System

Abstract

A system is provided.SOLUTION: A system, comprising: means for communicating with a database that manages user progress information; means for generating and providing learning content to a user; means for receiving and storing quiz results in the database; and means for automatically preparing the next learning content.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Low financial literacy among young people has a negative impact on personal financial stability and the socio-economy. Specifically, a lack of financial literacy leads to a lack of savings and investment, unregulated consumption and investment choices, stagnant corporate and economic development, reduced transparency in the financial industry, and instability in welfare and society. The purpose of this invention is to solve these problems and improve financial literacy among young people. [Means for solving the problem]

[0005] The present invention solves the above problems by providing a system including the following means.

[0006] The present invention provides a microlearning financial app including means for communicating with a database that manages user progress information, means for generating learning content and providing it to users, means for receiving quiz results and saving them in a database, and means for automatically preparing the next learning content. The present invention also provides an AI-guided virtual stock trading game app including means for updating virtual market data, managing users' trading histories and providing advice, receiving trading instructions and updating the database, and displaying updated data to users. The present invention also provides a community platform for improving financial literacy including means for managing user posts and questions, managing answers from other users and experts, scoring contributions and awarding points, and displaying points and rankings to users.

[0007] "User progress information" is data that records the progress and results of a user's activities such as learning and trading.

[0008] A "database" is a system that systematically stores and manages data such as user progress information, learning content, trading history, posts, questions, and points.

[0009] "Means of communication" refers to the technical means for sending and receiving data between a terminal and a server, and specifically includes internet connections and APIs.

[0010] "Learning content" refers to a collection of information provided to users to help them acquire financial knowledge, and may include text, videos, quizzes, etc.

[0011] "Quiz results" refers to data on answers to quizzes administered by users to evaluate their learning content, and the results of the evaluation.

[0012] "Virtual market data" refers to data necessary for simulating stock trading, such as price information and stock information for a virtually set up market.

[0013] "Trade history" is a record of the buying and selling that a user has done in virtual stock trading, and includes information such as the name, quantity, price, date and time.

[0014] "Advice" means guidelines or recommendations provided to help users learn or trade more effectively.

[0015] A "trade instruction" is an instruction for an operation or selection that a user makes when buying or selling a specific stock in virtual stock trading.

[0016] "Means of updating" are technical means of changing or adding records in the database based on new information.

[0017] "Posts and Questions" means information or questions shared by users on the community platform, including forum posts and Q&A style questions.

[0018] "Contribution" is a criterion for evaluating how much a user has contributed to community activities, and takes into account factors such as the quality and frequency of posts.

[0019] "Points" are a numerical representation of a user's contribution, and are rewards awarded according to activities within the community.

[0020] "Ranking" is a ranking based on a user's level of contribution and earned points, and allows comparison with other users. [Brief explanation of the drawings]

[0021] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0022] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0024] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0025] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0026] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0027] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0028] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0029] [First embodiment]

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

[0031] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0032] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0033] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0034] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0035] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0036] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0038] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0039] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0040] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0041] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0042] The present invention is a comprehensive system for improving financial literacy among young people. The system includes three main components: a micro-learning financial app, an AI-guided virtual stock trading game app, and a financial literacy community platform.

[0043] Microlearning Financial App

[0044] System Overview:

[0045] The purpose of microlearning financial apps is to enable users to learn financial knowledge in a short amount of time every day. Users access content delivered from a server using devices such as smartphones and tablets.

[0046] Process flow:

[0047] The device connects to the server using the user ID and requests the latest learning progress data. The server retrieves the user's progress information from the database and sends it to the device.

[0048] The terminal displays the next lesson content to the user based on the data received from the server. The user watches the lesson provided on the screen and progresses with their learning.

[0049] After completing a lesson, the user answers a quiz. The device sends the quiz results to the server, which stores them in a database. The next lesson is then automatically prepared.

[0050] Examples:

[0051] If a user wants to learn about "How Credit Cards Work," they can watch a three-minute lesson on their device, take a quiz, and then the results of the quiz will be sent to the server, which will then automatically prepare the next lesson on "Loans and Interest Rates."

[0052] AI-guided virtual stock trading game app

[0053] System Overview:

[0054] The app aims to enable users to gain practical financial knowledge through virtual stock trading experiences. An AI guide provides users with trading advice, allowing them to acquire trading skills without any risk.

[0055] Process flow:

[0056] The terminal connects to the server using the user ID and requests the latest portfolio data and market data. The server retrieves the user's portfolio data and market data from the database and sends them to the terminal.

[0057] The terminal receives market data and AI advice from the server and displays it to the user, who then uses the advice to buy or sell virtual stocks.

[0058] Trade instructions are sent to the server, trade results are recorded in a database, and updated portfolio data is sent to the terminal and displayed to the user.

[0059] Examples:

[0060] If a user decides to buy TechCorp stock, the AI ​​guide will advise them that "TechCorp stock is on an upward trend, so we recommend buying it." Once the user decides to buy and executes the trade, the results are sent to the server and recorded in the database. The portfolio after the trade is displayed on the terminal.

[0061] A community platform for improving financial literacy

[0062] System Overview:

[0063] The community platform allows users to share their knowledge and interact with other users and experts, and includes features such as forums, Q&A sections, and online workshops.

[0064] Process flow:

[0065] The device accesses the server using the user ID and requests the latest forum posts and Q&A data. The server retrieves the necessary data from the database and sends it to the device.

[0066] The device displays the latest community content to the user based on the data received from the server. The user posts on forums or asks questions and waits for answers from other users or experts.

[0067] Posts and replies are sent to the server and recorded in a database. The server evaluates the quality of the post and reply and awards points to the user. The terminal displays the user's points and ranking.

[0068] Examples:

[0069] When a user posts a question such as "I want to know about the risks of stock investment," other users and experts will provide answers. Users who post high-quality answers will be awarded points by the server, and their rankings will be updated.

[0070] These system features allow users to effectively learn, practice, and share financial knowledge with other users.

[0071] The processing flow will be explained below.

[0072] Microlearning Financial App

[0073] Processing Steps

[0074] Step 1:

[0075] The device connects to the server using the user ID and requests the user's latest learning progress data.

[0076] Step 2:

[0077] The server searches the database based on the received user ID and obtains the user's latest learning progress information.

[0078] Step 3:

[0079] The server transmits the acquired learning progress data to the terminal.

[0080] Step 4:

[0081] The terminal displays the next lesson content to the user based on the data received from the server.

[0082] Step 5:

[0083] The user watches and listens to the lessons displayed on the screen and progresses through the learning process.

[0084] Step 6:

[0085] The terminal displays a quiz to the user after the lesson is completed.

[0086] Step 7:

[0087] The user answers the quiz and inputs the answer into the terminal.

[0088] Step 8:

[0089] The terminal transmits the answer to the quiz to the server.

[0090] Step 9:

[0091] The server stores the quiz results in a database and automatically prepares the next learning content.

[0092] AI-guided virtual stock trading game app

[0093] Processing Steps

[0094] Step 1:

[0095] The terminal connects to the server using the user ID and requests the latest portfolio and market data.

[0096] Step 2:

[0097] The server retrieves the user's portfolio data and the latest market data from the database.

[0098] Step 3:

[0099] The server transmits the acquired data to the terminal.

[0100] Step 4:

[0101] The terminal displays market data received from the server and AI trading advice to the user.

[0102] Step 5:

[0103] Users can choose to follow AI advice or make their own trading decisions.

[0104] Step 6:

[0105] A user executes a trade by specifying the stock to be purchased or sold and the quantity.

[0106] Step 7:

[0107] The terminal transmits the user's trade instructions to the server.

[0108] Step 8:

[0109] The server processes the trade instructions to update the virtual market database and update the user's portfolio.

[0110] Step 9:

[0111] The server returns the updated portfolio data to the terminal.

[0112] Step 10:

[0113] The terminal displays the updated portfolio data to the user, allowing the user to confirm the trading results.

[0114] A community platform for improving financial literacy

[0115] Processing Steps

[0116] Step 1:

[0117] The device connects to the server using the user ID and requests the latest forum posts and Q&A data.

[0118] Step 2:

[0119] The server retrieves forum posts and Q&A data from a database.

[0120] Step 3:

[0121] The server transmits the acquired data to the terminal.

[0122] Step 4:

[0123] The terminal displays the latest community content to the user based on the data received from the server.

[0124] Step 5:

[0125] Users review forum posts and questions and make comments and replies as needed.

[0126] Step 6:

[0127] Users create new posts and questions in the community forums.

[0128] Step 7:

[0129] The terminal transmits user posts and questions to the server.

[0130] Step 8:

[0131] The server stores the received posts and questions in a database.

[0132] Step 9:

[0133] The server notifies other users of new posts and questions and shares them with the entire community.

[0134] Step 10:

[0135] The server scores the contribution of posts and replies and awards points to users.

[0136] Step 11:

[0137] The server updates the total points and ranking and sends them to the terminal.

[0138] Step 12:

[0139] The terminal displays the updated points and ranking to the user, allowing them to see their contribution to the community.

[0140] The above are the specific program processing steps in each system. We have explained in detail what operations the server, terminal, and user perform in each step.

[0141] Example 1

[0142] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0143] Traditional financial literacy education systems have struggled to provide personalized learning experiences based on users' progress. Virtual stock trading and community platforms also lack the appropriate advice and feedback to maximize users' learning outcomes. Furthermore, effective communication methods for sharing learned knowledge are often lacking.

[0144] 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.

[0145] In this invention, the server includes: means for communicating with a database that manages user progress information; means for generating learning content and providing it to the user; means for receiving quiz results and saving them in the database; means for automatically preparing the next learning content; means for customizing the next lesson content based on the user's individual learning history; and means for connecting to the server from a device such as a smartphone or tablet and requesting progress information. This allows users to efficiently take learning content that is tailored to their individual needs, improving learning effectiveness. The server also includes means for updating virtual market data, means for managing the user's trading history and providing advice, means for receiving trading instructions and updating the database, means for displaying the updated data to the user, means for displaying the latest market data and advice from the AI ​​guide to the user, and means for recording the user's virtual trading results in the database, allowing users to acquire practical trading skills without risk. Furthermore, the server includes means for managing user posts and questions, means for managing answers from other users and experts, means for scoring contributions and awarding points, means for displaying the points and rankings to users, means for requesting forum posts and Q&A data to display the latest community content, and means for evaluating the quality of posts and answers and awarding points, thereby promoting knowledge sharing and interaction among users and increasing motivation to learn and a sense of accomplishment.

[0146] A "database for managing user progress information" is a data storage system that stores information for recording and managing what a user has learned and their progress.

[0147] A "means for generating and providing learning content to users" is a system or method for creating new educational material based on the user's needs and learning history and delivering it to the user in an accessible format.

[0148] "Means for receiving quiz results and storing them in a database" refers to a system or method by which the server receives the results of the quiz answered by the user after studying and records them in a management database.

[0149] "Means for automatically preparing the next learning content" refers to a system or method that automatically selects and prepares the next learning content based on the user's learning progress and quiz results.

[0150] "Means for customizing the next lesson content based on the user's individual learning history" refers to a system or method that analyzes each user's past learning data and provides the most appropriate learning content individually based on that data.

[0151] "Means for connecting to a server from a terminal such as a smartphone or tablet and requesting progress information" refers to a system or method for connecting to a server using a mobile device and obtaining learning progress information from there.

[0152] A "means for updating virtual market data" is a system or method for periodically updating data to keep virtual financial market information current.

[0153] A "means for managing a user's trading history and providing advice" is a system or method for recording a user's virtual trading activity and providing advice on financial trading based thereon.

[0154] The "means for receiving trade instructions and updating the database" refers to a system or method for receiving information when a user issues a virtual trade instruction and updating the database.

[0155] The "means for displaying updated data to the user" refers to a system or method for displaying the latest virtual market information, the user's trading results, etc. on the user's device screen.

[0156] "Means for displaying the latest market data and advice from an AI guide to users" refers to a system or method that obtains the latest market information and provides users with AI-generated financial advice based on that information.

[0157] The "means for recording the results of a user's virtual trade in a database" refers to a system or method for storing the results of a virtual trade executed by a user in a database.

[0158] "Means for managing user posts and questions" refers to a system or method for processing and appropriately managing information and questions posted by users on the community platform.

[0159] "Means for managing responses from other users and experts" refers to a system or method for receiving and managing responses from other users and experts on the community platform.

[0160] "Means for scoring contributions and awarding points" refers to a system or method for evaluating the quality of users' posts and replies and awarding points accordingly.

[0161] The "means for displaying points and rankings to the user" refers to a system or method for visualizing the points and rankings earned by the user and displaying them on the user's device.

[0162] A "means for requesting forum posts and Q&A data to display the most recent community content" is a system or method that automatically retrieves the most recent posts to a forum or Q&A section and displays them to the user.

[0163] The "means for evaluating the quality of posts and replies and awarding points" refers to a system or method for evaluating the content of posts and replies made by users and awarding points according to their contribution.

[0164] MODE FOR CARRYING OUT THE INVENTION

[0165] The present invention is a comprehensive system for improving financial literacy among young people. The system includes three main components: a micro-learning financial app, an AI-guided virtual stock trading game app, and a financial literacy community platform.

[0166] Microlearning Financial App

[0167] System Overview:

[0168] The purpose of microlearning financial apps is to enable users to learn financial knowledge in a short amount of time every day. Users access content delivered from a server using devices such as smartphones and tablets.

[0169] Hardware and software used:

[0170] Mobile devices such as smartphones and tablets

[0171] Server (progress database, content distribution system)

[0172] Internet Connectivity Infrastructure

[0173] Specific data processing and calculation:

[0174] When a user launches the app, the server retrieves the user's learning progress information from the progress database and sends it to the device. The device uses this data to display the next lesson content to the user. When the user completes their learning and answers a quiz, the results are sent to the server and stored in the database. The server automatically selects and prepares the next learning content based on the user's progress.

[0175] Examples:

[0176] When a user learns about "How Credit Cards Work," the device retrieves the relevant lesson video from the server and displays it. After the lesson, the user answers a quiz, and the results are sent to the server, which then prepares the next lesson on "Loans and Interest Rates."

[0177] Example prompt sentence:

[0178] Please state the conditions for selecting the content of your next lesson.

[0179] AI-guided virtual stock trading game app

[0180] System Overview:

[0181] The app aims to enable users to gain practical financial knowledge through virtual stock trading experiences. An AI guide provides users with trading advice, allowing them to acquire trading skills without any risk.

[0182] Hardware and software used:

[0183] Mobile devices such as smartphones and tablets

[0184] Server (portfolio database, AI guide system, market database)

[0185] Internet Connectivity Infrastructure

[0186] Specific data processing and calculation:

[0187] When a user logs in, the terminal connects to the server using the user ID and retrieves the latest portfolio and market data. The server then retrieves this data from the database and displays it to the user. An AI guide also provides advice based on market data, and the user purchases or sells virtual stocks. After the trade is executed, the results are sent to the server and recorded in the database.

[0188] Examples:

[0189] If a user were to hypothetically buy TechCorp shares, the terminal would retrieve market data and AI-guided advice from the server and display it. Once the user decides to buy and executes the trade, the information is sent to the server for recording, and the new portfolio is displayed on the terminal.

[0190] Example prompt sentence:

[0191] "Please explain the circumstances under which you would recommend buying or selling TechCorp stock."

[0192] A community platform for improving financial literacy

[0193] System Overview:

[0194] The platform allows users to share their knowledge and interact with other users and experts, and includes features such as forums, Q&A sections, and online workshops.

[0195] Hardware and software used:

[0196] Devices such as smartphones, tablets, and PCs

[0197] Server (community database, posting management system)

[0198] Internet Connectivity Infrastructure

[0199] Specific data processing and calculation:

[0200] The device connects to the server using the user ID to retrieve the latest forum posts and Q&A data. The server retrieves this data from the database and sends it to the device. Users can post to the forum or ask questions and wait for answers from other users or experts. The posts and answers are sent to the server and recorded in the database. The server then evaluates the quality of these posts and answers and assigns points. The device then displays the points and rankings to the user.

[0201] Examples:

[0202] When a user posts a question about the risks of stock investment on the community platform, other users and experts respond. The server records the responses, evaluates the quality of the responses, and awards points. The terminal then displays the points and rankings to the user.

[0203] Example prompt sentence:

[0204] "Create the best answer to the question about the risks of stock investment."

[0205] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0206] Microlearning Financial App

[0207] Processing flow

[0208] Step 1:

[0209] Server connection by user ID

[0210] When a user launches the app, the device connects to the server using the user ID stored in the device.

[0211] Input: User ID

[0212] Data processing: The server receives the user ID and sends a query to the database to retrieve the learning progress data of the user.

[0213] Output: User's learning progress data

[0214] Specific operation: The server retrieves the user's progress information from the database and sends it to the device.

[0215] Step 2:

[0216] View lesson content

[0217] The terminal displays the next lesson content to the user based on the received learning progress data.

[0218] Input: Learning progress data received from the server

[0219] Data processing: The device analyzes the progress data and determines the next lesson content to display.

[0220] Output: Lesson content (e.g. video, text)

[0221] Specific operation: The device displays the next lesson content on the screen and the user begins learning.

[0222] Step 3:

[0223] Quiz Answers and Results Submission

[0224] The user answers a quiz that is displayed after the lesson is completed.

[0225] Input: User's quiz answer

[0226] Data processing: The terminal receives the user's answers and sends the results to the server.

[0227] Output: Quiz results

[0228] Specific operation: The device sends the quiz results to the server, which stores them in a database.

[0229] AI-guided virtual stock trading game app

[0230] Processing flow

[0231] Step 1:

[0232] Portfolio and Market Data Requests

[0233] When a user logs in, the terminal connects to the server using the user ID and requests the latest portfolio and market data.

[0234] Input: User ID

[0235] Data processing: The server retrieves portfolio data and market data from the database based on the user ID.

[0236] Output: Portfolio data, latest market data

[0237] Specific operation: The server sends the data retrieved from the database to the terminal.

[0238] Step 2:

[0239] Display market data and AI advice

[0240] The terminal displays the received market data and advice from the AI ​​guide to the user.

[0241] Inputs: Portfolio data, latest market data, AI advice

[0242] Data processing: The terminal analyzes the received market data and AI advice and presents appropriate information to the user.

[0243] Output: Market status and trading advice

[0244] Specific operation: The device displays market conditions and AI-guided advice to the user.

[0245] Step 3:

[0246] Trading instructions and results recording

[0247] A user trades (buys or sells) virtual stocks.

[0248] Input: User's trading instructions

[0249] Data processing: The terminal sends trade instructions to the server, which records the information in a database.

[0250] Output: Updated portfolio data

[0251] Specific operation: After the results of the trade are recorded in the database, the updated portfolio data is sent to the terminal.

[0252] A community platform for improving financial literacy

[0253] Processing flow

[0254] Step 1:

[0255] Requesting forum posts and Q&A data

[0256] The device accesses the server using the user ID and requests the latest forum posts and Q&A data.

[0257] Input: User ID

[0258] Data processing: The server retrieves the latest forum posts and Q&A data from the database based on the user ID.

[0259] Output: Forum post data, Q&A data

[0260] Specific operation: The server sends the acquired data to the terminal.

[0261] Step 2:

[0262] View community content and user activity

[0263] The terminal displays the latest community content to the user based on the received data.

[0264] Input: Forum post data, Q&A data

[0265] Data processing: The device analyzes the received data and selects and displays the latest content.

[0266] Output: Forum content, Q&A content to be displayed

[0267] What it does: The device displays recent posts and questions and answers on the screen, and users post and ask questions in the forum.

[0268] Step 3:

[0269] Recording and rating posts and responses

[0270] When a post or question is made, the device sends the content to the server.

[0271] Input: New post data, question and answer data

[0272] Data processing: The server records the received data in a database and evaluates its quality.

[0273] Output: Updated forum data, quality evaluation results, point data

[0274] Specific operation: The server stores posts and answers in a database and assigns points based on quality. The terminal displays the points and ranking to the user.

[0275] (Application example 1)

[0276] 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."

[0277] In recent years, low financial literacy among young people has become a problem. In particular, purchasing behavior on online shopping sites tends to be impulsive, leading to a lack of budget management. In such circumstances, young people find it difficult to make financial forecasts and are prone to long-term financial risk. Therefore, a system is needed to improve financial literacy in real time through online shopping site purchasing behavior, and to provide appropriate purchasing advice and budget management.

[0278] 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.

[0279] In this invention, the server includes means for communicating with a database that manages user progress information, means for generating study content and providing it to the user, means for receiving quiz results and saving them in the database, means for automatically preparing the next study content, means for receiving the user's purchasing data and providing purchasing advice within a budget, and means for updating post-purchase budget data and saving it in the database. This allows users to manage their budget while receiving appropriate financial advice in real time through their purchasing behavior on the online shopping site.

[0280] "User progress information" refers to the status and history achieved by the user in processes such as learning and purchasing.

[0281] A "database" is a system for managing information efficiently and consistently, storing, retrieving, and updating data.

[0282] "Learning Content" refers to educational materials and teaching materials provided to users to improve their financial literacy.

[0283] "Quiz results" refers to information on the results of a user's answers to a quiz-style test.

[0284] "Next learning content" refers to the next step of education provided based on the user's current learning situation and progress.

[0285] "User purchase data" refers to information about purchases made by a user on an online shopping site, such as the product name, purchase price, and purchase date and time.

[0286] "Buying advice within a budget" refers to recommendations and suggestions regarding what purchasing behavior a user should take within their budget.

[0287] "Post-purchase budget data" refers to information regarding the remaining budget after a user has completed a particular purchase.

[0288] "Virtual market data" refers to data of a virtual investment environment that simulates actual market data.

[0289] "User's trading history" refers to a record of transactions that a User has made in the virtual or real markets.

[0290] "Trade Instructions" refers to specific commands given by a user to buy or sell stocks or other financial instruments.

[0291] "User posts and questions" refers to information shared or questions expressed by users on the community platform.

[0292] "Responses from other users and experts" refers to information and advice provided in response to a user's post on the community platform.

[0293] "Scoring contribution" refers to users rating their activities on the community platform.

[0294] "Awarding points" refers to giving points as a reward for a user's community activities.

[0295] "Points and ranking" refers to the numerical value of the user's activity evaluation and the user's ranking generated based on that numerical value.

[0296] This invention is a comprehensive system for improving users' financial literacy, and is composed of the following major components:

[0297] System configuration

[0298] The system consists of the following main components:

[0299] 1. A database that manages user progress information:

[0300] The server maintains a database that centrally manages user progress information, including the user's learning activities, quiz results, purchase history, and budget information, and updates the database as needed.

[0301] 2. Learning content generation and delivery:

[0302] The server generates financial education learning content to be provided to users and provides it to devices such as smartphones and tablets. The learning content is personalized based on the user's progress.

[0303] 3. Receiving and storing quiz results:

[0304] The server receives the results of the user's answers to the quiz accompanying the learning content, stores them in a database, and automatically prepares the next learning content based on this data.

[0305] 4. Receiving purchasing data and providing budget advice:

[0306] When a user purchases a product on an online shopping site, the server receives the purchase data (product name, price, date and time, etc.) and provides appropriate purchasing advice within the user's budget based on this purchase data and the user's budget information.

[0307] 5. Update budget data after purchase:

[0308] After the purchase, the server updates the user's budget data and stores it in the database, realizing real-time budget management.

[0309] 6. Virtual Market Data and Trade History Management:

[0310] The server manages data on users' transactions in the virtual market and provides trading advice based on this data, allowing users to experience stock trading risk-free and gain practical financial knowledge.

[0311] 7. Maintaining the Community Platform:

[0312] The server manages user posts and questions, as well as answers from other users and experts. It scores the contribution of posts and answers, awards points, and displays them to users.

[0313] Hardware and Software Details

[0314] Hardware: smartphones, tablets, servers

[0315] Software: Flask (Python web framework), SQLite (database management)

[0316] Specific examples

[0317] For example, consider a situation where a user is trying to purchase a pair of sneakers for 10,000 yen on an online shopping site. In this case, the server first retrieves the user's budget information from the database and evaluates in real time whether the purchase is within budget. If the purchase is within budget, the server provides advice recommending the purchase and updates the budget data after the purchase. This series of steps allows the user to manage their budget in real time.

[0318] Prompt Sentence Examples

[0319] Build a smartphone app that manages a user's budget when purchasing certain items. When a user attempts to purchase an item, the app will receive the user ID and the item's price as input. It will then retrieve the user's remaining budget from the database and check whether the purchase is within the budget. The budget will also be updated after the purchase and the user will be notified. Please also provide an example program using Flask and SQLite.

[0320] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0321] Step 1:

[0322] The server receives a product purchase request from the user. The user ID and product price information are provided as input. Based on this, the server processes the data to retrieve the user's current budget information from the database. The output is the retrieved user's budget information.

[0323] Step 2:

[0324] The server compares the acquired budget information with the product price and performs data calculations to determine whether the purchase is possible within the budget. Specifically, the server subtracts the product price from the user's remaining budget, and if the result is 0 or greater, it recommends the purchase, and if it is less than 0, it notifies the user that the budget is exceeded. The input is the user's budget information and product price, and the output is advice information such as "purchase possible" or "over budget."

[0325] Step 3:

[0326] The terminal receives advice information from the server and displays it to the user, allowing the user to decide whether to proceed with the purchase. Specifically, the terminal displays the received advice on the screen and waits for the user's next action. The input is advice information from the server, and the output is the screen display.

[0327] Step 4:

[0328] When the user decides to make a purchase, the device sends that decision to the server. The server receives this information and performs data calculations to update the user's budget information. Specifically, the server subtracts the product price from the user's remaining budget and saves the updated budget data in the database. The input is the user's purchase intention and product price, and the output is the updated user's budget data.

[0329] Step 5:

[0330] The server sends confirmation of the purchase completion to the terminal. The terminal receives this information and notifies the user that the purchase is complete. Specifically, the terminal displays a "Purchase Complete" message on the screen and notifies the user that the budget has been updated. The input is the purchase completion notification from the server, and the output is the screen display.

[0331] Through these steps, users can receive budget management and financial advice in real time through their purchasing behavior on the online shopping site.

[0332] When generating a description using keywords from a generative AI model, the following prompts can be used:

[0333] "Build a smartphone app that manages a user's budget when purchasing certain products. When a user tries to purchase an item, the app will receive the user ID and the product price as input. It will then retrieve the user's remaining budget from a database and check whether the purchase is within the budget. The budget will also be updated after the purchase and the user will be notified. Please also provide an example program using Flask and SQLite."

[0334] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0335] This invention combines a comprehensive system for improving young people's financial literacy with an emotion engine that recognizes user emotions. The system includes three main components: a microlearning financial app, an AI-guided virtual stock trading game app, and a financial literacy improvement community platform. Furthermore, the emotion engine recognizes users' emotions and optimizes the learning experience based on their emotions.

[0336] Microlearning Financial App

[0337] System Overview:

[0338] The purpose of microlearning financial apps is to enable users to learn financial knowledge in a short amount of time every day. Users access content delivered from a server using devices such as smartphones and tablets. An emotion engine also recognizes the user's emotions and personalizes the learning experience.

[0339] Process flow:

[0340] The device connects to the server using the user ID and requests the latest learning progress data. The server retrieves the user's progress information from the database and sends it to the device.

[0341] The device displays the next lesson content to the user based on the data received from the server. The user continues learning by watching the lesson provided on the screen while their emotions are recognized in real time by the emotion engine.

[0342] The learning content is adapted based on the user's emotions: for example, if the user is feeling tired, the content is simplified, and if the user is perceived as easily distracted, the interactive elements are increased.

[0343] After completing the lesson, the user answers a quiz. The device sends the quiz results and emotion data to the server, which stores them in a database. The next lesson is then automatically prepared.

[0344] Examples:

[0345] For example, if a user wants to learn about "How Credit Cards Work," they watch a three-minute lesson displayed on their device and answer a quiz. The emotion engine assesses in real time whether the user is enjoying the lesson and deepening their understanding, and automatically prepares the next lesson on "Loans and Interest Rates" at the appropriate difficulty level.

[0346] AI-guided virtual stock trading game app

[0347] System Overview:

[0348] The app aims to enable users to gain practical financial knowledge through virtual stock trading experiences. An AI guide provides trading advice, and an emotion engine recognizes users' emotions and provides appropriate feedback.

[0349] Process flow:

[0350] The terminal connects to the server using the user ID and requests the latest portfolio data and market data. The server retrieves the user's portfolio data and market data from the database and sends them to the terminal.

[0351] The terminal receives market data and AI advice from the server and displays it to the user. The user then buys or sells virtual stocks based on the advice, which is based on sentiment analysis by the emotion engine.

[0352] The advice is tailored depending on the user's emotions: for example, if the user is feeling anxious, low-risk, conservative advice is offered.

[0353] Trade instructions are sent to the server, trade results are recorded in a database, and updated portfolio data is sent to the terminal and displayed to the user.

[0354] Examples:

[0355] If a user decides to buy TechCorp stock, the AI ​​guide will advise them that "TechCorp stock is on an upward trend, so we recommend buying." If the user feels unsure, the emotion engine will provide supplemental information to reduce the risk. Once the user decides to purchase and executes the trade, the results are sent to the server and recorded in the database. The portfolio after the trade is displayed on the terminal.

[0356] A community platform for improving financial literacy

[0357] System Overview:

[0358] The community platform provides a forum for users to share their knowledge and interact with other users and experts. It features forums, Q&A sections, online workshops, and an emotion engine that recognizes users' emotions to optimize communication.

[0359] Process flow:

[0360] The device accesses the server using the user ID and requests the latest forum posts and Q&A data. The server retrieves the necessary data from the database and sends it to the device.

[0361] The device displays the latest community content to the user based on the data received from the server. The user can post forums or ask questions, and wait for answers from other users and experts, while the emotion engine recognizes emotions in real time.

[0362] The community's scoring is adjusted based on the user's sentiment: for example, if a user feels satisfied, they will provide high-quality answers and receive more points.

[0363] Posts and answers are sent to the server and recorded in a database. The server evaluates the quality of the post and answer and awards points to the user. Updated points and rankings are sent to the device.

[0364] Examples:

[0365] When a user posts a question such as "I want to know about the risks of stock investment," other users and experts provide answers. The emotion engine analyzes the user's emotions, and if there is a lot of positive feedback, the server increases the points. The ranking is updated and displayed on the device.

[0366] These system features allow users to effectively learn, practice, and share financial knowledge with others. The incorporation of an emotion engine further enhances learning and trading experiences by optimizing according to users' emotions.

[0367] The processing flow will be explained below.

[0368] Microlearning Financial App

[0369] Processing Steps

[0370] Step 1:

[0371] The device connects to the server using the user ID and requests the user's latest learning progress data.

[0372] Step 2:

[0373] The server searches the database based on the received user ID and obtains the user's latest learning progress information.

[0374] Step 3:

[0375] The server transmits the acquired learning progress data to the terminal.

[0376] Step 4:

[0377] The terminal displays the next lesson content to the user based on the data received from the server.

[0378] Step 5:

[0379] The user watches and learns lessons presented on the screen.

[0380] Step 6:

[0381] The emotion engine analyzes the user's facial expressions and voice in real time to obtain emotional data.

[0382] Step 7:

[0383] The terminal adjusts the learning content based on the emotion data acquired by the emotion engine.

[0384] Step 8:

[0385] After the lesson is completed, the terminal displays a quiz to the user.

[0386] Step 9:

[0387] The user answers the quiz and inputs the answer into the terminal.

[0388] Step 10:

[0389] The terminal transmits the quiz answer results and emotion data to the server.

[0390] Step 11:

[0391] The server stores the quiz results and emotional data in a database and automatically prepares the next learning content.

[0392] AI-guided virtual stock trading game app

[0393] Processing Steps

[0394] Step 1:

[0395] The terminal connects to the server using the user ID and requests the latest portfolio and market data.

[0396] Step 2:

[0397] The server retrieves the user's portfolio data and the latest market data from the database.

[0398] Step 3:

[0399] The server transmits the acquired data to the terminal.

[0400] Step 4:

[0401] The terminal displays market data received from the server and AI trading advice to the user.

[0402] Step 5:

[0403] The emotion engine analyzes the user's facial expressions and voice in real time to obtain emotional data.

[0404] Step 6:

[0405] The device will then adjust the advice provided by the AI ​​guide based on the emotional data.

[0406] Step 7:

[0407] Users can choose to follow AI advice or make their own trading decisions.

[0408] Step 8:

[0409] A user executes a trade by specifying the stock to be purchased or sold and the quantity.

[0410] Step 9:

[0411] The terminal transmits the user's trade instructions to the server.

[0412] Step 10:

[0413] The server processes the trade instructions to update the virtual market database and update the user's portfolio.

[0414] Step 11:

[0415] The server returns the updated portfolio data to the terminal.

[0416] Step 12:

[0417] The terminal displays the updated portfolio data to the user, allowing the user to confirm the trading results.

[0418] A community platform for improving financial literacy

[0419] Processing Steps

[0420] Step 1:

[0421] The device connects to the server using the user ID and requests the latest forum posts and Q&A data.

[0422] Step 2:

[0423] The server retrieves forum posts and Q&A data from a database.

[0424] Step 3:

[0425] The server transmits the acquired data to the terminal.

[0426] Step 4:

[0427] The terminal displays the latest community content to the user based on the data received from the server.

[0428] Step 5:

[0429] Users review forum posts and questions and make comments and replies as needed.

[0430] Step 6:

[0431] The emotion engine analyzes the user's facial expressions and voice in real time to obtain emotional data.

[0432] Step 7:

[0433] The terminal adjusts the content of communication based on the emotion data acquired by the emotion engine.

[0434] Step 8:

[0435] Users create new posts and questions in the community forums.

[0436] Step 9:

[0437] The terminal sends user posts and questions to the server.

[0438] Step 10:

[0439] The server stores the received posts and questions in a database.

[0440] Step 11:

[0441] The server notifies other users of new posts and questions and shares them with the entire community.

[0442] Step 12:

[0443] The server scores contributions based on the quality of posts and responses and emotional data, and awards points to users.

[0444] Step 13:

[0445] The server sends the updated points and rankings to the terminal.

[0446] Step 14:

[0447] The terminal displays the updated points and ranking to the user, allowing them to see their contribution to the community.

[0448] The above are the specific program processing steps for each system that incorporates an emotion engine. In each step, the operations performed by the server, terminal, and user have been explained in detail.

[0449] Example 2

[0450] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0451] Conventional financial literacy improvement systems have difficulty responding to the emotional state of each user, and have not been able to fully optimize learning effects and trading experiences. Such systems are unable to personalize based on the user's interests, level of understanding, or emotional changes, making it difficult to maintain learning motivation or effectively convey financial knowledge.

[0452] 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.

[0453] In this invention, the server includes means for communicating with a database that manages user progress information, means for generating learning content and providing it to the user, means for recognizing the user's emotions in real time and using that data, means for receiving quiz results and emotional data and storing them in the database, and means for automatically adjusting and preparing the next learning content based on the user's emotional state, thereby providing an effective and individually optimized learning experience that reflects the user's emotional state.

[0454] "User progress information" refers to data that indicates the progress and achievement level of a user when using learning content.

[0455] "Means for communicating with a database" means means having communication capabilities for accessing a database and retrieving or storing information.

[0456] "Means for generating learning content and providing it to users" refers to means for creating educational content and distributing it to users.

[0457] "Means for recognizing user emotions in real time and using that data" refers to means for detecting user emotions in real time and using that information to personalize the learning experience.

[0458] The "means for receiving quiz results and emotion data and storing them in a database" refers to a means for receiving the user's quiz answer results and emotion data and storing them in a database.

[0459] "Means for automatically adjusting and preparing the next learning content based on the user's emotional state" refers to a means for dynamically adjusting learning content based on the user's emotional data and preparing the optimal next item.

[0460] "Means for updating virtual market data" refers to means for updating virtual market information with the latest data.

[0461] "Means for managing a user's trading history and providing advice" means means for recording and managing a user's trading history and providing trading advice to the user based on that history.

[0462] "Means for receiving trade instructions and updating the database" refers to means for receiving trading instructions from users and updating the database accordingly.

[0463] The "means for displaying updated data to the user" refers to a means for displaying the latest data updated by the server to the user.

[0464] "Means for managing user posts and questions" refers to means for recording and managing content and questions posted by users.

[0465] "Means for managing responses from other users and experts" refers to means for recording and managing responses from other users and experts.

[0466] The "means for scoring contributions and awarding points" refers to a means for evaluating a user's actions and contributions and awarding points.

[0467] The "means for displaying points and rankings to the user" refers to a means for displaying the evaluated points and user rankings in a form visible to the user.

[0468] This invention combines a comprehensive system for improving young people's financial literacy with an emotion engine that recognizes user emotions. The system includes three main components: a microlearning financial app, an AI-guided virtual stock trading game app, and a financial literacy improvement community platform. Furthermore, the emotion engine recognizes users' emotions and optimizes the learning experience based on their emotions.

[0469] Microlearning Financial App

[0470] The purpose of microlearning financial apps is to enable users to learn financial knowledge in a short amount of time every day. Users access content delivered from a server using devices such as smartphones and tablets. An emotion engine also recognizes the user's emotions and personalizes the learning experience.

[0471] The server connects to the database using the user's ID, retrieves the latest learning progress data, and sends it to the device. The device then displays the next lesson content to the user based on the received data. At this time, the emotion engine recognizes emotions from the user's facial expressions and voice in real time to optimize the learning experience.

[0472] As a specific example, if a user is learning about "how credit cards work," the emotion engine analyzes the user's reactions while watching a three-minute lesson displayed on the device. If the user feels tired, the next lesson will be simplified, and if the user's attention is distracted, the interactive elements will be increased. After completing the lesson, the user answers a quiz, and the quiz results and emotion data are sent to the server and stored in a database.

[0473] Example prompt sentence:

[0474] "Generate a three-minute lesson on how credit cards work and provide a quiz based on user sentiment."

[0475] AI-guided virtual stock trading game app

[0476] The app aims to enable users to gain practical financial knowledge through virtual stock trading experiences. An AI guide provides trading advice, and an emotion engine recognizes users' emotions and provides appropriate feedback.

[0477] The server uses the user ID to retrieve the user's portfolio data and market data from the database and transmits them to the terminal. The terminal displays the received market data and AI advice to the user. The emotion engine recognizes the user's emotions in real time and adjusts the content of the advice.

[0478] For example, when a user purchases a company's stock, the AI ​​guide will advise them that "this stock is on an upward trend, so we recommend purchasing it." If the user feels unsure, the emotion engine will provide supplemental information to reduce the risk. Once the user decides to purchase and executes the transaction, the result is sent to the server and recorded in the database.

[0479] Example prompt sentence:

[0480] "Provide TechCorp stock trading advice and generate feedback based on sentiment data."

[0481] A community platform for improving financial literacy

[0482] The community platform provides a forum for users to share their knowledge and interact with other users and experts. It features forums, Q&A sections, online workshops, and an emotion engine that recognizes users' emotions to optimize communication.

[0483] The server uses the user ID to retrieve the latest forum posts and Q&A data and transmits it to the device. The device displays community content based on the received data, and the emotion engine recognizes the user's emotions in real time.

[0484] For example, if a user posts a question such as "I want to know about the risks of stock investment," other users and experts will provide answers. The emotion engine analyzes the user's emotions, and if there is a lot of positive feedback, the server will award points to the user. The ranking is updated and displayed on the device.

[0485] Example prompt sentence:

[0486] "Generate answers to questions about the risk of stock investments and provide a points system based on sentiment data."

[0487] These system functions allow users to effectively learn, practice, and share financial knowledge with other users. The incorporation of an emotion engine provides optimal learning experiences and communication according to the user's emotions.

[0488] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0489] Microlearning financial app processing steps

[0490] Step 1: Obtaining user progress data

[0491] Input: User ID

[0492] Processing: The server receives the user ID sent from the terminal and retrieves the user's latest learning progress data from the database.

[0493] Output: Learning progress data (e.g. last lesson studied, progress)

[0494] Specific behavior:

[0495] The server queries the database to retrieve the user ID and associated progress data (e.g., last lesson ID, completion percentage).

[0496] Step 2: View learning content and start emotion recognition

[0497] Input: Learning progress data

[0498] Processing: The device determines the content of the next lesson based on the learning progress data received from the server, and activates the emotion engine to recognize the user's emotions in real time.

[0499] Output: Display of learning content, emotion data

[0500] Specific behavior:

[0501] The device uses the progress data to display the next lesson (e.g., a video about how credit cards work), and the emotion engine uses the camera to begin analyzing the user's facial expressions.

[0502] Step 3: Personalize content and display quizzes

[0503] Input: Emotion data, learning content

[0504] Processing: The device adjusts the next learning content based on the data obtained from the emotion engine in real time, and displays a quiz after the lesson is completed.

[0505] Output: Personalized learning content, quizzes

[0506] Specific behavior:

[0507] If the user feels tired, the device will simplify the content of the next lesson and automatically display a quiz after the lesson.

[0508] Step 4: Send quiz results and sentiment data

[0509] Input: Quiz results, emotion data

[0510] Processing: The device sends the user's quiz results and emotion data to the server.

[0511] Output: Data sent to the server

[0512] Specific behavior:

[0513] When the quiz is over, the device sends the user's answer data and emotion data obtained through facial recognition to the server.

[0514] Step 5: Update the database and prepare for the next lesson

[0515] Input: Quiz results, emotion data

[0516] Processing: The server stores the received data in a database and determines the next learning content based on it.

[0517] Output: What to display next

[0518] Specific behavior:

[0519] The server analyzes the quiz results and emotional data and updates the database with the next lesson content.

[0520] AI-guided virtual stock trading game app processing steps

[0521] Step 1: Obtain portfolio and market data

[0522] Input: User ID

[0523] Processing: The server receives the user ID from the terminal, retrieves the user's latest portfolio data from the database, and also collects market data.

[0524] Output: Portfolio data, market data

[0525] Specific behavior:

[0526] The server retrieves the user's portfolio and the latest market prices from a database and external APIs.

[0527] Step 2: Getting started with AI advice and emotion recognition

[0528] Input: Portfolio data, market data

[0529] Processing: The terminal displays the received data, the AI ​​guide provides trading advice to the user, and the emotion engine simultaneously recognizes the user's emotions.

[0530] Output: trading advice, sentiment data

[0531] Specific behavior:

[0532] The device displays advice such as "TechCorp stock is on the rise, so we recommend buying," and the emotion engine detects the user's anxiety.

[0533] Step 3: Execute trades and update data

[0534] Input: trading instructions, sentiment data

[0535] Processing: The user buys or sells virtual stocks, and the instruction is sent to the server, which updates the database and returns the result to the terminal.

[0536] Output: Updated portfolio data

[0537] Specific behavior:

[0538] When a user issues a trade instruction, the instruction is sent from the terminal to the server, which updates the database and returns the portfolio.

[0539] Financial literacy improvement community platform processing steps

[0540] Step 1: Obtain community data

[0541] Input: User ID

[0542] Processing: The server retrieves forum posts and Q&A data from the database using the user ID received from the device.

[0543] Output: Community data

[0544] Specific behavior:

[0545] The server retrieves the latest forum threads and Q&A information from the database.

[0546] Step 2: View posts, questions, and answers and start emotion recognition

[0547] Input: Community Data

[0548] Processing: The device displays the received data, and the emotion engine recognizes the user's emotions in real time.

[0549] Output: Forum posts, questions and answers, sentiment data

[0550] Specific behavior:

[0551] A user checks the "latest posts about the risks of stock investment," and the sentiment engine analyzes the user's sentiment.

[0552] Step 3: Emotional feedback and data storage

[0553] Input: Post content, emotion data

[0554] Processing: The server stores the post, response data, and sentiment data in a database and updates the user's points and ranking.

[0555] Output: Updated points, rankings

[0556] Specific behavior:

[0557] If a user receives a lot of positive feedback, the server will award points to the user and update their ranking.

[0558] Step 4: View your points and rankings

[0559] Input: Updated data

[0560] Processing: The terminal displays the points and ranking received from the server to the user.

[0561] Output: points, ranking

[0562] Specific behavior:

[0563] Based on the points the user has earned, a new ranking is displayed for the user to check.

[0564] (Application example 2)

[0565] 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."

[0566] There is a lack of effective ways for today's young people to improve their financial literacy. Furthermore, traditional learning systems are unable to personalize the learning experience based on the user's interests and emotions, resulting in poor learning efficiency. Since acquiring knowledge related to electronic payments is particularly relevant to daily life, it is necessary to optimize the learning experience.

[0567] 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.

[0568] In this invention, the server includes means for communicating with a database that manages user progress information, means for generating learning content and providing it to the user, means for receiving quiz results and saving them in the database, means for automatically preparing the next learning content, and means for recognizing the user's emotions and optimizing the learning experience based on those emotions. This allows the user to effectively learn financial knowledge through everyday electronic payments and provides an optimal learning experience tailored to their emotions.

[0569] "User progress information" is data that records and manages the progress of a user when studying.

[0570] A "database" is a system for storing information in an organized manner and for efficiently retrieving and updating it.

[0571] "Means of communication" refers to the technical methods and devices used to transmit and receive data between the database and the server.

[0572] "Learning Content" means educational materials, information, or lessons provided to Users to improve their financial literacy.

[0573] A "generation means" is a technology or device that creates learning content based on specific conditions.

[0574] "Means for providing" refers to the technology or devices used to display, notify, or transmit learning content to users.

[0575] "Quiz results" refers to the scores and answer data for a quiz that a user takes after studying the learning content.

[0576] "Next learning content" refers to the next learning material or information selected based on the user's current learning progress and quiz results.

[0577] "Automatic preparation means" refers to technology or devices that allow the system to automatically select and provide the next learning content based on the user's progress data and emotional data.

[0578] "Means for recognizing emotions" refers to technologies and devices for detecting and identifying a user's emotional state from facial expressions, voice, actions, etc.

[0579] "Means for optimizing the learning experience" refers to technologies and devices that adjust the content and methods of learning according to the user's emotional state and progress, thereby enabling effective learning.

[0580] "Virtual Market Data" means simulated stock market data and information.

[0581] "Trade history" refers to historical data of virtual stock trades made by a user.

[0582] "Means for providing advice" refers to technology or devices that provide appropriate trading advice based on a user's trading history and emotional data.

[0583] A "trade instruction" is an instruction or command for a user to buy or sell virtual stock.

[0584] "Means for updating" refers to techniques or devices that update the data in the database based on received trade instructions.

[0585] "Posts and Questions" are texts or messages that a User uses to share knowledge or raise questions with other Users or Experts on the Community Platform.

[0586] The "answer management means" refers to a technology or device that collects and organizes answers provided by users and experts and provides them to users.

[0587] "Contribution scoring means" refers to technology or devices that evaluate the quality of posts and responses made by users on the platform and award points to them.

[0588] "Means for awarding points" refers to the technology or device that awards points on the system according to the user's level of contribution.

[0589] The "means for displaying rankings" refers to a technique or device that creates rankings based on the points acquired by users and displays them to users.

[0590] "Communication optimizers" are technologies and devices that recognize users' emotions and effectively adjust community interactions accordingly.

[0591] The present invention relates to a technology for optimizing learning experiences by recognizing emotions in a system that manages user progress information, generates and provides learning content, and stores quiz results. It also includes a method for managing virtual market data and trading history, providing appropriate advice to users, and optimizing communication in a community platform.

[0592] System configuration

[0593] The system of the present invention consists of the following main components:

[0594] 1. Progress information management

[0595] The server has a means for communicating with a database that manages user progress information, including the user's learning progress and quiz results.

[0596] 2. Creation and provision of learning content

[0597] The server generates learning content and provides it to users, who access it via devices such as smartphones and tablets.

[0598] 3. Receiving and storing quiz results

[0599] The device sends the quiz results to the server, which stores them in a database, and the next learning content is automatically prepared.

[0600] 4. Emotion Recognition and Optimization

[0601] The server has the means to recognize the user's emotions and optimize the learning experience based on those emotions, using camera and voice analysis.

[0602] Virtual Market Data and Trading Advice

[0603] The server updates virtual market data and manages users' trading history. It receives trading instructions, updates the database, and adjusts advice based on sentiment. Users can use their terminals to buy and sell virtual stocks and view updated data.

[0604] Community Platform

[0605] The server manages user posts and questions, manages answers from other users and experts, scores contributions and awards points, and optimizes communication based on user sentiment data.

[0606] Hardware and Software

[0607] The specific hardware and software used to implement this system includes:

[0608] Hardware: smartphones, tablets, smart glasses, cameras.

[0609] Software: OpenCV (real-time video capture and processing), EmotionRecognition module (emotion recognition), FinancialAnalysis module (expense analysis), QuizGame module (quiz game).

[0610] Specific examples

[0611] When a user makes an electronic payment at a cafe using their smartphone, the app records the transaction and displays a message saying, "You spend a lot at cafes every month. Why not try enjoying coffee at home a few times a month?" If the user's facial expressions and voice indicate they are "interested," the app provides a detailed analysis of their cafe spending and a mini-game on how to reduce coffee costs.

[0612] Prompt Sentence Examples

[0613] Here are some examples of prompts for generative AI models:

[0614] text

[0615] When a user makes an electronic payment at a cafe, if their facial expression is recognized as "curious," provide a detailed analysis of their spending at the cafe and a mini-game based on that analysis. Implement a recommendation system that displays a warning if the user has spent more than a certain number of times at a cafe and suggests ways to save money. Cover the following items:

[0616] 1. Camera-based facial expression recognition.

[0617] 2. Analysis of historical expenditure data.

[0618] 3. Providing advice and mini-games based on the user's emotions.

[0619] This allows users to effectively learn financial knowledge through everyday electronic payments, providing an optimal learning experience that responds to their emotions.

[0620] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0621] Step 1:

[0622] The device activates the camera and captures the user's video. The input is video data from the camera. The device processes this video data in real time and recognizes emotions from the user's facial expressions and voice. OpenCV face detection and the EmotionRecognition module are used here. The output is the user's emotional data (e.g., curious, tired, etc.).

[0623] Step 2:

[0624] The device sends the user's emotional data to the server. The input is the emotional data obtained in step 1 above. The server receives this data and uses it to generate the next learning content in comparison with the user's current learning progress data. The server generates the learning content. The output is personalized learning content based on the emotional data and progress data.

[0625] Step 3:

[0626] The server sends the generated learning content to the terminal. The input is the learning content generated on the server. The terminal receives it and displays it on the interface. The output is the learning content that the user views.

[0627] Step 4:

[0628] The user watches the learning content provided on the device and answers the quiz questions. The input is the user's learning behavior and quiz answer data. The device collects this data and sends it to the server. The output is the user's quiz answer results.

[0629] Step 5:

[0630] The server receives the user's quiz answer results and stores them in a database. The input is the quiz answer results sent from the terminal. The server stores them in the database and begins preparing the next learning content. The output is the user's quiz results stored in the database.

[0631] Step 6:

[0632] When a user makes an everyday electronic payment, the terminal automatically captures the payment information and sends it along with emotional data to a server. The input is the electronic payment transaction data and emotional data. The server receives this data and performs a comparative analysis with past spending data. The output is the analysis results.

[0633] Step 7:

[0634] The server generates appropriate advice and warning messages based on the analysis results and sends them to the terminal. The input is the analysis results of the expenditure data performed on the server. The terminal displays this to the user. The output is advice and warning messages regarding the user's expenditures.

[0635] Step 8:

[0636] The device then recognizes the user's emotions again and uses them to inform the next step of learning or advice. This process continues as a loop. The input is updated emotional data, and the output is emotional data that will be reflected in the next learning content or advice.

[0637] In this way, the system uses users' emotional data to individually optimize their learning experience and feedback on everyday electronic payments, effectively improving financial literacy.

[0638] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0639] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0640] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0641] [Second embodiment]

[0642] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0643] 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.

[0644] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0645] 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.

[0646] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0647] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0648] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0649] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0650] 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.

[0651] 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.

[0652] 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.

[0653] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0654] The present invention is a comprehensive system for improving financial literacy among young people. The system includes three main components: a micro-learning financial app, an AI-guided virtual stock trading game app, and a financial literacy community platform.

[0655] Microlearning Financial App

[0656] System Overview:

[0657] The purpose of microlearning financial apps is to enable users to learn financial knowledge in a short amount of time every day. Users access content delivered from a server using devices such as smartphones and tablets.

[0658] Process flow:

[0659] The device connects to the server using the user ID and requests the latest learning progress data. The server retrieves the user's progress information from the database and sends it to the device.

[0660] The terminal displays the next lesson content to the user based on the data received from the server. The user watches the lesson provided on the screen and progresses with their learning.

[0661] After completing a lesson, the user answers a quiz. The device sends the quiz results to the server, which stores them in a database. The next lesson is then automatically prepared.

[0662] Examples:

[0663] If a user wants to learn about "How Credit Cards Work," they can watch a three-minute lesson on their device, take a quiz, and then the results of the quiz will be sent to the server, which will then automatically prepare the next lesson on "Loans and Interest Rates."

[0664] AI-guided virtual stock trading game app

[0665] System Overview:

[0666] The app aims to enable users to gain practical financial knowledge through virtual stock trading experiences. An AI guide provides users with trading advice, allowing them to acquire trading skills without any risk.

[0667] Process flow:

[0668] The terminal connects to the server using the user ID and requests the latest portfolio data and market data. The server retrieves the user's portfolio data and market data from the database and sends them to the terminal.

[0669] The terminal receives market data and AI advice from the server and displays it to the user, who then uses the advice to buy or sell virtual stocks.

[0670] Trade instructions are sent to the server, trade results are recorded in a database, and updated portfolio data is sent to the terminal and displayed to the user.

[0671] Examples:

[0672] If a user decides to buy TechCorp stock, the AI ​​guide will advise them that "TechCorp stock is on an upward trend, so we recommend buying it." Once the user decides to buy and executes the trade, the results are sent to the server and recorded in the database. The portfolio after the trade is displayed on the terminal.

[0673] A community platform for improving financial literacy

[0674] System Overview:

[0675] The community platform allows users to share their knowledge and interact with other users and experts, and includes features such as forums, Q&A sections, and online workshops.

[0676] Process flow:

[0677] The device accesses the server using the user ID and requests the latest forum posts and Q&A data. The server retrieves the necessary data from the database and sends it to the device.

[0678] The device displays the latest community content to the user based on the data received from the server. The user posts on forums or asks questions and waits for answers from other users or experts.

[0679] Posts and replies are sent to the server and recorded in a database. The server evaluates the quality of the post and reply and awards points to the user. The terminal displays the user's points and ranking.

[0680] Examples:

[0681] When a user posts a question such as "I want to know about the risks of stock investment," other users and experts will provide answers. Users who post high-quality answers will be awarded points by the server, and their rankings will be updated.

[0682] These system features allow users to effectively learn, practice, and share financial knowledge with other users.

[0683] The processing flow will be explained below.

[0684] Microlearning Financial App

[0685] Processing Steps

[0686] Step 1:

[0687] The device connects to the server using the user ID and requests the user's latest learning progress data.

[0688] Step 2:

[0689] The server searches the database based on the received user ID and obtains the user's latest learning progress information.

[0690] Step 3:

[0691] The server transmits the acquired learning progress data to the terminal.

[0692] Step 4:

[0693] The terminal displays the next lesson content to the user based on the data received from the server.

[0694] Step 5:

[0695] The user watches and listens to the lessons displayed on the screen and progresses through the learning process.

[0696] Step 6:

[0697] The terminal displays a quiz to the user after the lesson is completed.

[0698] Step 7:

[0699] The user answers the quiz and inputs the answer into the terminal.

[0700] Step 8:

[0701] The terminal transmits the answer to the quiz to the server.

[0702] Step 9:

[0703] The server stores the quiz results in a database and automatically prepares the next learning content.

[0704] AI-guided virtual stock trading game app

[0705] Processing Steps

[0706] Step 1:

[0707] The terminal connects to the server using the user ID and requests the latest portfolio and market data.

[0708] Step 2:

[0709] The server retrieves the user's portfolio data and the latest market data from the database.

[0710] Step 3:

[0711] The server transmits the acquired data to the terminal.

[0712] Step 4:

[0713] The terminal displays market data received from the server and AI trading advice to the user.

[0714] Step 5:

[0715] Users can choose to follow AI advice or make their own trading decisions.

[0716] Step 6:

[0717] A user executes a trade by specifying the stock to be purchased or sold and the quantity.

[0718] Step 7:

[0719] The terminal transmits the user's trade instructions to the server.

[0720] Step 8:

[0721] The server processes the trade instructions to update the virtual market database and update the user's portfolio.

[0722] Step 9:

[0723] The server returns the updated portfolio data to the terminal.

[0724] Step 10:

[0725] The terminal displays the updated portfolio data to the user, allowing the user to confirm the trading results.

[0726] A community platform for improving financial literacy

[0727] Processing Steps

[0728] Step 1:

[0729] The device connects to the server using the user ID and requests the latest forum posts and Q&A data.

[0730] Step 2:

[0731] The server retrieves forum posts and Q&A data from a database.

[0732] Step 3:

[0733] The server transmits the acquired data to the terminal.

[0734] Step 4:

[0735] The terminal displays the latest community content to the user based on the data received from the server.

[0736] Step 5:

[0737] Users review forum posts and questions and make comments and replies as needed.

[0738] Step 6:

[0739] Users create new posts and questions in the community forums.

[0740] Step 7:

[0741] The terminal transmits user posts and questions to the server.

[0742] Step 8:

[0743] The server stores the received posts and questions in a database.

[0744] Step 9:

[0745] The server notifies other users of new posts and questions and shares them with the entire community.

[0746] Step 10:

[0747] The server scores the contribution of posts and replies and awards points to users.

[0748] Step 11:

[0749] The server updates the total points and ranking and sends them to the terminal.

[0750] Step 12:

[0751] The terminal displays the updated points and ranking to the user, allowing them to see their contribution to the community.

[0752] The above are the specific program processing steps in each system. We have explained in detail what operations the server, terminal, and user perform in each step.

[0753] Example 1

[0754] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0755] Traditional financial literacy education systems have struggled to provide personalized learning experiences based on users' progress. Virtual stock trading and community platforms also lack the appropriate advice and feedback to maximize users' learning outcomes. Furthermore, effective communication methods for sharing learned knowledge are often lacking.

[0756] 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.

[0757] In this invention, the server includes: means for communicating with a database that manages user progress information; means for generating learning content and providing it to the user; means for receiving quiz results and saving them in the database; means for automatically preparing the next learning content; means for customizing the next lesson content based on the user's individual learning history; and means for connecting to the server from a device such as a smartphone or tablet and requesting progress information. This allows users to efficiently take learning content that is tailored to their individual needs, improving learning effectiveness. The server also includes means for updating virtual market data, means for managing the user's trading history and providing advice, means for receiving trading instructions and updating the database, means for displaying the updated data to the user, means for displaying the latest market data and advice from the AI ​​guide to the user, and means for recording the user's virtual trading results in the database, allowing users to acquire practical trading skills without risk. Furthermore, the server includes means for managing user posts and questions, means for managing answers from other users and experts, means for scoring contributions and awarding points, means for displaying the points and rankings to users, means for requesting forum posts and Q&A data to display the latest community content, and means for evaluating the quality of posts and answers and awarding points, thereby promoting knowledge sharing and interaction among users and increasing motivation to learn and a sense of accomplishment.

[0758] A "database for managing user progress information" is a data storage system that stores information for recording and managing what a user has learned and their progress.

[0759] A "means for generating and providing learning content to users" is a system or method for creating new educational material based on the user's needs and learning history and delivering it to the user in an accessible format.

[0760] "Means for receiving quiz results and storing them in a database" refers to a system or method by which the server receives the results of the quiz answered by the user after studying and records them in a management database.

[0761] "Means for automatically preparing the next learning content" refers to a system or method that automatically selects and prepares the next learning content based on the user's learning progress and quiz results.

[0762] "Means for customizing the next lesson content based on the user's individual learning history" refers to a system or method that analyzes each user's past learning data and provides the most appropriate learning content individually based on that data.

[0763] "Means for connecting to a server from a terminal such as a smartphone or tablet and requesting progress information" refers to a system or method for connecting to a server using a mobile device and obtaining learning progress information from there.

[0764] A "means for updating virtual market data" is a system or method for periodically updating data to keep virtual financial market information current.

[0765] A "means for managing a user's trading history and providing advice" is a system or method for recording a user's virtual trading activity and providing advice on financial trading based thereon.

[0766] The "means for receiving trade instructions and updating the database" refers to a system or method for receiving information when a user issues a virtual trade instruction and updating the database.

[0767] The "means for displaying updated data to the user" refers to a system or method for displaying the latest virtual market information, the user's trading results, etc. on the user's device screen.

[0768] "Means for displaying the latest market data and advice from an AI guide to users" refers to a system or method that obtains the latest market information and provides users with AI-generated financial advice based on that information.

[0769] The "means for recording the results of a user's virtual trade in a database" refers to a system or method for storing the results of a virtual trade executed by a user in a database.

[0770] "Means for managing user posts and questions" refers to a system or method for processing and appropriately managing information and questions posted by users on the community platform.

[0771] "Means for managing responses from other users and experts" refers to a system or method for receiving and managing responses from other users and experts on the community platform.

[0772] "Means for scoring contributions and awarding points" refers to a system or method for evaluating the quality of users' posts and replies and awarding points accordingly.

[0773] The "means for displaying points and rankings to the user" refers to a system or method for visualizing the points and rankings earned by the user and displaying them on the user's device.

[0774] A "means for requesting forum posts and Q&A data to display the most recent community content" is a system or method that automatically retrieves the most recent posts to a forum or Q&A section and displays them to the user.

[0775] The "means for evaluating the quality of posts and replies and awarding points" refers to a system or method for evaluating the content of posts and replies made by users and awarding points according to their contribution.

[0776] MODE FOR CARRYING OUT THE INVENTION

[0777] The present invention is a comprehensive system for improving financial literacy among young people. The system includes three main components: a micro-learning financial app, an AI-guided virtual stock trading game app, and a financial literacy community platform.

[0778] Microlearning Financial App

[0779] System Overview:

[0780] The purpose of microlearning financial apps is to enable users to learn financial knowledge in a short amount of time every day. Users access content delivered from a server using devices such as smartphones and tablets.

[0781] Hardware and software used:

[0782] Mobile devices such as smartphones and tablets

[0783] Server (progress database, content distribution system)

[0784] Internet Connectivity Infrastructure

[0785] Specific data processing and calculation:

[0786] When a user launches the app, the server retrieves the user's learning progress information from the progress database and sends it to the device. The device uses this data to display the next lesson content to the user. When the user completes their learning and answers a quiz, the results are sent to the server and stored in the database. The server automatically selects and prepares the next learning content based on the user's progress.

[0787] Examples:

[0788] When a user learns about "How Credit Cards Work," the device retrieves the relevant lesson video from the server and displays it. After the lesson, the user answers a quiz, and the results are sent to the server, which then prepares the next lesson on "Loans and Interest Rates."

[0789] Example prompt sentence:

[0790] Please state the conditions for selecting the content of your next lesson.

[0791] AI-guided virtual stock trading game app

[0792] System Overview:

[0793] The app aims to enable users to gain practical financial knowledge through virtual stock trading experiences. An AI guide provides users with trading advice, allowing them to acquire trading skills without any risk.

[0794] Hardware and software used:

[0795] Mobile devices such as smartphones and tablets

[0796] Server (portfolio database, AI guide system, market database)

[0797] Internet Connectivity Infrastructure

[0798] Specific data processing and calculation:

[0799] When a user logs in, the terminal connects to the server using the user ID and retrieves the latest portfolio and market data. The server then retrieves this data from the database and displays it to the user. An AI guide also provides advice based on market data, and the user purchases or sells virtual stocks. After the trade is executed, the results are sent to the server and recorded in the database.

[0800] Examples:

[0801] If a user were to hypothetically buy TechCorp shares, the terminal would retrieve market data and AI-guided advice from the server and display it. Once the user decides to buy and executes the trade, the information is sent to the server for recording, and the new portfolio is displayed on the terminal.

[0802] Example prompt sentence:

[0803] "Please explain the circumstances under which you would recommend buying or selling TechCorp stock."

[0804] A community platform for improving financial literacy

[0805] System Overview:

[0806] The platform allows users to share their knowledge and interact with other users and experts, and includes features such as forums, Q&A sections, and online workshops.

[0807] Hardware and software used:

[0808] Devices such as smartphones, tablets, and PCs

[0809] Server (community database, posting management system)

[0810] Internet Connectivity Infrastructure

[0811] Specific data processing and calculation:

[0812] The device connects to the server using the user ID to retrieve the latest forum posts and Q&A data. The server retrieves this data from the database and sends it to the device. Users can post to the forum or ask questions and wait for answers from other users or experts. The posts and answers are sent to the server and recorded in the database. The server then evaluates the quality of these posts and answers and assigns points. The device then displays the points and rankings to the user.

[0813] Examples:

[0814] When a user posts a question about the risks of stock investment on the community platform, other users and experts respond. The server records the responses, evaluates the quality of the responses, and awards points. The terminal then displays the points and rankings to the user.

[0815] Example prompt sentence:

[0816] "Create the best answer to the question about the risks of stock investment."

[0817] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0818] Microlearning Financial App

[0819] Processing flow

[0820] Step 1:

[0821] Server connection by user ID

[0822] When a user launches the app, the device connects to the server using the user ID stored in the device.

[0823] Input: User ID

[0824] Data processing: The server receives the user ID and sends a query to the database to retrieve the learning progress data of the user.

[0825] Output: User's learning progress data

[0826] Specific operation: The server retrieves the user's progress information from the database and sends it to the device.

[0827] Step 2:

[0828] View lesson content

[0829] The terminal displays the next lesson content to the user based on the received learning progress data.

[0830] Input: Learning progress data received from the server

[0831] Data processing: The device analyzes the progress data and determines the next lesson content to display.

[0832] Output: Lesson content (e.g. video, text)

[0833] Specific operation: The device displays the next lesson content on the screen and the user begins learning.

[0834] Step 3:

[0835] Quiz Answers and Results Submission

[0836] The user answers a quiz that is displayed after the lesson is completed.

[0837] Input: User's quiz answer

[0838] Data processing: The terminal receives the user's answers and sends the results to the server.

[0839] Output: Quiz results

[0840] Specific operation: The device sends the quiz results to the server, which stores them in a database.

[0841] AI-guided virtual stock trading game app

[0842] Processing flow

[0843] Step 1:

[0844] Portfolio and Market Data Requests

[0845] When a user logs in, the terminal connects to the server using the user ID and requests the latest portfolio and market data.

[0846] Input: User ID

[0847] Data processing: The server retrieves portfolio data and market data from the database based on the user ID.

[0848] Output: Portfolio data, latest market data

[0849] Specific operation: The server sends the data retrieved from the database to the terminal.

[0850] Step 2:

[0851] Display market data and AI advice

[0852] The terminal displays the received market data and advice from the AI ​​guide to the user.

[0853] Inputs: Portfolio data, latest market data, AI advice

[0854] Data processing: The terminal analyzes the received market data and AI advice and presents appropriate information to the user.

[0855] Output: Market status and trading advice

[0856] Specific operation: The device displays market conditions and AI-guided advice to the user.

[0857] Step 3:

[0858] Trading instructions and results recording

[0859] A user trades (buys or sells) virtual stocks.

[0860] Input: User's trading instructions

[0861] Data processing: The terminal sends trade instructions to the server, which records the information in a database.

[0862] Output: Updated portfolio data

[0863] Specific operation: After the results of the trade are recorded in the database, the updated portfolio data is sent to the terminal.

[0864] A community platform for improving financial literacy

[0865] Processing flow

[0866] Step 1:

[0867] Requesting forum posts and Q&A data

[0868] The device accesses the server using the user ID and requests the latest forum posts and Q&A data.

[0869] Input: User ID

[0870] Data processing: The server retrieves the latest forum posts and Q&A data from the database based on the user ID.

[0871] Output: Forum post data, Q&A data

[0872] Specific operation: The server sends the acquired data to the terminal.

[0873] Step 2:

[0874] View community content and user activity

[0875] The terminal displays the latest community content to the user based on the received data.

[0876] Input: Forum post data, Q&A data

[0877] Data processing: The device analyzes the received data and selects and displays the latest content.

[0878] Output: Forum content, Q&A content to be displayed

[0879] What it does: The device displays recent posts and questions and answers on the screen, and users post and ask questions in the forum.

[0880] Step 3:

[0881] Recording and rating posts and responses

[0882] When a post or question is made, the device sends the content to the server.

[0883] Input: New post data, question and answer data

[0884] Data processing: The server records the received data in a database and evaluates its quality.

[0885] Output: Updated forum data, quality evaluation results, point data

[0886] Specific operation: The server stores posts and answers in a database and assigns points based on quality. The terminal displays the points and ranking to the user.

[0887] (Application example 1)

[0888] 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."

[0889] In recent years, low financial literacy among young people has become a problem. In particular, purchasing behavior on online shopping sites tends to be impulsive, leading to a lack of budget management. In such circumstances, young people find it difficult to make financial forecasts and are prone to long-term financial risk. Therefore, a system is needed to improve financial literacy in real time through online shopping site purchasing behavior, and to provide appropriate purchasing advice and budget management.

[0890] 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.

[0891] In this invention, the server includes means for communicating with a database that manages user progress information, means for generating study content and providing it to the user, means for receiving quiz results and saving them in the database, means for automatically preparing the next study content, means for receiving the user's purchasing data and providing purchasing advice within a budget, and means for updating post-purchase budget data and saving it in the database. This allows users to manage their budget while receiving appropriate financial advice in real time through their purchasing behavior on the online shopping site.

[0892] "User progress information" refers to the status and history achieved by the user in processes such as learning and purchasing.

[0893] A "database" is a system for managing information efficiently and consistently, storing, retrieving, and updating data.

[0894] "Learning Content" refers to educational materials and teaching materials provided to users to improve their financial literacy.

[0895] "Quiz results" refers to information on the results of a user's answers to a quiz-style test.

[0896] "Next learning content" refers to the next step of education provided based on the user's current learning situation and progress.

[0897] "User purchase data" refers to information about purchases made by a user on an online shopping site, such as the product name, purchase price, and purchase date and time.

[0898] "Buying advice within a budget" refers to recommendations and suggestions regarding what purchasing behavior a user should take within their budget.

[0899] "Post-purchase budget data" refers to information regarding the remaining budget after a user has completed a particular purchase.

[0900] "Virtual market data" refers to data of a virtual investment environment that simulates actual market data.

[0901] "User's trading history" refers to a record of transactions that a User has made in the virtual or real markets.

[0902] "Trade Instructions" refers to specific commands given by a user to buy or sell stocks or other financial instruments.

[0903] "User posts and questions" refers to information shared or questions expressed by users on the community platform.

[0904] "Responses from other users and experts" refers to information and advice provided in response to a user's post on the community platform.

[0905] "Scoring contribution" refers to users rating their activities on the community platform.

[0906] "Awarding points" refers to giving points as a reward for a user's community activities.

[0907] "Points and ranking" refers to the numerical value of the user's activity evaluation and the user's ranking generated based on that numerical value.

[0908] This invention is a comprehensive system for improving users' financial literacy, and is composed of the following major components:

[0909] System configuration

[0910] The system consists of the following main components:

[0911] 1. A database that manages user progress information:

[0912] The server maintains a database that centrally manages user progress information, including the user's learning activities, quiz results, purchase history, and budget information, and updates the database as needed.

[0913] 2. Learning content generation and delivery:

[0914] The server generates financial education learning content to be provided to users and provides it to devices such as smartphones and tablets. The learning content is personalized based on the user's progress.

[0915] 3. Receiving and storing quiz results:

[0916] The server receives the results of the user's answers to the quiz accompanying the learning content, stores them in a database, and automatically prepares the next learning content based on this data.

[0917] 4. Receiving purchasing data and providing budget advice:

[0918] When a user purchases a product on an online shopping site, the server receives the purchase data (product name, price, date and time, etc.) and provides appropriate purchasing advice within the user's budget based on this purchase data and the user's budget information.

[0919] 5. Update budget data after purchase:

[0920] After the purchase, the server updates the user's budget data and stores it in the database, realizing real-time budget management.

[0921] 6. Virtual Market Data and Trade History Management:

[0922] The server manages data on users' transactions in the virtual market and provides trading advice based on this data, allowing users to experience stock trading risk-free and gain practical financial knowledge.

[0923] 7. Maintaining the Community Platform:

[0924] The server manages user posts and questions, as well as answers from other users and experts. It scores the contribution of posts and answers, awards points, and displays them to users.

[0925] Hardware and Software Details

[0926] Hardware: smartphones, tablets, servers

[0927] Software: Flask (Python web framework), SQLite (database management)

[0928] Specific examples

[0929] For example, consider a situation where a user is trying to purchase a pair of sneakers for 10,000 yen on an online shopping site. In this case, the server first retrieves the user's budget information from the database and evaluates in real time whether the purchase is within budget. If the purchase is within budget, the server provides advice recommending the purchase and updates the budget data after the purchase. This series of steps allows the user to manage their budget in real time.

[0930] Prompt Sentence Examples

[0931] Build a smartphone app that manages a user's budget when purchasing certain items. When a user attempts to purchase an item, the app will receive the user ID and the item's price as input. It will then retrieve the user's remaining budget from the database and check whether the purchase is within the budget. The budget will also be updated after the purchase and the user will be notified. Please also provide an example program using Flask and SQLite.

[0932] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0933] Step 1:

[0934] The server receives a product purchase request from the user. The user ID and product price information are provided as input. Based on this, the server processes the data to retrieve the user's current budget information from the database. The output is the retrieved user's budget information.

[0935] Step 2:

[0936] The server compares the acquired budget information with the product price and performs data calculations to determine whether the purchase is possible within the budget. Specifically, the server subtracts the product price from the user's remaining budget, and if the result is 0 or greater, it recommends the purchase, and if it is less than 0, it notifies the user that the budget is exceeded. The input is the user's budget information and product price, and the output is advice information such as "purchase possible" or "over budget."

[0937] Step 3:

[0938] The terminal receives advice information from the server and displays it to the user, allowing the user to decide whether to proceed with the purchase. Specifically, the terminal displays the received advice on the screen and waits for the user's next action. The input is advice information from the server, and the output is the screen display.

[0939] Step 4:

[0940] When the user decides to make a purchase, the device sends that decision to the server. The server receives this information and performs data calculations to update the user's budget information. Specifically, the server subtracts the product price from the user's remaining budget and saves the updated budget data in the database. The input is the user's purchase intention and product price, and the output is the updated user's budget data.

[0941] Step 5:

[0942] The server sends confirmation of the purchase completion to the terminal. The terminal receives this information and notifies the user that the purchase is complete. Specifically, the terminal displays a "Purchase Complete" message on the screen and notifies the user that the budget has been updated. The input is the purchase completion notification from the server, and the output is the screen display.

[0943] Through these steps, users can receive budget management and financial advice in real time through their purchasing behavior on the online shopping site.

[0944] When generating a description using keywords from a generative AI model, the following prompts can be used:

[0945] "Build a smartphone app that manages a user's budget when purchasing certain products. When a user tries to purchase an item, the app will receive the user ID and the product price as input. It will then retrieve the user's remaining budget from a database and check whether the purchase is within the budget. The budget will also be updated after the purchase and the user will be notified. Please also provide an example program using Flask and SQLite."

[0946] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0947] This invention combines a comprehensive system for improving young people's financial literacy with an emotion engine that recognizes user emotions. The system includes three main components: a microlearning financial app, an AI-guided virtual stock trading game app, and a financial literacy improvement community platform. Furthermore, the emotion engine recognizes users' emotions and optimizes the learning experience based on their emotions.

[0948] Microlearning Financial App

[0949] System Overview:

[0950] The purpose of microlearning financial apps is to enable users to learn financial knowledge in a short amount of time every day. Users access content delivered from a server using devices such as smartphones and tablets. An emotion engine also recognizes the user's emotions and personalizes the learning experience.

[0951] Process flow:

[0952] The device connects to the server using the user ID and requests the latest learning progress data. The server retrieves the user's progress information from the database and sends it to the device.

[0953] The device displays the next lesson content to the user based on the data received from the server. The user continues learning by watching the lesson provided on the screen while their emotions are recognized in real time by the emotion engine.

[0954] The learning content is adapted based on the user's emotions: for example, if the user is feeling tired, the content is simplified, and if the user is perceived as easily distracted, the interactive elements are increased.

[0955] After completing the lesson, the user answers a quiz. The device sends the quiz results and emotion data to the server, which stores them in a database. The next lesson is then automatically prepared.

[0956] Examples:

[0957] For example, if a user wants to learn about "How Credit Cards Work," they watch a three-minute lesson displayed on their device and answer a quiz. The emotion engine assesses in real time whether the user is enjoying the lesson and deepening their understanding, and automatically prepares the next lesson on "Loans and Interest Rates" at the appropriate difficulty level.

[0958] AI-guided virtual stock trading game app

[0959] System Overview:

[0960] The app aims to enable users to gain practical financial knowledge through virtual stock trading experiences. An AI guide provides trading advice, and an emotion engine recognizes users' emotions and provides appropriate feedback.

[0961] Process flow:

[0962] The terminal connects to the server using the user ID and requests the latest portfolio data and market data. The server retrieves the user's portfolio data and market data from the database and sends them to the terminal.

[0963] The terminal receives market data and AI advice from the server and displays it to the user. The user then buys or sells virtual stocks based on the advice, which is based on sentiment analysis by the emotion engine.

[0964] The advice is tailored depending on the user's emotions: for example, if the user is feeling anxious, low-risk, conservative advice is offered.

[0965] Trade instructions are sent to the server, trade results are recorded in a database, and updated portfolio data is sent to the terminal and displayed to the user.

[0966] Examples:

[0967] If a user decides to buy TechCorp stock, the AI ​​guide will advise them that "TechCorp stock is on an upward trend, so we recommend buying." If the user feels unsure, the emotion engine will provide supplemental information to reduce the risk. Once the user decides to purchase and executes the trade, the results are sent to the server and recorded in the database. The portfolio after the trade is displayed on the terminal.

[0968] A community platform for improving financial literacy

[0969] System Overview:

[0970] The community platform provides a forum for users to share their knowledge and interact with other users and experts. It features forums, Q&A sections, online workshops, and an emotion engine that recognizes users' emotions to optimize communication.

[0971] Process flow:

[0972] The device accesses the server using the user ID and requests the latest forum posts and Q&A data. The server retrieves the necessary data from the database and sends it to the device.

[0973] The device displays the latest community content to the user based on the data received from the server. The user can post forums or ask questions, and wait for answers from other users and experts, while the emotion engine recognizes emotions in real time.

[0974] The community's scoring is adjusted based on the user's sentiment: for example, if a user feels satisfied, they will provide high-quality answers and receive more points.

[0975] Posts and answers are sent to the server and recorded in a database. The server evaluates the quality of the post and answer and awards points to the user. Updated points and rankings are sent to the device.

[0976] Examples:

[0977] When a user posts a question such as "I want to know about the risks of stock investment," other users and experts provide answers. The emotion engine analyzes the user's emotions, and if there is a lot of positive feedback, the server increases the points. The ranking is updated and displayed on the device.

[0978] These system features allow users to effectively learn, practice, and share financial knowledge with others. The incorporation of an emotion engine further enhances learning and trading experiences by optimizing according to users' emotions.

[0979] The processing flow will be explained below.

[0980] Microlearning Financial App

[0981] Processing Steps

[0982] Step 1:

[0983] The device connects to the server using the user ID and requests the user's latest learning progress data.

[0984] Step 2:

[0985] The server searches the database based on the received user ID and obtains the user's latest learning progress information.

[0986] Step 3:

[0987] The server transmits the acquired learning progress data to the terminal.

[0988] Step 4:

[0989] The terminal displays the next lesson content to the user based on the data received from the server.

[0990] Step 5:

[0991] The user watches and learns lessons presented on the screen.

[0992] Step 6:

[0993] The emotion engine analyzes the user's facial expressions and voice in real time to obtain emotional data.

[0994] Step 7:

[0995] The terminal adjusts the learning content based on the emotion data acquired by the emotion engine.

[0996] Step 8:

[0997] After the lesson is completed, the terminal displays a quiz to the user.

[0998] Step 9:

[0999] The user answers the quiz and inputs the answer into the terminal.

[1000] Step 10:

[1001] The terminal transmits the quiz answer results and emotion data to the server.

[1002] Step 11:

[1003] The server stores the quiz results and emotional data in a database and automatically prepares the next learning content.

[1004] AI-guided virtual stock trading game app

[1005] Processing Steps

[1006] Step 1:

[1007] The terminal connects to the server using the user ID and requests the latest portfolio and market data.

[1008] Step 2:

[1009] The server retrieves the user's portfolio data and the latest market data from the database.

[1010] Step 3:

[1011] The server transmits the acquired data to the terminal.

[1012] Step 4:

[1013] The terminal displays market data received from the server and AI trading advice to the user.

[1014] Step 5:

[1015] The emotion engine analyzes the user's facial expressions and voice in real time to obtain emotional data.

[1016] Step 6:

[1017] The device will then adjust the advice provided by the AI ​​guide based on the emotional data.

[1018] Step 7:

[1019] Users can choose to follow AI advice or make their own trading decisions.

[1020] Step 8:

[1021] A user executes a trade by specifying the stock to be purchased or sold and the quantity.

[1022] Step 9:

[1023] The terminal transmits the user's trade instructions to the server.

[1024] Step 10:

[1025] The server processes the trade instructions to update the virtual market database and update the user's portfolio.

[1026] Step 11:

[1027] The server returns the updated portfolio data to the terminal.

[1028] Step 12:

[1029] The terminal displays the updated portfolio data to the user, allowing the user to confirm the trading results.

[1030] A community platform for improving financial literacy

[1031] Processing Steps

[1032] Step 1:

[1033] The device connects to the server using the user ID and requests the latest forum posts and Q&A data.

[1034] Step 2:

[1035] The server retrieves forum posts and Q&A data from a database.

[1036] Step 3:

[1037] The server transmits the acquired data to the terminal.

[1038] Step 4:

[1039] The terminal displays the latest community content to the user based on the data received from the server.

[1040] Step 5:

[1041] Users review forum posts and questions and make comments and replies as needed.

[1042] Step 6:

[1043] The emotion engine analyzes the user's facial expressions and voice in real time to obtain emotional data.

[1044] Step 7:

[1045] The terminal adjusts the content of communication based on the emotion data acquired by the emotion engine.

[1046] Step 8:

[1047] Users create new posts and questions in the community forums.

[1048] Step 9:

[1049] The terminal sends user posts and questions to the server.

[1050] Step 10:

[1051] The server stores the received posts and questions in a database.

[1052] Step 11:

[1053] The server notifies other users of new posts and questions and shares them with the entire community.

[1054] Step 12:

[1055] The server scores contributions based on the quality of posts and responses and emotional data, and awards points to users.

[1056] Step 13:

[1057] The server sends the updated points and rankings to the terminal.

[1058] Step 14:

[1059] The terminal displays the updated points and ranking to the user, allowing them to see their contribution to the community.

[1060] The above are the specific program processing steps for each system that incorporates an emotion engine. In each step, the operations performed by the server, terminal, and user have been explained in detail.

[1061] Example 2

[1062] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1063] Conventional financial literacy improvement systems have difficulty responding to the emotional state of each user, and have not been able to fully optimize learning effects and trading experiences. Such systems are unable to personalize based on the user's interests, level of understanding, or emotional changes, making it difficult to maintain learning motivation or effectively convey financial knowledge.

[1064] 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.

[1065] In this invention, the server includes means for communicating with a database that manages user progress information, means for generating learning content and providing it to the user, means for recognizing the user's emotions in real time and using that data, means for receiving quiz results and emotional data and storing them in the database, and means for automatically adjusting and preparing the next learning content based on the user's emotional state, thereby providing an effective and individually optimized learning experience that reflects the user's emotional state.

[1066] "User progress information" refers to data that indicates the progress and achievement level of a user when using learning content.

[1067] "Means for communicating with a database" means means having communication capabilities for accessing a database and retrieving or storing information.

[1068] "Means for generating learning content and providing it to users" refers to means for creating educational content and distributing it to users.

[1069] "Means for recognizing user emotions in real time and using that data" refers to means for detecting user emotions in real time and using that information to personalize the learning experience.

[1070] The "means for receiving quiz results and emotion data and storing them in a database" refers to a means for receiving the user's quiz answer results and emotion data and storing them in a database.

[1071] "Means for automatically adjusting and preparing the next learning content based on the user's emotional state" refers to a means for dynamically adjusting learning content based on the user's emotional data and preparing the optimal next item.

[1072] "Means for updating virtual market data" refers to means for updating virtual market information with the latest data.

[1073] "Means for managing a user's trading history and providing advice" means means for recording and managing a user's trading history and providing trading advice to the user based on that history.

[1074] "Means for receiving trade instructions and updating the database" refers to means for receiving trading instructions from users and updating the database accordingly.

[1075] The "means for displaying updated data to the user" refers to a means for displaying the latest data updated by the server to the user.

[1076] "Means for managing user posts and questions" refers to means for recording and managing content and questions posted by users.

[1077] "Means for managing responses from other users and experts" refers to means for recording and managing responses from other users and experts.

[1078] The "means for scoring contributions and awarding points" refers to a means for evaluating a user's actions and contributions and awarding points.

[1079] The "means for displaying points and rankings to the user" refers to a means for displaying the evaluated points and user rankings in a form visible to the user.

[1080] This invention combines a comprehensive system for improving young people's financial literacy with an emotion engine that recognizes user emotions. The system includes three main components: a microlearning financial app, an AI-guided virtual stock trading game app, and a financial literacy improvement community platform. Furthermore, the emotion engine recognizes users' emotions and optimizes the learning experience based on their emotions.

[1081] Microlearning Financial App

[1082] The purpose of microlearning financial apps is to enable users to learn financial knowledge in a short amount of time every day. Users access content delivered from a server using devices such as smartphones and tablets. An emotion engine also recognizes the user's emotions and personalizes the learning experience.

[1083] The server connects to the database using the user's ID, retrieves the latest learning progress data, and sends it to the device. The device then displays the next lesson content to the user based on the received data. At this time, the emotion engine recognizes emotions from the user's facial expressions and voice in real time to optimize the learning experience.

[1084] As a specific example, if a user is learning about "how credit cards work," the emotion engine analyzes the user's reactions while watching a three-minute lesson displayed on the device. If the user feels tired, the next lesson will be simplified, and if the user's attention is distracted, the interactive elements will be increased. After completing the lesson, the user answers a quiz, and the quiz results and emotion data are sent to the server and stored in a database.

[1085] Example prompt sentence:

[1086] "Generate a three-minute lesson on how credit cards work and provide a quiz based on user sentiment."

[1087] AI-guided virtual stock trading game app

[1088] The app aims to enable users to gain practical financial knowledge through virtual stock trading experiences. An AI guide provides trading advice, and an emotion engine recognizes users' emotions and provides appropriate feedback.

[1089] The server uses the user ID to retrieve the user's portfolio data and market data from the database and transmits them to the terminal. The terminal displays the received market data and AI advice to the user. The emotion engine recognizes the user's emotions in real time and adjusts the content of the advice.

[1090] For example, when a user purchases a company's stock, the AI ​​guide will advise them that "this stock is on an upward trend, so we recommend purchasing it." If the user feels unsure, the emotion engine will provide supplemental information to reduce the risk. Once the user decides to purchase and executes the transaction, the result is sent to the server and recorded in the database.

[1091] Example prompt sentence:

[1092] "Provide TechCorp stock trading advice and generate feedback based on sentiment data."

[1093] A community platform for improving financial literacy

[1094] The community platform provides a forum for users to share their knowledge and interact with other users and experts. It features forums, Q&A sections, online workshops, and an emotion engine that recognizes users' emotions to optimize communication.

[1095] The server uses the user ID to retrieve the latest forum posts and Q&A data and transmits it to the device. The device displays community content based on the received data, and the emotion engine recognizes the user's emotions in real time.

[1096] For example, if a user posts a question such as "I want to know about the risks of stock investment," other users and experts will provide answers. The emotion engine analyzes the user's emotions, and if there is a lot of positive feedback, the server will award points to the user. The ranking is updated and displayed on the device.

[1097] Example prompt sentence:

[1098] "Generate answers to questions about the risk of stock investments and provide a points system based on sentiment data."

[1099] These system functions allow users to effectively learn, practice, and share financial knowledge with other users. The incorporation of an emotion engine provides optimal learning experiences and communication according to the user's emotions.

[1100] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1101] Microlearning financial app processing steps

[1102] Step 1: Obtaining user progress data

[1103] Input: User ID

[1104] Processing: The server receives the user ID sent from the terminal and retrieves the user's latest learning progress data from the database.

[1105] Output: Learning progress data (e.g. last lesson studied, progress)

[1106] Specific behavior:

[1107] The server queries the database to retrieve the user ID and associated progress data (e.g., last lesson ID, completion percentage).

[1108] Step 2: View learning content and start emotion recognition

[1109] Input: Learning progress data

[1110] Processing: The device determines the content of the next lesson based on the learning progress data received from the server, and activates the emotion engine to recognize the user's emotions in real time.

[1111] Output: Display of learning content, emotion data

[1112] Specific behavior:

[1113] The device uses the progress data to display the next lesson (e.g., a video about how credit cards work), and the emotion engine uses the camera to begin analyzing the user's facial expressions.

[1114] Step 3: Personalize content and display quizzes

[1115] Input: Emotion data, learning content

[1116] Processing: The device adjusts the next learning content based on the data obtained from the emotion engine in real time, and displays a quiz after the lesson is completed.

[1117] Output: Personalized learning content, quizzes

[1118] Specific behavior:

[1119] If the user feels tired, the device will simplify the content of the next lesson and automatically display a quiz after the lesson.

[1120] Step 4: Send quiz results and sentiment data

[1121] Input: Quiz results, emotion data

[1122] Processing: The device sends the user's quiz results and emotion data to the server.

[1123] Output: Data sent to the server

[1124] Specific behavior:

[1125] When the quiz is over, the device sends the user's answer data and emotion data obtained through facial recognition to the server.

[1126] Step 5: Update the database and prepare for the next lesson

[1127] Input: Quiz results, emotion data

[1128] Processing: The server stores the received data in a database and determines the next learning content based on it.

[1129] Output: What to display next

[1130] Specific behavior:

[1131] The server analyzes the quiz results and emotional data and updates the database with the next lesson content.

[1132] AI-guided virtual stock trading game app processing steps

[1133] Step 1: Obtain portfolio and market data

[1134] Input: User ID

[1135] Processing: The server receives the user ID from the terminal, retrieves the user's latest portfolio data from the database, and also collects market data.

[1136] Output: Portfolio data, market data

[1137] Specific behavior:

[1138] The server retrieves the user's portfolio and the latest market prices from a database and external APIs.

[1139] Step 2: Getting started with AI advice and emotion recognition

[1140] Input: Portfolio data, market data

[1141] Processing: The terminal displays the received data, the AI ​​guide provides trading advice to the user, and the emotion engine simultaneously recognizes the user's emotions.

[1142] Output: trading advice, sentiment data

[1143] Specific behavior:

[1144] The device displays advice such as "TechCorp stock is on the rise, so we recommend buying," and the emotion engine detects the user's anxiety.

[1145] Step 3: Execute trades and update data

[1146] Input: trading instructions, sentiment data

[1147] Processing: The user buys or sells virtual stocks, and the instruction is sent to the server, which updates the database and returns the result to the terminal.

[1148] Output: Updated portfolio data

[1149] Specific behavior:

[1150] When a user issues a trade instruction, the instruction is sent from the terminal to the server, which updates the database and returns the portfolio.

[1151] Financial literacy improvement community platform processing steps

[1152] Step 1: Obtain community data

[1153] Input: User ID

[1154] Processing: The server retrieves forum posts and Q&A data from the database using the user ID received from the device.

[1155] Output: Community data

[1156] Specific behavior:

[1157] The server retrieves the latest forum threads and Q&A information from the database.

[1158] Step 2: View posts, questions, and answers and start emotion recognition

[1159] Input: Community Data

[1160] Processing: The device displays the received data, and the emotion engine recognizes the user's emotions in real time.

[1161] Output: Forum posts, questions and answers, sentiment data

[1162] Specific behavior:

[1163] A user checks the "latest posts about the risks of stock investment," and the sentiment engine analyzes the user's sentiment.

[1164] Step 3: Emotional feedback and data storage

[1165] Input: Post content, emotion data

[1166] Processing: The server stores the post, response data, and sentiment data in a database and updates the user's points and ranking.

[1167] Output: Updated points, rankings

[1168] Specific behavior:

[1169] If a user receives a lot of positive feedback, the server will award points to the user and update their ranking.

[1170] Step 4: View your points and rankings

[1171] Input: Updated data

[1172] Processing: The terminal displays the points and ranking received from the server to the user.

[1173] Output: points, ranking

[1174] Specific behavior:

[1175] Based on the points the user has earned, a new ranking is displayed for the user to check.

[1176] (Application example 2)

[1177] 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."

[1178] There is a lack of effective ways for today's young people to improve their financial literacy. Furthermore, traditional learning systems are unable to personalize the learning experience based on the user's interests and emotions, resulting in poor learning efficiency. Since acquiring knowledge related to electronic payments is particularly relevant to daily life, it is necessary to optimize the learning experience.

[1179] 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.

[1180] In this invention, the server includes means for communicating with a database that manages user progress information, means for generating learning content and providing it to the user, means for receiving quiz results and saving them in the database, means for automatically preparing the next learning content, and means for recognizing the user's emotions and optimizing the learning experience based on those emotions. This allows the user to effectively learn financial knowledge through everyday electronic payments and provides an optimal learning experience tailored to their emotions.

[1181] "User progress information" is data that records and manages the progress of a user when studying.

[1182] A "database" is a system for storing information in an organized manner and for efficiently retrieving and updating it.

[1183] "Means of communication" refers to the technical methods and devices used to transmit and receive data between the database and the server.

[1184] "Learning Content" means educational materials, information, or lessons provided to Users to improve their financial literacy.

[1185] A "generation means" is a technology or device that creates learning content based on specific conditions.

[1186] "Means for providing" refers to the technology or devices used to display, notify, or transmit learning content to users.

[1187] "Quiz results" refers to the scores and answer data for a quiz that a user takes after studying the learning content.

[1188] "Next learning content" refers to the next learning material or information selected based on the user's current learning progress and quiz results.

[1189] "Automatic preparation means" refers to technology or devices that allow the system to automatically select and provide the next learning content based on the user's progress data and emotional data.

[1190] "Means for recognizing emotions" refers to technologies and devices for detecting and identifying a user's emotional state from facial expressions, voice, actions, etc.

[1191] "Means for optimizing the learning experience" refers to technologies and devices that adjust the content and methods of learning according to the user's emotional state and progress, thereby enabling effective learning.

[1192] "Virtual Market Data" means simulated stock market data and information.

[1193] "Trade history" refers to historical data of virtual stock trades made by a user.

[1194] "Means for providing advice" refers to technology or devices that provide appropriate trading advice based on a user's trading history and emotional data.

[1195] A "trade instruction" is an instruction or command for a user to buy or sell virtual stock.

[1196] "Means for updating" refers to techniques or devices that update the data in the database based on received trade instructions.

[1197] "Posts and Questions" are texts or messages that a User uses to share knowledge or raise questions with other Users or Experts on the Community Platform.

[1198] The "answer management means" refers to a technology or device that collects and organizes answers provided by users and experts and provides them to users.

[1199] "Contribution scoring means" refers to technology or devices that evaluate the quality of posts and responses made by users on the platform and award points to them.

[1200] "Means for awarding points" refers to the technology or device that awards points on the system according to the user's level of contribution.

[1201] The "means for displaying rankings" refers to a technique or device that creates rankings based on the points acquired by users and displays them to users.

[1202] "Communication optimizers" are technologies and devices that recognize users' emotions and effectively adjust community interactions accordingly.

[1203] The present invention relates to a technology for optimizing learning experiences by recognizing emotions in a system that manages user progress information, generates and provides learning content, and stores quiz results. It also includes a method for managing virtual market data and trading history, providing appropriate advice to users, and optimizing communication in a community platform.

[1204] System configuration

[1205] The system of the present invention consists of the following main components:

[1206] 1. Progress information management

[1207] The server has a means for communicating with a database that manages user progress information, including the user's learning progress and quiz results.

[1208] 2. Creation and provision of learning content

[1209] The server generates learning content and provides it to users, who access it via devices such as smartphones and tablets.

[1210] 3. Receiving and storing quiz results

[1211] The device sends the quiz results to the server, which stores them in a database, and the next learning content is automatically prepared.

[1212] 4. Emotion Recognition and Optimization

[1213] The server has the means to recognize the user's emotions and optimize the learning experience based on those emotions, using camera and voice analysis.

[1214] Virtual Market Data and Trading Advice

[1215] The server updates virtual market data and manages users' trading history. It receives trading instructions, updates the database, and adjusts advice based on sentiment. Users can use their terminals to buy and sell virtual stocks and view updated data.

[1216] Community Platform

[1217] The server manages user posts and questions, manages answers from other users and experts, scores contributions and awards points, and optimizes communication based on user sentiment data.

[1218] Hardware and Software

[1219] The specific hardware and software used to implement this system includes:

[1220] Hardware: smartphones, tablets, smart glasses, cameras.

[1221] Software: OpenCV (real-time video capture and processing), EmotionRecognition module (emotion recognition), FinancialAnalysis module (expense analysis), QuizGame module (quiz game).

[1222] Specific examples

[1223] When a user makes an electronic payment at a cafe using their smartphone, the app records the transaction and displays a message saying, "You spend a lot at cafes every month. Why not try enjoying coffee at home a few times a month?" If the user's facial expressions and voice indicate they are "interested," the app provides a detailed analysis of their cafe spending and a mini-game on how to reduce coffee costs.

[1224] Prompt Sentence Examples

[1225] Here are some examples of prompts for generative AI models:

[1226] text

[1227] When a user makes an electronic payment at a cafe, if their facial expression is recognized as "curious," provide a detailed analysis of their spending at the cafe and a mini-game based on that analysis. Implement a recommendation system that displays a warning if the user has spent more than a certain number of times at a cafe and suggests ways to save money. Cover the following items:

[1228] 1. Camera-based facial expression recognition.

[1229] 2. Analysis of historical expenditure data.

[1230] 3. Providing advice and mini-games based on the user's emotions.

[1231] This allows users to effectively learn financial knowledge through everyday electronic payments, providing an optimal learning experience that responds to their emotions.

[1232] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1233] Step 1:

[1234] The device activates the camera and captures the user's video. The input is video data from the camera. The device processes this video data in real time and recognizes emotions from the user's facial expressions and voice. OpenCV face detection and the EmotionRecognition module are used here. The output is the user's emotional data (e.g., curious, tired, etc.).

[1235] Step 2:

[1236] The device sends the user's emotional data to the server. The input is the emotional data obtained in step 1 above. The server receives this data and uses it to generate the next learning content in comparison with the user's current learning progress data. The server generates the learning content. The output is personalized learning content based on the emotional data and progress data.

[1237] Step 3:

[1238] The server sends the generated learning content to the terminal. The input is the learning content generated on the server. The terminal receives it and displays it on the interface. The output is the learning content that the user views.

[1239] Step 4:

[1240] The user watches the learning content provided on the device and answers the quiz questions. The input is the user's learning behavior and quiz answer data. The device collects this data and sends it to the server. The output is the user's quiz answer results.

[1241] Step 5:

[1242] The server receives the user's quiz answer results and stores them in a database. The input is the quiz answer results sent from the terminal. The server stores them in the database and begins preparing the next learning content. The output is the user's quiz results stored in the database.

[1243] Step 6:

[1244] When a user makes an everyday electronic payment, the terminal automatically captures the payment information and sends it along with emotional data to a server. The input is the electronic payment transaction data and emotional data. The server receives this data and performs a comparative analysis with past spending data. The output is the analysis results.

[1245] Step 7:

[1246] The server generates appropriate advice and warning messages based on the analysis results and sends them to the terminal. The input is the analysis results of the expenditure data performed on the server. The terminal displays this to the user. The output is advice and warning messages regarding the user's expenditures.

[1247] Step 8:

[1248] The device then recognizes the user's emotions again and uses them to inform the next step of learning or advice. This process continues as a loop. The input is updated emotional data, and the output is emotional data that will be reflected in the next learning content or advice.

[1249] In this way, the system uses users' emotional data to individually optimize their learning experience and feedback on everyday electronic payments, effectively improving financial literacy.

[1250] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1251] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1252] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1253] [Third embodiment]

[1254] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1255] 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.

[1256] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1257] 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.

[1258] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1259] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1260] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1261] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1262] 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.

[1263] 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.

[1264] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1265] 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."

[1266] The present invention is a comprehensive system for improving financial literacy among young people. The system includes three main components: a micro-learning financial app, an AI-guided virtual stock trading game app, and a financial literacy community platform.

[1267] Microlearning Financial App

[1268] System Overview:

[1269] The purpose of microlearning financial apps is to enable users to learn financial knowledge in a short amount of time every day. Users access content delivered from a server using devices such as smartphones and tablets.

[1270] Process flow:

[1271] The device connects to the server using the user ID and requests the latest learning progress data. The server retrieves the user's progress information from the database and sends it to the device.

[1272] The terminal displays the next lesson content to the user based on the data received from the server. The user watches the lesson provided on the screen and progresses with their learning.

[1273] After completing a lesson, the user answers a quiz. The device sends the quiz results to the server, which stores them in a database. The next lesson is then automatically prepared.

[1274] Examples:

[1275] If a user wants to learn about "How Credit Cards Work," they can watch a three-minute lesson on their device, take a quiz, and then the results of the quiz will be sent to the server, which will then automatically prepare the next lesson on "Loans and Interest Rates."

[1276] AI-guided virtual stock trading game app

[1277] System Overview:

[1278] The app aims to enable users to gain practical financial knowledge through virtual stock trading experiences. An AI guide provides users with trading advice, allowing them to acquire trading skills without any risk.

[1279] Process flow:

[1280] The terminal connects to the server using the user ID and requests the latest portfolio data and market data. The server retrieves the user's portfolio data and market data from the database and sends them to the terminal.

[1281] The terminal receives market data and AI advice from the server and displays it to the user, who then uses the advice to buy or sell virtual stocks.

[1282] Trade instructions are sent to the server, trade results are recorded in a database, and updated portfolio data is sent to the terminal and displayed to the user.

[1283] Examples:

[1284] If a user decides to buy TechCorp stock, the AI ​​guide will advise them that "TechCorp stock is on an upward trend, so we recommend buying it." Once the user decides to buy and executes the trade, the results are sent to the server and recorded in the database. The portfolio after the trade is displayed on the terminal.

[1285] A community platform for improving financial literacy

[1286] System Overview:

[1287] The community platform allows users to share their knowledge and interact with other users and experts, and includes features such as forums, Q&A sections, and online workshops.

[1288] Process flow:

[1289] The device accesses the server using the user ID and requests the latest forum posts and Q&A data. The server retrieves the necessary data from the database and sends it to the device.

[1290] The device displays the latest community content to the user based on the data received from the server. The user posts on forums or asks questions and waits for answers from other users or experts.

[1291] Posts and replies are sent to the server and recorded in a database. The server evaluates the quality of the post and reply and awards points to the user. The terminal displays the user's points and ranking.

[1292] Examples:

[1293] When a user posts a question such as "I want to know about the risks of stock investment," other users and experts will provide answers. Users who post high-quality answers will be awarded points by the server, and their rankings will be updated.

[1294] These system features allow users to effectively learn, practice, and share financial knowledge with other users.

[1295] The processing flow will be explained below.

[1296] Microlearning Financial App

[1297] Processing Steps

[1298] Step 1:

[1299] The device connects to the server using the user ID and requests the user's latest learning progress data.

[1300] Step 2:

[1301] The server searches the database based on the received user ID and obtains the user's latest learning progress information.

[1302] Step 3:

[1303] The server transmits the acquired learning progress data to the terminal.

[1304] Step 4:

[1305] The terminal displays the next lesson content to the user based on the data received from the server.

[1306] Step 5:

[1307] The user watches and listens to the lessons displayed on the screen and progresses through the learning process.

[1308] Step 6:

[1309] The terminal displays a quiz to the user after the lesson is completed.

[1310] Step 7:

[1311] The user answers the quiz and inputs the answer into the terminal.

[1312] Step 8:

[1313] The terminal transmits the answer to the quiz to the server.

[1314] Step 9:

[1315] The server stores the quiz results in a database and automatically prepares the next learning content.

[1316] AI-guided virtual stock trading game app

[1317] Processing Steps

[1318] Step 1:

[1319] The terminal connects to the server using the user ID and requests the latest portfolio and market data.

[1320] Step 2:

[1321] The server retrieves the user's portfolio data and the latest market data from the database.

[1322] Step 3:

[1323] The server transmits the acquired data to the terminal.

[1324] Step 4:

[1325] The terminal displays market data received from the server and AI trading advice to the user.

[1326] Step 5:

[1327] Users can choose to follow AI advice or make their own trading decisions.

[1328] Step 6:

[1329] A user executes a trade by specifying the stock to be purchased or sold and the quantity.

[1330] Step 7:

[1331] The terminal transmits the user's trade instructions to the server.

[1332] Step 8:

[1333] The server processes the trade instructions to update the virtual market database and update the user's portfolio.

[1334] Step 9:

[1335] The server returns the updated portfolio data to the terminal.

[1336] Step 10:

[1337] The terminal displays the updated portfolio data to the user, allowing the user to confirm the trading results.

[1338] A community platform for improving financial literacy

[1339] Processing Steps

[1340] Step 1:

[1341] The device connects to the server using the user ID and requests the latest forum posts and Q&A data.

[1342] Step 2:

[1343] The server retrieves forum posts and Q&A data from a database.

[1344] Step 3:

[1345] The server transmits the acquired data to the terminal.

[1346] Step 4:

[1347] The terminal displays the latest community content to the user based on the data received from the server.

[1348] Step 5:

[1349] Users review forum posts and questions and make comments and replies as needed.

[1350] Step 6:

[1351] Users create new posts and questions in the community forums.

[1352] Step 7:

[1353] The terminal transmits user posts and questions to the server.

[1354] Step 8:

[1355] The server stores the received posts and questions in a database.

[1356] Step 9:

[1357] The server notifies other users of new posts and questions and shares them with the entire community.

[1358] Step 10:

[1359] The server scores the contribution of posts and replies and awards points to users.

[1360] Step 11:

[1361] The server updates the total points and ranking and sends them to the terminal.

[1362] Step 12:

[1363] The terminal displays the updated points and ranking to the user, allowing them to see their contribution to the community.

[1364] The above are the specific program processing steps in each system. We have explained in detail what operations the server, terminal, and user perform in each step.

[1365] Example 1

[1366] 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."

[1367] Traditional financial literacy education systems have struggled to provide personalized learning experiences based on users' progress. Virtual stock trading and community platforms also lack the appropriate advice and feedback to maximize users' learning outcomes. Furthermore, effective communication methods for sharing learned knowledge are often lacking.

[1368] 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.

[1369] In this invention, the server includes: means for communicating with a database that manages user progress information; means for generating learning content and providing it to the user; means for receiving quiz results and saving them in the database; means for automatically preparing the next learning content; means for customizing the next lesson content based on the user's individual learning history; and means for connecting to the server from a device such as a smartphone or tablet and requesting progress information. This allows users to efficiently take learning content that is tailored to their individual needs, improving learning effectiveness. The server also includes means for updating virtual market data, means for managing the user's trading history and providing advice, means for receiving trading instructions and updating the database, means for displaying the updated data to the user, means for displaying the latest market data and advice from the AI ​​guide to the user, and means for recording the user's virtual trading results in the database, allowing users to acquire practical trading skills without risk. Furthermore, the server includes means for managing user posts and questions, means for managing answers from other users and experts, means for scoring contributions and awarding points, means for displaying the points and rankings to users, means for requesting forum posts and Q&A data to display the latest community content, and means for evaluating the quality of posts and answers and awarding points, thereby promoting knowledge sharing and interaction among users and increasing motivation to learn and a sense of accomplishment.

[1370] A "database for managing user progress information" is a data storage system that stores information for recording and managing what a user has learned and their progress.

[1371] A "means for generating and providing learning content to users" is a system or method for creating new educational material based on the user's needs and learning history and delivering it to the user in an accessible format.

[1372] "Means for receiving quiz results and storing them in a database" refers to a system or method by which the server receives the results of the quiz answered by the user after studying and records them in a management database.

[1373] "Means for automatically preparing the next learning content" refers to a system or method that automatically selects and prepares the next learning content based on the user's learning progress and quiz results.

[1374] "Means for customizing the next lesson content based on the user's individual learning history" refers to a system or method that analyzes each user's past learning data and provides the most appropriate learning content individually based on that data.

[1375] "Means for connecting to a server from a terminal such as a smartphone or tablet and requesting progress information" refers to a system or method for connecting to a server using a mobile device and obtaining learning progress information from there.

[1376] A "means for updating virtual market data" is a system or method for periodically updating data to keep virtual financial market information current.

[1377] A "means for managing a user's trading history and providing advice" is a system or method for recording a user's virtual trading activity and providing advice on financial trading based thereon.

[1378] The "means for receiving trade instructions and updating the database" refers to a system or method for receiving information when a user issues a virtual trade instruction and updating the database.

[1379] The "means for displaying updated data to the user" refers to a system or method for displaying the latest virtual market information, the user's trading results, etc. on the user's device screen.

[1380] "Means for displaying the latest market data and advice from an AI guide to users" refers to a system or method that obtains the latest market information and provides users with AI-generated financial advice based on that information.

[1381] The "means for recording the results of a user's virtual trade in a database" refers to a system or method for storing the results of a virtual trade executed by a user in a database.

[1382] "Means for managing user posts and questions" refers to a system or method for processing and appropriately managing information and questions posted by users on the community platform.

[1383] "Means for managing responses from other users and experts" refers to a system or method for receiving and managing responses from other users and experts on the community platform.

[1384] "Means for scoring contributions and awarding points" refers to a system or method for evaluating the quality of users' posts and replies and awarding points accordingly.

[1385] The "means for displaying points and rankings to the user" refers to a system or method for visualizing the points and rankings earned by the user and displaying them on the user's device.

[1386] A "means for requesting forum posts and Q&A data to display the most recent community content" is a system or method that automatically retrieves the most recent posts to a forum or Q&A section and displays them to the user.

[1387] The "means for evaluating the quality of posts and replies and awarding points" refers to a system or method for evaluating the content of posts and replies made by users and awarding points according to their contribution.

[1388] MODE FOR CARRYING OUT THE INVENTION

[1389] The present invention is a comprehensive system for improving financial literacy among young people. The system includes three main components: a micro-learning financial app, an AI-guided virtual stock trading game app, and a financial literacy community platform.

[1390] Microlearning Financial App

[1391] System Overview:

[1392] The purpose of microlearning financial apps is to enable users to learn financial knowledge in a short amount of time every day. Users access content delivered from a server using devices such as smartphones and tablets.

[1393] Hardware and software used:

[1394] Mobile devices such as smartphones and tablets

[1395] Server (progress database, content distribution system)

[1396] Internet Connectivity Infrastructure

[1397] Specific data processing and calculation:

[1398] When a user launches the app, the server retrieves the user's learning progress information from the progress database and sends it to the device. The device uses this data to display the next lesson content to the user. When the user completes their learning and answers a quiz, the results are sent to the server and stored in the database. The server automatically selects and prepares the next learning content based on the user's progress.

[1399] Examples:

[1400] When a user learns about "How Credit Cards Work," the device retrieves the relevant lesson video from the server and displays it. After the lesson, the user answers a quiz, and the results are sent to the server, which then prepares the next lesson on "Loans and Interest Rates."

[1401] Example prompt sentence:

[1402] Please state the conditions for selecting the content of your next lesson.

[1403] AI-guided virtual stock trading game app

[1404] System Overview:

[1405] The app aims to enable users to gain practical financial knowledge through virtual stock trading experiences. An AI guide provides users with trading advice, allowing them to acquire trading skills without any risk.

[1406] Hardware and software used:

[1407] Mobile devices such as smartphones and tablets

[1408] Server (portfolio database, AI guide system, market database)

[1409] Internet Connectivity Infrastructure

[1410] Specific data processing and calculation:

[1411] When a user logs in, the terminal connects to the server using the user ID and retrieves the latest portfolio and market data. The server then retrieves this data from the database and displays it to the user. An AI guide also provides advice based on market data, and the user purchases or sells virtual stocks. After the trade is executed, the results are sent to the server and recorded in the database.

[1412] Examples:

[1413] If a user were to hypothetically buy TechCorp shares, the terminal would retrieve market data and AI-guided advice from the server and display it. Once the user decides to buy and executes the trade, the information is sent to the server for recording, and the new portfolio is displayed on the terminal.

[1414] Example prompt sentence:

[1415] "Please explain the circumstances under which you would recommend buying or selling TechCorp stock."

[1416] A community platform for improving financial literacy

[1417] System Overview:

[1418] The platform allows users to share their knowledge and interact with other users and experts, and includes features such as forums, Q&A sections, and online workshops.

[1419] Hardware and software used:

[1420] Devices such as smartphones, tablets, and PCs

[1421] Server (community database, posting management system)

[1422] Internet Connectivity Infrastructure

[1423] Specific data processing and calculation:

[1424] The device connects to the server using the user ID to retrieve the latest forum posts and Q&A data. The server retrieves this data from the database and sends it to the device. Users can post to the forum or ask questions and wait for answers from other users or experts. The posts and answers are sent to the server and recorded in the database. The server then evaluates the quality of these posts and answers and assigns points. The device then displays the points and rankings to the user.

[1425] Examples:

[1426] When a user posts a question about the risks of stock investment on the community platform, other users and experts respond. The server records the responses, evaluates the quality of the responses, and awards points. The terminal then displays the points and rankings to the user.

[1427] Example prompt sentence:

[1428] "Create the best answer to the question about the risks of stock investment."

[1429] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1430] Microlearning Financial App

[1431] Processing flow

[1432] Step 1:

[1433] Server connection by user ID

[1434] When a user launches the app, the device connects to the server using the user ID stored in the device.

[1435] Input: User ID

[1436] Data processing: The server receives the user ID and sends a query to the database to retrieve the learning progress data of the user.

[1437] Output: User's learning progress data

[1438] Specific operation: The server retrieves the user's progress information from the database and sends it to the device.

[1439] Step 2:

[1440] View lesson content

[1441] The terminal displays the next lesson content to the user based on the received learning progress data.

[1442] Input: Learning progress data received from the server

[1443] Data processing: The device analyzes the progress data and determines the next lesson content to display.

[1444] Output: Lesson content (e.g. video, text)

[1445] Specific operation: The device displays the next lesson content on the screen and the user begins learning.

[1446] Step 3:

[1447] Quiz Answers and Results Submission

[1448] The user answers a quiz that is displayed after the lesson is completed.

[1449] Input: User's quiz answer

[1450] Data processing: The terminal receives the user's answers and sends the results to the server.

[1451] Output: Quiz results

[1452] Specific operation: The device sends the quiz results to the server, which stores them in a database.

[1453] AI-guided virtual stock trading game app

[1454] Processing flow

[1455] Step 1:

[1456] Portfolio and Market Data Requests

[1457] When a user logs in, the terminal connects to the server using the user ID and requests the latest portfolio and market data.

[1458] Input: User ID

[1459] Data processing: The server retrieves portfolio data and market data from the database based on the user ID.

[1460] Output: Portfolio data, latest market data

[1461] Specific operation: The server sends the data retrieved from the database to the terminal.

[1462] Step 2:

[1463] Display market data and AI advice

[1464] The terminal displays the received market data and advice from the AI ​​guide to the user.

[1465] Inputs: Portfolio data, latest market data, AI advice

[1466] Data processing: The terminal analyzes the received market data and AI advice and presents appropriate information to the user.

[1467] Output: Market status and trading advice

[1468] Specific operation: The device displays market conditions and AI-guided advice to the user.

[1469] Step 3:

[1470] Trading instructions and results recording

[1471] A user trades (buys or sells) virtual stocks.

[1472] Input: User's trading instructions

[1473] Data processing: The terminal sends trade instructions to the server, which records the information in a database.

[1474] Output: Updated portfolio data

[1475] Specific operation: After the results of the trade are recorded in the database, the updated portfolio data is sent to the terminal.

[1476] A community platform for improving financial literacy

[1477] Processing flow

[1478] Step 1:

[1479] Requesting forum posts and Q&A data

[1480] The device accesses the server using the user ID and requests the latest forum posts and Q&A data.

[1481] Input: User ID

[1482] Data processing: The server retrieves the latest forum posts and Q&A data from the database based on the user ID.

[1483] Output: Forum post data, Q&A data

[1484] Specific operation: The server sends the acquired data to the terminal.

[1485] Step 2:

[1486] View community content and user activity

[1487] The terminal displays the latest community content to the user based on the received data.

[1488] Input: Forum post data, Q&A data

[1489] Data processing: The device analyzes the received data and selects and displays the latest content.

[1490] Output: Forum content, Q&A content to be displayed

[1491] What it does: The device displays recent posts and questions and answers on the screen, and users post and ask questions in the forum.

[1492] Step 3:

[1493] Recording and rating posts and responses

[1494] When a post or question is made, the device sends the content to the server.

[1495] Input: New post data, question and answer data

[1496] Data processing: The server records the received data in a database and evaluates its quality.

[1497] Output: Updated forum data, quality evaluation results, point data

[1498] Specific operation: The server stores posts and answers in a database and assigns points based on quality. The terminal displays the points and ranking to the user.

[1499] (Application example 1)

[1500] 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."

[1501] In recent years, low financial literacy among young people has become a problem. In particular, purchasing behavior on online shopping sites tends to be impulsive, leading to a lack of budget management. In such circumstances, young people find it difficult to make financial forecasts and are prone to long-term financial risk. Therefore, a system is needed to improve financial literacy in real time through online shopping site purchasing behavior, and to provide appropriate purchasing advice and budget management.

[1502] 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.

[1503] In this invention, the server includes means for communicating with a database that manages user progress information, means for generating study content and providing it to the user, means for receiving quiz results and saving them in the database, means for automatically preparing the next study content, means for receiving the user's purchasing data and providing purchasing advice within a budget, and means for updating post-purchase budget data and saving it in the database. This allows users to manage their budget while receiving appropriate financial advice in real time through their purchasing behavior on the online shopping site.

[1504] "User progress information" refers to the status and history achieved by the user in processes such as learning and purchasing.

[1505] A "database" is a system for managing information efficiently and consistently, storing, retrieving, and updating data.

[1506] "Learning Content" refers to educational materials and teaching materials provided to users to improve their financial literacy.

[1507] "Quiz results" refers to information on the results of a user's answers to a quiz-style test.

[1508] "Next learning content" refers to the next step of education provided based on the user's current learning situation and progress.

[1509] "User purchase data" refers to information about purchases made by a user on an online shopping site, such as the product name, purchase price, and purchase date and time.

[1510] "Buying advice within a budget" refers to recommendations and suggestions regarding what purchasing behavior a user should take within their budget.

[1511] "Post-purchase budget data" refers to information regarding the remaining budget after a user has completed a particular purchase.

[1512] "Virtual market data" refers to data of a virtual investment environment that simulates actual market data.

[1513] "User's trading history" refers to a record of transactions that a User has made in the virtual or real markets.

[1514] "Trade Instructions" refers to specific commands given by a user to buy or sell stocks or other financial instruments.

[1515] "User posts and questions" refers to information shared or questions expressed by users on the community platform.

[1516] "Responses from other users and experts" refers to information and advice provided in response to a user's post on the community platform.

[1517] "Scoring contribution" refers to users rating their activities on the community platform.

[1518] "Awarding points" refers to giving points as a reward for a user's community activities.

[1519] "Points and ranking" refers to the numerical value of the user's activity evaluation and the user's ranking generated based on that numerical value.

[1520] This invention is a comprehensive system for improving users' financial literacy, and is composed of the following major components:

[1521] System configuration

[1522] The system consists of the following main components:

[1523] 1. A database that manages user progress information:

[1524] The server maintains a database that centrally manages user progress information, including the user's learning activities, quiz results, purchase history, and budget information, and updates the database as needed.

[1525] 2. Learning content generation and delivery:

[1526] The server generates financial education learning content to be provided to users and provides it to devices such as smartphones and tablets. The learning content is personalized based on the user's progress.

[1527] 3. Receiving and storing quiz results:

[1528] The server receives the results of the user's answers to the quiz accompanying the learning content, stores them in a database, and automatically prepares the next learning content based on this data.

[1529] 4. Receiving purchasing data and providing budget advice:

[1530] When a user purchases a product on an online shopping site, the server receives the purchase data (product name, price, date and time, etc.) and provides appropriate purchasing advice within the user's budget based on this purchase data and the user's budget information.

[1531] 5. Update budget data after purchase:

[1532] After the purchase, the server updates the user's budget data and stores it in the database, realizing real-time budget management.

[1533] 6. Virtual Market Data and Trade History Management:

[1534] The server manages data on users' transactions in the virtual market and provides trading advice based on this data, allowing users to experience stock trading risk-free and gain practical financial knowledge.

[1535] 7. Maintaining the Community Platform:

[1536] The server manages user posts and questions, as well as answers from other users and experts. It scores the contribution of posts and answers, awards points, and displays them to users.

[1537] Hardware and Software Details

[1538] Hardware: smartphones, tablets, servers

[1539] Software: Flask (Python web framework), SQLite (database management)

[1540] Specific examples

[1541] For example, consider a situation where a user is trying to purchase a pair of sneakers for 10,000 yen on an online shopping site. In this case, the server first retrieves the user's budget information from the database and evaluates in real time whether the purchase is within budget. If the purchase is within budget, the server provides advice recommending the purchase and updates the budget data after the purchase. This series of steps allows the user to manage their budget in real time.

[1542] Prompt Sentence Examples

[1543] Build a smartphone app that manages a user's budget when purchasing certain items. When a user attempts to purchase an item, the app will receive the user ID and the item's price as input. It will then retrieve the user's remaining budget from the database and check whether the purchase is within the budget. The budget will also be updated after the purchase and the user will be notified. Please also provide an example program using Flask and SQLite.

[1544] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1545] Step 1:

[1546] The server receives a product purchase request from the user. The user ID and product price information are provided as input. Based on this, the server processes the data to retrieve the user's current budget information from the database. The output is the retrieved user's budget information.

[1547] Step 2:

[1548] The server compares the acquired budget information with the product price and performs data calculations to determine whether the purchase is possible within the budget. Specifically, the server subtracts the product price from the user's remaining budget, and if the result is 0 or greater, it recommends the purchase, and if it is less than 0, it notifies the user that the budget is exceeded. The input is the user's budget information and product price, and the output is advice information such as "purchase possible" or "over budget."

[1549] Step 3:

[1550] The terminal receives advice information from the server and displays it to the user, allowing the user to decide whether to proceed with the purchase. Specifically, the terminal displays the received advice on the screen and waits for the user's next action. The input is advice information from the server, and the output is the screen display.

[1551] Step 4:

[1552] When the user decides to make a purchase, the device sends that decision to the server. The server receives this information and performs data calculations to update the user's budget information. Specifically, the server subtracts the product price from the user's remaining budget and saves the updated budget data in the database. The input is the user's purchase intention and product price, and the output is the updated user's budget data.

[1553] Step 5:

[1554] The server sends confirmation of the purchase completion to the terminal. The terminal receives this information and notifies the user that the purchase is complete. Specifically, the terminal displays a "Purchase Complete" message on the screen and notifies the user that the budget has been updated. The input is the purchase completion notification from the server, and the output is the screen display.

[1555] Through these steps, users can receive budget management and financial advice in real time through their purchasing behavior on the online shopping site.

[1556] When generating a description using keywords from a generative AI model, the following prompts can be used:

[1557] "Build a smartphone app that manages a user's budget when purchasing certain products. When a user tries to purchase an item, the app will receive the user ID and the product price as input. It will then retrieve the user's remaining budget from a database and check whether the purchase is within the budget. The budget will also be updated after the purchase and the user will be notified. Please also provide an example program using Flask and SQLite."

[1558] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1559] This invention combines a comprehensive system for improving young people's financial literacy with an emotion engine that recognizes user emotions. The system includes three main components: a microlearning financial app, an AI-guided virtual stock trading game app, and a financial literacy improvement community platform. Furthermore, the emotion engine recognizes users' emotions and optimizes the learning experience based on their emotions.

[1560] Microlearning Financial App

[1561] System Overview:

[1562] The purpose of microlearning financial apps is to enable users to learn financial knowledge in a short amount of time every day. Users access content delivered from a server using devices such as smartphones and tablets. An emotion engine also recognizes the user's emotions and personalizes the learning experience.

[1563] Process flow:

[1564] The device connects to the server using the user ID and requests the latest learning progress data. The server retrieves the user's progress information from the database and sends it to the device.

[1565] The device displays the next lesson content to the user based on the data received from the server. The user continues learning by watching the lesson provided on the screen while their emotions are recognized in real time by the emotion engine.

[1566] The learning content is adapted based on the user's emotions: for example, if the user is feeling tired, the content is simplified, and if the user is perceived as easily distracted, the interactive elements are increased.

[1567] After completing the lesson, the user answers a quiz. The device sends the quiz results and emotion data to the server, which stores them in a database. The next lesson is then automatically prepared.

[1568] Examples:

[1569] For example, if a user wants to learn about "How Credit Cards Work," they watch a three-minute lesson displayed on their device and answer a quiz. The emotion engine assesses in real time whether the user is enjoying the lesson and deepening their understanding, and automatically prepares the next lesson on "Loans and Interest Rates" at the appropriate difficulty level.

[1570] AI-guided virtual stock trading game app

[1571] System Overview:

[1572] The app aims to enable users to gain practical financial knowledge through virtual stock trading experiences. An AI guide provides trading advice, and an emotion engine recognizes users' emotions and provides appropriate feedback.

[1573] Process flow:

[1574] The terminal connects to the server using the user ID and requests the latest portfolio data and market data. The server retrieves the user's portfolio data and market data from the database and sends them to the terminal.

[1575] The terminal receives market data and AI advice from the server and displays it to the user. The user then buys or sells virtual stocks based on the advice, which is based on sentiment analysis by the emotion engine.

[1576] The advice is tailored depending on the user's emotions: for example, if the user is feeling anxious, low-risk, conservative advice is offered.

[1577] Trade instructions are sent to the server, trade results are recorded in a database, and updated portfolio data is sent to the terminal and displayed to the user.

[1578] Examples:

[1579] If a user decides to buy TechCorp stock, the AI ​​guide will advise them that "TechCorp stock is on an upward trend, so we recommend buying." If the user feels unsure, the emotion engine will provide supplemental information to reduce the risk. Once the user decides to purchase and executes the trade, the results are sent to the server and recorded in the database. The portfolio after the trade is displayed on the terminal.

[1580] A community platform for improving financial literacy

[1581] System Overview:

[1582] The community platform provides a forum for users to share their knowledge and interact with other users and experts. It features forums, Q&A sections, online workshops, and an emotion engine that recognizes users' emotions to optimize communication.

[1583] Process flow:

[1584] The device accesses the server using the user ID and requests the latest forum posts and Q&A data. The server retrieves the necessary data from the database and sends it to the device.

[1585] The device displays the latest community content to the user based on the data received from the server. The user can post forums or ask questions, and wait for answers from other users and experts, while the emotion engine recognizes emotions in real time.

[1586] The community's scoring is adjusted based on the user's sentiment: for example, if a user feels satisfied, they will provide high-quality answers and receive more points.

[1587] Posts and answers are sent to the server and recorded in a database. The server evaluates the quality of the post and answer and awards points to the user. Updated points and rankings are sent to the device.

[1588] Examples:

[1589] When a user posts a question such as "I want to know about the risks of stock investment," other users and experts provide answers. The emotion engine analyzes the user's emotions, and if there is a lot of positive feedback, the server increases the points. The ranking is updated and displayed on the device.

[1590] These system features allow users to effectively learn, practice, and share financial knowledge with others. The incorporation of an emotion engine further enhances learning and trading experiences by optimizing according to users' emotions.

[1591] The processing flow will be explained below.

[1592] Microlearning Financial App

[1593] Processing Steps

[1594] Step 1:

[1595] The device connects to the server using the user ID and requests the user's latest learning progress data.

[1596] Step 2:

[1597] The server searches the database based on the received user ID and obtains the user's latest learning progress information.

[1598] Step 3:

[1599] The server transmits the acquired learning progress data to the terminal.

[1600] Step 4:

[1601] The terminal displays the next lesson content to the user based on the data received from the server.

[1602] Step 5:

[1603] The user watches and learns lessons presented on the screen.

[1604] Step 6:

[1605] The emotion engine analyzes the user's facial expressions and voice in real time to obtain emotional data.

[1606] Step 7:

[1607] The terminal adjusts the learning content based on the emotion data acquired by the emotion engine.

[1608] Step 8:

[1609] After the lesson is completed, the terminal displays a quiz to the user.

[1610] Step 9:

[1611] The user answers the quiz and inputs the answer into the terminal.

[1612] Step 10:

[1613] The terminal transmits the quiz answer results and emotion data to the server.

[1614] Step 11:

[1615] The server stores the quiz results and emotional data in a database and automatically prepares the next learning content.

[1616] AI-guided virtual stock trading game app

[1617] Processing Steps

[1618] Step 1:

[1619] The terminal connects to the server using the user ID and requests the latest portfolio and market data.

[1620] Step 2:

[1621] The server retrieves the user's portfolio data and the latest market data from the database.

[1622] Step 3:

[1623] The server transmits the acquired data to the terminal.

[1624] Step 4:

[1625] The terminal displays market data received from the server and AI trading advice to the user.

[1626] Step 5:

[1627] The emotion engine analyzes the user's facial expressions and voice in real time to obtain emotional data.

[1628] Step 6:

[1629] The device will then adjust the advice provided by the AI ​​guide based on the emotional data.

[1630] Step 7:

[1631] Users can choose to follow AI advice or make their own trading decisions.

[1632] Step 8:

[1633] A user executes a trade by specifying the stock to be purchased or sold and the quantity.

[1634] Step 9:

[1635] The terminal transmits the user's trade instructions to the server.

[1636] Step 10:

[1637] The server processes the trade instructions to update the virtual market database and update the user's portfolio.

[1638] Step 11:

[1639] The server returns the updated portfolio data to the terminal.

[1640] Step 12:

[1641] The terminal displays the updated portfolio data to the user, allowing the user to confirm the trading results.

[1642] A community platform for improving financial literacy

[1643] Processing Steps

[1644] Step 1:

[1645] The device connects to the server using the user ID and requests the latest forum posts and Q&A data.

[1646] Step 2:

[1647] The server retrieves forum posts and Q&A data from a database.

[1648] Step 3:

[1649] The server transmits the acquired data to the terminal.

[1650] Step 4:

[1651] The terminal displays the latest community content to the user based on the data received from the server.

[1652] Step 5:

[1653] Users review forum posts and questions and make comments and replies as needed.

[1654] Step 6:

[1655] The emotion engine analyzes the user's facial expressions and voice in real time to obtain emotional data.

[1656] Step 7:

[1657] The terminal adjusts the content of communication based on the emotion data acquired by the emotion engine.

[1658] Step 8:

[1659] Users create new posts and questions in the community forums.

[1660] Step 9:

[1661] The terminal sends user posts and questions to the server.

[1662] Step 10:

[1663] The server stores the received posts and questions in a database.

[1664] Step 11:

[1665] The server notifies other users of new posts and questions and shares them with the entire community.

[1666] Step 12:

[1667] The server scores contributions based on the quality of posts and responses and emotional data, and awards points to users.

[1668] Step 13:

[1669] The server sends the updated points and rankings to the terminal.

[1670] Step 14:

[1671] The terminal displays the updated points and ranking to the user, allowing them to see their contribution to the community.

[1672] The above are the specific program processing steps for each system that incorporates an emotion engine. In each step, the operations performed by the server, terminal, and user have been explained in detail.

[1673] Example 2

[1674] 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."

[1675] Conventional financial literacy improvement systems have difficulty responding to the emotional state of each user, and have not been able to fully optimize learning effects and trading experiences. Such systems are unable to personalize based on the user's interests, level of understanding, or emotional changes, making it difficult to maintain learning motivation or effectively convey financial knowledge.

[1676] 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.

[1677] In this invention, the server includes means for communicating with a database that manages user progress information, means for generating learning content and providing it to the user, means for recognizing the user's emotions in real time and using that data, means for receiving quiz results and emotional data and storing them in the database, and means for automatically adjusting and preparing the next learning content based on the user's emotional state, thereby providing an effective and individually optimized learning experience that reflects the user's emotional state.

[1678] "User progress information" refers to data that indicates the progress and achievement level of a user when using learning content.

[1679] "Means for communicating with a database" means means having communication capabilities for accessing a database and retrieving or storing information.

[1680] "Means for generating learning content and providing it to users" refers to means for creating educational content and distributing it to users.

[1681] "Means for recognizing user emotions in real time and using that data" refers to means for detecting user emotions in real time and using that information to personalize the learning experience.

[1682] The "means for receiving quiz results and emotion data and storing them in a database" refers to a means for receiving the user's quiz answer results and emotion data and storing them in a database.

[1683] "Means for automatically adjusting and preparing the next learning content based on the user's emotional state" refers to a means for dynamically adjusting learning content based on the user's emotional data and preparing the optimal next item.

[1684] "Means for updating virtual market data" refers to means for updating virtual market information with the latest data.

[1685] "Means for managing a user's trading history and providing advice" means means for recording and managing a user's trading history and providing trading advice to the user based on that history.

[1686] "Means for receiving trade instructions and updating the database" refers to means for receiving trading instructions from users and updating the database accordingly.

[1687] The "means for displaying updated data to the user" refers to a means for displaying the latest data updated by the server to the user.

[1688] "Means for managing user posts and questions" refers to means for recording and managing content and questions posted by users.

[1689] "Means for managing responses from other users and experts" refers to means for recording and managing responses from other users and experts.

[1690] The "means for scoring contributions and awarding points" refers to a means for evaluating a user's actions and contributions and awarding points.

[1691] The "means for displaying points and rankings to the user" refers to a means for displaying the evaluated points and user rankings in a form visible to the user.

[1692] This invention combines a comprehensive system for improving young people's financial literacy with an emotion engine that recognizes user emotions. The system includes three main components: a microlearning financial app, an AI-guided virtual stock trading game app, and a financial literacy improvement community platform. Furthermore, the emotion engine recognizes users' emotions and optimizes the learning experience based on their emotions.

[1693] Microlearning Financial App

[1694] The purpose of microlearning financial apps is to enable users to learn financial knowledge in a short amount of time every day. Users access content delivered from a server using devices such as smartphones and tablets. An emotion engine also recognizes the user's emotions and personalizes the learning experience.

[1695] The server connects to the database using the user's ID, retrieves the latest learning progress data, and sends it to the device. The device then displays the next lesson content to the user based on the received data. At this time, the emotion engine recognizes emotions from the user's facial expressions and voice in real time to optimize the learning experience.

[1696] As a specific example, if a user is learning about "how credit cards work," the emotion engine analyzes the user's reactions while watching a three-minute lesson displayed on the device. If the user feels tired, the next lesson will be simplified, and if the user's attention is distracted, the interactive elements will be increased. After completing the lesson, the user answers a quiz, and the quiz results and emotion data are sent to the server and stored in a database.

[1697] Example prompt sentence:

[1698] "Generate a three-minute lesson on how credit cards work and provide a quiz based on user sentiment."

[1699] AI-guided virtual stock trading game app

[1700] The app aims to enable users to gain practical financial knowledge through virtual stock trading experiences. An AI guide provides trading advice, and an emotion engine recognizes users' emotions and provides appropriate feedback.

[1701] The server uses the user ID to retrieve the user's portfolio data and market data from the database and transmits them to the terminal. The terminal displays the received market data and AI advice to the user. The emotion engine recognizes the user's emotions in real time and adjusts the content of the advice.

[1702] For example, when a user purchases a company's stock, the AI ​​guide will advise them that "this stock is on an upward trend, so we recommend purchasing it." If the user feels unsure, the emotion engine will provide supplemental information to reduce the risk. Once the user decides to purchase and executes the transaction, the result is sent to the server and recorded in the database.

[1703] Example prompt sentence:

[1704] "Provide TechCorp stock trading advice and generate feedback based on sentiment data."

[1705] A community platform for improving financial literacy

[1706] The community platform provides a forum for users to share their knowledge and interact with other users and experts. It features forums, Q&A sections, online workshops, and an emotion engine that recognizes users' emotions to optimize communication.

[1707] The server uses the user ID to retrieve the latest forum posts and Q&A data and transmits it to the device. The device displays community content based on the received data, and the emotion engine recognizes the user's emotions in real time.

[1708] For example, if a user posts a question such as "I want to know about the risks of stock investment," other users and experts will provide answers. The emotion engine analyzes the user's emotions, and if there is a lot of positive feedback, the server will award points to the user. The ranking is updated and displayed on the device.

[1709] Example prompt sentence:

[1710] "Generate answers to questions about the risk of stock investments and provide a points system based on sentiment data."

[1711] These system functions allow users to effectively learn, practice, and share financial knowledge with other users. The incorporation of an emotion engine provides optimal learning experiences and communication according to the user's emotions.

[1712] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1713] Microlearning financial app processing steps

[1714] Step 1: Obtaining user progress data

[1715] Input: User ID

[1716] Processing: The server receives the user ID sent from the terminal and retrieves the user's latest learning progress data from the database.

[1717] Output: Learning progress data (e.g. last lesson studied, progress)

[1718] Specific behavior:

[1719] The server queries the database to retrieve the user ID and associated progress data (e.g., last lesson ID, completion percentage).

[1720] Step 2: View learning content and start emotion recognition

[1721] Input: Learning progress data

[1722] Processing: The device determines the content of the next lesson based on the learning progress data received from the server, and activates the emotion engine to recognize the user's emotions in real time.

[1723] Output: Display of learning content, emotion data

[1724] Specific behavior:

[1725] The device uses the progress data to display the next lesson (e.g., a video about how credit cards work), and the emotion engine uses the camera to begin analyzing the user's facial expressions.

[1726] Step 3: Personalize content and display quizzes

[1727] Input: Emotion data, learning content

[1728] Processing: The device adjusts the next learning content based on the data obtained from the emotion engine in real time, and displays a quiz after the lesson is completed.

[1729] Output: Personalized learning content, quizzes

[1730] Specific behavior:

[1731] If the user feels tired, the device will simplify the content of the next lesson and automatically display a quiz after the lesson.

[1732] Step 4: Send quiz results and sentiment data

[1733] Input: Quiz results, emotion data

[1734] Processing: The device sends the user's quiz results and emotion data to the server.

[1735] Output: Data sent to the server

[1736] Specific behavior:

[1737] When the quiz is over, the device sends the user's answer data and emotion data obtained through facial recognition to the server.

[1738] Step 5: Update the database and prepare for the next lesson

[1739] Input: Quiz results, emotion data

[1740] Processing: The server stores the received data in a database and determines the next learning content based on it.

[1741] Output: What to display next

[1742] Specific behavior:

[1743] The server analyzes the quiz results and emotional data and updates the database with the next lesson content.

[1744] AI-guided virtual stock trading game app processing steps

[1745] Step 1: Obtain portfolio and market data

[1746] Input: User ID

[1747] Processing: The server receives the user ID from the terminal, retrieves the user's latest portfolio data from the database, and also collects market data.

[1748] Output: Portfolio data, market data

[1749] Specific behavior:

[1750] The server retrieves the user's portfolio and the latest market prices from a database and external APIs.

[1751] Step 2: Getting started with AI advice and emotion recognition

[1752] Input: Portfolio data, market data

[1753] Processing: The terminal displays the received data, the AI ​​guide provides trading advice to the user, and the emotion engine simultaneously recognizes the user's emotions.

[1754] Output: trading advice, sentiment data

[1755] Specific behavior:

[1756] The device displays advice such as "TechCorp stock is on the rise, so we recommend buying," and the emotion engine detects the user's anxiety.

[1757] Step 3: Execute trades and update data

[1758] Input: trading instructions, sentiment data

[1759] Processing: The user buys or sells virtual stocks, and the instruction is sent to the server, which updates the database and returns the result to the terminal.

[1760] Output: Updated portfolio data

[1761] Specific behavior:

[1762] When a user issues a trade instruction, the instruction is sent from the terminal to the server, which updates the database and returns the portfolio.

[1763] Financial literacy improvement community platform processing steps

[1764] Step 1: Obtain community data

[1765] Input: User ID

[1766] Processing: The server retrieves forum posts and Q&A data from the database using the user ID received from the device.

[1767] Output: Community data

[1768] Specific behavior:

[1769] The server retrieves the latest forum threads and Q&A information from the database.

[1770] Step 2: View posts, questions, and answers and start emotion recognition

[1771] Input: Community Data

[1772] Processing: The device displays the received data, and the emotion engine recognizes the user's emotions in real time.

[1773] Output: Forum posts, questions and answers, sentiment data

[1774] Specific behavior:

[1775] A user checks the "latest posts about the risks of stock investment," and the sentiment engine analyzes the user's sentiment.

[1776] Step 3: Emotional feedback and data storage

[1777] Input: Post content, emotion data

[1778] Processing: The server stores the post, response data, and sentiment data in a database and updates the user's points and ranking.

[1779] Output: Updated points, rankings

[1780] Specific behavior:

[1781] If a user receives a lot of positive feedback, the server will award points to the user and update their ranking.

[1782] Step 4: View your points and rankings

[1783] Input: Updated data

[1784] Processing: The terminal displays the points and ranking received from the server to the user.

[1785] Output: points, ranking

[1786] Specific behavior:

[1787] Based on the points the user has earned, a new ranking is displayed for the user to check.

[1788] (Application example 2)

[1789] 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."

[1790] There is a lack of effective ways for today's young people to improve their financial literacy. Furthermore, traditional learning systems are unable to personalize the learning experience based on the user's interests and emotions, resulting in poor learning efficiency. Since acquiring knowledge related to electronic payments is particularly relevant to daily life, it is necessary to optimize the learning experience.

[1791] 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.

[1792] In this invention, the server includes means for communicating with a database that manages user progress information, means for generating learning content and providing it to the user, means for receiving quiz results and saving them in the database, means for automatically preparing the next learning content, and means for recognizing the user's emotions and optimizing the learning experience based on those emotions. This allows the user to effectively learn financial knowledge through everyday electronic payments and provides an optimal learning experience tailored to their emotions.

[1793] "User progress information" is data that records and manages the progress of a user when studying.

[1794] A "database" is a system for storing information in an organized manner and for efficiently retrieving and updating it.

[1795] "Means of communication" refers to the technical methods and devices used to transmit and receive data between the database and the server.

[1796] "Learning Content" means educational materials, information, or lessons provided to Users to improve their financial literacy.

[1797] A "generation means" is a technology or device that creates learning content based on specific conditions.

[1798] "Means for providing" refers to the technology or devices used to display, notify, or transmit learning content to users.

[1799] "Quiz results" refers to the scores and answer data for a quiz that a user takes after studying the learning content.

[1800] "Next learning content" refers to the next learning material or information selected based on the user's current learning progress and quiz results.

[1801] "Automatic preparation means" refers to technology or devices that allow the system to automatically select and provide the next learning content based on the user's progress data and emotional data.

[1802] "Means for recognizing emotions" refers to technologies and devices for detecting and identifying a user's emotional state from facial expressions, voice, actions, etc.

[1803] "Means for optimizing the learning experience" refers to technologies and devices that adjust the content and methods of learning according to the user's emotional state and progress, thereby enabling effective learning.

[1804] "Virtual Market Data" means simulated stock market data and information.

[1805] "Trade history" refers to historical data of virtual stock trades made by a user.

[1806] "Means for providing advice" refers to technology or devices that provide appropriate trading advice based on a user's trading history and emotional data.

[1807] A "trade instruction" is an instruction or command for a user to buy or sell virtual stock.

[1808] "Means for updating" refers to techniques or devices that update the data in the database based on received trade instructions.

[1809] "Posts and Questions" are texts or messages that a User uses to share knowledge or raise questions with other Users or Experts on the Community Platform.

[1810] The "answer management means" refers to a technology or device that collects and organizes answers provided by users and experts and provides them to users.

[1811] "Contribution scoring means" refers to technology or devices that evaluate the quality of posts and responses made by users on the platform and award points to them.

[1812] "Means for awarding points" refers to the technology or device that awards points on the system according to the user's level of contribution.

[1813] The "means for displaying rankings" refers to a technique or device that creates rankings based on the points acquired by users and displays them to users.

[1814] "Communication optimizers" are technologies and devices that recognize users' emotions and effectively adjust community interactions accordingly.

[1815] The present invention relates to a technology for optimizing learning experiences by recognizing emotions in a system that manages user progress information, generates and provides learning content, and stores quiz results. It also includes a method for managing virtual market data and trading history, providing appropriate advice to users, and optimizing communication in a community platform.

[1816] System configuration

[1817] The system of the present invention consists of the following main components:

[1818] 1. Progress information management

[1819] The server has a means for communicating with a database that manages user progress information, including the user's learning progress and quiz results.

[1820] 2. Creation and provision of learning content

[1821] The server generates learning content and provides it to users, who access it via devices such as smartphones and tablets.

[1822] 3. Receiving and storing quiz results

[1823] The device sends the quiz results to the server, which stores them in a database, and the next learning content is automatically prepared.

[1824] 4. Emotion Recognition and Optimization

[1825] The server has the means to recognize the user's emotions and optimize the learning experience based on those emotions, using camera and voice analysis.

[1826] Virtual Market Data and Trading Advice

[1827] The server updates virtual market data and manages users' trading history. It receives trading instructions, updates the database, and adjusts advice based on sentiment. Users can use their terminals to buy and sell virtual stocks and view updated data.

[1828] Community Platform

[1829] The server manages user posts and questions, manages answers from other users and experts, scores contributions and awards points, and optimizes communication based on user sentiment data.

[1830] Hardware and Software

[1831] The specific hardware and software used to implement this system includes:

[1832] Hardware: smartphones, tablets, smart glasses, cameras.

[1833] Software: OpenCV (real-time video capture and processing), EmotionRecognition module (emotion recognition), FinancialAnalysis module (expense analysis), QuizGame module (quiz game).

[1834] Specific examples

[1835] When a user makes an electronic payment at a cafe using their smartphone, the app records the transaction and displays a message saying, "You spend a lot at cafes every month. Why not try enjoying coffee at home a few times a month?" If the user's facial expressions and voice indicate they are "interested," the app provides a detailed analysis of their cafe spending and a mini-game on how to reduce coffee costs.

[1836] Prompt Sentence Examples

[1837] Here are some examples of prompts for generative AI models:

[1838] text

[1839] When a user makes an electronic payment at a cafe, if their facial expression is recognized as "curious," provide a detailed analysis of their spending at the cafe and a mini-game based on that analysis. Implement a recommendation system that displays a warning if the user has spent more than a certain number of times at a cafe and suggests ways to save money. Cover the following items:

[1840] 1. Camera-based facial expression recognition.

[1841] 2. Analysis of historical expenditure data.

[1842] 3. Providing advice and mini-games based on the user's emotions.

[1843] This allows users to effectively learn financial knowledge through everyday electronic payments, providing an optimal learning experience that responds to their emotions.

[1844] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1845] Step 1:

[1846] The device activates the camera and captures the user's video. The input is video data from the camera. The device processes this video data in real time and recognizes emotions from the user's facial expressions and voice. OpenCV face detection and the EmotionRecognition module are used here. The output is the user's emotional data (e.g., curious, tired, etc.).

[1847] Step 2:

[1848] The device sends the user's emotional data to the server. The input is the emotional data obtained in step 1 above. The server receives this data and uses it to generate the next learning content in comparison with the user's current learning progress data. The server generates the learning content. The output is personalized learning content based on the emotional data and progress data.

[1849] Step 3:

[1850] The server sends the generated learning content to the terminal. The input is the learning content generated on the server. The terminal receives it and displays it on the interface. The output is the learning content that the user views.

[1851] Step 4:

[1852] The user watches the learning content provided on the device and answers the quiz questions. The input is the user's learning behavior and quiz answer data. The device collects this data and sends it to the server. The output is the user's quiz answer results.

[1853] Step 5:

[1854] The server receives the user's quiz answer results and stores them in a database. The input is the quiz answer results sent from the terminal. The server stores them in the database and begins preparing the next learning content. The output is the user's quiz results stored in the database.

[1855] Step 6:

[1856] When a user makes an everyday electronic payment, the terminal automatically captures the payment information and sends it along with emotional data to a server. The input is the electronic payment transaction data and emotional data. The server receives this data and performs a comparative analysis with past spending data. The output is the analysis results.

[1857] Step 7:

[1858] The server generates appropriate advice and warning messages based on the analysis results and sends them to the terminal. The input is the analysis results of the expenditure data performed on the server. The terminal displays this to the user. The output is advice and warning messages regarding the user's expenditures.

[1859] Step 8:

[1860] The device then recognizes the user's emotions again and uses them to inform the next step of learning or advice. This process continues as a loop. The input is updated emotional data, and the output is emotional data that will be reflected in the next learning content or advice.

[1861] In this way, the system uses users' emotional data to individually optimize their learning experience and feedback on everyday electronic payments, effectively improving financial literacy.

[1862] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1863] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1864] 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.

[1865] [Fourth embodiment]

[1866] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1867] 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.

[1868] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1869] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1870] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1871] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1872] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1873] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1874] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1875] 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.

[1876] 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.

[1877] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1878] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1879] The present invention is a comprehensive system for improving financial literacy among young people. The system includes three main components: a micro-learning financial app, an AI-guided virtual stock trading game app, and a financial literacy community platform.

[1880] Microlearning Financial App

[1881] System Overview:

[1882] The purpose of microlearning financial apps is to enable users to learn financial knowledge in a short amount of time every day. Users access content delivered from a server using devices such as smartphones and tablets.

[1883] Process flow:

[1884] The device connects to the server using the user ID and requests the latest learning progress data. The server retrieves the user's progress information from the database and sends it to the device.

[1885] The terminal displays the next lesson content to the user based on the data received from the server. The user watches the lesson provided on the screen and progresses with their learning.

[1886] After completing a lesson, the user answers a quiz. The device sends the quiz results to the server, which stores them in a database. The next lesson is then automatically prepared.

[1887] Examples:

[1888] If a user wants to learn about "How Credit Cards Work," they can watch a three-minute lesson on their device, take a quiz, and then the results of the quiz will be sent to the server, which will then automatically prepare the next lesson on "Loans and Interest Rates."

[1889] AI-guided virtual stock trading game app

[1890] System Overview:

[1891] The app aims to enable users to gain practical financial knowledge through virtual stock trading experiences. An AI guide provides users with trading advice, allowing them to acquire trading skills without any risk.

[1892] Process flow:

[1893] The terminal connects to the server using the user ID and requests the latest portfolio data and market data. The server retrieves the user's portfolio data and market data from the database and sends them to the terminal.

[1894] The terminal receives market data and AI advice from the server and displays it to the user, who then uses the advice to buy or sell virtual stocks.

[1895] Trade instructions are sent to the server, trade results are recorded in a database, and updated portfolio data is sent to the terminal and displayed to the user.

[1896] Examples:

[1897] If a user decides to buy TechCorp stock, the AI ​​guide will advise them that "TechCorp stock is on an upward trend, so we recommend buying it." Once the user decides to buy and executes the trade, the results are sent to the server and recorded in the database. The portfolio after the trade is displayed on the terminal.

[1898] A community platform for improving financial literacy

[1899] System Overview:

[1900] The community platform allows users to share their knowledge and interact with other users and experts, and includes features such as forums, Q&A sections, and online workshops.

[1901] Process flow:

[1902] The device accesses the server using the user ID and requests the latest forum posts and Q&A data. The server retrieves the necessary data from the database and sends it to the device.

[1903] The device displays the latest community content to the user based on the data received from the server. The user posts on forums or asks questions and waits for answers from other users or experts.

[1904] Posts and replies are sent to the server and recorded in a database. The server evaluates the quality of the post and reply and awards points to the user. The terminal displays the user's points and ranking.

[1905] Examples:

[1906] When a user posts a question such as "I want to know about the risks of stock investment," other users and experts will provide answers. Users who post high-quality answers will be awarded points by the server, and their rankings will be updated.

[1907] These system features allow users to effectively learn, practice, and share financial knowledge with other users.

[1908] The processing flow will be explained below.

[1909] Microlearning Financial App

[1910] Processing Steps

[1911] Step 1:

[1912] The device connects to the server using the user ID and requests the user's latest learning progress data.

[1913] Step 2:

[1914] The server searches the database based on the received user ID and obtains the user's latest learning progress information.

[1915] Step 3:

[1916] The server transmits the acquired learning progress data to the terminal.

[1917] Step 4:

[1918] The terminal displays the next lesson content to the user based on the data received from the server.

[1919] Step 5:

[1920] The user watches and listens to the lessons displayed on the screen and progresses through the learning process.

[1921] Step 6:

[1922] The terminal displays a quiz to the user after the lesson is completed.

[1923] Step 7:

[1924] The user answers the quiz and inputs the answer into the terminal.

[1925] Step 8:

[1926] The terminal transmits the answer to the quiz to the server.

[1927] Step 9:

[1928] The server stores the quiz results in a database and automatically prepares the next learning content.

[1929] AI-guided virtual stock trading game app

[1930] Processing Steps

[1931] Step 1:

[1932] The terminal connects to the server using the user ID and requests the latest portfolio and market data.

[1933] Step 2:

[1934] The server retrieves the user's portfolio data and the latest market data from the database.

[1935] Step 3:

[1936] The server transmits the acquired data to the terminal.

[1937] Step 4:

[1938] The terminal displays market data received from the server and AI trading advice to the user.

[1939] Step 5:

[1940] Users can choose to follow AI advice or make their own trading decisions.

[1941] Step 6:

[1942] A user executes a trade by specifying the stock to be purchased or sold and the quantity.

[1943] Step 7:

[1944] The terminal transmits the user's trade instructions to the server.

[1945] Step 8:

[1946] The server processes the trade instructions to update the virtual market database and update the user's portfolio.

[1947] Step 9:

[1948] The server returns the updated portfolio data to the terminal.

[1949] Step 10:

[1950] The terminal displays the updated portfolio data to the user, allowing the user to confirm the trading results.

[1951] A community platform for improving financial literacy

[1952] Processing Steps

[1953] Step 1:

[1954] The device connects to the server using the user ID and requests the latest forum posts and Q&A data.

[1955] Step 2:

[1956] The server retrieves forum posts and Q&A data from a database.

[1957] Step 3:

[1958] The server transmits the acquired data to the terminal.

[1959] Step 4:

[1960] The terminal displays the latest community content to the user based on the data received from the server.

[1961] Step 5:

[1962] Users review forum posts and questions and make comments and replies as needed.

[1963] Step 6:

[1964] Users create new posts and questions in the community forums.

[1965] Step 7:

[1966] The terminal transmits user posts and questions to the server.

[1967] Step 8:

[1968] The server stores the received posts and questions in a database.

[1969] Step 9:

[1970] The server notifies other users of new posts and questions and shares them with the entire community.

[1971] Step 10:

[1972] The server scores the contribution of posts and replies and awards points to users.

[1973] Step 11:

[1974] The server updates the total points and ranking and sends them to the terminal.

[1975] Step 12:

[1976] The terminal displays the updated points and ranking to the user, allowing them to see their contribution to the community.

[1977] The above are the specific program processing steps in each system. We have explained in detail what operations the server, terminal, and user perform in each step.

[1978] Example 1

[1979] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1980] Traditional financial literacy education systems have struggled to provide personalized learning experiences based on users' progress. Virtual stock trading and community platforms also lack the appropriate advice and feedback to maximize users' learning outcomes. Furthermore, effective communication methods for sharing learned knowledge are often lacking.

[1981] 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.

[1982] In this invention, the server includes: means for communicating with a database that manages user progress information; means for generating learning content and providing it to the user; means for receiving quiz results and saving them in the database; means for automatically preparing the next learning content; means for customizing the next lesson content based on the user's individual learning history; and means for connecting to the server from a device such as a smartphone or tablet and requesting progress information. This allows users to efficiently take learning content that is tailored to their individual needs, improving learning effectiveness. The server also includes means for updating virtual market data, means for managing the user's trading history and providing advice, means for receiving trading instructions and updating the database, means for displaying the updated data to the user, means for displaying the latest market data and advice from the AI ​​guide to the user, and means for recording the user's virtual trading results in the database, allowing users to acquire practical trading skills without risk. Furthermore, the server includes means for managing user posts and questions, means for managing answers from other users and experts, means for scoring contributions and awarding points, means for displaying the points and rankings to users, means for requesting forum posts and Q&A data to display the latest community content, and means for evaluating the quality of posts and answers and awarding points, thereby promoting knowledge sharing and interaction among users and increasing motivation to learn and a sense of accomplishment.

[1983] A "database for managing user progress information" is a data storage system that stores information for recording and managing what a user has learned and their progress.

[1984] A "means for generating and providing learning content to users" is a system or method for creating new educational material based on the user's needs and learning history and delivering it to the user in an accessible format.

[1985] "Means for receiving quiz results and storing them in a database" refers to a system or method by which the server receives the results of the quiz answered by the user after studying and records them in a management database.

[1986] "Means for automatically preparing the next learning content" refers to a system or method that automatically selects and prepares the next learning content based on the user's learning progress and quiz results.

[1987] "Means for customizing the next lesson content based on the user's individual learning history" refers to a system or method that analyzes each user's past learning data and provides the most appropriate learning content individually based on that data.

[1988] "Means for connecting to a server from a terminal such as a smartphone or tablet and requesting progress information" refers to a system or method for connecting to a server using a mobile device and obtaining learning progress information from there.

[1989] A "means for updating virtual market data" is a system or method for periodically updating data to keep virtual financial market information current.

[1990] A "means for managing a user's trading history and providing advice" is a system or method for recording a user's virtual trading activity and providing advice on financial trading based thereon.

[1991] The "means for receiving trade instructions and updating the database" refers to a system or method for receiving information when a user issues a virtual trade instruction and updating the database.

[1992] The "means for displaying updated data to the user" refers to a system or method for displaying the latest virtual market information, the user's trading results, etc. on the user's device screen.

[1993] "Means for displaying the latest market data and advice from an AI guide to users" refers to a system or method that obtains the latest market information and provides users with AI-generated financial advice based on that information.

[1994] The "means for recording the results of a user's virtual trade in a database" refers to a system or method for storing the results of a virtual trade executed by a user in a database.

[1995] "Means for managing user posts and questions" refers to a system or method for processing and appropriately managing information and questions posted by users on the community platform.

[1996] "Means for managing responses from other users and experts" refers to a system or method for receiving and managing responses from other users and experts on the community platform.

[1997] "Means for scoring contributions and awarding points" refers to a system or method for evaluating the quality of users' posts and replies and awarding points accordingly.

[1998] The "means for displaying points and rankings to the user" refers to a system or method for visualizing the points and rankings earned by the user and displaying them on the user's device.

[1999] A "means for requesting forum posts and Q&A data to display the most recent community content" is a system or method that automatically retrieves the most recent posts to a forum or Q&A section and displays them to the user.

[2000] The "means for evaluating the quality of posts and replies and awarding points" refers to a system or method for evaluating the content of posts and replies made by users and awarding points according to their contribution.

[2001] MODE FOR CARRYING OUT THE INVENTION

[2002] The present invention is a comprehensive system for improving financial literacy among young people. The system includes three main components: a micro-learning financial app, an AI-guided virtual stock trading game app, and a financial literacy community platform.

[2003] Microlearning Financial App

[2004] System Overview:

[2005] The purpose of microlearning financial apps is to enable users to learn financial knowledge in a short amount of time every day. Users access content delivered from a server using devices such as smartphones and tablets.

[2006] Hardware and software used:

[2007] Mobile devices such as smartphones and tablets

[2008] Server (progress database, content distribution system)

[2009] Internet Connectivity Infrastructure

[2010] Specific data processing and calculation:

[2011] When a user launches the app, the server retrieves the user's learning progress information from the progress database and sends it to the device. The device uses this data to display the next lesson content to the user. When the user completes their learning and answers a quiz, the results are sent to the server and stored in the database. The server automatically selects and prepares the next learning content based on the user's progress.

[2012] Examples:

[2013] When a user learns about "How Credit Cards Work," the device retrieves the relevant lesson video from the server and displays it. After the lesson, the user answers a quiz, and the results are sent to the server, which then prepares the next lesson on "Loans and Interest Rates."

[2014] Example prompt sentence:

[2015] Please state the conditions for selecting the content of your next lesson.

[2016] AI-guided virtual stock trading game app

[2017] System Overview:

[2018] The app aims to enable users to gain practical financial knowledge through virtual stock trading experiences. An AI guide provides users with trading advice, allowing them to acquire trading skills without any risk.

[2019] Hardware and software used:

[2020] Mobile devices such as smartphones and tablets

[2021] Server (portfolio database, AI guide system, market database)

[2022] Internet Connectivity Infrastructure

[2023] Specific data processing and calculation:

[2024] When a user logs in, the terminal connects to the server using the user ID and retrieves the latest portfolio and market data. The server then retrieves this data from the database and displays it to the user. An AI guide also provides advice based on market data, and the user purchases or sells virtual stocks. After the trade is executed, the results are sent to the server and recorded in the database.

[2025] Examples:

[2026] If a user were to hypothetically buy TechCorp shares, the terminal would retrieve market data and AI-guided advice from the server and display it. Once the user decides to buy and executes the trade, the information is sent to the server for recording, and the new portfolio is displayed on the terminal.

[2027] Example prompt sentence:

[2028] "Please explain the circumstances under which you would recommend buying or selling TechCorp stock."

[2029] A community platform for improving financial literacy

[2030] System Overview:

[2031] The platform allows users to share their knowledge and interact with other users and experts, and includes features such as forums, Q&A sections, and online workshops.

[2032] Hardware and software used:

[2033] Devices such as smartphones, tablets, and PCs

[2034] Server (community database, posting management system)

[2035] Internet Connectivity Infrastructure

[2036] Specific data processing and calculation:

[2037] The device connects to the server using the user ID to retrieve the latest forum posts and Q&A data. The server retrieves this data from the database and sends it to the device. Users can post to the forum or ask questions and wait for answers from other users or experts. The posts and answers are sent to the server and recorded in the database. The server then evaluates the quality of these posts and answers and assigns points. The device then displays the points and rankings to the user.

[2038] Examples:

[2039] When a user posts a question about the risks of stock investment on the community platform, other users and experts respond. The server records the responses, evaluates the quality of the responses, and awards points. The terminal then displays the points and rankings to the user.

[2040] Example prompt sentence:

[2041] "Create the best answer to the question about the risks of stock investment."

[2042] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2043] Microlearning Financial App

[2044] Processing flow

[2045] Step 1:

[2046] Server connection by user ID

[2047] When a user launches the app, the device connects to the server using the user ID stored in the device.

[2048] Input: User ID

[2049] Data processing: The server receives the user ID and sends a query to the database to retrieve the learning progress data of the user.

[2050] Output: User's learning progress data

[2051] Specific operation: The server retrieves the user's progress information from the database and sends it to the device.

[2052] Step 2:

[2053] View lesson content

[2054] The terminal displays the next lesson content to the user based on the received learning progress data.

[2055] Input: Learning progress data received from the server

[2056] Data processing: The device analyzes the progress data and determines the next lesson content to display.

[2057] Output: Lesson content (e.g. video, text)

[2058] Specific operation: The device displays the next lesson content on the screen and the user begins learning.

[2059] Step 3:

[2060] Quiz Answers and Results Submission

[2061] The user answers a quiz that is displayed after the lesson is completed.

[2062] Input: User's quiz answer

[2063] Data processing: The terminal receives the user's answers and sends the results to the server.

[2064] Output: Quiz results

[2065] Specific operation: The device sends the quiz results to the server, which stores them in a database.

[2066] AI-guided virtual stock trading game app

[2067] Processing flow

[2068] Step 1:

[2069] Portfolio and Market Data Requests

[2070] When a user logs in, the terminal connects to the server using the user ID and requests the latest portfolio and market data.

[2071] Input: User ID

[2072] Data processing: The server retrieves portfolio data and market data from the database based on the user ID.

[2073] Output: Portfolio data, latest market data

[2074] Specific operation: The server sends the data retrieved from the database to the terminal.

[2075] Step 2:

[2076] Display market data and AI advice

[2077] The terminal displays the received market data and advice from the AI ​​guide to the user.

[2078] Inputs: Portfolio data, latest market data, AI advice

[2079] Data processing: The terminal analyzes the received market data and AI advice and presents appropriate information to the user.

[2080] Output: Market status and trading advice

[2081] Specific operation: The device displays market conditions and AI-guided advice to the user.

[2082] Step 3:

[2083] Trading instructions and results recording

[2084] A user trades (buys or sells) virtual stocks.

[2085] Input: User's trading instructions

[2086] Data processing: The terminal sends trade instructions to the server, which records the information in a database.

[2087] Output: Updated portfolio data

[2088] Specific operation: After the results of the trade are recorded in the database, the updated portfolio data is sent to the terminal.

[2089] A community platform for improving financial literacy

[2090] Processing flow

[2091] Step 1:

[2092] Requesting forum posts and Q&A data

[2093] The device accesses the server using the user ID and requests the latest forum posts and Q&A data.

[2094] Input: User ID

[2095] Data processing: The server retrieves the latest forum posts and Q&A data from the database based on the user ID.

[2096] Output: Forum post data, Q&A data

[2097] Specific operation: The server sends the acquired data to the terminal.

[2098] Step 2:

[2099] View community content and user activity

[2100] The terminal displays the latest community content to the user based on the received data.

[2101] Input: Forum post data, Q&A data

[2102] Data processing: The device analyzes the received data and selects and displays the latest content.

[2103] Output: Forum content, Q&A content to be displayed

[2104] What it does: The device displays recent posts and questions and answers on the screen, and users post and ask questions in the forum.

[2105] Step 3:

[2106] Recording and rating posts and responses

[2107] When a post or question is made, the device sends the content to the server.

[2108] Input: New post data, question and answer data

[2109] Data processing: The server records the received data in a database and evaluates its quality.

[2110] Output: Updated forum data, quality evaluation results, point data

[2111] Specific operation: The server stores posts and answers in a database and assigns points based on quality. The terminal displays the points and ranking to the user.

[2112] (Application example 1)

[2113] 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."

[2114] In recent years, low financial literacy among young people has become a problem. In particular, purchasing behavior on online shopping sites tends to be impulsive, leading to a lack of budget management. In such circumstances, young people find it difficult to make financial forecasts and are prone to long-term financial risk. Therefore, a system is needed to improve financial literacy in real time through online shopping site purchasing behavior, and to provide appropriate purchasing advice and budget management.

[2115] 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.

[2116] In this invention, the server includes means for communicating with a database that manages user progress information, means for generating study content and providing it to the user, means for receiving quiz results and saving them in the database, means for automatically preparing the next study content, means for receiving the user's purchasing data and providing purchasing advice within a budget, and means for updating post-purchase budget data and saving it in the database. This allows users to manage their budget while receiving appropriate financial advice in real time through their purchasing behavior on the online shopping site.

[2117] "User progress information" refers to the status and history achieved by the user in processes such as learning and purchasing.

[2118] A "database" is a system for managing information efficiently and consistently, storing, retrieving, and updating data.

[2119] "Learning Content" refers to educational materials and teaching materials provided to users to improve their financial literacy.

[2120] "Quiz results" refers to information on the results of a user's answers to a quiz-style test.

[2121] "Next learning content" refers to the next step of education provided based on the user's current learning situation and progress.

[2122] "User purchase data" refers to information about purchases made by a user on an online shopping site, such as the product name, purchase price, and purchase date and time.

[2123] "Buying advice within a budget" refers to recommendations and suggestions regarding what purchasing behavior a user should take within their budget.

[2124] "Post-purchase budget data" refers to information regarding the remaining budget after a user has completed a particular purchase.

[2125] "Virtual market data" refers to data of a virtual investment environment that simulates actual market data.

[2126] "User's trading history" refers to a record of transactions that a User has made in the virtual or real markets.

[2127] "Trade Instructions" refers to specific commands given by a user to buy or sell stocks or other financial instruments.

[2128] "User posts and questions" refers to information shared or questions expressed by users on the community platform.

[2129] "Responses from other users and experts" refers to information and advice provided in response to a user's post on the community platform.

[2130] "Scoring contribution" refers to users rating their activities on the community platform.

[2131] "Awarding points" refers to giving points as a reward for a user's community activities.

[2132] "Points and ranking" refers to the numerical value of the user's activity evaluation and the user's ranking generated based on that numerical value.

[2133] This invention is a comprehensive system for improving users' financial literacy, and is composed of the following major components:

[2134] System configuration

[2135] The system consists of the following main components:

[2136] 1. A database that manages user progress information:

[2137] The server maintains a database that centrally manages user progress information, including the user's learning activities, quiz results, purchase history, and budget information, and updates the database as needed.

[2138] 2. Learning content generation and delivery:

[2139] The server generates financial education learning content to be provided to users and provides it to devices such as smartphones and tablets. The learning content is personalized based on the user's progress.

[2140] 3. Receiving and storing quiz results:

[2141] The server receives the results of the user's answers to the quiz accompanying the learning content, stores them in a database, and automatically prepares the next learning content based on this data.

[2142] 4. Receiving purchasing data and providing budget advice:

[2143] When a user purchases a product on an online shopping site, the server receives the purchase data (product name, price, date and time, etc.) and provides appropriate purchasing advice within the user's budget based on this purchase data and the user's budget information.

[2144] 5. Update budget data after purchase:

[2145] After the purchase, the server updates the user's budget data and stores it in the database, realizing real-time budget management.

[2146] 6. Virtual Market Data and Trade History Management:

[2147] The server manages data on users' transactions in the virtual market and provides trading advice based on this data, allowing users to experience stock trading risk-free and gain practical financial knowledge.

[2148] 7. Maintaining the Community Platform:

[2149] The server manages user posts and questions, as well as answers from other users and experts. It scores the contribution of posts and answers, awards points, and displays them to users.

[2150] Hardware and Software Details

[2151] Hardware: smartphones, tablets, servers

[2152] Software: Flask (Python web framework), SQLite (database management)

[2153] Specific examples

[2154] For example, consider a situation where a user is trying to purchase a pair of sneakers for 10,000 yen on an online shopping site. In this case, the server first retrieves the user's budget information from the database and evaluates in real time whether the purchase is within budget. If the purchase is within budget, the server provides advice recommending the purchase and updates the budget data after the purchase. This series of steps allows the user to manage their budget in real time.

[2155] Prompt Sentence Examples

[2156] Build a smartphone app that manages a user's budget when purchasing certain items. When a user attempts to purchase an item, the app will receive the user ID and the item's price as input. It will then retrieve the user's remaining budget from the database and check whether the purchase is within the budget. The budget will also be updated after the purchase and the user will be notified. Please also provide an example program using Flask and SQLite.

[2157] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2158] Step 1:

[2159] The server receives a product purchase request from the user. The user ID and product price information are provided as input. Based on this, the server processes the data to retrieve the user's current budget information from the database. The output is the retrieved user's budget information.

[2160] Step 2:

[2161] The server compares the acquired budget information with the product price and performs data calculations to determine whether the purchase is possible within the budget. Specifically, the server subtracts the product price from the user's remaining budget, and if the result is 0 or greater, it recommends the purchase, and if it is less than 0, it notifies the user that the budget is exceeded. The input is the user's budget information and product price, and the output is advice information such as "purchase possible" or "over budget."

[2162] Step 3:

[2163] The terminal receives advice information from the server and displays it to the user, allowing the user to decide whether to proceed with the purchase. Specifically, the terminal displays the received advice on the screen and waits for the user's next action. The input is advice information from the server, and the output is the screen display.

[2164] Step 4:

[2165] When the user decides to make a purchase, the device sends that decision to the server. The server receives this information and performs data calculations to update the user's budget information. Specifically, the server subtracts the product price from the user's remaining budget and saves the updated budget data in the database. The input is the user's purchase intention and product price, and the output is the updated user's budget data.

[2166] Step 5:

[2167] The server sends confirmation of the purchase completion to the terminal. The terminal receives this information and notifies the user that the purchase is complete. Specifically, the terminal displays a "Purchase Complete" message on the screen and notifies the user that the budget has been updated. The input is the purchase completion notification from the server, and the output is the screen display.

[2168] Through these steps, users can receive budget management and financial advice in real time through their purchasing behavior on the online shopping site.

[2169] When generating a description using keywords from a generative AI model, the following prompts can be used:

[2170] "Build a smartphone app that manages a user's budget when purchasing certain products. When a user tries to purchase an item, the app will receive the user ID and the product price as input. It will then retrieve the user's remaining budget from a database and check whether the purchase is within the budget. The budget will also be updated after the purchase and the user will be notified. Please also provide an example program using Flask and SQLite."

[2171] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[2172] This invention combines a comprehensive system for improving young people's financial literacy with an emotion engine that recognizes user emotions. The system includes three main components: a microlearning financial app, an AI-guided virtual stock trading game app, and a financial literacy improvement community platform. Furthermore, the emotion engine recognizes users' emotions and optimizes the learning experience based on their emotions.

[2173] Microlearning Financial App

[2174] System Overview:

[2175] The purpose of microlearning financial apps is to enable users to learn financial knowledge in a short amount of time every day. Users access content delivered from a server using devices such as smartphones and tablets. An emotion engine also recognizes the user's emotions and personalizes the learning experience.

[2176] Process flow:

[2177] The device connects to the server using the user ID and requests the latest learning progress data. The server retrieves the user's progress information from the database and sends it to the device.

[2178] The device displays the next lesson content to the user based on the data received from the server. The user continues learning by watching the lesson provided on the screen while their emotions are recognized in real time by the emotion engine.

[2179] The learning content is adapted based on the user's emotions: for example, if the user is feeling tired, the content is simplified, and if the user is perceived as easily distracted, the interactive elements are increased.

[2180] After completing the lesson, the user answers a quiz. The device sends the quiz results and emotion data to the server, which stores them in a database. The next lesson is then automatically prepared.

[2181] Examples:

[2182] For example, if a user wants to learn about "How Credit Cards Work," they watch a three-minute lesson displayed on their device and answer a quiz. The emotion engine assesses in real time whether the user is enjoying the lesson and deepening their understanding, and automatically prepares the next lesson on "Loans and Interest Rates" at the appropriate difficulty level.

[2183] AI-guided virtual stock trading game app

[2184] System Overview:

[2185] The app aims to enable users to gain practical financial knowledge through virtual stock trading experiences. An AI guide provides trading advice, and an emotion engine recognizes users' emotions and provides appropriate feedback.

[2186] Process flow:

[2187] The terminal connects to the server using the user ID and requests the latest portfolio data and market data. The server retrieves the user's portfolio data and market data from the database and sends them to the terminal.

[2188] The terminal receives market data and AI advice from the server and displays it to the user. The user then buys or sells virtual stocks based on the advice, which is based on sentiment analysis by the emotion engine.

[2189] The advice is tailored depending on the user's emotions: for example, if the user is feeling anxious, low-risk, conservative advice is offered.

[2190] Trade instructions are sent to the server, trade results are recorded in a database, and updated portfolio data is sent to the terminal and displayed to the user.

[2191] Examples:

[2192] If a user decides to buy TechCorp stock, the AI ​​guide will advise them that "TechCorp stock is on an upward trend, so we recommend buying." If the user feels unsure, the emotion engine will provide supplemental information to reduce the risk. Once the user decides to purchase and executes the trade, the results are sent to the server and recorded in the database. The portfolio after the trade is displayed on the terminal.

[2193] A community platform for improving financial literacy

[2194] System Overview:

[2195] The community platform provides a forum for users to share their knowledge and interact with other users and experts. It features forums, Q&A sections, online workshops, and an emotion engine that recognizes users' emotions to optimize communication.

[2196] Process flow:

[2197] The device accesses the server using the user ID and requests the latest forum posts and Q&A data. The server retrieves the necessary data from the database and sends it to the device.

[2198] The device displays the latest community content to the user based on the data received from the server. The user can post forums or ask questions, and wait for answers from other users and experts, while the emotion engine recognizes emotions in real time.

[2199] The community's scoring is adjusted based on the user's sentiment: for example, if a user feels satisfied, they will provide high-quality answers and receive more points.

[2200] Posts and answers are sent to the server and recorded in a database. The server evaluates the quality of the post and answer and awards points to the user. Updated points and rankings are sent to the device.

[2201] Examples:

[2202] When a user posts a question such as "I want to know about the risks of stock investment," other users and experts provide answers. The emotion engine analyzes the user's emotions, and if there is a lot of positive feedback, the server increases the points. The ranking is updated and displayed on the device.

[2203] These system features allow users to effectively learn, practice, and share financial knowledge with others. The incorporation of an emotion engine further enhances learning and trading experiences by optimizing according to users' emotions.

[2204] The processing flow will be explained below.

[2205] Microlearning Financial App

[2206] Processing Steps

[2207] Step 1:

[2208] The device connects to the server using the user ID and requests the user's latest learning progress data.

[2209] Step 2:

[2210] The server searches the database based on the received user ID and obtains the user's latest learning progress information.

[2211] Step 3:

[2212] The server transmits the acquired learning progress data to the terminal.

[2213] Step 4:

[2214] The terminal displays the next lesson content to the user based on the data received from the server.

[2215] Step 5:

[2216] The user watches and learns lessons presented on the screen.

[2217] Step 6:

[2218] The emotion engine analyzes the user's facial expressions and voice in real time to obtain emotional data.

[2219] Step 7:

[2220] The terminal adjusts the learning content based on the emotion data acquired by the emotion engine.

[2221] Step 8:

[2222] After the lesson is completed, the terminal displays a quiz to the user.

[2223] Step 9:

[2224] The user answers the quiz and inputs the answer into the terminal.

[2225] Step 10:

[2226] The terminal transmits the quiz answer results and emotion data to the server.

[2227] Step 11:

[2228] The server stores the quiz results and emotional data in a database and automatically prepares the next learning content.

[2229] AI-guided virtual stock trading game app

[2230] Processing Steps

[2231] Step 1:

[2232] The terminal connects to the server using the user ID and requests the latest portfolio and market data.

[2233] Step 2:

[2234] The server retrieves the user's portfolio data and the latest market data from the database.

[2235] Step 3:

[2236] The server transmits the acquired data to the terminal.

[2237] Step 4:

[2238] The terminal displays market data received from the server and AI trading advice to the user.

[2239] Step 5:

[2240] The emotion engine analyzes the user's facial expressions and voice in real time to obtain emotional data.

[2241] Step 6:

[2242] The device will then adjust the advice provided by the AI ​​guide based on the emotional data.

[2243] Step 7:

[2244] Users can choose to follow AI advice or make their own trading decisions.

[2245] Step 8:

[2246] A user executes a trade by specifying the stock to be purchased or sold and the quantity.

[2247] Step 9:

[2248] The terminal transmits the user's trade instructions to the server.

[2249] Step 10:

[2250] The server processes the trade instructions to update the virtual market database and update the user's portfolio.

[2251] Step 11:

[2252] The server returns the updated portfolio data to the terminal.

[2253] Step 12:

[2254] The terminal displays the updated portfolio data to the user, allowing the user to confirm the trading results.

[2255] A community platform for improving financial literacy

[2256] Processing Steps

[2257] Step 1:

[2258] The device connects to the server using the user ID and requests the latest forum posts and Q&A data.

[2259] Step 2:

[2260] The server retrieves forum posts and Q&A data from a database.

[2261] Step 3:

[2262] The server transmits the acquired data to the terminal.

[2263] Step 4:

[2264] The terminal displays the latest community content to the user based on the data received from the server.

[2265] Step 5:

[2266] Users review forum posts and questions and make comments and replies as needed.

[2267] Step 6:

[2268] The emotion engine analyzes the user's facial expressions and voice in real time to obtain emotional data.

[2269] Step 7:

[2270] The terminal adjusts the content of communication based on the emotion data acquired by the emotion engine.

[2271] Step 8:

[2272] Users create new posts and questions in the community forums.

[2273] Step 9:

[2274] The terminal sends user posts and questions to the server.

[2275] Step 10:

[2276] The server stores the received posts and questions in a database.

[2277] Step 11:

[2278] The server notifies other users of new posts and questions and shares them with the entire community.

[2279] Step 12:

[2280] The server scores contributions based on the quality of posts and responses and emotional data, and awards points to users.

[2281] Step 13:

[2282] The server sends the updated points and rankings to the terminal.

[2283] Step 14:

[2284] The terminal displays the updated points and ranking to the user, allowing them to see their contribution to the community.

[2285] The above are the specific program processing steps for each system that incorporates an emotion engine. In each step, the operations performed by the server, terminal, and user have been explained in detail.

[2286] Example 2

[2287] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2288] Conventional financial literacy improvement systems have difficulty responding to the emotional state of each user, and have not been able to fully optimize learning effects and trading experiences. Such systems are unable to personalize based on the user's interests, level of understanding, or emotional changes, making it difficult to maintain learning motivation or effectively convey financial knowledge.

[2289] 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.

[2290] In this invention, the server includes means for communicating with a database that manages user progress information, means for generating learning content and providing it to the user, means for recognizing the user's emotions in real time and using that data, means for receiving quiz results and emotional data and storing them in the database, and means for automatically adjusting and preparing the next learning content based on the user's emotional state, thereby providing an effective and individually optimized learning experience that reflects the user's emotional state.

[2291] "User progress information" refers to data that indicates the progress and achievement level of a user when using learning content.

[2292] "Means for communicating with a database" means means having communication capabilities for accessing a database and retrieving or storing information.

[2293] "Means for generating learning content and providing it to users" refers to means for creating educational content and distributing it to users.

[2294] "Means for recognizing user emotions in real time and using that data" refers to means for detecting user emotions in real time and using that information to personalize the learning experience.

[2295] The "means for receiving quiz results and emotion data and storing them in a database" refers to a means for receiving the user's quiz answer results and emotion data and storing them in a database.

[2296] "Means for automatically adjusting and preparing the next learning content based on the user's emotional state" refers to a means for dynamically adjusting learning content based on the user's emotional data and preparing the optimal next item.

[2297] "Means for updating virtual market data" refers to means for updating virtual market information with the latest data.

[2298] "Means for managing a user's trading history and providing advice" means means for recording and managing a user's trading history and providing trading advice to the user based on that history.

[2299] "Means for receiving trade instructions and updating the database" refers to means for receiving trading instructions from users and updating the database accordingly.

[2300] The "means for displaying updated data to the user" refers to a means for displaying the latest data updated by the server to the user.

[2301] "Means for managing user posts and questions" refers to means for recording and managing content and questions posted by users.

[2302] "Means for managing responses from other users and experts" refers to means for recording and managing responses from other users and experts.

[2303] The "means for scoring contributions and awarding points" refers to a m...

Claims

1. means for communicating with a database that manages user progress information; A means for generating and providing learning content to users; means for receiving and storing quiz results in a database; A means to automatically prepare the next learning content, A system including:

2. a means for updating the virtual market data; A means for managing a user's trading history and providing advice; means for receiving trade instructions and updating the database; means for displaying the updated data to the user; The system of claim 1 , comprising:

3. a means of managing user posts and questions; a means of managing responses from other users and experts; A means for scoring contributions and awarding points; means for displaying points and rankings to a user; The system of claim 1 , comprising:

Images