When the user tells the server about their weaknesses in math, the server suggests products such as math textbooks, notebooks, and online courses.

[1194] Step 5: The server continues to dialogue with the user using generative AI to collect information about life events. For example, the server uses generative AI to continue dialogue with the user and collect information about student-specific life events, such as before an exam or before submitting a report. If the user mentions that they need to make a study plan before an exam, the server suggests past exam guides and a study plan creation app.

[1195] Step 6: The server processes the product selected by the user. For example, the server processes the product selected by the user from the products proposed. The server processes the purchase of the product selected by the user and notifies the user that the purchase is completed.

[1196] As described above, after a user starts the app and enters their grade and school information, the server interacts with the user to understand their learning needs and life events, and suggests appropriate products. The user selects a suggested product, and the server processes the purchase and sends the user a notification that the purchase has been completed. This realizes a system that supports the user's learning experience.

[1197] Example 1

[1198] Next, a description will be given of Example 1. In the following description, the data processing device 12 is referred to as a "server" and the robot 414 is referred to as a "terminal."

[1199] Conventional learning support systems lack effective product suggestions tailored to the user's learning needs and life events. In addition, since there is no system that consistently supports the process from product selection to purchase, it is difficult for users to efficiently obtain the learning materials and gadgets they need. Furthermore, detailed understanding of needs through dialogue with users using generative AI models is insufficient.

[1200] 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.

[1201] In this invention, the server includes a means for setting the grade or school information of the user in advance, a means for acquiring learning difficulties or goals through dialogue with the user using a generative AI model, and a means for proposing products such as textbooks, notebooks, or online courses according to the learning difficulties or goals. This makes it possible to propose products with high accuracy according to the learning needs of the user.

[1202] "Grade" is information indicating the academic grade in which the user is currently enrolled.

[1203] "School information" is information about the educational institution that the user attends.

[1204] A "generative AI model" is an artificial intelligence algorithm that generates appropriate responses or suggestions based on human input.

[1205] "Difficult points in learning" refers to areas or issues that the user finds particularly difficult in learning.

[1206] "Goal" refers to the specific purpose or outcome that a user wants to achieve through learning.

[1207] "Instructional Materials" are learning resources such as books, notes, online courses, etc. that are used to assist the user in their learning.

[1208] "Gadgets" refers to electronic devices and tools that aid in learning.

[1209] "Products" refers collectively to all learning materials and gadgets proposed to aid learning.

[1210] A "life event" refers to an important event that a user experiences at a particular time, such as before an exam or before submitting a report.

[1211] The "purchase process" refers to a series of procedures including payments and other procedures required to purchase the product selected by the user.

[1212] A "notification" is information or a message sent from the server to the user.

[1213] To implement the present invention, information is exchanged between the server, the terminal, and the user. The necessary hardware and software, as well as specific operation examples, are described below.

[1214] Hardware used

[1215] Server (a server equipped with a high-performance CPU and large-capacity memory)

[1216] Database server (e.g. MySQL, PostgreSQL)

[1217] User's device (smartphone, PC, etc.)

[1218] Software used

[1219] Generative AI models (e.g. OpenAI ChatGPT)

[1220] Database management systems (e.g. MySQL, PostgreSQL)

[1221] Web application frameworks (e.g. Django, Flask)

[1222] Network communication protocol (e.g. HTTP / HTTPS)

[1223] Working Example

[1224] 1. User input operations

[1225] The user starts up a dedicated application on their smartphone or computer, enters their grade and school information into the form displayed on the application screen, and clicks the "Submit" button.

[1226] 2. Receiving and storing data on the server side

[1227] The server receives the grade and school information entered by the user as an HTTP request and saves it as a new entry in the database.

[1228] 3. Dialogue using generative AI

[1229] The server starts the generative AI model and starts a dialogue with the user. For example, it asks, "Hello. What are you having trouble with in the learning you are currently doing?" It analyzes the user's response and understands the learning difficulties and goals.

[1230] 4. Product proposal

[1231] Based on the acquired learning difficulties and goals, the server searches a database for appropriate learning materials and gadgets (e.g., mathematics textbooks and online courses) and suggests them to the user.

[1232] 5. Ongoing dialogue and information gathering

[1233] The server uses a generative AI to ask the user, "Is there anything else you're having trouble with studying or schoolwork?" and, if it gets a response like, "I have an important math exam next week," it records this information.

[1234] 6. Product re-proposal based on life events

[1235] Based on the collected life events, the server re-searches the database for related products (e.g., exam preparation notes and manuals) and suggests them to the user.

[1236] 7. Purchase Processing and Notifications

[1237] When the user selects a product, the server receives the purchase request, communicates with the payment system, and executes the purchase process. When the purchase is complete, the server sends a "purchase completed" notification to the user.

[1238] Examples of prompt statements

[1239] "I'm in the third year of middle school and I'm not good at math. I have exams coming up. Can you tell me some effective study methods and useful study materials?"

[1240] Using these prompts, the generative AI model can understand the user's specific learning needs and difficulties and suggest suitable learning materials and online courses from its database, allowing users to receive effective learning support tailored to their grade level and learning goals.

[1241] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1242] Step 1:

[1243] The user enters grade and school information from the terminal. The user starts the application, enters their grade and school information in the form on the screen, and clicks the "Submit" button. The input data is the user's grade and school information. This is sent to the server.

[1244] Step 2:

[1245] The server receives the input information and saves it in the database. The server parses the user's grade and school information received as an HTTP request and saves it as a new record in the database (e.g. MySQL, PostgreSQL). During this process, a database insert operation is performed and a confirmation message is generated if successful.

[1246] Step 3:

[1247] The server uses a generative AI model to start a dialogue with the user and understands the learning difficulties and goals. The server starts a generative AI model (e.g., ChatGPT by OpenAI) and asks the user, "Hello. What are you having particular difficulty with in the learning you are currently working on?" The server analyzes the text data received as the user's response and extracts the learning difficulties and goals.

[1248] Step 4:

[1249] The server searches the database for products that meet the user's learning needs and suggests them. The server searches the database for related textbooks, notes, or online courses based on the extracted learning difficulties and goals. The server sends the product list obtained as the search result to the user in the form of a suggestion message.

[1250] Step 5:

[1251] The server continues to use the generative AI model to continue the dialogue with the user, collecting information about life events such as before an exam or before submitting a report. The server asks, "Is there anything else you're having trouble with regarding your studies or schoolwork?" If the user responds, "I have an important math exam next week," the server analyzes the text data and records it as life event information.

[1252] Step 6:

[1253] The server re-searches the database for products that match the user's life event and suggests them. The server again searches the database for related products (e.g., exam preparation notes and manuals) based on the collected life event information. The search results are sent to the user in the form of a suggestion message.

[1254] Step 7:

[1255] The user selects a product. The user checks the list of products suggested by the server and selects the product he or she wants to purchase by clicking the "Purchase" button. The selection information is sent to the server.

[1256] Step 8:

[1257] The server processes the purchase of the selected item and sends a notification of purchase completion to the user. The server receives the purchase request, communicates with the payment system to perform the appropriate payment processing, and if the payment is successful, generates a notification message of purchase completion and sends it to the user.

[1258] (Application example 1)

[1259] 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."

[1260] Conventional learning support systems have difficulty in timely proposing appropriate learning materials and products that match the individual learning needs and life events of learners. In addition, it has been difficult to grasp specific difficulties and goals through dialogue with learners and provide optimal resources accordingly. This has made it difficult to maximize the learning effect of learners.

[1261] 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.

[1262] In this invention, the server includes a means for setting the user's grade or school information in advance, a means for acquiring learning difficulties or goals through dialogue with the user using a generative AI model, a means for proposing products such as textbooks, notes, or online courses according to the learning difficulties or goals, a means for collecting the user's life events (e.g., before an exam, before submitting a report) and proposing timely products, a means for processing the purchase of the product selected by the user and notifying the user of the completion of the purchase, and a means for generating prompt sentences for dialogue using a generative AI model. This makes it possible to propose and purchase appropriate resources according to the user's learning needs and life events.

[1263] The "means for setting the user's grade or school information in advance" refers to a method for inputting and registering information about the grade or school the user belongs to in advance into the system.

[1264] A "generative AI model" is an artificial intelligence model that uses machine learning algorithms to interact with users and generate data.

[1265] The "means for acquiring learning difficulties or goals" refers to a method for identifying, through dialogue with users, which learning content they are having difficulty with or which learning goals they want to achieve.

[1266] A "means for suggesting products that are textbooks, notes, or online courses" is a method for selecting and recommending suitable learning materials or online educational resources to a user based on learning difficulties and goals.

[1267] The "means for collecting user's life events" is a method by which a user collects information about a specific event, such as before an exam or before submitting a report.

[1268] The "means for proposing timely products" is a method for proposing the most useful product to the user at that time based on collected life event information.

[1269] The "means for carrying out the purchasing process for the product selected by the user and notifying the user of the completion of the purchase" refers to a method for carrying out the purchasing process for the product selected by the user and notifying the user of the completion of the purchase.

[1270] A "means for generating prompts for dialogue using a generative AI model" is a method for automatically generating questions or instructions for effective dialogue with a user using a generative AI model.

[1271] This invention is an embodiment of a system that suggests learning materials and gadgets that match the user's learning needs and life events, and supports the purchase procedure. The system includes the following components.

[1272] Hardware Configuration

[1273] server:

[1274] Amazon Web Services (AWS), Google Cloud, or Azure

[1275] User device:

[1276] Smartphone (iOS or Android)

[1277] Software configuration and processing

[1278] The server has the following software and functions:

[1279] Database:

[1280] Relational databases such as MySQL and PostgreSQL

[1281] Stores user information, product information, and life event information

[1282] Generative AI models:

[1283] Advanced conversational AI models such as OpenAI ChatGPT

[1284] Through dialogue with the user, the system understands the learning difficulties and goals and generates prompts

[1285] Purchase Processing System:

[1286] Integrate payment processors like Stripe and PayPal

[1287] Implementation Procedure

[1288] 1. User Registration:

[1289] A user launches the app and enters grade or school information, which is then stored in a database on the server.

[1290] 2. Interactive learning support:

[1291] When a user inquires about a particular learning difficulty or goal, the generative AI model on the server collects detailed information through dialogue. For example, if a user asks, "I don't understand mathematical functions," the generative AI model generates a prompt such as, "What learning materials can help me understand?"

[1292] 3. Study material suggestions:

[1293] Based on the collected information, the server searches its database for appropriate learning materials (textbooks, notes, online courses, etc.) and suggests them to the user.

[1294] 4. Life Event Support:

[1295] When a user provides information about a life event, such as before an exam or before submitting a report, the generative AI model suggests timely products that match that event.

[1296] 5. Product Purchase:

[1297] The user selects the suggested product and completes the purchase procedure. The server processes the purchase and issues a purchase completion notification.

[1298] Examples

[1299] For example, if a user is having difficulty learning about mathematical functions, the difficulty is identified through the dialogue function of the smartphone app. The generative AI model generates a prompt, "What kind of study materials do you need about mathematical functions?" and suggests appropriate study materials from a past database. When the user selects, "I want exam preparation notes," the purchase procedure is completed through the payment system, and a notification that "purchase has been completed" is sent to the user.

[1300] Examples of prompt statements

[1301] If a user asks, "I don't understand a mathematical function":

[1302] "What teaching materials can help me understand math functions?"

[1303] Example of the answer generated:

[1304] "There are books and online courses that explain mathematical functions. I can suggest these products. Would you be interested?"

[1305] In this way, a system is constructed that can efficiently suggest and purchase appropriate resources according to the user's learning needs and life events.

[1306] The flow of the specific process in the application example 1 will be described with reference to FIG.

[1307] Step 1:

[1308] User Registration:

[1309] A user starts the smartphone app and registers their grade and school information. The input is provided by the user, and the server receives this input and stores it in a database. This organizes the user's basic information and uses it for subsequent customized suggestions.

[1310] Input: Grade, School Information

[1311] Output: User information stored in the database

[1312] Step 2:

[1313] Interacting with generative AI models:

[1314] The user asks questions about their learning difficulties and goals through the app. The conversational bot using the generative AI model analyzes the user's input, generates appropriate prompts, and continues the conversation. For example, if the user types, "Mathematical functions are difficult," the generative AI model responds, "Which part specifically is difficult?"

[1315] Input: User question

[1316] Output: Response prompts from a generative AI model

[1317] Step 3:

[1318] Identifying learning challenges and goals:

[1319] Through dialogue with the generative AI model, the server identifies the user's learning difficulties and goals. If the user specifically answers, for example, "I don't understand how to draw a graph of a function," that information is sent to the server and stored.

[1320] Input: User interaction

[1321] Output: Identified learning difficulties and goals

[1322] Step 4:

[1323] Suggested teaching materials:

[1324] Based on the identified learning difficulties and goals, the server searches the database for appropriate learning materials (textbooks, notes, online courses, etc.) and suggests them to the user. For example, learning materials for "how to draw a graph of a function" are suggested.

[1325] Input: Learning difficulties and goals

[1326] Output: A list of suggested materials

[1327] Step 5:

[1328] Collecting life event information:

[1329] When a user provides information about a life event, such as before an exam or before submitting a report, the server collects that information and the generative AI model suggests timely products to meet the user's needs. For example, when a user says, "I have a math exam next week," a notebook for exam preparation is suggested.

[1330] Input: Life event information

[1331] Output: Product suggestions based on life events

[1332] Step 6:

[1333] Checkout:

[1334] The user selects the suggested learning materials and completes the purchase procedure. The server processes the payment and sends the user a notification that the purchase is complete. Payment is processed using a payment service such as Stripe or PayPal.

[1335] Input: User's purchase selection

[1336] Output: Purchase completion notification

[1337] Step 7:

[1338] Post-purchase notice:

[1339] After the purchase procedure is completed, the server sends a notification of purchase completion to the user, so that the user can confirm that the purchase process was completed successfully.

[1340] Input: Purchase completion data

[1341] Output: Notification to user that purchase is complete

[1342] The above are the specific process steps for carrying out the invention.

[1343] Furthermore, an emotion engine that estimates the emotion of the user may be combined. That is, the identification processing unit 290 may estimate the emotion of the user using the emotion identification model 59, and perform identification processing using the emotion of the user.

[1344] In this case, the system includes the following elements:

[1345] 1. The server has the function of receiving the user's grade and school information and storing it in a database.

[1346] 2. The server will utilize generative AI to engage in dialogue with users and understand their learning difficulties and goals.

[1347] 3. The server has the function of searching the database and suggesting products such as textbooks, notebooks, and online courses according to the user's learning needs.

[1348] 4. The server will have the ability to utilize generative AI to continue dialogue with the user and collect information about life events.

[1349] 5. The server is equipped with an emotion engine that recognizes the user's emotions and has the ability to analyze the user's emotional state.

[1350] 6. The server will have the ability to customize learning support and product suggestions according to the user's emotional state.

[1351] This allows the server to understand the user's learning needs and recommend appropriate learning materials and gadgets. It can also recognize the user's emotional state and customize learning support and product suggestions to match the user's emotions.

[1352] As a concrete example, a user starts the app and inputs their grade and school information. The server understands the user's learning difficulties and goals through dialogue with the user. When the user tells the server what they are weak at in math, the server searches the database for math textbooks, notes, and online courses and suggests them. At the same time, the server uses an emotion engine to analyze the user's emotional state, and if it determines that the user is feeling anxious or stressed, it suggests appropriate study support and relaxation methods.

[1353] In this way, product suggestions tailored to the user's learning needs and emotional support are provided via the server, providing a more personalized learning experience.

[1354] The process flow will be explained below.

[1355] Step 1: The user launches the app on the device. For example, the user launches the app and enters grade and school information.

[1356] Step 2: The server receives the user's information and stores it in a database. For example, the server receives the grade and school information entered by the user and stores it in a database.

[1357] Step 3: The server uses generative AI to initiate a dialogue with the user. For example, the server uses generative AI to initiate a dialogue with the user. The server generates questions about the user’s learning needs, difficulties, and goals, and receives the user’s answers.

[1358] Step 4: The server analyzes the user's answers and identifies the elements and trends of learning. For example, the server analyzes the user's answers and identifies the elements and trends of learning. When the user tells the server about their weaknesses in math, the server suggests products such as math textbooks, notebooks, and online courses.

[1359] Step 5: The server continues to dialogue with the user using generative AI to collect information about life events. For example, the server uses generative AI to continue dialogue with the user and collect information about student-specific life events, such as before an exam or before submitting a paper. If the user mentions that they need to make a study plan before an exam, the server suggests past exam guides and a study plan creation application.

[1360] Step 6: The server combines an emotion engine that recognizes the user's emotions and analyzes the user's emotional state. For example, the server uses the emotion engine to analyze information such as the user's speech and facial expressions to recognize the user's emotional state. If the server determines that the user is feeling anxious or stressed, it will provide appropriate study support or suggest ways to relax.

[1361] Step 7: The server customizes learning support and product suggestions based on the user's emotional state. For example, the server customizes learning support and product suggestions based on the user's emotional state. If the server determines that the user needs relaxation, it suggests relaxing music or a meditation application.

[1362] That's it. After the user starts the app and enters their grade and school information, the server will understand information about the user's learning needs and life events through dialogue with the user and suggest appropriate products. At the same time, the server will use an emotion engine to analyze the user's emotional state and provide support and suggestions tailored to the user's emotions. This makes it possible to more individually customize the user's learning experience and provide support based on emotions.

[1363] Example 2

[1364] Next, a description will be given of Example 2. In the following description, the data processing device 12 is referred to as a "server" and the robot 414 is referred to as a "terminal."

[1365] Conventional learning support systems can provide learning materials and learning resources according to the user's learning needs, but it is difficult to provide personalized support that takes into account the user's emotional state. In addition, there is a lack of flexible learning material suggestions that respond to the user's life events and changes in daily life. This makes it difficult to provide an optimal learning experience for each individual user.

[1366] 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.

[1367] In this invention, the server includes a means for setting the grade or school information of the user in advance, a means for acquiring learning difficulties or goals through dialogue with the user using a generative AI model, a means for proposing products, which are teaching materials or online courses, according to the learning difficulties or goals, a means for combining an emotion engine for analyzing the emotional state of the user, and a means for customizing the suggesting means according to the emotional state of the user. This enables flexible teaching material suggestions that take into account the user's emotions and life events, and personalized learning support.

[1368] "User" refers to an individual who receives learning support using this system.

[1369] The "grade" is information indicating the educational stage of the educational institution in which the user is currently enrolled.

[1370] "School information" is information that includes details such as the name and location of the educational institution that the user attends.

[1371] A "generative AI model" is a type of artificial intelligence (AI) that uses natural language processing to interact with users and generate answers to their input and questions.

[1372] "Difficulties in learning" refers to subjects or content that the user finds particularly difficult to understand in learning.

[1373] "Goal" is information indicating the purpose or goal of learning that the user wishes to achieve.

[1374] "Instructional Materials" refers to educational materials such as textbooks, notes, online courses, etc. that a User uses to study.

[1375] "Means of suggestion" refers to a mechanism by which the server presents appropriate learning materials and products according to the user's learning needs.

[1376] An "emotion engine" refers to an algorithm or software that analyzes a user's language expressions and dialogue content to determine their emotional state (e.g., anxiety, stress, joy, etc.).

[1377] "Emotional state" refers to the psychological state that a user is feeling at a given moment, and includes factors such as motivation for learning, anxiety, and stress.

[1378] "Life events" refer to major events that occur in the user's daily life (e.g. exams, submitting reports, entering higher education, etc.).

[1379] The "means for carrying out purchase processing" refers to a mechanism for carrying out the procedure for purchasing the product selected by the user online or offline.

[1380] "Means for notifying the user of the completion of purchase" refers to a mechanism for executing a procedure to notify the user that the purchase of the product selected by the user has been completed.

[1381] This invention is a system that suggests learning materials and gadgets according to the user's learning needs and further personalizes support based on the user's emotional state. This system is composed of three main elements: a server, a terminal, and a user.

[1382] 1. Enter and save user information

[1383] server:

[1384] When a user launches an application on a terminal and enters grade and school information, that information is sent to the server. The server stores the user information received from the application in a database (e.g., MySQL or PostgreSQL). This stored information is used to provide a personalized learning experience for each user.

[1385] Examples:

[1386] The user enters "second year high school student" and "XX High School" into the application's input form. This information is sent to the server and saved in the database.

[1387] 2. Understanding learning difficulties through dialogue with users

[1388] server:

[1389] The server uses a generative AI model (e.g., ChatGPT by OpenAI) to converse with the user. Through the dialogue, the server understands the user's learning difficulties and goals, and uses that information to prepare to suggest appropriate learning materials.

[1390] Examples:

[1391] The user enters, "I'm not good at math," and the generative AI model asks, "Which part is difficult for you?" The user answers, "Calculus is difficult."

[1392] 3. Product suggestions based on learning needs

[1393] server:

[1394] The server searches a database for appropriate learning materials (e.g., mathematics textbooks, notes, online courses) and suggests them based on the user's learning difficulties and goals.

[1395] Examples:

[1396] If a user says that they are having difficulty with "calculus," the server will search the database for related learning materials and suggest, "We recommend these textbooks and online courses." A list of candidates will be displayed to the user on the terminal.

[1397] 4. Collecting life events through user interaction

[1398] server:

[1399] Generative AI models are used to collect information about users' life events (e.g. exams and paper submissions) to further customize learning support.

[1400] Examples:

[1401] When a user says, "I'm taking the university entrance exam next year," the generative AI model asks, "Which university and faculty are you aiming for?" to which the user answers, "The Faculty of Engineering at XX University."

[1402] 5. Emotion Analysis Using an Emotion Engine

[1403] server:

[1404] The server uses an emotion engine (e.g. IBM Watson's Tone Analyzer) to analyze the user's emotional state from their input and dialogue, and based on this information, determines whether the user is feeling anxious or stressed.

[1405] Examples:

[1406] When a user types, "I'm very anxious about studying math," the emotion engine recognizes the emotion "anxiety."

[1407] 6. Providing emotional support

[1408] server:

[1409] Based on the analyzed emotional state, the system customizes the suggestions to the user, and for users who feel anxious or stressed, it provides advice on how to relax or increase motivation.

[1410] Examples:

[1411] If the emotion engine recognizes the user as "anxious," the server will suggest, "Try taking some deep breaths to relax," and again provide appropriate learning resources.

[1412] Examples of Prompt Statements

[1413] 1. User Information Collection:

[1414] Please enter your grade and school information.

[1415] "What year are you in? What is the name of the school you go to?"

[1416] 2. Understanding learning difficulties:

[1417] "What are you having difficulty with in your studies?"

[1418] Which specific subjects or units are difficult for you?

[1419] 3. Suggested teaching materials:

[1420] "We'll suggest materials that fit your learning needs. Would you prefer a textbook, notes, or an online course?"

[1421] "I understand that you are looking for materials on calculus. I recommend the following products."

[1422] 4. Emotional state analysis:

[1423] “What emotions have you been feeling as a result of your recent learning?”

[1424] "If you have any anxiety or stress about your studies, please tell us the specifics."

[1425] By following this format, it is possible to realize a system that can provide flexible learning material suggestions based on the user's emotions and life events, and individualized learning support.

[1426] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1427] Step 1:

[1428] Entering and saving user information

[1429] A user starts the application on a terminal and inputs grade and school information. The input information (grade, school name) is sent to the server. The server stores the received information in a database (e.g. MySQL or PostgreSQL). This makes it possible to provide support tailored to the individual learning needs of each user.

[1430] Specific behavior:

[1431] The user enters their grade as "second year high school student" and the name of their school as "XX High School" in the app's input form.

[1432] The input information is sent to the server, which stores it in a database.

[1433] input:

[1434] Grade: "2nd year high school student"

[1435] School name: "XX High School"

[1436] output:

[1437] The grade and school name are stored in a database.

[1438] Step 2:

[1439] Understanding learning difficulties through dialogue with users

[1440] The server uses a generative AI model (e.g., ChatGPT by OpenAI) to initiate a dialogue with the user. Through the dialogue, the server understands the user's learning difficulties and goals. The user's answers are sent to the server, and the understood content is stored.

[1441] Specific behavior:

[1442] User types, "I'm not good at math."

[1443] The server uses a generative AI model to ask, "What part specifically is difficult?"

[1444] A user answered, "Differential and integral calculus is difficult."

[1445] input:

[1446] User answers: "I'm not good at math," "Calculus is difficult"

[1447] output:

[1448] Learning difficulty: "Calculus" is stored in the database.

[1449] Step 3:

[1450] Product suggestions based on learning needs

[1451] The server searches the database for appropriate learning materials based on the user's learning difficulties and goals, and suggests them to the user. The suggested learning materials are sent to the user's terminal and displayed.

[1452] Specific behavior:

[1453] The server searches a database for learning materials (e.g., textbooks, notes, online courses) related to "Calculus."

[1454] The search results are presented to the user.

[1455] input:

[1456] Difficulty in learning: "Calculus"

[1457] output:

[1458] A list of suggested teaching materials is displayed on the user's terminal.

[1459] Step 4:

[1460] Collecting information about life events

[1461] The server uses the generative AI model to collect information about life events (e.g. exams and report submissions) from interactions with the user. The collected information is sent to the server and stored.

[1462] Specific behavior:

[1463] The user says, "I have to take the university entrance exam next year."

[1464] The generative AI model asks, "Which university and department are you aiming for?"

[1465] The user answers, "XX University, Faculty of Engineering."

[1466] input:

[1467] User's life event information: "I have to take the university entrance exam next year", "XX University's Engineering Department"

[1468] output:

[1469] Life event information is stored in a database.

[1470] Step 5:

[1471] Emotion analysis using emotion engine

[1472] The server uses an emotion engine (e.g., IBM Watson's Tone Analyzer) to analyze the user's emotional state from their input and dialogue. The analyzed emotion information is stored on the server.

[1473] Specific behavior:

[1474] A user types, "I'm really anxious about studying math."

[1475] The emotion engine recognizes the emotion of "anxiety."

[1476] input:

[1477] User says: "I'm really anxious about studying math."

[1478] output:

[1479] The recognized emotion: "anxiety" is stored in the database.

[1480] Step 6:

[1481] Providing emotional support

[1482] The server customizes the content of suggestions to the user based on the analyzed emotional state, and learning support and advice appropriate to the emotional state are sent to the user's device and displayed.

[1483] Specific behavior:

[1484] If the server detects that you are "anxious," it will suggest relaxation techniques and learning resources.

[1485] The user is presented with a message such as "Try taking a deep breath to relax" and learning resources.

[1486] input:

[1487] Recognized emotion: "Anxiety"

[1488] output:

[1489] The customized suggestions are displayed on the user's device.

[1490] (Application example 2)

[1491] 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".

[1492] Conventional learning support systems were unable to adequately respond to the individual needs of users and were limited to providing uniform learning materials and support. In addition, the system did not make suggestions that took into account the user's emotional state, which could result in a decrease in learning effectiveness. Furthermore, there was a lack of suggestions that were tailored to important life events such as exams and report submissions. There is a need for a system that can solve these problems and provide a personalized learning experience.

[1493] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means. In this invention, the server includes a means for setting the grade or school information of the user in advance, a means for using a generative AI to have a dialogue with the user and acquiring learning difficulties or goals through the dialogue with the user, a means for collecting information on a life event before an exam or before submitting a report through the dialogue with the user, a prompt sentence for instructing to suggest a product, which is a textbook, a notebook, or an online course, based on the learning difficulties or goals and information on the life event, a means for suggesting the product to the user using the generative AI, a means for analyzing the emotional state of the user using an emotion analysis engine, a prompt sentence for instructing to suggest learning support or a relaxation method based on the emotional state of the user, a means for suggesting the learning support or relaxation method to the user using the generative AI, a means for accepting the selection of the proposed product, a means for purchasing the product selected by the user, and a means for notifying the user of the completion of the purchase. This makes it possible to suggest educational materials tailored to the individual needs of each user and provide support tailored to their emotions.

[1494] "User" refers to an individual who uses the learning support system.

[1495] "Grade" means the stage at which students advance in their school education.

[1496] "School information" refers to information about the educational institution to which the user belongs.

[1497] "Data generation model" refers to an algorithm that uses generative AI technology to interact with users and generate information.

[1498] "Difficulty points in learning" refers to areas or issues that users find difficult to understand in their studies.

[1499] A "goal" refers to a specific learning objective that a user wishes to achieve.

[1500] "Teaching materials" means study materials such as textbooks and notebooks used for study.

[1501] "Online Course" refers to a program of study delivered via the Internet.

[1502] "Products" refers to suggested educational materials and online courses to assist users in their learning.

[1503] "Emotion Analysis Engine" means technology for recognizing and analyzing a user's emotional state.

[1504] "Learning support" refers to specific assistance and help to help users learn.

[1505] "Relaxation methods" refers to suggestions and methods for the user to reduce stress.

[1506] The term "system" refers to a configuration in which multiple means are combined to achieve a series of functions.

[1507] The present invention provides a system for providing appropriate learning materials and support according to a user's learning needs. Specifically, the system includes means including the following elements.

[1508] 1. Hardware and Software Configuration

[1509] Hardware: Mainly smartphones are used. Users use learning support applications on their smartphones.

[1510] software:

[1511] Front-end: Use a front-end framework such as React Native.

[1512] Backend: Uses technologies such as Node.js or Express.

[1513] Database: Use a database technology such as MongoDB or MySQL.

[1514] Sentiment analysis engine: Use sentiment analysis technologies such as Amazon Rekognition.

[1515] Generative AI models: Use generative AI models such as OpenAI's GPT.

[1516] 2. Management of User Information

[1517] The server receives basic information such as grade and school information entered by the user and stores it in a database. This information is the basis for the system to understand the user's learning difficulties and goals and make appropriate suggestions.

[1518] 3. User Dialogue Using Generative AI Models

[1519] The user launches the app and begins a dialogue with the generative AI. The generative AI uses natural language processing technology to gain a detailed understanding of the user's learning difficulties and goals. Based on the information obtained from this dialogue, the server uses the generative AI and a prompt sentence to suggest products such as textbooks, notes, or online courses based on the user's learning difficulties or goals to search the database and suggest learning materials (textbooks, notes, online courses, etc.) suitable for the user.

[1520] 4. Emotional state analysis and customization suggestions

[1521] The emotion analysis engine analyzes the user's emotional state from facial expressions, voice, etc. For example, if the user is feeling stressed or anxious, the server uses a prompt to suggest learning support or relaxation methods appropriate to the user's state, and generative AI to suggest learning support or relaxation methods. In this way, customized support is provided according to the user's emotional state.

[1522] 5. Collecting and suggesting life events according to context

[1523] The server collects information about life events, such as before an exam or before submitting a report, through dialogue with the generative AI. Based on the information obtained from the dialogue, the server uses the generative AI and a prompt to suggest products, such as textbooks, notes, or online courses, based on the learning difficulties or goals and the information about the life events, to search the database and provide timely educational materials and support to the user.

[1524] Examples:

[1525] When a second-year junior high school student uses this system, he or she first inputs their grade and school information. Then, through dialogue with the generative AI, it becomes clear that the student has difficulty with geometry problems in mathematics. It also becomes clear that the student has a mathematics exam next week. Based on this information, the server suggests related online courses and exercise books. Also, if the system detects through the emotion analysis engine that the user is feeling stressed, it suggests light exercise videos as a way to relax.

[1526] Example prompts for suggesting products: "A user in the 8th grade is having difficulty with geometry problems in mathematics. Next week, there will be an exam on geometry problems in mathematics. Please suggest some related learning materials or courses." An example prompt to suggest relaxation techniques: "I've noticed that I've been feeling stressed lately, so please provide me with some relaxation and motivational content."

[1527] In this way, the system of the present invention provides personalized support according to the user's learning needs and emotional state, resulting in a more effective learning experience.

[1528] The flow of the specific process in the application example 2 will be described with reference to FIG.

[1529] Step 1:

[1530] The user launches the smartphone app and enters grade and school information. The entered information is sent to the server and saved in the database. In this step, grade and school information is received as input data, and the process of saving this in the database is carried out. Specifically, the user enters their information into the form and presses the "Submit" button, which sends the data to the server.

[1531] Step 2:

[1532] The server uses the generative AI model to initiate a dialogue with the user. As the user continues the dialogue on the app, the generative AI analyzes the text input to understand the user's learning difficulties and goals. During this process, the user's input data is sent to the generative AI model and analyzed using natural language processing. The user's learning difficulties and goals are obtained as output. Information about life events is also obtained.

[1533] Step 3:

[1534] Based on the analyzed learning difficulties, goals, and information on life events, the server uses a generative AI and a prompt sentence instructing the server to suggest products such as textbooks, notes, or online courses from a database and suggests them to the user. In this step, the learning difficulties and goals are input data, and the suggested learning materials or courses are obtained as output. In specific operations, the server uses the generative AI to execute a database query and displays the results on the user's app screen.

[1535] Step 4:

[1536] The server uses an emotion analysis engine to analyze the user's emotional state. The user's facial expressions and voice data are input and processed by the emotion analysis engine. The output is the emotional state the user is feeling (stress, anxiety, etc.). Specifically, the server uses the smartphone's camera and microphone to collect the user's facial expressions and voice and transmits them to the analysis server.

[1537] Step 5:

[1538] The server uses a generative AI and a prompt sentence that instructs the server to suggest learning support or relaxation methods based on the analyzed emotional state, to suggest learning support or relaxation methods to the user. In this step, the emotional state is used as input data, and the suggested learning support or relaxation methods are obtained as output. In concrete terms, the server searches for and displays appropriate relaxation content or support guides based on the results of the emotion analysis.

[1539] Step 6:

[1540] The server accepts the user's selection of suggested teaching materials and support content, and processes the purchase of the selected product. In this step, the selected product information is input, and the server outputs the purchase process and a notification of purchase completion. In concrete terms, when the user presses the "Purchase" button, the server executes the purchase process and payment process for the selected product, and sends a completion notification to the user.

[1541] In this way, the system of the present invention uses a generative AI model and sentiment analysis engine based on user input data to execute a series of processes that suggest optimal learning materials and support to the user.

[1542] 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 a voice indicating a user input for 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.

[1543] 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 making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data according to 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.

[1544] In the above embodiment, an example was given in which the specific process was performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the robot 414.

[1545] The emotion identification model 59 as an emotion engine may determine the emotion of the user according to a specific mapping. Specifically, the emotion identification model 59 may determine the emotion of the user according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the emotion of the robot, and the identification processing unit 290 may perform identification processing using the emotion of the robot.

[1546] FIG. 9 is a diagram showing 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. The closer to the center of the concentric circles, the more primitive emotions are arranged. The more outside the concentric circles, the more emotions that represent states and actions that arise from a state of mind are arranged. Emotions are a concept that includes emotions and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions that occur in the brain are arranged. On the right side of the concentric circles, emotions that are generally induced by situational judgment are arranged. On the upper and lower sides of the concentric circles, emotions that are generally generated from reactions that occur in the brain and are induced by situational judgment are arranged. In addition, on the upper side of the concentric circles, emotions of "pleasure" are arranged, and on the lower side, emotions of "discomfort" are arranged. In this way, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1547] These emotions are distributed in the 3 o'clock direction of emotion map 400 and usually 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.

[1548] The inside of emotion map 400 represents what is going on inside one's mind, and the outside of emotion map 400 represents behavior, so the further out you go on emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1549] Here, human emotions are based on various balances such as posture and blood sugar level, and when these balances are far from the ideal, it indicates an unpleasant state, and when they are close to the ideal, it indicates a pleasant state. Emotions can also be created for robots, cars, motorcycles, etc., based on various balances such as posture and battery level, so that when these balances are far from the ideal, it indicates an unpleasant state, and when they are close to the ideal, it indicates a pleasant state. The emotion map may be generated, for example, based on the emotion map of Dr. Mitsuyoshi (Research on speech emotion recognition and emotion brain physiological signal analysis system, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). On the left half of the emotion map, emotions belonging to an area called "reaction" where sensation is dominant are lined up. On the right half of the emotion map, emotions belonging to an area called "situation" where situation recognition is dominant are lined up.

[1550] The emotion map defines two emotions that promote learning. The first is the negative emotion around the middle of "repentance" or "remorse" on the situation side. In other words, this is 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 the positive emotion around "desire" on the response side. In other words, this is when the robot has positive feelings such as "I want more" or "I want to know more."

[1551] The emotion identification model 59 inputs the user input to a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the emotion of the user. This neural network is pre-trained based on multiple learning data that are combinations of the 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, "relief," "calm," and "encouraging," have similar emotion values.

[1552] Although the system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, the system according to the present disclosure is not necessarily implemented in 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 that runs on a personal computer, or an application that runs on a smartphone or the like. The method according to the present disclosure may be provided to a user in the form of SaaS (Software as a Service).

[1553] In the above embodiment, an example is 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 the external device may generate data according to input data.

[1554] 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 Universal Serial Bus (USB) 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.

[1555] In addition, 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 upon request from the data processing device 12.

[1556] 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.

[1557] As the hardware resource for executing the specific process, various processors as shown below can be used. An example of the processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing the specific process by executing software, i.e., a program. Another example of the processor is a dedicated electric circuit, which is a processor having a circuit configuration designed exclusively for executing the specific process, such as a Field-Programmable Gate Array (FPGA), a Programmable Logic Device (PLD), or an Application Specific Integrated Circuit (ASIC). Each processor has a built-in or connected memory, and each processor executes the specific process by using the memory.

[1558] The hardware resource that executes the specific process may be one of these various processors, or may be 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 process may be a single processor.

[1559] As an example of a configuration using one 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 configuration using a processor that realizes the functions of the 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.

[1560] Furthermore, more specifically, the hardware structure of these various processors can be an electric circuit that combines circuit elements such as semiconductor elements. The specific processes described above are merely examples. It goes without saying that unnecessary steps may be deleted, new steps may be added, or the order of processes may be changed without departing from the spirit of the invention.

[1561] The above description and illustrations are detailed descriptions 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, function, action, and effect is an example of the configuration, function, action, and effect 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 description and illustrations, within the scope of the gist of the technology of the present disclosure. In addition, in order to avoid confusion and to facilitate understanding of the parts related to the technology of the present disclosure, the above description and illustrations omit explanations of technical common sense that do not require explanation in order to enable the implementation of the technology of the present disclosure.

[1562] All publications, patent applications, and standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or standard was specifically and individually indicated to be incorporated by reference.

[1563] The following is further disclosed regarding the above embodiment.

[1564] (Claim 1) A system for suggesting learning materials or gadgets tailored to learning needs, comprising: A means for presetting a user's grade or school information; A means for acquiring learning difficulties or goals through dialogue with the user by utilizing a data generation model; A means for suggesting a product, which may be a textbook, a notebook, or an online course, according to the difficulty or goal of the study; A system including:

[1565] (Claim 2) The method further includes a means for collecting information regarding a life event before an exam or a report submission through a dialogue with the user by utilizing the data generation model; The system according to claim 1 , wherein the suggesting means suggests the product in accordance with a life event of the user.

[1566] (Claim 3) A means for carrying out purchase processing of the product selected by the user; means for notifying the user of the completion of the purchase; 3. The system of claim 1 or claim 2, further comprising:

[1567] (Claim 4) A means for analyzing the user's speech or facial expression to recognize the user's emotional state; means for customizing the product suggestions in response to the emotional state of the user; The system of claim 1 further comprising:

[1568] (Claim 5) A means for analyzing the user's speech or facial expression to recognize the user's emotional state; means for providing feedback or engagement to enhance motivation for learning in response to the emotional state of the user; The system of claim 1 further comprising:

[1569] (Claim 6) A means for analyzing the user's speech or facial expression to recognize the user's emotional state; means for tracking changes in the user's emotional state and providing support or rewards according to the user's learning progress or achievements; The system of claim 1 further comprising:

[1570] "Example 1"

[1571] (Claim 1) A means for presetting a user's grade or school information; A means for acquiring learning difficulties or goals through dialogue with the user using a generative AI model; A means for suggesting a product, which may be a textbook, a notebook, or an online course, depending on the difficulty or goal of the study; A means for collecting information regarding a life event of a user, such as before an exam or before submitting a report; A means for proposing products in accordance with the life events; A means for carrying out purchase processing of the product selected by the user; means for notifying the user of the completion of the purchase; A system including:

[1572] (Claim 2) The system of claim 1, further comprising a means for collecting information regarding a life event before an exam or before a report is submitted through dialogue with the user using a generative AI model, wherein the suggesting means suggests the product in accordance with the user's life event.

[1573] (Claim 3) 2. The system according to claim 1, further comprising: means for carrying out a purchase process for the product selected by the user; and means for notifying the user of completion of the purchase.

[1574] "Application example 1"

[1575] (Claim 1) A means for presetting a user's grade or school information; A means for acquiring learning difficulties or goals through dialogue with the user using a generative AI model; A means for suggesting a product, which may be a textbook, a notebook, or an online course, depending on the difficulty or goal of the study; A means of collecting information about the user's life events (e.g. before an exam, before submitting a report) and suggesting timely products; A means for carrying out a purchase process for the product selected by the user and notifying the user of the completion of the purchase; A means for generating prompt sentences to engage in dialogue using a generative AI model; A system including:

[1576] (Claim 2) 2. The system of claim 1, further comprising: a generative AI model for collecting information about the user's life events through interaction with the user.

[1577] (Claim 3) 2. The system according to claim 1, further comprising: means for carrying out a purchase process for the product selected by the user and notifying the user of completion of the purchase.

[1578] "Example 2 of combining emotion engines"

[1579] (Claim 1) A means for presetting a user's grade or school information; A means for acquiring learning difficulties or goals through dialogue with the user using a generative AI model; A means for suggesting products, which are educational materials or online courses, according to the learning difficulties or goals; a combination of an emotion engine for analyzing the emotional state of the user; means for customizing the suggesting means in response to an emotional state of the user; A system including:

[1580] (Claim 2) Further comprising a means for collecting information regarding life events through interaction with the user using a generative AI model. The system according to claim 1 , wherein the suggesting means suggests the product in accordance with a life event of the user.

[1581] (Claim 3) A means for carrying out purchase processing of the product selected by the user; means for notifying the user of the completion of the purchase; 3. The system of claim 1 or claim 2, further comprising:

[1582] "Application example 2 when combining emotion engines"

[1583] (Claim 1) A means for presetting a user's grade or school information; A means for acquiring learning difficulties or goals through dialogue with the user by utilizing a data generation model; A means for suggesting a product, which may be a textbook, a notebook, or an online course, depending on the difficulty or goal of the study; means for analyzing the emotional state of the user using an emotion analysis engine; A means for suggesting learning support and relaxation methods according to the emotional state of the user; A system including:

[1584] (Claim 2) The method further includes a means for collecting information regarding a life event before an exam or a report submission through a dialogue with the user using a data generation model; The system according to claim 1 , wherein the suggesting means suggests the product in accordance with a life event of the user.

[1585] (Claim 3) A means for carrying out purchase processing of the product selected by the user; means for notifying the user of the completion of the purchase; The system of claim 1 further comprising: [Explanation of symbols]

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Claims

1. A means for presetting a user's grade or school information; A means for using a generative AI to have a dialogue with the user and acquiring learning difficulties or goals through the dialogue with the user; A means for collecting information regarding a life event before an exam or before a report is submitted through a dialogue with the user; a prompt for suggesting a product, such as a textbook, a notebook, or an online course, based on the learning difficulty or goal and the information about the life event, and using the generative AI to suggest the product to the user; A system including:

2. means for analyzing the emotional state of the user using an emotion analysis engine; The system of claim 1, further comprising: a prompt sentence instructing the user to suggest learning support or relaxation methods based on the user's emotional state; and a means for using the generative AI to suggest the learning support or relaxation methods to the user.

3. means for accepting the proposed selection of the product; A means for carrying out purchase processing of the product selected by the user; 2. The system of claim 1, further comprising: means for notifying the user of a completed purchase.

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