System

Abstract

A system is provided.SOLUTION: A system, comprising: means for displaying online learning content to a user, wherein the online learning content is provided using a generative AI; means for automatically suggesting a next learning step based on the user's learning progress; means for scoring a quiz result answered by the user and generating feedback; and means for providing points or coupons according to the progress of the learning.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] With the recent development of information technology (IT), basic IT literacy and programming skills have become increasingly important. However, there is a lack of educational tools for learning these skills efficiently and enjoyably. Furthermore, existing online learning platforms lack the necessary mechanisms for providing flexible content tailored to individual learning paces and for motivating students. Given this current situation, there is a lack of mechanisms for providing feedback based on learning progress, automatically suggesting the next learning step, and providing incentives to increase learning motivation. The purpose of this invention is to solve these issues and provide a system that allows users to learn IT and programming knowledge efficiently and enjoyably. [Means for solving the problem]

[0005] By providing a means to display online learning content provided by generative AI to users, the system provides optimal content according to each individual's learning pace and progress. Furthermore, by providing a means to automatically suggest the next learning step based on the user's learning progress, efficient learning is achieved. By providing a means to grade the results of quizzes answered by users and generate instant feedback, the effectiveness of learning is improved. Furthermore, by providing a means to award points and coupons according to learning progress, users' motivation to learn is strengthened. This system enables users to acquire IT and programming knowledge in a fun and efficient way.

[0006] "Generative AI" is an artificial intelligence technology that analyzes a user's learning progress and automatically generates optimal learning content and feedback.

[0007] "Online learning content" refers to digital materials such as teaching materials and practice questions that users can access via the Internet to acquire knowledge about IT and programming.

[0008] "User" refers to an individual or organization that uses this system to learn IT and programming knowledge.

[0009] "Study progress" is an index that indicates how far the user has progressed in their studies, and includes the progress and level of understanding of the learning content.

[0010] A "learning step" is the progression or section of content or assignments that a user studies.

[0011] "Automatic suggestion" is a function in which the system automatically recommends the next content or step to learn based on the user's learning history and progress.

[0012] A "quiz" is a set of questions that are answered by the user to check the level of understanding of the learning content.

[0013] "Scoring" is the process of evaluating a user's quiz answers and determining whether they are correct or incorrect.

[0014] "Feedback" refers to advice and evaluation comments provided to the user based on their learning progress and quiz results.

[0015] "Points" are a type of incentive that users can earn based on their learning progress and quiz results, and once they have accumulated a certain amount, they can be exchanged for rewards.

[0016] A "coupon" is a discount or special coupon that can be received by a user when they achieve a certain level of learning progress or quiz score, and can be exchanged for a specific service or product. [Brief explanation of the drawings]

[0017] [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

[0018] 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.

[0019] First, the terms used in the following description will be explained.

[0020] 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).

[0021] 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.

[0022] 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.

[0023] 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.

[0024] 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."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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."

[0038] The present invention provides an online learning system that utilizes generative AI to enable users to learn IT and programming knowledge in a fun and efficient manner. Specific embodiments of this system are described in detail below.

[0039] User Registration and Login

[0040] User Registration

[0041] The user enters the required information, such as name, email address, and password, and sends it from the device to the server. The server stores this information in a database and returns a message to the user indicating successful registration. The user can then create an account and begin learning.

[0042] User Login

[0043] When logging in, a registered user enters their username and password and sends them from their terminal to the server. The server compares them with the information in the database and determines whether authentication is successful. If authentication is successful, a login success message is returned and the user can access the system. If authentication is unsuccessful, a login failure message is displayed.

[0044] Providing learning content

[0045] Obtaining learning history and displaying content

[0046] After logging in, the user clicks the "Start Learning" button, which sends a request from the device to the server. The server retrieves the user's learning history from the database and generates an optimal learning path based on that information. The online learning content corresponding to this learning path is sent to the device and displayed to the user.

[0047] Quiz grading and feedback

[0048] Take the quiz and submit your answers

[0049] After completing the learning content, the user answers the provided quiz, and the device sends the user's answers to the server.

[0050] Grade quizzes and provide feedback

[0051] The server compares the user's answer with the correct answer data in the database, calculates a score, generates a feedback message based on the score and sends it to the terminal, and simultaneously records the user's score in the database. The terminal displays the score and feedback to the user.

[0052] Suggested next steps

[0053] Suggestions for next learning content

[0054] The server determines the next learning content based on the user's most recent learning history and score. This information is sent to the device and displayed as the user's next learning step. This allows the user to always know the appropriate next learning task.

[0055] Points and coupons

[0056] Points awarded based on learning outcomes

[0057] The server calculates the points to be awarded based on the user's latest score and learning progress. The calculated points are added to the user's account, and a message informing the user that the points have been earned is sent to the device. The device then displays the message to the user, encouraging them to learn.

[0058] Specific examples

[0059] Example 1: When a user creates a new account

[0060] The user enters their name, email address, and password and clicks the Register button. The device sends this information to the server, which stores it in a database. If registration is successful, the device displays a "Registration successful" message to the user.

[0061] Example 2: When a user takes a quiz

[0062] Users complete learning content and answer quizzes. The device sends the user's answers to the server, which scores them. Feedback and scores are generated and sent to the device, which displays them to the user. Users can instantly check their learning progress and receive advice on how to proceed to the next step.

[0063] This completes the embodiment of the present invention. This system allows users to acquire IT and programming knowledge efficiently and enjoyably.

[0064] The processing flow will be explained below.

[0065] User Registration and Login

[0066] User Registration

[0067] Step 1:

[0068] The user enters their name, email address, and password and clicks the "Register" button.

[0069] Step 2:

[0070] The terminal transmits the user's input information to the server.

[0071] Step 3:

[0072] The server stores the received user information in a database.

[0073] Step 4:

[0074] The server returns a message to the terminal indicating successful registration.

[0075] Step 5:

[0076] The terminal displays a "Registration successful" message to the user.

[0077] User Login

[0078] Step 1:

[0079] The user enters their username and password and clicks the "Login" button.

[0080] Step 2:

[0081] The device sends the authentication information to the server.

[0082] Step 3:

[0083] The server checks the authentication information against the information in its database to verify its accuracy.

[0084] Step 4:

[0085] If the server is successful in authentication, it returns a "Login successful" message to the terminal. If it fails, it returns a "Login failed" message.

[0086] Step 5:

[0087] The terminal displays a "Login successful" or "Login unsuccessful" message to the user.

[0088] Providing learning content

[0089] Obtaining learning history and displaying content

[0090] Step 1:

[0091] After logging in, the user clicks the "Start learning" button.

[0092] Step 2:

[0093] The device sends a request to the server.

[0094] Step 3:

[0095] The server retrieves the user's learning history from the database.

[0096] Step 4:

[0097] The server generates a new learning path based on the learning history.

[0098] Step 5:

[0099] The server transmits the generated learning content to the terminal.

[0100] Step 6:

[0101] The device displays the learning content to the user.

[0102] Quiz grading and feedback

[0103] Take the quiz and submit your answers

[0104] Step 1:

[0105] Users study learning content and take quizzes.

[0106] Step 2:

[0107] The terminal sends the user's response to the server.

[0108] Grade quizzes and provide feedback

[0109] Step 1:

[0110] The server retrieves the correct answer data from the database.

[0111] Step 2:

[0112] The server compares the user's answer with the correct answer data and calculates a score.

[0113] Step 3:

[0114] The server generates a feedback message based on the score.

[0115] Step 4:

[0116] The server sends a feedback message and a score to the device.

[0117] Step 5:

[0118] The device displays feedback and a score to the user.

[0119] Step 6:

[0120] The server records the user's score in a database.

[0121] Suggested next steps

[0122] Suggestions for next learning content

[0123] Step 1:

[0124] The server identifies the next learning step based on the user's latest learning history and score.

[0125] Step 2:

[0126] The server sends the next learning step content to the terminal.

[0127] Step 3:

[0128] The terminal displays the next learning step to the user.

[0129] Points and coupons

[0130] Points awarded based on learning outcomes

[0131] Step 1:

[0132] The server calculates the points to be awarded based on the user's learning progress and score.

[0133] Step 2:

[0134] The server adds the calculated points to the user's account.

[0135] Step 3:

[0136] The server sends a message to the terminal indicating that points have been earned.

[0137] Step 4:

[0138] The terminal displays a points acquisition message to the user.

[0139] Example 1

[0140] 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."

[0141] The present invention aims to solve the problem that, in an online system that allows users to learn IT and programming knowledge efficiently and enjoyably, it is difficult to provide appropriate learning steps according to the user's learning progress, provide feedback based on individual learning history, and issue points and rewards to increase motivation to learn.

[0142] 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.

[0143] In this invention, the server includes means for managing registration information entered by the user, means for authenticating the user based on the registration information, means for acquiring the learning history of the authenticated user, means for generating adaptive learning content based on the learning history, means for displaying the generated content to the user, means for scoring the results of quizzes answered by the user and generating feedback, means for automatically suggesting the next learning step based on the user's learning progress, and means for calculating points and rewards according to the learning progress and notifying the user. This allows the user to continuously receive appropriate learning content according to their learning progress, enabling them to effectively acquire knowledge while maintaining their motivation to learn.

[0144] "User" refers to an individual or corporation that uses the online learning system to learn.

[0145] "Registration Information" refers to information such as name, email address, and password provided by a User to the System.

[0146] "Study history" refers to data that records the learning content that a user has done on the system, as well as their progress and scores.

[0147] "Adaptive learning content" refers to optimal learning materials and question sets that are generated based on a user's individual learning history and scores.

[0148] "Quiz" refers to questions or assignments provided to users who have completed learning content.

[0149] "Feedback" refers to evaluations and advice for the user that are generated based on the results of the quiz.

[0150] "Points" are a type of reward given by the system based on the user's learning progress and results, and refer to a numerical value used to increase motivation to learn.

[0151] "Rewards" refers to incentives such as points or coupons that users can earn as they progress with their studies.

[0152] "Next learning step" refers to the next learning content or task that the system automatically suggests based on the user's current learning situation and history.

[0153] "Authentication" refers to the process of verifying a user's identity based on registration information in order to properly access a system.

[0154] "Generative AI model" refers to an artificial intelligence model used to generate optimal learning content and feedback based on a user's learning history and quiz results.

[0155] "Database" refers to a data management system for storing and managing users' learning history, registration information, etc.

[0156] "Content display" refers to the process of displaying the generated learning materials and question sets on the user's device.

[0157] "Customization" refers to individually adjusting the next learning content and steps based on the user's learning history and score.

[0158] This invention details the technology for building an online learning system, which allows users to acquire IT and programming knowledge efficiently and enjoyably.

[0159] User Registration and Login

[0160] User Registration

[0161] 1. The user enters information such as their name, email address, and password, and sends it from their device to the server.

[0162] 2. The server receives this information and stores it in a MySQL database, using Python's Flask framework and SQLAlchemy.

[0163] 3. The server returns a "Registration successful" message to the terminal, which the terminal displays to the user.

[0164] User Login

[0165] 1. The registered user enters their email address and password and sends them from their device to the server.

[0166] 2. The server authenticates the user against information stored in a database.

[0167] 3. If authentication is successful, the server returns a "Login successful" message, which the terminal displays to the user. If authentication is unsuccessful, a "Login failed" message is displayed.

[0168] Providing learning content

[0169] Obtaining learning history and displaying content

[0170] 1. After logging in, the user clicks the "Start learning" button, and the device sends a request to the server.

[0171] 2. The server retrieves the user's learning history from the database.

[0172] 3. Based on the acquired history, the server uses a generative AI model to generate adaptive learning content.

[0173] 4. The generated learning content is sent to the device and displayed to the user.

[0174] Run and grade quizzes

[0175] Take the quiz and submit your answers

[0176] 1. The user completes the learning content and answers the provided quiz. The device sends the user's answers to the server.

[0177] 2. The server receives the answer, compares it with the correct answers in the database, and calculates a score.

[0178] Grade quizzes and provide feedback

[0179] 1. The server generates a feedback message based on the score, possibly using a generative AI model.

[0180] 2. Feedback and scores are sent to the device and displayed to the user.

[0181] Suggested next steps

[0182] 1. The server determines what the user should learn next based on their most recent learning history and scores. This process is also carried out using a generative AI model.

[0183] 2. The server sends the next learning step to the terminal and displays it to the user.

[0184] Points and coupons

[0185] 1. The server calculates the points to be awarded based on the user's learning progress and achievements.

[0186] 2. The calculated points are added to the user's account, and the server sends a message to the terminal indicating that the points have been earned.

[0187] 3. The device displays a message to the user about earning points, encouraging them to study.

[0188] Specific examples

[0189] Example 1: When a user creates a new account

[0190] 1. The user enters their name, email address, and password and clicks the Register button.

[0191] 2. The device sends this information to the server as an HTTP POST request.

[0192] 3. The server stores the received data in a database and sends a success message to the terminal.

[0193] 4. The terminal displays a "Registration successful" message to the user.

[0194] Example 2: When a user takes a quiz

[0195] Users complete learning content and take quizzes.

[0196] The device sends the user's response to the server as an HTTP POST request.

[0197] The server scores the answers and generates a score and feedback message that is sent to the device.

[0198] The device displays the score and feedback to the user, allowing them to see their progress and receive advice on how to proceed.

[0199] This invention enables users to efficiently acquire knowledge of IT and programming, and allows them to continue learning while maintaining their motivation to learn.

[0200] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0201] Detailed explanation of the processing steps

[0202] User Registration

[0203] Step 1:

[0204] The user enters their name, email address, and password and clicks the register button. This sends the input information from the device to the server. The data format sent is JSON.

[0205] Step 2:

[0206] The server receives the received user information using the Flask framework and processes the data appropriately (for example, hashing the password).

[0207] Step 3:

[0208] The server uses SQLAlchemy to store the processed data in a database (MySQL), which includes the user's name, email address, and hashed password.

[0209] Step 4:

[0210] The server generates a message indicating successful registration and returns it to the terminal as an HTTP response. The terminal displays this message to the user to notify them that registration was successful.

[0211] User Login

[0212] Step 1:

[0213] The user enters their email address and password and clicks the login button. The entered information is sent from the terminal to the server. The data format sent is JSON.

[0214] Step 2:

[0215] The server queries the database using SQLAlchemy to match the login information received with the registration information retrieved from the database. The password entered is hashed and compared to the hash value in the database.

[0216] Step 3:

[0217] The server judges the authentication result, and if successful, generates a "Login successful" message and returns it to the terminal. If unsuccessful, it generates a "Login failed" message and returns it to the terminal. The terminal displays the received message to the user.

[0218] Providing learning content

[0219] Step 1:

[0220] After logging in, when the user clicks the "Start learning" button, the device sends a request including the user ID to the server.

[0221] Step 2:

[0222] The server executes a query using SQLAlchemy to retrieve the learning history from the database based on the received user ID.

[0223] Step 3:

[0224] The server inputs the acquired learning history into the generative AI model as prompt sentences to generate an optimal learning path. This input includes the user's past learning history and current score.

[0225] Step 4:

[0226] The server selects the corresponding learning content based on the generated learning path and sends it to the terminal, which then displays the received content to the user.

[0227] Run and grade quizzes

[0228] Step 1:

[0229] The user completes the learning content and answers the provided quizzes, and the device records the user's answers.

[0230] Step 2:

[0231] The device sends the recorded quiz answers to the server as an HTTP POST request in JSON format.

[0232] Step 3:

[0233] The server compares the received answers with the correct answers in the database and calculates a score, using SQLAlchemy.

[0234] Step 4:

[0235] The server generates a feedback message based on the score, possibly using a generative AI model in the generation process.

[0236] Step 5:

[0237] The server sends the feedback and score to the device, which then displays it to the user, allowing the user to check their learning progress.

[0238] Suggested next steps

[0239] Step 1:

[0240] The server retrieves the latest learning history and quiz scores from the database, using SQLAlchemy.

[0241] Step 2:

[0242] The server uses the information it has acquired to determine what to learn next, a step that uses a generative AI model.

[0243] Step 3:

[0244] The server sends the next learning step to the terminal, which then displays it to the user, allowing the user to continue learning to the next step.

[0245] Points and coupons

[0246] Step 1:

[0247] The server calculates the points to be awarded based on the user's learning progress and achievements, and this calculation may use a generative AI model.

[0248] Step 2:

[0249] The calculated points are added to the user's account, and the server generates a message notifying the user of the points being earned and sends it to the terminal.

[0250] Step 3:

[0251] The device displays a message to the user that they have earned points, allowing them to maintain their motivation to study while continuing to study.

[0252] (Application example 1)

[0253] 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."

[0254] Conventional online learning systems offer features such as automatically suggesting the next learning step based on the user's learning progress, automatically scoring quizzes, providing feedback, and awarding points and coupons. However, these systems are often implemented through standard displays, which often lack a sense of realism and immersion. Furthermore, user interaction is limited, with real-time feedback and voice and gesture control underutilized. This leads to issues such as a decline in motivation and a lack of engagement.

[0255] 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.

[0256] In this invention, the server includes a device that displays online learning content provided by using generative AI to the user, a device that allows learning in a virtual space using a wearable device such as smart glasses, a device that automatically suggests the user's next learning step based on their learning progress, a device that scores the results of quizzes answered by the user and generates feedback, a device that recognizes voice and gesture inputs and sends quiz answers to the server, and a device that awards points and coupons according to the user's learning progress.This allows users to have a more realistic and immersive learning experience, and can increase their motivation and engagement in learning through real-time feedback and interactive operations.

[0257] "Generative AI" is a type of artificial intelligence that automatically generates and provides learning content for users.

[0258] "Online learning content" means digital educational materials provided via the Internet.

[0259] "Smart glasses" are wearable devices that use display technology to overlay virtual information onto the real world.

[0260] "Wearable devices" is a general term for electronic devices worn by users.

[0261] A "virtual space" is a virtual environment generated by computer simulation.

[0262] "Study progress" is information indicating the process by which the user advances in their studies and the state of progress.

[0263] "Auto-suggestion" is a feature where the system presents the user with the best next steps or content based on data.

[0264] A "quiz" is a set of questions to assess the user's level of understanding.

[0265] "Scoring" is a process in which a user assigns points based on their answers to a quiz.

[0266] "Feedback" refers to information about evaluations and areas for improvement provided to users.

[0267] "Voice input" is a method of recognizing a user's speech and sending information to a system.

[0268] "Gesture input" is a method in which sensors read the user's movements and send information to the system.

[0269] A "server" is a computer system that provides services to clients over a network.

[0270] "Points" are digital evaluation units awarded based on a user's learning progress and achievements.

[0271] A "coupon" is a discount ticket or service coupon given to a user depending on the results of their learning.

[0272] This invention realizes an online learning system using generative AI in combination with wearable devices such as smart glasses, which provides users with a more immersive learning experience, allowing for real-time feedback and interactive operation.

[0273] Hardware and Software Configuration

[0274] Hardware used:

[0275] Smart glasses: A wearable device worn by the user that uses display technology to overlay a virtual space onto the real world.

[0276] Server: A computer system that provides services to clients over the Internet.

[0277] Software used:

[0278] Generative AI models: Use artificial intelligence models such as GPT-4 to generate learning content and next learning steps.

[0279] Database: Manages user learning history and scores using SQLite etc.

[0280] Flask: A Python web framework that handles server-side processing.

[0281] System Operation

[0282] 1. User Registration and Login:

[0283] The server stores the authentication information provided by the user, such as the name, email address, and password, in a database and registers the user. When logging in, the entered authentication information is compared with the information in the database to determine whether the authentication was successful.

[0284] 2. Providing online learning content:

[0285] When a user wears smart glasses and logs into the virtual space, the server uses the generative AI model to generate appropriate learning content, which is then displayed on the smart glasses' display.

[0286] 3. Track your progress and suggest next steps:

[0287] The server records the user's learning progress in a database and automatically suggests the next step to learn based on that data, ensuring that the user is always on the optimal learning path.

[0288] 4. Take the quiz and provide feedback:

[0289] After completing the learning content, the user answers a quiz using the smart glasses. The quiz is answered using voice or gesture input, and the data is sent to the server. The server scores the quiz results and generates feedback that is displayed on the smart glasses' display.

[0290] 5. Points and coupons awarded:

[0291] The server calculates points based on the user's learning progress and quiz scores, and issues coupons at appropriate times, thereby increasing the user's motivation to study.

[0292] Specific examples

[0293] Example of user registration:

[0294] The user puts on the smart glasses and executes the "Register" command using voice commands. When the user enters their name, email address, and password by voice, the smart glasses recognize it and send it to the server, completing the registration.

[0295] A concrete example of running a quiz:

[0296] After completing the learning content, users answer quizzes displayed on the smart glasses display using voice or gestures. The answers are recognized by the smart glasses' sensors and sent to the server.

[0297] Example of an input prompt for a generative AI model:

[0298] Generate the next best learning content based on the user's learning history data. Below is the user's learning history.

[0299] Lesson 1: ... (detail)

[0300] Lesson 2: ... (detail)

[0301] Generate what content is best for you next.

[0302] Unlike traditional display learning, this system allows users to enjoy a more interactive and realistic learning experience. By utilizing real-time feedback and voice and gesture input, learning motivation and engagement are significantly improved.

[0303] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0304] Step 1:

[0305] The user puts on the smart glasses and executes the "Register" command with a voice command. The voice recognition system of the smart glasses receives the name, email address, and password, and sends this data to the server. The server stores the received data in a database, and returns a "Register Successful" message to the user if registration is successful. The input is the name, email address, and password, and the output is the registration success message.

[0306] Step 2:

[0307] To log in, a user enters their username and password via voice commands through the smart glasses. The smart glasses then send this authentication information to the server, which checks it against the information in its database. If the authentication is successful, the server returns a "login successful" message, and the user can enter the virtual space. The input is the username and password, and the output is the login successful message.

[0308] Step 3:

[0309] When a user logs into the virtual space, the server generates a prompt based on the user's learning history data and sends a request to the generative AI model to generate the next optimal learning content. The generative AI model generates the learning content and returns the data to the server. The server sends the content to the smart glasses and displays it to the user. The input is the user's learning history data, and the output is the learning content.

[0310] Step 4:

[0311] After the user has completed the learning content, the server generates a quiz and displays it on the smart glasses' display. The user answers the quiz through voice or gestures, and the answer data is sent to the server by the smart glasses. The input is the user's quiz answer, and the output is the quiz answer data.

[0312] Step 5:

[0313] The server compares the received quiz answer data with the correct answer data in the database and calculates a score. Based on this score, the server generates a feedback message and sends it to the smart glasses. The smart glasses display the feedback and score to the user. The input is the quiz answer data and correct answer data, and the output is the score and feedback message.

[0314] Step 6:

[0315] The server records the user's latest learning history and score in a database and requests the generative AI model to suggest the next learning content. The generative AI model generates the next learning step and returns that information to the server. The server then sends the next learning step to the smart glasses and displays it to the user. The input is the user's latest learning history and score, and the output is the next learning content.

[0316] Step 7:

[0317] The server calculates points based on the user's learning progress and quiz scores, and issues coupons in a timely manner. The points and coupon information are sent to the smart glasses and displayed to the user. The input is the learning progress and score, and the output is the points and coupon information.

[0318] 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.

[0319] The present invention provides an online learning system that utilizes generative AI and an emotion engine to enable users to effectively learn IT and programming knowledge. Specific embodiments of this system are described in detail below.

[0320] User Registration and Login

[0321] User Registration

[0322] The user enters the required information, such as name, email address, and password, and sends it from the device to the server. The server stores this information in a database and returns a message to the user indicating successful registration. The user can then create an account and begin learning.

[0323] User Login

[0324] When logging in, a registered user enters their username and password and sends them from their terminal to the server. The server compares them with the information in the database and determines whether authentication is successful. If authentication is successful, a login success message is returned and the user can access the system. If authentication is unsuccessful, a login failure message is displayed.

[0325] Providing learning content

[0326] Obtaining learning history and displaying content

[0327] After logging in, the user clicks the "Start Learning" button, which sends a request from the device to the server. The server retrieves the user's learning history from the database and generates an optimal learning path based on that information. The online learning content corresponding to this learning path is sent to the device and displayed to the user.

[0328] Quiz grading and feedback

[0329] Take the quiz and submit your answers

[0330] After completing the learning content, the user answers the provided quiz, and the device sends the user's answers to the server.

[0331] Grade quizzes and provide feedback

[0332] The server compares the user's answer with the correct answer data in the database and calculates a score. It generates a feedback message based on the score and sends it to the terminal. At the same time, it records the user's score in the database. The terminal displays the score and feedback to the user.

[0333] Suggested next steps

[0334] Suggestions for next learning content

[0335] The server determines the next learning content based on the user's most recent learning history and score. This information is sent to the device and displayed as the user's next learning step. This allows the user to always know the appropriate next learning task.

[0336] Points and coupons

[0337] Points awarded based on learning outcomes

[0338] The server calculates the points to be awarded based on the user's latest score and learning progress. The calculated points are added to the user's account, and a message informing the user that the points have been earned is sent to the device. The device then displays the message to the user, encouraging them to learn.

[0339] Introducing the Emotion Engine

[0340] Emotion Engine Functions

[0341] The emotion engine has the function of recognizing the user's emotional state in real time through facial expression and voice analysis. This recognized emotional information is integrated into various functions of the system as follows:

[0342] Adjusting content based on emotions

[0343] The emotional engine recognizes the user's emotional state and adjusts the difficulty of the learning content if it detects stress, for example: if the user is relaxed, more challenging content can be provided.

[0344] Modifying Feedback Based on Emotions

[0345] An emotion engine recognizes the user's emotional state and adjusts feedback messages accordingly, for example, providing more detailed explanations or encouraging messages if the user is confused.

[0346] Adjusted the points system to increase motivation to learn

[0347] The emotional engine recognizes the user's emotional state and adjusts the criteria for awarding points and coupons. If the user is tired or unmotivated, extra bonus points will be awarded to encourage learning.

[0348] Suggesting a break

[0349] If the emotion engine detects stress or fatigue in the user, the system will suggest a break, allowing the user to continue learning without straining themselves.

[0350] Specific examples

[0351] Example 1: When a user creates a new account

[0352] The user enters their name, email address, and password and clicks the Register button. The device sends this information to the server, which stores it in a database. If registration is successful, the device displays a "Registration successful" message to the user.

[0353] Example 2: When a user takes a quiz

[0354] Users complete learning content and answer quizzes. The device sends the user's answers to the server, which scores them. Feedback and scores are generated and sent to the device, which displays them to the user. Users can instantly check their learning progress and receive advice on how to proceed to the next step.

[0355] This concludes the embodiment of the present invention. This system allows users to acquire IT and programming knowledge efficiently and enjoyably. The introduction of an emotion engine is expected to provide a learning experience that is tailored to each individual user, further improving learning effectiveness.

[0356] The processing flow will be explained below.

[0357] User Registration and Login

[0358] User Registration

[0359] Step 1:

[0360] The user enters their name, email address, and password and clicks the "Register" button.

[0361] Step 2:

[0362] The terminal transmits the user's input information to the server.

[0363] Step 3:

[0364] The server stores the received user information in a database.

[0365] Step 4:

[0366] The server returns a message to the terminal indicating successful registration.

[0367] Step 5:

[0368] The terminal displays a "Registration successful" message to the user.

[0369] User Login

[0370] Step 1:

[0371] The user enters their username and password and clicks the "Login" button.

[0372] Step 2:

[0373] The device sends the authentication information to the server.

[0374] Step 3:

[0375] The server checks the authentication information against the information in its database to verify its accuracy.

[0376] Step 4:

[0377] If the server is successful in authentication, it returns a "Login successful" message to the terminal. If it fails, it returns a "Login failed" message.

[0378] Step 5:

[0379] The terminal displays a "Login successful" or "Login unsuccessful" message to the user.

[0380] Providing learning content

[0381] Obtaining learning history and displaying content

[0382] Step 1:

[0383] After logging in, the user clicks the "Start learning" button.

[0384] Step 2:

[0385] The device sends a request to the server.

[0386] Step 3:

[0387] The server retrieves the user's learning history from the database.

[0388] Step 4:

[0389] The server generates a new learning path based on the learning history.

[0390] Step 5:

[0391] The server transmits the generated learning content to the terminal.

[0392] Step 6:

[0393] The device displays the learning content to the user.

[0394] Quiz grading and feedback

[0395] Take the quiz and submit your answers

[0396] Step 1:

[0397] Users study learning content and take quizzes.

[0398] Step 2:

[0399] The terminal sends the user's response to the server.

[0400] Grade quizzes and provide feedback

[0401] Step 1:

[0402] The server retrieves the correct answer data from the database.

[0403] Step 2:

[0404] The server compares the user's answer with the correct answer data and calculates a score.

[0405] Step 3:

[0406] The server generates a feedback message based on the score.

[0407] Step 4:

[0408] The server sends a feedback message and a score to the device.

[0409] Step 5:

[0410] The device displays feedback and a score to the user.

[0411] Step 6:

[0412] The server records the user's score in a database.

[0413] Suggested next steps

[0414] Suggestions for next learning content

[0415] Step 1:

[0416] The server identifies the next learning step based on the user's latest learning history and score.

[0417] Step 2:

[0418] The server sends the next learning step content to the terminal.

[0419] Step 3:

[0420] The terminal displays the next learning step to the user.

[0421] Points and coupons

[0422] Points awarded based on learning outcomes

[0423] Step 1:

[0424] The server calculates the points to be awarded based on the user's learning progress and score.

[0425] Step 2:

[0426] The server adds the calculated points to the user's account.

[0427] Step 3:

[0428] The server sends a message to the terminal indicating that points have been earned.

[0429] Step 4:

[0430] The terminal displays a points acquisition message to the user.

[0431] Introducing the Emotion Engine

[0432] Emotion Engine Functions

[0433] Step 1:

[0434] The emotion engine analyzes the user's facial expressions and voice in real time.

[0435] Step 2:

[0436] The emotion engine transmits the analyzed emotion data to the server.

[0437] Step 3:

[0438] The emotional data received by the server is stored in a database and used to adjust current learning content and feedback.

[0439] Adjusting content based on emotions

[0440] Step 1:

[0441] The server determines the user's emotional state based on data from the emotion engine.

[0442] Step 2:

[0443] The server adjusts the difficulty of the learning content according to the emotional state.

[0444] Step 3:

[0445] The adapted learning content is sent to the device.

[0446] Step 4:

[0447] The device displays the tailored content to the user.

[0448] Modifying Feedback Based on Emotions

[0449] Step 1:

[0450] The server determines the user's emotional state based on data from the emotion engine.

[0451] Step 2:

[0452] The server generates a feedback message according to the emotional state.

[0453] Step 3:

[0454] The generated feedback is sent to the device.

[0455] Step 4:

[0456] The device displays tailored feedback to the user.

[0457] Adjusted the points system to increase motivation to learn

[0458] Step 1:

[0459] The server determines the user's emotional state based on data from the emotion engine.

[0460] Step 2:

[0461] The server adjusts the criteria for awarding points and coupons depending on the emotional state of the user.

[0462] Step 3:

[0463] Calculate adjusted points or coupons and add them to the user's account.

[0464] Step 4:

[0465] A message about points being earned is sent to the terminal.

[0466] Step 5:

[0467] The terminal displays the tailored points earning message to the user.

[0468] Suggesting a break

[0469] Step 1:

[0470] The server detects the user's stress and fatigue state based on data from the emotion engine.

[0471] Step 2:

[0472] The server generates a message suggesting a break and sends it to the terminal.

[0473] Step 3:

[0474] The terminal displays a message suggesting that the user take a break.

[0475] Example 2

[0476] 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."

[0477] While existing online learning systems offer basic functions such as tracking users' learning progress, scoring quizzes, and suggesting next steps, they lack consideration for the user's emotional state, which means the effectiveness of learning is not maximized. Furthermore, due to complex authentication processes and lack of break suggestions based on progress, there is a risk that users' motivation to learn will decrease. Furthermore, the inability to provide emotional feedback or adjust point allocation makes it difficult to provide an optimal learning experience tailored to each individual user.

[0478] 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.

[0479] In this invention, the server includes a means for displaying online learning content provided by a generation AI to the user, a means for automatically suggesting the next learning step based on the user's learning progress, a means for scoring the results of quizzes answered by the user and generating feedback, a means for awarding points or coupons according to the user's learning progress, a means for recognizing the user's emotions in real time and adjusting the difficulty level of the learning content, and a means for adjusting feedback messages based on the user's emotions. This enables the provision of adaptive learning content that takes into account the user's emotional state and the adjustment of the point system to maintain motivation while continuing to learn. Furthermore, the server can improve learning efficiency by suggesting breaks when fatigue or stress is detected.

[0480] "Generative AI" is a technology that uses artificial intelligence to automatically generate content such as text, images, and audio.

[0481] "Online learning content" refers to educational teaching materials and resources provided via the Internet.

[0482] "User's learning progress" is information indicating the results the user has achieved through their learning activities and their current level of achievement.

[0483] The "next learning step" refers to the next learning task or learning material that the user should tackle after completing the current learning content.

[0484] "Scoring the quiz results" means calculating and evaluating the percentage of correct answers and scores for the quiz answers given by the user.

[0485] "Generating feedback" means providing advice and comments based on the user's learning progress and quiz results.

[0486] "Giving points or coupons" means giving points or discount coupons as a reward for the user's learning activities.

[0487] "Real-time emotion recognition" means instantly analyzing and understanding a user's emotional state based on their facial expressions, voice, and behavior.

[0488] "Adjusting the difficulty level of learning content" means changing the difficulty level of the learning materials according to the user's emotions and learning progress.

[0489] "Adjusting the feedback message" means providing feedback whose content is in accordance with the user's emotional state.

[0490] "Performing authentication based on authentication information" means checking the username and password provided by the user and verifying their validity.

[0491] "Retrieving learning history from database" means searching and retrieving records of the user's past learning activities from the database.

[0492] "Generating an adaptive learning path" means determining the optimal learning order and learning materials based on the user's learning history and progress.

[0493] "Recording answers and reflecting them in the next study" means that the results of the user's answers to quizzes and tests are saved and used the next time they study.

[0494] "Suggest a break" means encouraging the user to temporarily stop studying when they feel tired or stressed.

[0495] "Individually customizing" means adjusting the content and progress to suit each user's individual situation.

[0496] "Calculating points" means calculating the points acquired based on the user's learning activities.

[0497] "Adjusting points and coupons" means changing the content and amount of rewards given depending on the user's emotional state and effort.

[0498] The present invention provides an online learning system that utilizes generative AI and an emotion engine to enable users to effectively learn IT and programming knowledge. Specific embodiments of this system are described in detail below.

[0499] User Registration and Login

[0500] This system requires user registration first. The user enters their name, email address, and password, and sends them from their terminal to the server. The server stores this information in a database and sends a message to the user indicating successful registration to the terminal. The database used in this process is a relational database management system such as MySQL.

[0501] Next, the user logs in using the registered information. They enter their username and password and send them from the terminal to the server. The server compares them with the information in the database and determines whether the authentication was successful. If successful, a login success message is returned and the user can access the system. If unsuccessful, a login failure message is displayed.

[0502] Providing learning content

[0503] When a logged-in user clicks the "Start Learning" button, a request is sent from the device to the server. The server retrieves the user's learning history from a database and generates an optimal learning path based on that information. A generative AI model (e.g., GPT-3) is used in this process. Online learning content corresponding to the generated learning path is sent to the device and displayed to the user.

[0504] Quiz grading and feedback

[0505] After completing the learning content, the user answers the provided quiz. The device sends the user's answers to the server. The server compares the user's answers with the correct answers in the database and calculates a score. A feedback message is generated based on the score and sent to the device. At the same time, the user's score is recorded in the database. The device displays the score and feedback to the user.

[0506] Suggested next steps

[0507] The server determines the next learning content based on the user's most recent learning history and score. This information is sent to the device and displayed as the user's next learning step. This allows the user to always know the appropriate next learning task.

[0508] Points and coupons

[0509] The server calculates the points to be awarded based on the user's latest score and learning progress. The calculated points are added to the user's account, and a message informing the user that the points have been earned is sent to the device. The device then displays the message to the user, encouraging them to learn.

[0510] Introducing the Emotion Engine

[0511] The emotion engine has the ability to recognize the user's emotional state in real time through facial expression and voice analysis. This recognized emotional information is integrated into various functions of the system as follows: If the emotion engine recognizes the user's emotional state and detects, for example, stress, it can adjust the difficulty of the learning content. If the user is relaxed, it can provide more challenging content.

[0512] The emotion engine also adjusts feedback messages based on the user's emotional state. If the user is confused, it will provide more detailed explanations or encouraging messages. Furthermore, the emotion engine recognizes the user's emotional state and adjusts the criteria for awarding points and coupons. If the user is tired or unmotivated, it can award extra bonus points to motivate them to continue learning.

[0513] If the emotion engine detects stress or fatigue in the user, the system will suggest a break, allowing the user to continue learning without straining themselves.

[0514] Specific examples

[0515] Example 1: When a user creates a new account

[0516] The user enters their name, email address, and password and clicks the Register button. The device sends this information to the server, which stores it in a database (e.g., MySQL). If registration is successful, the device displays a "Registration successful" message to the user.

[0517] Example 2: When a user takes a quiz

[0518] Users complete learning content and answer quizzes. The device sends the user's answers to the server, which scores them. Feedback and scores are generated and sent to the device, which displays them to the user. Users can instantly check their learning progress and receive advice on how to proceed to the next step.

[0519] Prompt Sentence Examples

[0520] By inputting the prompt sentence "Generate a prompt to suggest the next learning step," the generative AI model can suggest appropriate learning steps.

[0521] The above is a specific embodiment of the online learning system of the present invention. This system allows users to acquire IT and programming knowledge efficiently and enjoyably. The introduction of an emotion engine is expected to provide users with a personalized learning experience, further improving learning effectiveness.

[0522] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0523] Step 1: User Registration

[0524] The user enters their name, email address, and password and clicks the Register button.

[0525] The terminal sends this information to the server using the HTTPS protocol.

[0526] The server performs validation checks on the transmitted information (checking the format, password strength, etc.).

[0527] If validation passes, the server saves the information in a database (e.g. MySQL) and generates a registration success message.

[0528] The server sends a registration success message to the terminal, and the terminal displays the message "Registration successful" to the user.

[0529] Input: Name, email address, password, Output: Registration successful message.

[0530] Step 2: User Login

[0531] The user enters their username (or email address) and password and clicks the login button.

[0532] The terminal transmits this information to the server.

[0533] The server authenticates the user by checking the information in the database, for example by comparing the hash value of the entered password with the hash value in the database.

[0534] If authentication is successful, the server generates a token (e.g., a JWT token) and sends it to the terminal.

[0535] The terminal receives the token and starts the user's session. It displays a success message to the user.

[0536] Input: Username (or email address), password. Output: Authentication token, login success message.

[0537] Step 3: Provide learning content

[0538] The user clicks the "Start Learning" button.

[0539] The terminal sends a request to the server.

[0540] The server retrieves the user's learning history from the database and processes the information.

[0541] The server uses a generative AI model (e.g., GPT-3) to generate the optimal learning path.

[0542] The server transmits the generated learning content to the terminal, which displays it to the user.

[0543] Input: Learning start request, Output: Optimal learning content.

[0544] Step 4: Run and grade the quiz

[0545] Users complete learning content and take quizzes.

[0546] The terminal transmits the user's answer to the server.

[0547] The server compares the user's answer with the correct answer data in the database and calculates a score.

[0548] The server generates a feedback message based on the calculated score and sends it to the terminal.

[0549] The terminal displays a feedback message and score to the user.

[0550] Input: quiz answers, Output: scores, feedback messages.

[0551] Step 5: Suggest next learning steps

[0552] The server determines what to study next based on the most recent learning history and score.

[0553] The server uses the generative AI model to generate prompts (e.g., "Generate a prompt that suggests the next learning step") and determine the next learning path.

[0554] The server sends the next learning content to the terminal, which then displays it to the user.

[0555] Input: Latest learning history and score, Output: Next learning content.

[0556] Step 6: Points and coupons awarded

[0557] The server calculates the points to be awarded based on the latest score and learning progress.

[0558] The calculated points are recorded in a database by the server.

[0559] The server sends a points acquisition message to the terminal, which displays it to the user.

[0560] Input: Latest score, Output: Calculated points, Points earned message.

[0561] Step 7: Use the Emotion Engine

[0562] The emotion engine analyzes the user's facial expressions and voice to recognize emotions in real time.

[0563] Based on the emotional information recognized by the emotion engine, the server adjusts the difficulty level of the learning content.

[0564] The server also adjusts the feedback message according to the emotional state and sends it to the terminal.

[0565] If the emotion engine detects stress or fatigue, the server generates a message suggesting a break and sends it to the terminal.

[0566] The terminal displays these messages to the user.

[0567] Input: User's facial expressions and voice, Output: Tailored learning content, feedback messages, break suggestion messages.

[0568] (Application example 2)

[0569] 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."

[0570] Conventional online learning systems provide learning paths and quiz feedback based on a user's learning progress and history, but lack the ability to analyze the user's emotional state in real time and dynamically adjust learning content and feedback. As a result, users' motivation tends to drop and learning efficiency declines. In addition, point systems to improve motivation to learn are limited, making continuity of learning an issue.

[0571] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for displaying online learning content provided to the user using a generation AI, a means for automatically suggesting the next learning step based on the user's learning progress, a means for scoring the results of quizzes answered by the user and generating feedback, a means for awarding points or coupons according to the learning progress, a means for analyzing the user's emotional state using the camera and microphone of the smart device, and a means for adjusting the learning content based on the analysis results. This makes it possible to provide a dynamic learning experience that corresponds to the user's emotional state, increasing motivation to learn and enabling effective knowledge acquisition.

[0572] "Learning Content" means educational content created using generative AI and made available to users through an online platform.

[0573] "Generative AI" is a type of artificial intelligence that generates optimal learning paths and feedback based on a user's learning history and response results.

[0574] A "quiz" is a question-based test presented to a user after completing learning content, and is a means of assessing the user's level of understanding of the learning.

[0575] "Points" are rewards given to users according to their progress and achievements in learning, and are used to increase the user's motivation to learn.

[0576] A "coupon" is something that is given to a user as a reward for learning activities, and can be exchanged for a specific service or product.

[0577] A "smart device" is a device equipped with a camera and a microphone and used to analyze the emotional state of a user.

[0578] The "emotion engine" is a technology that analyzes the user's facial expressions and voice to recognize their emotional state in real time.

[0579] An "adaptive learning path" is an individually customized learning path that is generated based on a user's learning history and current learning progress.

[0580] A "feedback message" is a message for learning support that is provided according to the user's quiz results and emotional state.

[0581] "Break suggestion" is a function that suggests to the user that they take a break if the emotion engine detects stress or fatigue in the user.

[0582] System Overview

[0583] This invention is an online learning system that utilizes generative AI and an emotion engine to enable users to effectively learn IT and programming knowledge. This system provides learning content to users via smart devices (such as smartphones and tablets) and dynamically adjusts the learning experience according to the user's learning progress and emotional state.

[0584] User Registration and Login

[0585] The server stores the authentication information provided by the user, such as name, email address, and password, in a database, which allows the user to access the learning system. After registration and login, the server manages the user's learning history and provides an adaptive learning path for the next time the user studies.

[0586] Providing learning content

[0587] The server uses generative AI to generate online learning content and displays it on the user's device. When the user clicks the "Start Learning" button, the server retrieves the user's learning history from the database and generates an optimal learning path based on that information. The content corresponding to that learning path is sent to the device and displayed to the user.

[0588] Quiz grading and feedback

[0589] When the user finishes the learning content, a quiz is displayed. When the user answers the quiz, the device sends the answer to the server, which compares it with the correct answer data and calculates a score. A feedback message is generated based on this score and displayed to the user via the device. The user's score is also reflected in the generation of the next learning path.

[0590] Introducing the Emotion Engine

[0591] The server utilizes an emotion engine that analyzes the user's emotional state in real time using the smart device's camera and microphone. For example, if the emotion engine detects that the user is stressed, it can adjust the difficulty of the learning content or suggest a break. Feedback messages are also adjusted based on the user's emotional state.

[0592] A points system to increase motivation to learn

[0593] The server awards points and coupons based on the user's learning progress and quiz scores. These points are displayed on the user's device and can be used to exchange for rewards. In particular, if the emotion engine detects a decline in the user's motivation, it can award special bonus points to improve the user's motivation to learn.

[0594] Specific examples

[0595] For example, when a user creates a new account and begins studying and taking a quiz, the emotion engine detects a decline in concentration from the user's facial expressions. In this case, the difficulty level of the learning content is automatically lowered to allow the user to continue studying at a comfortable pace. The feedback message provided after the quiz is graded is also adjusted to include words of encouragement or additional explanation.

[0596] Prompt Sentence Examples

[0597] Generate new quiz questions below to prompt your AI model with the right feedback to help users overcome emotional disorders.

[0598] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0599] Step 1:

[0600] A user registers by entering their name, email address, and password on their terminal. They provide their name, email address, and password as input and send them from the terminal to the server. The server stores this information in a database and sends a "Registration successful" message to the terminal as output, which is displayed to the user.

[0601] Step 2:

[0602] A user logs in by entering an email address and password on the terminal. The email address and password are provided as input and sent from the terminal to the server. The server compares them with the user information in the database and performs authentication. If authentication is successful, a "Login successful" message is output and sent to the terminal. If authentication fails, a "Login failed" message is displayed.

[0603] Step 3:

[0604] After logging in, the user clicks the "Start Learning" button. The device sends a request to the server, providing the user's authentication information as input. The server retrieves the user's learning history from the database and uses generative AI to generate an optimal learning path. Online learning content based on this learning path is sent to the device as output and displayed to the user.

[0605] Step 4:

[0606] Users study according to the learning content provided on their devices. While studying, the smart device's camera and microphone capture the user's facial expressions and voice, collecting emotional data as input. The server's emotion engine analyzes this data and recognizes the user's emotional state in real time. For example, if stress or fatigue is detected, the difficulty level will be adjusted or a break will be suggested.

[0607] Step 5:

[0608] After completing the study, the user answers the quiz on the device. The user's answers are provided as input and sent from the device to the server. The server compares the user's answers with the correct answers in the database and calculates a score. A feedback message is generated based on the score, and the feedback message and score are sent as output to the device and displayed to the user.

[0609] Step 6:

[0610] The server determines the next learning content based on the user's latest learning history and score. This information is taken as input from the database, and the optimal next learning step is output and sent to the terminal. The user then performs the next learning activity based on this.

[0611] Step 7:

[0612] The server calculates points and coupons according to the user's learning progress and quiz scores. The server uses the user's learning history and score as input, and the calculated points and coupons are added to the user's account as output. A message about the points earned is sent to the terminal, which then displays it to the user.

[0613] Step 8:

[0614] While the user continues learning, the emotion engine continuously collects and analyzes the user's emotional data. Feedback messages and learning content are dynamically adjusted according to the user's emotional state. For example, a confused user may be provided with detailed explanations, and a user with low motivation may be awarded extra bonus points.

[0615] Example prompt

[0616] Generate new quiz questions below to prompt your AI model with the right feedback to help users overcome emotional disorders.

[0617] 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.

[0618] 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.

[0619] 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.

[0620] [Second embodiment]

[0621] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0622] 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.

[0623] 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).

[0624] 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.

[0625] 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.

[0626] 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).

[0627] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0628] 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.

[0629] 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.

[0630] 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.

[0631] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0632] 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."

[0633] The present invention provides an online learning system that utilizes generative AI to enable users to learn IT and programming knowledge in a fun and efficient manner. Specific embodiments of this system are described in detail below.

[0634] User Registration and Login

[0635] User Registration

[0636] The user enters the required information, such as name, email address, and password, and sends it from the device to the server. The server stores this information in a database and returns a message to the user indicating successful registration. The user can then create an account and begin learning.

[0637] User Login

[0638] When logging in, a registered user enters their username and password and sends them from their terminal to the server. The server compares them with the information in the database and determines whether authentication is successful. If authentication is successful, a login success message is returned and the user can access the system. If authentication is unsuccessful, a login failure message is displayed.

[0639] Providing learning content

[0640] Obtaining learning history and displaying content

[0641] After logging in, the user clicks the "Start Learning" button, which sends a request from the device to the server. The server retrieves the user's learning history from the database and generates an optimal learning path based on that information. The online learning content corresponding to this learning path is sent to the device and displayed to the user.

[0642] Quiz grading and feedback

[0643] Take the quiz and submit your answers

[0644] After completing the learning content, the user answers the provided quiz, and the device sends the user's answers to the server.

[0645] Grade quizzes and provide feedback

[0646] The server compares the user's answer with the correct answer data in the database, calculates a score, generates a feedback message based on the score and sends it to the terminal, and simultaneously records the user's score in the database. The terminal displays the score and feedback to the user.

[0647] Suggested next steps

[0648] Suggestions for next learning content

[0649] The server determines the next learning content based on the user's most recent learning history and score. This information is sent to the device and displayed as the user's next learning step. This allows the user to always know the appropriate next learning task.

[0650] Points and coupons

[0651] Points awarded based on learning outcomes

[0652] The server calculates the points to be awarded based on the user's latest score and learning progress. The calculated points are added to the user's account, and a message informing the user that the points have been earned is sent to the device. The device then displays the message to the user, encouraging them to learn.

[0653] Specific examples

[0654] Example 1: When a user creates a new account

[0655] The user enters their name, email address, and password and clicks the Register button. The device sends this information to the server, which stores it in a database. If registration is successful, the device displays a "Registration successful" message to the user.

[0656] Example 2: When a user takes a quiz

[0657] Users complete learning content and answer quizzes. The device sends the user's answers to the server, which scores them. Feedback and scores are generated and sent to the device, which displays them to the user. Users can instantly check their learning progress and receive advice on how to proceed to the next step.

[0658] This completes the embodiment of the present invention. This system allows users to acquire IT and programming knowledge efficiently and enjoyably.

[0659] The processing flow will be explained below.

[0660] User Registration and Login

[0661] User Registration

[0662] Step 1:

[0663] The user enters their name, email address, and password and clicks the "Register" button.

[0664] Step 2:

[0665] The terminal transmits the user's input information to the server.

[0666] Step 3:

[0667] The server stores the received user information in a database.

[0668] Step 4:

[0669] The server returns a message to the terminal indicating successful registration.

[0670] Step 5:

[0671] The terminal displays a "Registration successful" message to the user.

[0672] User Login

[0673] Step 1:

[0674] The user enters their username and password and clicks the "Login" button.

[0675] Step 2:

[0676] The device sends the authentication information to the server.

[0677] Step 3:

[0678] The server checks the authentication information against the information in its database to verify its accuracy.

[0679] Step 4:

[0680] If the server is successful in authentication, it returns a "Login successful" message to the terminal. If it fails, it returns a "Login failed" message.

[0681] Step 5:

[0682] The terminal displays a "Login successful" or "Login unsuccessful" message to the user.

[0683] Providing learning content

[0684] Obtaining learning history and displaying content

[0685] Step 1:

[0686] After logging in, the user clicks the "Start learning" button.

[0687] Step 2:

[0688] The device sends a request to the server.

[0689] Step 3:

[0690] The server retrieves the user's learning history from the database.

[0691] Step 4:

[0692] The server generates a new learning path based on the learning history.

[0693] Step 5:

[0694] The server transmits the generated learning content to the terminal.

[0695] Step 6:

[0696] The device displays the learning content to the user.

[0697] Quiz grading and feedback

[0698] Take the quiz and submit your answers

[0699] Step 1:

[0700] Users study learning content and take quizzes.

[0701] Step 2:

[0702] The terminal sends the user's response to the server.

[0703] Grade quizzes and provide feedback

[0704] Step 1:

[0705] The server retrieves the correct answer data from the database.

[0706] Step 2:

[0707] The server compares the user's answer with the correct answer data and calculates a score.

[0708] Step 3:

[0709] The server generates a feedback message based on the score.

[0710] Step 4:

[0711] The server sends a feedback message and a score to the device.

[0712] Step 5:

[0713] The device displays feedback and a score to the user.

[0714] Step 6:

[0715] The server records the user's score in a database.

[0716] Suggested next steps

[0717] Suggestions for next learning content

[0718] Step 1:

[0719] The server identifies the next learning step based on the user's latest learning history and score.

[0720] Step 2:

[0721] The server sends the next learning step content to the terminal.

[0722] Step 3:

[0723] The terminal displays the next learning step to the user.

[0724] Points and coupons

[0725] Points awarded based on learning outcomes

[0726] Step 1:

[0727] The server calculates the points to be awarded based on the user's learning progress and score.

[0728] Step 2:

[0729] The server adds the calculated points to the user's account.

[0730] Step 3:

[0731] The server sends a message to the terminal indicating that points have been earned.

[0732] Step 4:

[0733] The terminal displays a points acquisition message to the user.

[0734] Example 1

[0735] 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."

[0736] The present invention aims to solve the problem that, in an online system that allows users to learn IT and programming knowledge efficiently and enjoyably, it is difficult to provide appropriate learning steps according to the user's learning progress, provide feedback based on individual learning history, and issue points and rewards to increase motivation to learn.

[0737] 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.

[0738] In this invention, the server includes means for managing registration information entered by the user, means for authenticating the user based on the registration information, means for acquiring the learning history of the authenticated user, means for generating adaptive learning content based on the learning history, means for displaying the generated content to the user, means for scoring the results of quizzes answered by the user and generating feedback, means for automatically suggesting the next learning step based on the user's learning progress, and means for calculating points and rewards according to the learning progress and notifying the user. This allows the user to continuously receive appropriate learning content according to their learning progress, enabling them to effectively acquire knowledge while maintaining their motivation to learn.

[0739] "User" refers to an individual or corporation that uses the online learning system to learn.

[0740] "Registration Information" refers to information such as name, email address, and password provided by a User to the System.

[0741] "Study history" refers to data that records the learning content that a user has done on the system, as well as their progress and scores.

[0742] "Adaptive learning content" refers to optimal learning materials and question sets that are generated based on a user's individual learning history and scores.

[0743] "Quiz" refers to questions or assignments provided to users who have completed learning content.

[0744] "Feedback" refers to evaluations and advice for the user that are generated based on the results of the quiz.

[0745] "Points" are a type of reward given by the system based on the user's learning progress and results, and refer to a numerical value used to increase motivation to learn.

[0746] "Rewards" refers to incentives such as points or coupons that users can earn as they progress with their studies.

[0747] "Next learning step" refers to the next learning content or task that the system automatically suggests based on the user's current learning situation and history.

[0748] "Authentication" refers to the process of verifying a user's identity based on registration information in order to properly access a system.

[0749] "Generative AI model" refers to an artificial intelligence model used to generate optimal learning content and feedback based on a user's learning history and quiz results.

[0750] "Database" refers to a data management system for storing and managing users' learning history, registration information, etc.

[0751] "Content display" refers to the process of displaying the generated learning materials and question sets on the user's device.

[0752] "Customization" refers to individually adjusting the next learning content and steps based on the user's learning history and score.

[0753] This invention details the technology for building an online learning system, which allows users to acquire IT and programming knowledge efficiently and enjoyably.

[0754] User Registration and Login

[0755] User Registration

[0756] 1. The user enters information such as their name, email address, and password, and sends it from their device to the server.

[0757] 2. The server receives this information and stores it in a MySQL database, using Python's Flask framework and SQLAlchemy.

[0758] 3. The server returns a "Registration successful" message to the terminal, which the terminal displays to the user.

[0759] User Login

[0760] 1. The registered user enters their email address and password and sends them from their device to the server.

[0761] 2. The server authenticates the user against information stored in a database.

[0762] 3. If authentication is successful, the server returns a "Login successful" message, which the terminal displays to the user. If authentication is unsuccessful, a "Login failed" message is displayed.

[0763] Providing learning content

[0764] Obtaining learning history and displaying content

[0765] 1. After logging in, the user clicks the "Start learning" button, and the device sends a request to the server.

[0766] 2. The server retrieves the user's learning history from the database.

[0767] 3. Based on the acquired history, the server uses a generative AI model to generate adaptive learning content.

[0768] 4. The generated learning content is sent to the device and displayed to the user.

[0769] Run and grade quizzes

[0770] Take the quiz and submit your answers

[0771] 1. The user completes the learning content and answers the provided quiz. The device sends the user's answers to the server.

[0772] 2. The server receives the answer, compares it with the correct answers in the database, and calculates a score.

[0773] Grade quizzes and provide feedback

[0774] 1. The server generates a feedback message based on the score, possibly using a generative AI model.

[0775] 2. Feedback and scores are sent to the device and displayed to the user.

[0776] Suggested next steps

[0777] 1. The server determines what the user should learn next based on their most recent learning history and scores. This process is also carried out using a generative AI model.

[0778] 2. The server sends the next learning step to the terminal and displays it to the user.

[0779] Points and coupons

[0780] 1. The server calculates the points to be awarded based on the user's learning progress and achievements.

[0781] 2. The calculated points are added to the user's account, and the server sends a message to the terminal indicating that the points have been earned.

[0782] 3. The device displays a message to the user about earning points, encouraging them to study.

[0783] Specific examples

[0784] Example 1: When a user creates a new account

[0785] 1. The user enters their name, email address, and password and clicks the Register button.

[0786] 2. The device sends this information to the server as an HTTP POST request.

[0787] 3. The server stores the received data in a database and sends a success message to the terminal.

[0788] 4. The terminal displays a "Registration successful" message to the user.

[0789] Example 2: When a user takes a quiz

[0790] Users complete learning content and take quizzes.

[0791] The device sends the user's response to the server as an HTTP POST request.

[0792] The server scores the answers and generates a score and feedback message that is sent to the device.

[0793] The device displays the score and feedback to the user, allowing them to see their progress and receive advice on how to proceed.

[0794] This invention enables users to efficiently acquire knowledge of IT and programming, and allows them to continue learning while maintaining their motivation to learn.

[0795] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0796] Detailed explanation of the processing steps

[0797] User Registration

[0798] Step 1:

[0799] The user enters their name, email address, and password and clicks the register button. This sends the input information from the device to the server. The data format sent is JSON.

[0800] Step 2:

[0801] The server receives the received user information using the Flask framework and processes the data appropriately (for example, hashing the password).

[0802] Step 3:

[0803] The server uses SQLAlchemy to store the processed data in a database (MySQL), which includes the user's name, email address, and hashed password.

[0804] Step 4:

[0805] The server generates a message indicating successful registration and returns it to the terminal as an HTTP response. The terminal displays this message to the user to notify them that registration was successful.

[0806] User Login

[0807] Step 1:

[0808] The user enters their email address and password and clicks the login button. The entered information is sent from the terminal to the server. The data format sent is JSON.

[0809] Step 2:

[0810] The server queries the database using SQLAlchemy to match the login information received with the registration information retrieved from the database. The password entered is hashed and compared to the hash value in the database.

[0811] Step 3:

[0812] The server judges the authentication result, and if successful, generates a "Login successful" message and returns it to the terminal. If unsuccessful, it generates a "Login failed" message and returns it to the terminal. The terminal displays the received message to the user.

[0813] Providing learning content

[0814] Step 1:

[0815] After logging in, when the user clicks the "Start learning" button, the device sends a request including the user ID to the server.

[0816] Step 2:

[0817] The server executes a query using SQLAlchemy to retrieve the learning history from the database based on the received user ID.

[0818] Step 3:

[0819] The server inputs the acquired learning history into the generative AI model as prompt sentences to generate an optimal learning path. This input includes the user's past learning history and current score.

[0820] Step 4:

[0821] The server selects the corresponding learning content based on the generated learning path and sends it to the terminal, which then displays the received content to the user.

[0822] Run and grade quizzes

[0823] Step 1:

[0824] The user completes the learning content and answers the provided quizzes, and the device records the user's answers.

[0825] Step 2:

[0826] The device sends the recorded quiz answers to the server as an HTTP POST request in JSON format.

[0827] Step 3:

[0828] The server compares the received answers with the correct answers in the database and calculates a score, using SQLAlchemy.

[0829] Step 4:

[0830] The server generates a feedback message based on the score, possibly using a generative AI model in the generation process.

[0831] Step 5:

[0832] The server sends the feedback and score to the device, which then displays it to the user, allowing the user to check their learning progress.

[0833] Suggested next steps

[0834] Step 1:

[0835] The server retrieves the latest learning history and quiz scores from the database, using SQLAlchemy.

[0836] Step 2:

[0837] The server uses the information it has acquired to determine what to learn next, a step that uses a generative AI model.

[0838] Step 3:

[0839] The server sends the next learning step to the terminal, which then displays it to the user, allowing the user to continue learning to the next step.

[0840] Points and coupons

[0841] Step 1:

[0842] The server calculates the points to be awarded based on the user's learning progress and achievements, and this calculation may use a generative AI model.

[0843] Step 2:

[0844] The calculated points are added to the user's account, and the server generates a message notifying the user of the points being earned and sends it to the terminal.

[0845] Step 3:

[0846] The device displays a message to the user that they have earned points, allowing them to maintain their motivation to study while continuing to study.

[0847] (Application example 1)

[0848] 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."

[0849] Conventional online learning systems offer features such as automatically suggesting the next learning step based on the user's learning progress, automatically scoring quizzes, providing feedback, and awarding points and coupons. However, these systems are often implemented through standard displays, which often lack a sense of realism and immersion. Furthermore, user interaction is limited, with real-time feedback and voice and gesture control underutilized. This leads to issues such as a decline in motivation and a lack of engagement.

[0850] 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.

[0851] In this invention, the server includes a device that displays online learning content provided by using generative AI to the user, a device that allows learning in a virtual space using a wearable device such as smart glasses, a device that automatically suggests the user's next learning step based on their learning progress, a device that scores the results of quizzes answered by the user and generates feedback, a device that recognizes voice and gesture inputs and sends quiz answers to the server, and a device that awards points and coupons according to the user's learning progress.This allows users to have a more realistic and immersive learning experience, and can increase their motivation and engagement in learning through real-time feedback and interactive operations.

[0852] "Generative AI" is a type of artificial intelligence that automatically generates and provides learning content for users.

[0853] "Online learning content" means digital educational materials provided via the Internet.

[0854] "Smart glasses" are wearable devices that use display technology to overlay virtual information onto the real world.

[0855] "Wearable devices" is a general term for electronic devices worn by users.

[0856] A "virtual space" is a virtual environment generated by computer simulation.

[0857] "Study progress" is information indicating the process by which the user advances in their studies and the state of progress.

[0858] "Auto-suggestion" is a feature where the system presents the user with the best next steps or content based on data.

[0859] A "quiz" is a set of questions to assess the user's level of understanding.

[0860] "Scoring" is a process in which a user assigns points based on their answers to a quiz.

[0861] "Feedback" refers to information about evaluations and areas for improvement provided to users.

[0862] "Voice input" is a method of recognizing a user's speech and sending information to a system.

[0863] "Gesture input" is a method in which sensors read the user's movements and send information to the system.

[0864] A "server" is a computer system that provides services to clients over a network.

[0865] "Points" are digital evaluation units awarded based on a user's learning progress and achievements.

[0866] A "coupon" is a discount ticket or service coupon given to a user depending on the results of their learning.

[0867] This invention realizes an online learning system using generative AI in combination with wearable devices such as smart glasses, which provides users with a more immersive learning experience, allowing for real-time feedback and interactive operation.

[0868] Hardware and Software Configuration

[0869] Hardware used:

[0870] Smart glasses: A wearable device worn by the user that uses display technology to overlay a virtual space onto the real world.

[0871] Server: A computer system that provides services to clients over the Internet.

[0872] Software used:

[0873] Generative AI models: Use artificial intelligence models such as GPT-4 to generate learning content and next learning steps.

[0874] Database: Manages user learning history and scores using SQLite etc.

[0875] Flask: A Python web framework that handles server-side processing.

[0876] System Operation

[0877] 1. User Registration and Login:

[0878] The server stores the authentication information provided by the user, such as the name, email address, and password, in a database and registers the user. When logging in, the entered authentication information is compared with the information in the database to determine whether the authentication was successful.

[0879] 2. Providing online learning content:

[0880] When a user wears smart glasses and logs into the virtual space, the server uses the generative AI model to generate appropriate learning content, which is then displayed on the smart glasses' display.

[0881] 3. Track your progress and suggest next steps:

[0882] The server records the user's learning progress in a database and automatically suggests the next step to learn based on that data, ensuring that the user is always on the optimal learning path.

[0883] 4. Take the quiz and provide feedback:

[0884] After completing the learning content, the user answers a quiz using the smart glasses. The quiz is answered using voice or gesture input, and the data is sent to the server. The server scores the quiz results and generates feedback that is displayed on the smart glasses' display.

[0885] 5. Points and coupons awarded:

[0886] The server calculates points based on the user's learning progress and quiz scores, and issues coupons at appropriate times, thereby increasing the user's motivation to study.

[0887] Specific examples

[0888] Example of user registration:

[0889] The user puts on the smart glasses and executes the "Register" command using voice commands. When the user enters their name, email address, and password by voice, the smart glasses recognize it and send it to the server, completing the registration.

[0890] A concrete example of running a quiz:

[0891] After completing the learning content, users answer quizzes displayed on the smart glasses display using voice or gestures. The answers are recognized by the smart glasses' sensors and sent to the server.

[0892] Example of an input prompt for a generative AI model:

[0893] Generate the next best learning content based on the user's learning history data. Below is the user's learning history.

[0894] Lesson 1: ... (detail)

[0895] Lesson 2: ... (detail)

[0896] Generate what content is best for you next.

[0897] Unlike traditional display learning, this system allows users to enjoy a more interactive and realistic learning experience. By utilizing real-time feedback and voice and gesture input, learning motivation and engagement are significantly improved.

[0898] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0899] Step 1:

[0900] The user puts on the smart glasses and executes the "Register" command with a voice command. The voice recognition system of the smart glasses receives the name, email address, and password, and sends this data to the server. The server stores the received data in a database, and returns a "Register Successful" message to the user if registration is successful. The input is the name, email address, and password, and the output is the registration success message.

[0901] Step 2:

[0902] To log in, a user enters their username and password via voice commands through the smart glasses. The smart glasses then send this authentication information to the server, which checks it against the information in its database. If the authentication is successful, the server returns a "login successful" message, and the user can enter the virtual space. The input is the username and password, and the output is the login successful message.

[0903] Step 3:

[0904] When a user logs into the virtual space, the server generates a prompt based on the user's learning history data and sends a request to the generative AI model to generate the next optimal learning content. The generative AI model generates the learning content and returns the data to the server. The server sends the content to the smart glasses and displays it to the user. The input is the user's learning history data, and the output is the learning content.

[0905] Step 4:

[0906] After the user has completed the learning content, the server generates a quiz and displays it on the smart glasses' display. The user answers the quiz through voice or gestures, and the answer data is sent to the server by the smart glasses. The input is the user's quiz answer, and the output is the quiz answer data.

[0907] Step 5:

[0908] The server compares the received quiz answer data with the correct answer data in the database and calculates a score. Based on this score, the server generates a feedback message and sends it to the smart glasses. The smart glasses display the feedback and score to the user. The input is the quiz answer data and correct answer data, and the output is the score and feedback message.

[0909] Step 6:

[0910] The server records the user's latest learning history and score in a database and requests the generative AI model to suggest the next learning content. The generative AI model generates the next learning step and returns that information to the server. The server then sends the next learning step to the smart glasses and displays it to the user. The input is the user's latest learning history and score, and the output is the next learning content.

[0911] Step 7:

[0912] The server calculates points based on the user's learning progress and quiz scores, and issues coupons in a timely manner. The points and coupon information are sent to the smart glasses and displayed to the user. The input is the learning progress and score, and the output is the points and coupon information.

[0913] 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.

[0914] The present invention provides an online learning system that utilizes generative AI and an emotion engine to enable users to effectively learn IT and programming knowledge. Specific embodiments of this system are described in detail below.

[0915] User Registration and Login

[0916] User Registration

[0917] The user enters the required information, such as name, email address, and password, and sends it from the device to the server. The server stores this information in a database and returns a message to the user indicating successful registration. The user can then create an account and begin learning.

[0918] User Login

[0919] When logging in, a registered user enters their username and password and sends them from their terminal to the server. The server compares them with the information in the database and determines whether authentication is successful. If authentication is successful, a login success message is returned and the user can access the system. If authentication is unsuccessful, a login failure message is displayed.

[0920] Providing learning content

[0921] Obtaining learning history and displaying content

[0922] After logging in, the user clicks the "Start Learning" button, which sends a request from the device to the server. The server retrieves the user's learning history from the database and generates an optimal learning path based on that information. The online learning content corresponding to this learning path is sent to the device and displayed to the user.

[0923] Quiz grading and feedback

[0924] Take the quiz and submit your answers

[0925] After completing the learning content, the user answers the provided quiz, and the device sends the user's answers to the server.

[0926] Grade quizzes and provide feedback

[0927] The server compares the user's answer with the correct answer data in the database and calculates a score. It generates a feedback message based on the score and sends it to the terminal. At the same time, it records the user's score in the database. The terminal displays the score and feedback to the user.

[0928] Suggested next steps

[0929] Suggestions for next learning content

[0930] The server determines the next learning content based on the user's most recent learning history and score. This information is sent to the device and displayed as the user's next learning step. This allows the user to always know the appropriate next learning task.

[0931] Points and coupons

[0932] Points awarded based on learning outcomes

[0933] The server calculates the points to be awarded based on the user's latest score and learning progress. The calculated points are added to the user's account, and a message informing the user that the points have been earned is sent to the device. The device then displays the message to the user, encouraging them to learn.

[0934] Introducing the Emotion Engine

[0935] Emotion Engine Functions

[0936] The emotion engine has the function of recognizing the user's emotional state in real time through facial expression and voice analysis. This recognized emotional information is integrated into various functions of the system as follows:

[0937] Adjusting content based on emotions

[0938] The emotional engine recognizes the user's emotional state and adjusts the difficulty of the learning content if it detects stress, for example: if the user is relaxed, more challenging content can be provided.

[0939] Modifying Feedback Based on Emotions

[0940] An emotion engine recognizes the user's emotional state and adjusts feedback messages accordingly, for example, providing more detailed explanations or encouraging messages if the user is confused.

[0941] Adjusted the points system to increase motivation to learn

[0942] The emotional engine recognizes the user's emotional state and adjusts the criteria for awarding points and coupons. If the user is tired or unmotivated, extra bonus points will be awarded to encourage learning.

[0943] Suggesting a break

[0944] If the emotion engine detects stress or fatigue in the user, the system will suggest a break, allowing the user to continue learning without straining themselves.

[0945] Specific examples

[0946] Example 1: When a user creates a new account

[0947] The user enters their name, email address, and password and clicks the Register button. The device sends this information to the server, which stores it in a database. If registration is successful, the device displays a "Registration successful" message to the user.

[0948] Example 2: When a user takes a quiz

[0949] Users complete learning content and answer quizzes. The device sends the user's answers to the server, which scores them. Feedback and scores are generated and sent to the device, which displays them to the user. Users can instantly check their learning progress and receive advice on how to proceed to the next step.

[0950] This concludes the embodiment of the present invention. This system allows users to acquire IT and programming knowledge efficiently and enjoyably. The introduction of an emotion engine is expected to provide a learning experience that is tailored to each individual user, further improving learning effectiveness.

[0951] The processing flow will be explained below.

[0952] User Registration and Login

[0953] User Registration

[0954] Step 1:

[0955] The user enters their name, email address, and password and clicks the "Register" button.

[0956] Step 2:

[0957] The terminal transmits the user's input information to the server.

[0958] Step 3:

[0959] The server stores the received user information in a database.

[0960] Step 4:

[0961] The server returns a message to the terminal indicating successful registration.

[0962] Step 5:

[0963] The terminal displays a "Registration successful" message to the user.

[0964] User Login

[0965] Step 1:

[0966] The user enters their username and password and clicks the "Login" button.

[0967] Step 2:

[0968] The device sends the authentication information to the server.

[0969] Step 3:

[0970] The server checks the authentication information against the information in its database to verify its accuracy.

[0971] Step 4:

[0972] If the server is successful in authentication, it returns a "Login successful" message to the terminal. If it fails, it returns a "Login failed" message.

[0973] Step 5:

[0974] The terminal displays a "Login successful" or "Login unsuccessful" message to the user.

[0975] Providing learning content

[0976] Obtaining learning history and displaying content

[0977] Step 1:

[0978] After logging in, the user clicks the "Start learning" button.

[0979] Step 2:

[0980] The device sends a request to the server.

[0981] Step 3:

[0982] The server retrieves the user's learning history from the database.

[0983] Step 4:

[0984] The server generates a new learning path based on the learning history.

[0985] Step 5:

[0986] The server transmits the generated learning content to the terminal.

[0987] Step 6:

[0988] The device displays the learning content to the user.

[0989] Quiz grading and feedback

[0990] Take the quiz and submit your answers

[0991] Step 1:

[0992] Users study learning content and take quizzes.

[0993] Step 2:

[0994] The terminal sends the user's response to the server.

[0995] Grade quizzes and provide feedback

[0996] Step 1:

[0997] The server retrieves the correct answer data from the database.

[0998] Step 2:

[0999] The server compares the user's answer with the correct answer data and calculates a score.

[1000] Step 3:

[1001] The server generates a feedback message based on the score.

[1002] Step 4:

[1003] The server sends a feedback message and a score to the device.

[1004] Step 5:

[1005] The device displays feedback and a score to the user.

[1006] Step 6:

[1007] The server records the user's score in a database.

[1008] Suggested next steps

[1009] Suggestions for next learning content

[1010] Step 1:

[1011] The server identifies the next learning step based on the user's latest learning history and score.

[1012] Step 2:

[1013] The server sends the next learning step content to the terminal.

[1014] Step 3:

[1015] The terminal displays the next learning step to the user.

[1016] Points and coupons

[1017] Points awarded based on learning outcomes

[1018] Step 1:

[1019] The server calculates the points to be awarded based on the user's learning progress and score.

[1020] Step 2:

[1021] The server adds the calculated points to the user's account.

[1022] Step 3:

[1023] The server sends a message to the terminal indicating that points have been earned.

[1024] Step 4:

[1025] The terminal displays a points acquisition message to the user.

[1026] Introducing the Emotion Engine

[1027] Emotion Engine Functions

[1028] Step 1:

[1029] The emotion engine analyzes the user's facial expressions and voice in real time.

[1030] Step 2:

[1031] The emotion engine transmits the analyzed emotion data to the server.

[1032] Step 3:

[1033] The emotional data received by the server is stored in a database and used to adjust current learning content and feedback.

[1034] Adjusting content based on emotions

[1035] Step 1:

[1036] The server determines the user's emotional state based on data from the emotion engine.

[1037] Step 2:

[1038] The server adjusts the difficulty of the learning content according to the emotional state.

[1039] Step 3:

[1040] The adapted learning content is sent to the device.

[1041] Step 4:

[1042] The device displays the tailored content to the user.

[1043] Modifying Feedback Based on Emotions

[1044] Step 1:

[1045] The server determines the user's emotional state based on data from the emotion engine.

[1046] Step 2:

[1047] The server generates a feedback message according to the emotional state.

[1048] Step 3:

[1049] The generated feedback is sent to the device.

[1050] Step 4:

[1051] The device displays tailored feedback to the user.

[1052] Adjusted the points system to increase motivation to learn

[1053] Step 1:

[1054] The server determines the user's emotional state based on data from the emotion engine.

[1055] Step 2:

[1056] The server adjusts the criteria for awarding points and coupons depending on the emotional state of the user.

[1057] Step 3:

[1058] Calculate adjusted points or coupons and add them to the user's account.

[1059] Step 4:

[1060] A message about points being earned is sent to the terminal.

[1061] Step 5:

[1062] The terminal displays the tailored points earning message to the user.

[1063] Suggesting a break

[1064] Step 1:

[1065] The server detects the user's stress and fatigue state based on data from the emotion engine.

[1066] Step 2:

[1067] The server generates a message suggesting a break and sends it to the terminal.

[1068] Step 3:

[1069] The terminal displays a message suggesting that the user take a break.

[1070] Example 2

[1071] 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."

[1072] While existing online learning systems offer basic functions such as tracking users' learning progress, scoring quizzes, and suggesting next steps, they lack consideration for the user's emotional state, which means the effectiveness of learning is not maximized. Furthermore, due to complex authentication processes and lack of break suggestions based on progress, there is a risk that users' motivation to learn will decrease. Furthermore, the inability to provide emotional feedback or adjust point allocation makes it difficult to provide an optimal learning experience tailored to each individual user.

[1073] 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.

[1074] In this invention, the server includes a means for displaying online learning content provided by a generation AI to the user, a means for automatically suggesting the next learning step based on the user's learning progress, a means for scoring the results of quizzes answered by the user and generating feedback, a means for awarding points or coupons according to the user's learning progress, a means for recognizing the user's emotions in real time and adjusting the difficulty level of the learning content, and a means for adjusting feedback messages based on the user's emotions. This enables the provision of adaptive learning content that takes into account the user's emotional state and the adjustment of the point system to maintain motivation while continuing to learn. Furthermore, the server can improve learning efficiency by suggesting breaks when fatigue or stress is detected.

[1075] "Generative AI" is a technology that uses artificial intelligence to automatically generate content such as text, images, and audio.

[1076] "Online learning content" refers to educational teaching materials and resources provided via the Internet.

[1077] "User's learning progress" is information indicating the results the user has achieved through their learning activities and their current level of achievement.

[1078] The "next learning step" refers to the next learning task or learning material that the user should tackle after completing the current learning content.

[1079] "Scoring the quiz results" means calculating and evaluating the percentage of correct answers and scores for the quiz answers given by the user.

[1080] "Generating feedback" means providing advice and comments based on the user's learning progress and quiz results.

[1081] "Giving points or coupons" means giving points or discount coupons as a reward for the user's learning activities.

[1082] "Real-time emotion recognition" means instantly analyzing and understanding a user's emotional state based on their facial expressions, voice, and behavior.

[1083] "Adjusting the difficulty level of learning content" means changing the difficulty level of the learning materials according to the user's emotions and learning progress.

[1084] "Adjusting the feedback message" means providing feedback whose content is in accordance with the user's emotional state.

[1085] "Performing authentication based on authentication information" means checking the username and password provided by the user and verifying their validity.

[1086] "Retrieving learning history from database" means searching and retrieving records of the user's past learning activities from the database.

[1087] "Generating an adaptive learning path" means determining the optimal learning order and learning materials based on the user's learning history and progress.

[1088] "Recording answers and reflecting them in the next study" means that the results of the user's answers to quizzes and tests are saved and used the next time they study.

[1089] "Suggest a break" means encouraging the user to temporarily stop studying when they feel tired or stressed.

[1090] "Individually customizing" means adjusting the content and progress to suit each user's individual situation.

[1091] "Calculating points" means calculating the points acquired based on the user's learning activities.

[1092] "Adjusting points and coupons" means changing the content and amount of rewards given depending on the user's emotional state and effort.

[1093] The present invention provides an online learning system that utilizes generative AI and an emotion engine to enable users to effectively learn IT and programming knowledge. Specific embodiments of this system are described in detail below.

[1094] User Registration and Login

[1095] This system requires user registration first. The user enters their name, email address, and password, and sends them from their terminal to the server. The server stores this information in a database and sends a message to the user indicating successful registration to the terminal. The database used in this process is a relational database management system such as MySQL.

[1096] Next, the user logs in using the registered information. They enter their username and password and send them from the terminal to the server. The server compares them with the information in the database and determines whether the authentication was successful. If successful, a login success message is returned and the user can access the system. If unsuccessful, a login failure message is displayed.

[1097] Providing learning content

[1098] When a logged-in user clicks the "Start Learning" button, a request is sent from the device to the server. The server retrieves the user's learning history from a database and generates an optimal learning path based on that information. A generative AI model (e.g., GPT-3) is used in this process. Online learning content corresponding to the generated learning path is sent to the device and displayed to the user.

[1099] Quiz grading and feedback

[1100] After completing the learning content, the user answers the provided quiz. The device sends the user's answers to the server. The server compares the user's answers with the correct answers in the database and calculates a score. A feedback message is generated based on the score and sent to the device. At the same time, the user's score is recorded in the database. The device displays the score and feedback to the user.

[1101] Suggested next steps

[1102] The server determines the next learning content based on the user's most recent learning history and score. This information is sent to the device and displayed as the user's next learning step. This allows the user to always know the appropriate next learning task.

[1103] Points and coupons

[1104] The server calculates the points to be awarded based on the user's latest score and learning progress. The calculated points are added to the user's account, and a message informing the user that the points have been earned is sent to the device. The device then displays the message to the user, encouraging them to learn.

[1105] Introducing the Emotion Engine

[1106] The emotion engine has the ability to recognize the user's emotional state in real time through facial expression and voice analysis. This recognized emotional information is integrated into various functions of the system as follows: If the emotion engine recognizes the user's emotional state and detects, for example, stress, it can adjust the difficulty of the learning content. If the user is relaxed, it can provide more challenging content.

[1107] The emotion engine also adjusts feedback messages based on the user's emotional state. If the user is confused, it will provide more detailed explanations or encouraging messages. Furthermore, the emotion engine recognizes the user's emotional state and adjusts the criteria for awarding points and coupons. If the user is tired or unmotivated, it can award extra bonus points to motivate them to continue learning.

[1108] If the emotion engine detects stress or fatigue in the user, the system will suggest a break, allowing the user to continue learning without straining themselves.

[1109] Specific examples

[1110] Example 1: When a user creates a new account

[1111] The user enters their name, email address, and password and clicks the Register button. The device sends this information to the server, which stores it in a database (e.g., MySQL). If registration is successful, the device displays a "Registration successful" message to the user.

[1112] Example 2: When a user takes a quiz

[1113] Users complete learning content and answer quizzes. The device sends the user's answers to the server, which scores them. Feedback and scores are generated and sent to the device, which displays them to the user. Users can instantly check their learning progress and receive advice on how to proceed to the next step.

[1114] Prompt Sentence Examples

[1115] By inputting the prompt sentence "Generate a prompt to suggest the next learning step," the generative AI model can suggest appropriate learning steps.

[1116] The above is a specific embodiment of the online learning system of the present invention. This system allows users to acquire IT and programming knowledge efficiently and enjoyably. The introduction of an emotion engine is expected to provide users with a personalized learning experience, further improving learning effectiveness.

[1117] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1118] Step 1: User Registration

[1119] The user enters their name, email address, and password and clicks the Register button.

[1120] The terminal sends this information to the server using the HTTPS protocol.

[1121] The server performs validation checks on the transmitted information (checking the format, password strength, etc.).

[1122] If validation passes, the server saves the information in a database (e.g. MySQL) and generates a registration success message.

[1123] The server sends a registration success message to the terminal, and the terminal displays the message "Registration successful" to the user.

[1124] Input: Name, email address, password, Output: Registration successful message.

[1125] Step 2: User Login

[1126] The user enters their username (or email address) and password and clicks the login button.

[1127] The terminal transmits this information to the server.

[1128] The server authenticates the user by checking the information in the database, for example by comparing the hash value of the entered password with the hash value in the database.

[1129] If authentication is successful, the server generates a token (e.g., a JWT token) and sends it to the terminal.

[1130] The terminal receives the token and starts the user's session. It displays a success message to the user.

[1131] Input: Username (or email address), password. Output: Authentication token, login success message.

[1132] Step 3: Provide learning content

[1133] The user clicks the "Start Learning" button.

[1134] The terminal sends a request to the server.

[1135] The server retrieves the user's learning history from the database and processes the information.

[1136] The server uses a generative AI model (e.g., GPT-3) to generate the optimal learning path.

[1137] The server transmits the generated learning content to the terminal, which displays it to the user.

[1138] Input: Learning start request, Output: Optimal learning content.

[1139] Step 4: Run and grade the quiz

[1140] Users complete learning content and take quizzes.

[1141] The terminal transmits the user's answer to the server.

[1142] The server compares the user's answer with the correct answer data in the database and calculates a score.

[1143] The server generates a feedback message based on the calculated score and sends it to the terminal.

[1144] The terminal displays a feedback message and score to the user.

[1145] Input: quiz answers, Output: scores, feedback messages.

[1146] Step 5: Suggest next learning steps

[1147] The server determines what to study next based on the most recent learning history and score.

[1148] The server uses the generative AI model to generate prompts (e.g., "Generate a prompt that suggests the next learning step") and determine the next learning path.

[1149] The server sends the next learning content to the terminal, which then displays it to the user.

[1150] Input: Latest learning history and score, Output: Next learning content.

[1151] Step 6: Points and coupons awarded

[1152] The server calculates the points to be awarded based on the latest score and learning progress.

[1153] The calculated points are recorded in a database by the server.

[1154] The server sends a points acquisition message to the terminal, which displays it to the user.

[1155] Input: Latest score, Output: Calculated points, Points earned message.

[1156] Step 7: Use the Emotion Engine

[1157] The emotion engine analyzes the user's facial expressions and voice to recognize emotions in real time.

[1158] Based on the emotional information recognized by the emotion engine, the server adjusts the difficulty level of the learning content.

[1159] The server also adjusts the feedback message according to the emotional state and sends it to the terminal.

[1160] If the emotion engine detects stress or fatigue, the server generates a message suggesting a break and sends it to the terminal.

[1161] The terminal displays these messages to the user.

[1162] Input: User's facial expressions and voice, Output: Tailored learning content, feedback messages, break suggestion messages.

[1163] (Application example 2)

[1164] 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."

[1165] Conventional online learning systems provide learning paths and quiz feedback based on a user's learning progress and history, but lack the ability to analyze the user's emotional state in real time and dynamically adjust learning content and feedback. As a result, users' motivation tends to drop and learning efficiency declines. In addition, point systems to improve motivation to learn are limited, making continuity of learning an issue.

[1166] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for displaying online learning content provided to the user using a generation AI, a means for automatically suggesting the next learning step based on the user's learning progress, a means for scoring the results of quizzes answered by the user and generating feedback, a means for awarding points or coupons according to the learning progress, a means for analyzing the user's emotional state using the camera and microphone of the smart device, and a means for adjusting the learning content based on the analysis results. This makes it possible to provide a dynamic learning experience that corresponds to the user's emotional state, increasing motivation to learn and enabling effective knowledge acquisition.

[1167] "Learning Content" means educational content created using generative AI and made available to users through an online platform.

[1168] "Generative AI" is a type of artificial intelligence that generates optimal learning paths and feedback based on a user's learning history and response results.

[1169] A "quiz" is a question-based test presented to a user after completing learning content, and is a means of assessing the user's level of understanding of the learning.

[1170] "Points" are rewards given to users according to their progress and achievements in learning, and are used to increase the user's motivation to learn.

[1171] A "coupon" is something that is given to a user as a reward for learning activities, and can be exchanged for a specific service or product.

[1172] A "smart device" is a device equipped with a camera and a microphone and used to analyze the emotional state of a user.

[1173] The "emotion engine" is a technology that analyzes the user's facial expressions and voice to recognize their emotional state in real time.

[1174] An "adaptive learning path" is an individually customized learning path that is generated based on a user's learning history and current learning progress.

[1175] A "feedback message" is a message for learning support that is provided according to the user's quiz results and emotional state.

[1176] "Break suggestion" is a function that suggests to the user that they take a break if the emotion engine detects stress or fatigue in the user.

[1177] System Overview

[1178] This invention is an online learning system that utilizes generative AI and an emotion engine to enable users to effectively learn IT and programming knowledge. This system provides learning content to users via smart devices (such as smartphones and tablets) and dynamically adjusts the learning experience according to the user's learning progress and emotional state.

[1179] User Registration and Login

[1180] The server stores the authentication information provided by the user, such as name, email address, and password, in a database, which allows the user to access the learning system. After registration and login, the server manages the user's learning history and provides an adaptive learning path for the next time the user studies.

[1181] Providing learning content

[1182] The server uses generative AI to generate online learning content and displays it on the user's device. When the user clicks the "Start Learning" button, the server retrieves the user's learning history from the database and generates an optimal learning path based on that information. The content corresponding to that learning path is sent to the device and displayed to the user.

[1183] Quiz grading and feedback

[1184] When the user finishes the learning content, a quiz is displayed. When the user answers the quiz, the device sends the answer to the server, which compares it with the correct answer data and calculates a score. A feedback message is generated based on this score and displayed to the user via the device. The user's score is also reflected in the generation of the next learning path.

[1185] Introducing the Emotion Engine

[1186] The server utilizes an emotion engine that analyzes the user's emotional state in real time using the smart device's camera and microphone. For example, if the emotion engine detects that the user is stressed, it can adjust the difficulty of the learning content or suggest a break. Feedback messages are also adjusted based on the user's emotional state.

[1187] A points system to increase motivation to learn

[1188] The server awards points and coupons based on the user's learning progress and quiz scores. These points are displayed on the user's device and can be used to exchange for rewards. In particular, if the emotion engine detects a decline in the user's motivation, it can award special bonus points to improve the user's motivation to learn.

[1189] Specific examples

[1190] For example, when a user creates a new account and begins studying and taking a quiz, the emotion engine detects a decline in concentration from the user's facial expressions. In this case, the difficulty level of the learning content is automatically lowered to allow the user to continue studying at a comfortable pace. The feedback message provided after the quiz is graded is also adjusted to include words of encouragement or additional explanation.

[1191] Prompt Sentence Examples

[1192] Generate new quiz questions below to prompt your AI model with the right feedback to help users overcome emotional disorders.

[1193] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1194] Step 1:

[1195] A user registers by entering their name, email address, and password on their terminal. They provide their name, email address, and password as input and send them from the terminal to the server. The server stores this information in a database and sends a "Registration successful" message to the terminal as output, which is displayed to the user.

[1196] Step 2:

[1197] A user logs in by entering an email address and password on the terminal. The email address and password are provided as input and sent from the terminal to the server. The server compares them with the user information in the database and performs authentication. If authentication is successful, a "Login successful" message is output and sent to the terminal. If authentication fails, a "Login failed" message is displayed.

[1198] Step 3:

[1199] After logging in, the user clicks the "Start Learning" button. The device sends a request to the server, providing the user's authentication information as input. The server retrieves the user's learning history from the database and uses generative AI to generate an optimal learning path. Online learning content based on this learning path is sent to the device as output and displayed to the user.

[1200] Step 4:

[1201] Users study according to the learning content provided on their devices. While studying, the smart device's camera and microphone capture the user's facial expressions and voice, collecting emotional data as input. The server's emotion engine analyzes this data and recognizes the user's emotional state in real time. For example, if stress or fatigue is detected, the difficulty level will be adjusted or a break will be suggested.

[1202] Step 5:

[1203] After completing the study, the user answers the quiz on the device. The user's answers are provided as input and sent from the device to the server. The server compares the user's answers with the correct answers in the database and calculates a score. A feedback message is generated based on the score, and the feedback message and score are sent as output to the device and displayed to the user.

[1204] Step 6:

[1205] The server determines the next learning content based on the user's latest learning history and score. This information is taken as input from the database, and the optimal next learning step is output and sent to the terminal. The user then performs the next learning activity based on this.

[1206] Step 7:

[1207] The server calculates points and coupons according to the user's learning progress and quiz scores. The server uses the user's learning history and score as input, and the calculated points and coupons are added to the user's account as output. A message about the points earned is sent to the terminal, which then displays it to the user.

[1208] Step 8:

[1209] While the user continues learning, the emotion engine continuously collects and analyzes the user's emotional data. Feedback messages and learning content are dynamically adjusted according to the user's emotional state. For example, a confused user may be provided with detailed explanations, and a user with low motivation may be awarded extra bonus points.

[1210] Example prompt

[1211] Generate new quiz questions below to prompt your AI model with the right feedback to help users overcome emotional disorders.

[1212] 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.

[1213] 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.

[1214] 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.

[1215] [Third embodiment]

[1216] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1217] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1218] 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).

[1219] 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.

[1220] 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.

[1221] 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).

[1222] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1223] 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.

[1224] 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.

[1225] 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.

[1226] 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.

[1227] 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."

[1228] The present invention provides an online learning system that utilizes generative AI to enable users to learn IT and programming knowledge in a fun and efficient manner. Specific embodiments of this system are described in detail below.

[1229] User Registration and Login

[1230] User Registration

[1231] The user enters the required information, such as name, email address, and password, and sends it from the device to the server. The server stores this information in a database and returns a message to the user indicating successful registration. The user can then create an account and begin learning.

[1232] User Login

[1233] When logging in, a registered user enters their username and password and sends them from their terminal to the server. The server compares them with the information in the database and determines whether authentication is successful. If authentication is successful, a login success message is returned and the user can access the system. If authentication is unsuccessful, a login failure message is displayed.

[1234] Providing learning content

[1235] Obtaining learning history and displaying content

[1236] After logging in, the user clicks the "Start Learning" button, which sends a request from the device to the server. The server retrieves the user's learning history from the database and generates an optimal learning path based on that information. The online learning content corresponding to this learning path is sent to the device and displayed to the user.

[1237] Quiz grading and feedback

[1238] Take the quiz and submit your answers

[1239] After completing the learning content, the user answers the provided quiz, and the device sends the user's answers to the server.

[1240] Grade quizzes and provide feedback

[1241] The server compares the user's answer with the correct answer data in the database, calculates a score, generates a feedback message based on the score and sends it to the terminal, and simultaneously records the user's score in the database. The terminal displays the score and feedback to the user.

[1242] Suggested next steps

[1243] Suggestions for next learning content

[1244] The server determines the next learning content based on the user's most recent learning history and score. This information is sent to the device and displayed as the user's next learning step. This allows the user to always know the appropriate next learning task.

[1245] Points and coupons

[1246] Points awarded based on learning outcomes

[1247] The server calculates the points to be awarded based on the user's latest score and learning progress. The calculated points are added to the user's account, and a message informing the user that the points have been earned is sent to the device. The device then displays the message to the user, encouraging them to learn.

[1248] Specific examples

[1249] Example 1: When a user creates a new account

[1250] The user enters their name, email address, and password and clicks the Register button. The device sends this information to the server, which stores it in a database. If registration is successful, the device displays a "Registration successful" message to the user.

[1251] Example 2: When a user takes a quiz

[1252] Users complete learning content and answer quizzes. The device sends the user's answers to the server, which scores them. Feedback and scores are generated and sent to the device, which displays them to the user. Users can instantly check their learning progress and receive advice on how to proceed to the next step.

[1253] This completes the embodiment of the present invention. This system allows users to acquire IT and programming knowledge efficiently and enjoyably.

[1254] The processing flow will be explained below.

[1255] User Registration and Login

[1256] User Registration

[1257] Step 1:

[1258] The user enters their name, email address, and password and clicks the "Register" button.

[1259] Step 2:

[1260] The terminal transmits the user's input information to the server.

[1261] Step 3:

[1262] The server stores the received user information in a database.

[1263] Step 4:

[1264] The server returns a message to the terminal indicating successful registration.

[1265] Step 5:

[1266] The terminal displays a "Registration successful" message to the user.

[1267] User Login

[1268] Step 1:

[1269] The user enters their username and password and clicks the "Login" button.

[1270] Step 2:

[1271] The device sends the authentication information to the server.

[1272] Step 3:

[1273] The server checks the authentication information against the information in its database to verify its accuracy.

[1274] Step 4:

[1275] If the server is successful in authentication, it returns a "Login successful" message to the terminal. If it fails, it returns a "Login failed" message.

[1276] Step 5:

[1277] The terminal displays a "Login successful" or "Login unsuccessful" message to the user.

[1278] Providing learning content

[1279] Obtaining learning history and displaying content

[1280] Step 1:

[1281] After logging in, the user clicks the "Start learning" button.

[1282] Step 2:

[1283] The device sends a request to the server.

[1284] Step 3:

[1285] The server retrieves the user's learning history from the database.

[1286] Step 4:

[1287] The server generates a new learning path based on the learning history.

[1288] Step 5:

[1289] The server transmits the generated learning content to the terminal.

[1290] Step 6:

[1291] The device displays the learning content to the user.

[1292] Quiz grading and feedback

[1293] Take the quiz and submit your answers

[1294] Step 1:

[1295] Users study learning content and take quizzes.

[1296] Step 2:

[1297] The terminal sends the user's response to the server.

[1298] Grade quizzes and provide feedback

[1299] Step 1:

[1300] The server retrieves the correct answer data from the database.

[1301] Step 2:

[1302] The server compares the user's answer with the correct answer data and calculates a score.

[1303] Step 3:

[1304] The server generates a feedback message based on the score.

[1305] Step 4:

[1306] The server sends a feedback message and a score to the device.

[1307] Step 5:

[1308] The device displays feedback and a score to the user.

[1309] Step 6:

[1310] The server records the user's score in a database.

[1311] Suggested next steps

[1312] Suggestions for next learning content

[1313] Step 1:

[1314] The server identifies the next learning step based on the user's latest learning history and score.

[1315] Step 2:

[1316] The server sends the next learning step content to the terminal.

[1317] Step 3:

[1318] The terminal displays the next learning step to the user.

[1319] Points and coupons

[1320] Points awarded based on learning outcomes

[1321] Step 1:

[1322] The server calculates the points to be awarded based on the user's learning progress and score.

[1323] Step 2:

[1324] The server adds the calculated points to the user's account.

[1325] Step 3:

[1326] The server sends a message to the terminal indicating that points have been earned.

[1327] Step 4:

[1328] The terminal displays a points acquisition message to the user.

[1329] Example 1

[1330] 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."

[1331] The present invention aims to solve the problem that, in an online system that allows users to learn IT and programming knowledge efficiently and enjoyably, it is difficult to provide appropriate learning steps according to the user's learning progress, provide feedback based on individual learning history, and issue points and rewards to increase motivation to learn.

[1332] 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.

[1333] In this invention, the server includes means for managing registration information entered by the user, means for authenticating the user based on the registration information, means for acquiring the learning history of the authenticated user, means for generating adaptive learning content based on the learning history, means for displaying the generated content to the user, means for scoring the results of quizzes answered by the user and generating feedback, means for automatically suggesting the next learning step based on the user's learning progress, and means for calculating points and rewards according to the learning progress and notifying the user. This allows the user to continuously receive appropriate learning content according to their learning progress, enabling them to effectively acquire knowledge while maintaining their motivation to learn.

[1334] "User" refers to an individual or corporation that uses the online learning system to learn.

[1335] "Registration Information" refers to information such as name, email address, and password provided by a User to the System.

[1336] "Study history" refers to data that records the learning content that a user has done on the system, as well as their progress and scores.

[1337] "Adaptive learning content" refers to optimal learning materials and question sets that are generated based on a user's individual learning history and scores.

[1338] "Quiz" refers to questions or assignments provided to users who have completed learning content.

[1339] "Feedback" refers to evaluations and advice for the user that are generated based on the results of the quiz.

[1340] "Points" are a type of reward given by the system based on the user's learning progress and results, and refer to a numerical value used to increase motivation to learn.

[1341] "Rewards" refers to incentives such as points or coupons that users can earn as they progress with their studies.

[1342] "Next learning step" refers to the next learning content or task that the system automatically suggests based on the user's current learning situation and history.

[1343] "Authentication" refers to the process of verifying a user's identity based on registration information in order to properly access a system.

[1344] "Generative AI model" refers to an artificial intelligence model used to generate optimal learning content and feedback based on a user's learning history and quiz results.

[1345] "Database" refers to a data management system for storing and managing users' learning history, registration information, etc.

[1346] "Content display" refers to the process of displaying the generated learning materials and question sets on the user's device.

[1347] "Customization" refers to individually adjusting the next learning content and steps based on the user's learning history and score.

[1348] This invention details the technology for building an online learning system, which allows users to acquire IT and programming knowledge efficiently and enjoyably.

[1349] User Registration and Login

[1350] User Registration

[1351] 1. The user enters information such as their name, email address, and password, and sends it from their device to the server.

[1352] 2. The server receives this information and stores it in a MySQL database, using Python's Flask framework and SQLAlchemy.

[1353] 3. The server returns a "Registration successful" message to the terminal, which the terminal displays to the user.

[1354] User Login

[1355] 1. The registered user enters their email address and password and sends them from their device to the server.

[1356] 2. The server authenticates the user against information stored in a database.

[1357] 3. If authentication is successful, the server returns a "Login successful" message, which the terminal displays to the user. If authentication is unsuccessful, a "Login failed" message is displayed.

[1358] Providing learning content

[1359] Obtaining learning history and displaying content

[1360] 1. After logging in, the user clicks the "Start learning" button, and the device sends a request to the server.

[1361] 2. The server retrieves the user's learning history from the database.

[1362] 3. Based on the acquired history, the server uses a generative AI model to generate adaptive learning content.

[1363] 4. The generated learning content is sent to the device and displayed to the user.

[1364] Run and grade quizzes

[1365] Take the quiz and submit your answers

[1366] 1. The user completes the learning content and answers the provided quiz. The device sends the user's answers to the server.

[1367] 2. The server receives the answer, compares it with the correct answers in the database, and calculates a score.

[1368] Grade quizzes and provide feedback

[1369] 1. The server generates a feedback message based on the score, possibly using a generative AI model.

[1370] 2. Feedback and scores are sent to the device and displayed to the user.

[1371] Suggested next steps

[1372] 1. The server determines what the user should learn next based on their most recent learning history and scores. This process is also carried out using a generative AI model.

[1373] 2. The server sends the next learning step to the terminal and displays it to the user.

[1374] Points and coupons

[1375] 1. The server calculates the points to be awarded based on the user's learning progress and achievements.

[1376] 2. The calculated points are added to the user's account, and the server sends a message to the terminal indicating that the points have been earned.

[1377] 3. The device displays a message to the user about earning points, encouraging them to study.

[1378] Specific examples

[1379] Example 1: When a user creates a new account

[1380] 1. The user enters their name, email address, and password and clicks the Register button.

[1381] 2. The device sends this information to the server as an HTTP POST request.

[1382] 3. The server stores the received data in a database and sends a success message to the terminal.

[1383] 4. The terminal displays a "Registration successful" message to the user.

[1384] Example 2: When a user takes a quiz

[1385] Users complete learning content and take quizzes.

[1386] The device sends the user's response to the server as an HTTP POST request.

[1387] The server scores the answers and generates a score and feedback message that is sent to the device.

[1388] The device displays the score and feedback to the user, allowing them to see their progress and receive advice on how to proceed.

[1389] This invention enables users to efficiently acquire knowledge of IT and programming, and allows them to continue learning while maintaining their motivation to learn.

[1390] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1391] Detailed explanation of the processing steps

[1392] User Registration

[1393] Step 1:

[1394] The user enters their name, email address, and password and clicks the register button. This sends the input information from the device to the server. The data format sent is JSON.

[1395] Step 2:

[1396] The server receives the received user information using the Flask framework and processes the data appropriately (for example, hashing the password).

[1397] Step 3:

[1398] The server uses SQLAlchemy to store the processed data in a database (MySQL), which includes the user's name, email address, and hashed password.

[1399] Step 4:

[1400] The server generates a message indicating successful registration and returns it to the terminal as an HTTP response. The terminal displays this message to the user to notify them that registration was successful.

[1401] User Login

[1402] Step 1:

[1403] The user enters their email address and password and clicks the login button. The entered information is sent from the terminal to the server. The data format sent is JSON.

[1404] Step 2:

[1405] The server queries the database using SQLAlchemy to match the login information received with the registration information retrieved from the database. The password entered is hashed and compared to the hash value in the database.

[1406] Step 3:

[1407] The server judges the authentication result, and if successful, generates a "Login successful" message and returns it to the terminal. If unsuccessful, it generates a "Login failed" message and returns it to the terminal. The terminal displays the received message to the user.

[1408] Providing learning content

[1409] Step 1:

[1410] After logging in, when the user clicks the "Start learning" button, the device sends a request including the user ID to the server.

[1411] Step 2:

[1412] The server executes a query using SQLAlchemy to retrieve the learning history from the database based on the received user ID.

[1413] Step 3:

[1414] The server inputs the acquired learning history into the generative AI model as prompt sentences to generate an optimal learning path. This input includes the user's past learning history and current score.

[1415] Step 4:

[1416] The server selects the corresponding learning content based on the generated learning path and sends it to the terminal, which then displays the received content to the user.

[1417] Run and grade quizzes

[1418] Step 1:

[1419] The user completes the learning content and answers the provided quizzes, and the device records the user's answers.

[1420] Step 2:

[1421] The device sends the recorded quiz answers to the server as an HTTP POST request in JSON format.

[1422] Step 3:

[1423] The server compares the received answers with the correct answers in the database and calculates a score, using SQLAlchemy.

[1424] Step 4:

[1425] The server generates a feedback message based on the score, possibly using a generative AI model in the generation process.

[1426] Step 5:

[1427] The server sends the feedback and score to the device, which then displays it to the user, allowing the user to check their learning progress.

[1428] Suggested next steps

[1429] Step 1:

[1430] The server retrieves the latest learning history and quiz scores from the database, using SQLAlchemy.

[1431] Step 2:

[1432] The server uses the information it has acquired to determine what to learn next, a step that uses a generative AI model.

[1433] Step 3:

[1434] The server sends the next learning step to the terminal, which then displays it to the user, allowing the user to continue learning to the next step.

[1435] Points and coupons

[1436] Step 1:

[1437] The server calculates the points to be awarded based on the user's learning progress and achievements, and this calculation may use a generative AI model.

[1438] Step 2:

[1439] The calculated points are added to the user's account, and the server generates a message notifying the user of the points being earned and sends it to the terminal.

[1440] Step 3:

[1441] The device displays a message to the user that they have earned points, allowing them to maintain their motivation to study while continuing to study.

[1442] (Application example 1)

[1443] 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."

[1444] Conventional online learning systems offer features such as automatically suggesting the next learning step based on the user's learning progress, automatically scoring quizzes, providing feedback, and awarding points and coupons. However, these systems are often implemented through standard displays, which often lack a sense of realism and immersion. Furthermore, user interaction is limited, with real-time feedback and voice and gesture control underutilized. This leads to issues such as a decline in motivation and a lack of engagement.

[1445] 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.

[1446] In this invention, the server includes a device that displays online learning content provided by using generative AI to the user, a device that allows learning in a virtual space using a wearable device such as smart glasses, a device that automatically suggests the user's next learning step based on their learning progress, a device that scores the results of quizzes answered by the user and generates feedback, a device that recognizes voice and gesture inputs and sends quiz answers to the server, and a device that awards points and coupons according to the user's learning progress.This allows users to have a more realistic and immersive learning experience, and can increase their motivation and engagement in learning through real-time feedback and interactive operations.

[1447] "Generative AI" is a type of artificial intelligence that automatically generates and provides learning content for users.

[1448] "Online learning content" means digital educational materials provided via the Internet.

[1449] "Smart glasses" are wearable devices that use display technology to overlay virtual information onto the real world.

[1450] "Wearable devices" is a general term for electronic devices worn by users.

[1451] A "virtual space" is a virtual environment generated by computer simulation.

[1452] "Study progress" is information indicating the process by which the user advances in their studies and the state of progress.

[1453] "Auto-suggestion" is a feature where the system presents the user with the best next steps or content based on data.

[1454] A "quiz" is a set of questions to assess the user's level of understanding.

[1455] "Scoring" is a process in which a user assigns points based on their answers to a quiz.

[1456] "Feedback" refers to information about evaluations and areas for improvement provided to users.

[1457] "Voice input" is a method of recognizing a user's speech and sending information to a system.

[1458] "Gesture input" is a method in which sensors read the user's movements and send information to the system.

[1459] A "server" is a computer system that provides services to clients over a network.

[1460] "Points" are digital evaluation units awarded based on a user's learning progress and achievements.

[1461] A "coupon" is a discount ticket or service coupon given to a user depending on the results of their learning.

[1462] This invention realizes an online learning system using generative AI in combination with wearable devices such as smart glasses, which provides users with a more immersive learning experience, allowing for real-time feedback and interactive operation.

[1463] Hardware and Software Configuration

[1464] Hardware used:

[1465] Smart glasses: A wearable device worn by the user that uses display technology to overlay a virtual space onto the real world.

[1466] Server: A computer system that provides services to clients over the Internet.

[1467] Software used:

[1468] Generative AI models: Use artificial intelligence models such as GPT-4 to generate learning content and next learning steps.

[1469] Database: Manages user learning history and scores using SQLite etc.

[1470] Flask: A Python web framework that handles server-side processing.

[1471] System Operation

[1472] 1. User Registration and Login:

[1473] The server stores the authentication information provided by the user, such as the name, email address, and password, in a database and registers the user. When logging in, the entered authentication information is compared with the information in the database to determine whether the authentication was successful.

[1474] 2. Providing online learning content:

[1475] When a user wears smart glasses and logs into the virtual space, the server uses the generative AI model to generate appropriate learning content, which is then displayed on the smart glasses' display.

[1476] 3. Track your progress and suggest next steps:

[1477] The server records the user's learning progress in a database and automatically suggests the next step to learn based on that data, ensuring that the user is always on the optimal learning path.

[1478] 4. Take the quiz and provide feedback:

[1479] After completing the learning content, the user answers a quiz using the smart glasses. The quiz is answered using voice or gesture input, and the data is sent to the server. The server scores the quiz results and generates feedback that is displayed on the smart glasses' display.

[1480] 5. Points and coupons awarded:

[1481] The server calculates points based on the user's learning progress and quiz scores, and issues coupons at appropriate times, thereby increasing the user's motivation to study.

[1482] Specific examples

[1483] Example of user registration:

[1484] The user puts on the smart glasses and executes the "Register" command using voice commands. When the user enters their name, email address, and password by voice, the smart glasses recognize it and send it to the server, completing the registration.

[1485] A concrete example of running a quiz:

[1486] After completing the learning content, users answer quizzes displayed on the smart glasses display using voice or gestures. The answers are recognized by the smart glasses' sensors and sent to the server.

[1487] Example of an input prompt for a generative AI model:

[1488] Generate the next best learning content based on the user's learning history data. Below is the user's learning history.

[1489] Lesson 1: ... (detail)

[1490] Lesson 2: ... (detail)

[1491] Generate what content is best for you next.

[1492] Unlike traditional display learning, this system allows users to enjoy a more interactive and realistic learning experience. By utilizing real-time feedback and voice and gesture input, learning motivation and engagement are significantly improved.

[1493] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1494] Step 1:

[1495] The user puts on the smart glasses and executes the "Register" command with a voice command. The voice recognition system of the smart glasses receives the name, email address, and password, and sends this data to the server. The server stores the received data in a database, and returns a "Register Successful" message to the user if registration is successful. The input is the name, email address, and password, and the output is the registration success message.

[1496] Step 2:

[1497] To log in, a user enters their username and password via voice commands through the smart glasses. The smart glasses then send this authentication information to the server, which checks it against the information in its database. If the authentication is successful, the server returns a "login successful" message, and the user can enter the virtual space. The input is the username and password, and the output is the login successful message.

[1498] Step 3:

[1499] When a user logs into the virtual space, the server generates a prompt based on the user's learning history data and sends a request to the generative AI model to generate the next optimal learning content. The generative AI model generates the learning content and returns the data to the server. The server sends the content to the smart glasses and displays it to the user. The input is the user's learning history data, and the output is the learning content.

[1500] Step 4:

[1501] After the user has completed the learning content, the server generates a quiz and displays it on the smart glasses' display. The user answers the quiz through voice or gestures, and the answer data is sent to the server by the smart glasses. The input is the user's quiz answer, and the output is the quiz answer data.

[1502] Step 5:

[1503] The server compares the received quiz answer data with the correct answer data in the database and calculates a score. Based on this score, the server generates a feedback message and sends it to the smart glasses. The smart glasses display the feedback and score to the user. The input is the quiz answer data and correct answer data, and the output is the score and feedback message.

[1504] Step 6:

[1505] The server records the user's latest learning history and score in a database and requests the generative AI model to suggest the next learning content. The generative AI model generates the next learning step and returns that information to the server. The server then sends the next learning step to the smart glasses and displays it to the user. The input is the user's latest learning history and score, and the output is the next learning content.

[1506] Step 7:

[1507] The server calculates points based on the user's learning progress and quiz scores, and issues coupons in a timely manner. The points and coupon information are sent to the smart glasses and displayed to the user. The input is the learning progress and score, and the output is the points and coupon information.

[1508] 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.

[1509] The present invention provides an online learning system that utilizes generative AI and an emotion engine to enable users to effectively learn IT and programming knowledge. Specific embodiments of this system are described in detail below.

[1510] User Registration and Login

[1511] User Registration

[1512] The user enters the required information, such as name, email address, and password, and sends it from the device to the server. The server stores this information in a database and returns a message to the user indicating successful registration. The user can then create an account and begin learning.

[1513] User Login

[1514] When logging in, a registered user enters their username and password and sends them from their terminal to the server. The server compares them with the information in the database and determines whether authentication is successful. If authentication is successful, a login success message is returned and the user can access the system. If authentication is unsuccessful, a login failure message is displayed.

[1515] Providing learning content

[1516] Obtaining learning history and displaying content

[1517] After logging in, the user clicks the "Start Learning" button, which sends a request from the device to the server. The server retrieves the user's learning history from the database and generates an optimal learning path based on that information. The online learning content corresponding to this learning path is sent to the device and displayed to the user.

[1518] Quiz grading and feedback

[1519] Take the quiz and submit your answers

[1520] After completing the learning content, the user answers the provided quiz, and the device sends the user's answers to the server.

[1521] Grade quizzes and provide feedback

[1522] The server compares the user's answer with the correct answer data in the database and calculates a score. It generates a feedback message based on the score and sends it to the terminal. At the same time, it records the user's score in the database. The terminal displays the score and feedback to the user.

[1523] Suggested next steps

[1524] Suggestions for next learning content

[1525] The server determines the next learning content based on the user's most recent learning history and score. This information is sent to the device and displayed as the user's next learning step. This allows the user to always know the appropriate next learning task.

[1526] Points and coupons

[1527] Points awarded based on learning outcomes

[1528] The server calculates the points to be awarded based on the user's latest score and learning progress. The calculated points are added to the user's account, and a message informing the user that the points have been earned is sent to the device. The device then displays the message to the user, encouraging them to learn.

[1529] Introducing the Emotion Engine

[1530] Emotion Engine Functions

[1531] The emotion engine has the function of recognizing the user's emotional state in real time through facial expression and voice analysis. This recognized emotional information is integrated into various functions of the system as follows:

[1532] Adjusting content based on emotions

[1533] The emotional engine recognizes the user's emotional state and adjusts the difficulty of the learning content if it detects stress, for example: if the user is relaxed, more challenging content can be provided.

[1534] Modifying Feedback Based on Emotions

[1535] An emotion engine recognizes the user's emotional state and adjusts feedback messages accordingly, for example, providing more detailed explanations or encouraging messages if the user is confused.

[1536] Adjusted the points system to increase motivation to learn

[1537] The emotional engine recognizes the user's emotional state and adjusts the criteria for awarding points and coupons. If the user is tired or unmotivated, extra bonus points will be awarded to encourage learning.

[1538] Suggesting a break

[1539] If the emotion engine detects stress or fatigue in the user, the system will suggest a break, allowing the user to continue learning without straining themselves.

[1540] Specific examples

[1541] Example 1: When a user creates a new account

[1542] The user enters their name, email address, and password and clicks the Register button. The device sends this information to the server, which stores it in a database. If registration is successful, the device displays a "Registration successful" message to the user.

[1543] Example 2: When a user takes a quiz

[1544] Users complete learning content and answer quizzes. The device sends the user's answers to the server, which scores them. Feedback and scores are generated and sent to the device, which displays them to the user. Users can instantly check their learning progress and receive advice on how to proceed to the next step.

[1545] This concludes the embodiment of the present invention. This system allows users to acquire IT and programming knowledge efficiently and enjoyably. The introduction of an emotion engine is expected to provide a learning experience that is tailored to each individual user, further improving learning effectiveness.

[1546] The processing flow will be explained below.

[1547] User Registration and Login

[1548] User Registration

[1549] Step 1:

[1550] The user enters their name, email address, and password and clicks the "Register" button.

[1551] Step 2:

[1552] The terminal transmits the user's input information to the server.

[1553] Step 3:

[1554] The server stores the received user information in a database.

[1555] Step 4:

[1556] The server returns a message to the terminal indicating successful registration.

[1557] Step 5:

[1558] The terminal displays a "Registration successful" message to the user.

[1559] User Login

[1560] Step 1:

[1561] The user enters their username and password and clicks the "Login" button.

[1562] Step 2:

[1563] The device sends the authentication information to the server.

[1564] Step 3:

[1565] The server checks the authentication information against the information in its database to verify its accuracy.

[1566] Step 4:

[1567] If the server is successful in authentication, it returns a "Login successful" message to the terminal. If it fails, it returns a "Login failed" message.

[1568] Step 5:

[1569] The terminal displays a "Login successful" or "Login unsuccessful" message to the user.

[1570] Providing learning content

[1571] Obtaining learning history and displaying content

[1572] Step 1:

[1573] After logging in, the user clicks the "Start learning" button.

[1574] Step 2:

[1575] The device sends a request to the server.

[1576] Step 3:

[1577] The server retrieves the user's learning history from the database.

[1578] Step 4:

[1579] The server generates a new learning path based on the learning history.

[1580] Step 5:

[1581] The server transmits the generated learning content to the terminal.

[1582] Step 6:

[1583] The device displays the learning content to the user.

[1584] Quiz grading and feedback

[1585] Take the quiz and submit your answers

[1586] Step 1:

[1587] Users study learning content and take quizzes.

[1588] Step 2:

[1589] The terminal sends the user's response to the server.

[1590] Grade quizzes and provide feedback

[1591] Step 1:

[1592] The server retrieves the correct answer data from the database.

[1593] Step 2:

[1594] The server compares the user's answer with the correct answer data and calculates a score.

[1595] Step 3:

[1596] The server generates a feedback message based on the score.

[1597] Step 4:

[1598] The server sends a feedback message and a score to the device.

[1599] Step 5:

[1600] The device displays feedback and a score to the user.

[1601] Step 6:

[1602] The server records the user's score in a database.

[1603] Suggested next steps

[1604] Suggestions for next learning content

[1605] Step 1:

[1606] The server identifies the next learning step based on the user's latest learning history and score.

[1607] Step 2:

[1608] The server sends the next learning step content to the terminal.

[1609] Step 3:

[1610] The terminal displays the next learning step to the user.

[1611] Points and coupons

[1612] Points awarded based on learning outcomes

[1613] Step 1:

[1614] The server calculates the points to be awarded based on the user's learning progress and score.

[1615] Step 2:

[1616] The server adds the calculated points to the user's account.

[1617] Step 3:

[1618] The server sends a message to the terminal indicating that points have been earned.

[1619] Step 4:

[1620] The terminal displays a points acquisition message to the user.

[1621] Introducing the Emotion Engine

[1622] Emotion Engine Functions

[1623] Step 1:

[1624] The emotion engine analyzes the user's facial expressions and voice in real time.

[1625] Step 2:

[1626] The emotion engine transmits the analyzed emotion data to the server.

[1627] Step 3:

[1628] The emotional data received by the server is stored in a database and used to adjust current learning content and feedback.

[1629] Adjusting content based on emotions

[1630] Step 1:

[1631] The server determines the user's emotional state based on data from the emotion engine.

[1632] Step 2:

[1633] The server adjusts the difficulty of the learning content according to the emotional state.

[1634] Step 3:

[1635] The adapted learning content is sent to the device.

[1636] Step 4:

[1637] The device displays the tailored content to the user.

[1638] Modifying Feedback Based on Emotions

[1639] Step 1:

[1640] The server determines the user's emotional state based on data from the emotion engine.

[1641] Step 2:

[1642] The server generates a feedback message according to the emotional state.

[1643] Step 3:

[1644] The generated feedback is sent to the device.

[1645] Step 4:

[1646] The device displays tailored feedback to the user.

[1647] Adjusted the points system to increase motivation to learn

[1648] Step 1:

[1649] The server determines the user's emotional state based on data from the emotion engine.

[1650] Step 2:

[1651] The server adjusts the criteria for awarding points and coupons depending on the emotional state of the user.

[1652] Step 3:

[1653] Calculate adjusted points or coupons and add them to the user's account.

[1654] Step 4:

[1655] A message about points being earned is sent to the terminal.

[1656] Step 5:

[1657] The terminal displays the tailored points earning message to the user.

[1658] Suggesting a break

[1659] Step 1:

[1660] The server detects the user's stress and fatigue state based on data from the emotion engine.

[1661] Step 2:

[1662] The server generates a message suggesting a break and sends it to the terminal.

[1663] Step 3:

[1664] The terminal displays a message suggesting that the user take a break.

[1665] Example 2

[1666] 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."

[1667] While existing online learning systems offer basic functions such as tracking users' learning progress, scoring quizzes, and suggesting next steps, they lack consideration for the user's emotional state, which means the effectiveness of learning is not maximized. Furthermore, due to complex authentication processes and lack of break suggestions based on progress, there is a risk that users' motivation to learn will decrease. Furthermore, the inability to provide emotional feedback or adjust point allocation makes it difficult to provide an optimal learning experience tailored to each individual user.

[1668] 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.

[1669] In this invention, the server includes a means for displaying online learning content provided by a generation AI to the user, a means for automatically suggesting the next learning step based on the user's learning progress, a means for scoring the results of quizzes answered by the user and generating feedback, a means for awarding points or coupons according to the user's learning progress, a means for recognizing the user's emotions in real time and adjusting the difficulty level of the learning content, and a means for adjusting feedback messages based on the user's emotions. This enables the provision of adaptive learning content that takes into account the user's emotional state and the adjustment of the point system to maintain motivation while continuing to learn. Furthermore, the server can improve learning efficiency by suggesting breaks when fatigue or stress is detected.

[1670] "Generative AI" is a technology that uses artificial intelligence to automatically generate content such as text, images, and audio.

[1671] "Online learning content" refers to educational teaching materials and resources provided via the Internet.

[1672] "User's learning progress" is information indicating the results the user has achieved through their learning activities and their current level of achievement.

[1673] The "next learning step" refers to the next learning task or learning material that the user should tackle after completing the current learning content.

[1674] "Scoring the quiz results" means calculating and evaluating the percentage of correct answers and scores for the quiz answers given by the user.

[1675] "Generating feedback" means providing advice and comments based on the user's learning progress and quiz results.

[1676] "Giving points or coupons" means giving points or discount coupons as a reward for the user's learning activities.

[1677] "Real-time emotion recognition" means instantly analyzing and understanding a user's emotional state based on their facial expressions, voice, and behavior.

[1678] "Adjusting the difficulty level of learning content" means changing the difficulty level of the learning materials according to the user's emotions and learning progress.

[1679] "Adjusting the feedback message" means providing feedback whose content is in accordance with the user's emotional state.

[1680] "Performing authentication based on authentication information" means checking the username and password provided by the user and verifying their validity.

[1681] "Retrieving learning history from database" means searching and retrieving records of the user's past learning activities from the database.

[1682] "Generating an adaptive learning path" means determining the optimal learning order and learning materials based on the user's learning history and progress.

[1683] "Recording answers and reflecting them in the next study" means that the results of the user's answers to quizzes and tests are saved and used the next time they study.

[1684] "Suggest a break" means encouraging the user to temporarily stop studying when they feel tired or stressed.

[1685] "Individually customizing" means adjusting the content and progress to suit each user's individual situation.

[1686] "Calculating points" means calculating the points acquired based on the user's learning activities.

[1687] "Adjusting points and coupons" means changing the content and amount of rewards given depending on the user's emotional state and effort.

[1688] The present invention provides an online learning system that utilizes generative AI and an emotion engine to enable users to effectively learn IT and programming knowledge. Specific embodiments of this system are described in detail below.

[1689] User Registration and Login

[1690] This system requires user registration first. The user enters their name, email address, and password, and sends them from their terminal to the server. The server stores this information in a database and sends a message to the user indicating successful registration to the terminal. The database used in this process is a relational database management system such as MySQL.

[1691] Next, the user logs in using the registered information. They enter their username and password and send them from the terminal to the server. The server compares them with the information in the database and determines whether the authentication was successful. If successful, a login success message is returned and the user can access the system. If unsuccessful, a login failure message is displayed.

[1692] Providing learning content

[1693] When a logged-in user clicks the "Start Learning" button, a request is sent from the device to the server. The server retrieves the user's learning history from a database and generates an optimal learning path based on that information. A generative AI model (e.g., GPT-3) is used in this process. Online learning content corresponding to the generated learning path is sent to the device and displayed to the user.

[1694] Quiz grading and feedback

[1695] After completing the learning content, the user answers the provided quiz. The device sends the user's answers to the server. The server compares the user's answers with the correct answers in the database and calculates a score. A feedback message is generated based on the score and sent to the device. At the same time, the user's score is recorded in the database. The device displays the score and feedback to the user.

[1696] Suggested next steps

[1697] The server determines the next learning content based on the user's most recent learning history and score. This information is sent to the device and displayed as the user's next learning step. This allows the user to always know the appropriate next learning task.

[1698] Points and coupons

[1699] The server calculates the points to be awarded based on the user's latest score and learning progress. The calculated points are added to the user's account, and a message informing the user that the points have been earned is sent to the device. The device then displays the message to the user, encouraging them to learn.

[1700] Introducing the Emotion Engine

[1701] The emotion engine has the ability to recognize the user's emotional state in real time through facial expression and voice analysis. This recognized emotional information is integrated into various functions of the system as follows: If the emotion engine recognizes the user's emotional state and detects, for example, stress, it can adjust the difficulty of the learning content. If the user is relaxed, it can provide more challenging content.

[1702] The emotion engine also adjusts feedback messages based on the user's emotional state. If the user is confused, it will provide more detailed explanations or encouraging messages. Furthermore, the emotion engine recognizes the user's emotional state and adjusts the criteria for awarding points and coupons. If the user is tired or unmotivated, it can award extra bonus points to motivate them to continue learning.

[1703] If the emotion engine detects stress or fatigue in the user, the system will suggest a break, allowing the user to continue learning without straining themselves.

[1704] Specific examples

[1705] Example 1: When a user creates a new account

[1706] The user enters their name, email address, and password and clicks the Register button. The device sends this information to the server, which stores it in a database (e.g., MySQL). If registration is successful, the device displays a "Registration successful" message to the user.

[1707] Example 2: When a user takes a quiz

[1708] Users complete learning content and answer quizzes. The device sends the user's answers to the server, which scores them. Feedback and scores are generated and sent to the device, which displays them to the user. Users can instantly check their learning progress and receive advice on how to proceed to the next step.

[1709] Prompt Sentence Examples

[1710] By inputting the prompt sentence "Generate a prompt to suggest the next learning step," the generative AI model can suggest appropriate learning steps.

[1711] The above is a specific embodiment of the online learning system of the present invention. This system allows users to acquire IT and programming knowledge efficiently and enjoyably. The introduction of an emotion engine is expected to provide users with a personalized learning experience, further improving learning effectiveness.

[1712] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1713] Step 1: User Registration

[1714] The user enters their name, email address, and password and clicks the Register button.

[1715] The terminal sends this information to the server using the HTTPS protocol.

[1716] The server performs validation checks on the transmitted information (checking the format, password strength, etc.).

[1717] If validation passes, the server saves the information in a database (e.g. MySQL) and generates a registration success message.

[1718] The server sends a registration success message to the terminal, and the terminal displays the message "Registration successful" to the user.

[1719] Input: Name, email address, password, Output: Registration successful message.

[1720] Step 2: User Login

[1721] The user enters their username (or email address) and password and clicks the login button.

[1722] The terminal transmits this information to the server.

[1723] The server authenticates the user by checking the information in the database, for example by comparing the hash value of the entered password with the hash value in the database.

[1724] If authentication is successful, the server generates a token (e.g., a JWT token) and sends it to the terminal.

[1725] The terminal receives the token and starts the user's session. It displays a success message to the user.

[1726] Input: Username (or email address), password. Output: Authentication token, login success message.

[1727] Step 3: Provide learning content

[1728] The user clicks the "Start Learning" button.

[1729] The terminal sends a request to the server.

[1730] The server retrieves the user's learning history from the database and processes the information.

[1731] The server uses a generative AI model (e.g., GPT-3) to generate the optimal learning path.

[1732] The server transmits the generated learning content to the terminal, which displays it to the user.

[1733] Input: Learning start request, Output: Optimal learning content.

[1734] Step 4: Run and grade the quiz

[1735] Users complete learning content and take quizzes.

[1736] The terminal transmits the user's answer to the server.

[1737] The server compares the user's answer with the correct answer data in the database and calculates a score.

[1738] The server generates a feedback message based on the calculated score and sends it to the terminal.

[1739] The terminal displays a feedback message and score to the user.

[1740] Input: quiz answers, Output: scores, feedback messages.

[1741] Step 5: Suggest next learning steps

[1742] The server determines what to study next based on the most recent learning history and score.

[1743] The server uses the generative AI model to generate prompts (e.g., "Generate a prompt that suggests the next learning step") and determine the next learning path.

[1744] The server sends the next learning content to the terminal, which then displays it to the user.

[1745] Input: Latest learning history and score, Output: Next learning content.

[1746] Step 6: Points and coupons awarded

[1747] The server calculates the points to be awarded based on the latest score and learning progress.

[1748] The calculated points are recorded in a database by the server.

[1749] The server sends a points acquisition message to the terminal, which displays it to the user.

[1750] Input: Latest score, Output: Calculated points, Points earned message.

[1751] Step 7: Use the Emotion Engine

[1752] The emotion engine analyzes the user's facial expressions and voice to recognize emotions in real time.

[1753] Based on the emotional information recognized by the emotion engine, the server adjusts the difficulty level of the learning content.

[1754] The server also adjusts the feedback message according to the emotional state and sends it to the terminal.

[1755] If the emotion engine detects stress or fatigue, the server generates a message suggesting a break and sends it to the terminal.

[1756] The terminal displays these messages to the user.

[1757] Input: User's facial expressions and voice, Output: Tailored learning content, feedback messages, break suggestion messages.

[1758] (Application example 2)

[1759] 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."

[1760] Conventional online learning systems provide learning paths and quiz feedback based on a user's learning progress and history, but lack the ability to analyze the user's emotional state in real time and dynamically adjust learning content and feedback. As a result, users' motivation tends to drop and learning efficiency declines. In addition, point systems to improve motivation to learn are limited, making continuity of learning an issue.

[1761] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for displaying online learning content provided to the user using a generation AI, a means for automatically suggesting the next learning step based on the user's learning progress, a means for scoring the results of quizzes answered by the user and generating feedback, a means for awarding points or coupons according to the learning progress, a means for analyzing the user's emotional state using the camera and microphone of the smart device, and a means for adjusting the learning content based on the analysis results. This makes it possible to provide a dynamic learning experience that corresponds to the user's emotional state, increasing motivation to learn and enabling effective knowledge acquisition.

[1762] "Learning Content" means educational content created using generative AI and made available to users through an online platform.

[1763] "Generative AI" is a type of artificial intelligence that generates optimal learning paths and feedback based on a user's learning history and response results.

[1764] A "quiz" is a question-based test presented to a user after completing learning content, and is a means of assessing the user's level of understanding of the learning.

[1765] "Points" are rewards given to users according to their progress and achievements in learning, and are used to increase the user's motivation to learn.

[1766] A "coupon" is something that is given to a user as a reward for learning activities, and can be exchanged for a specific service or product.

[1767] A "smart device" is a device equipped with a camera and a microphone and used to analyze the emotional state of a user.

[1768] The "emotion engine" is a technology that analyzes the user's facial expressions and voice to recognize their emotional state in real time.

[1769] An "adaptive learning path" is an individually customized learning path that is generated based on a user's learning history and current learning progress.

[1770] A "feedback message" is a message for learning support that is provided according to the user's quiz results and emotional state.

[1771] "Break suggestion" is a function that suggests to the user that they take a break if the emotion engine detects stress or fatigue in the user.

[1772] System Overview

[1773] This invention is an online learning system that utilizes generative AI and an emotion engine to enable users to effectively learn IT and programming knowledge. This system provides learning content to users via smart devices (such as smartphones and tablets) and dynamically adjusts the learning experience according to the user's learning progress and emotional state.

[1774] User Registration and Login

[1775] The server stores the authentication information provided by the user, such as name, email address, and password, in a database, which allows the user to access the learning system. After registration and login, the server manages the user's learning history and provides an adaptive learning path for the next time the user studies.

[1776] Providing learning content

[1777] The server uses generative AI to generate online learning content and displays it on the user's device. When the user clicks the "Start Learning" button, the server retrieves the user's learning history from the database and generates an optimal learning path based on that information. The content corresponding to that learning path is sent to the device and displayed to the user.

[1778] Quiz grading and feedback

[1779] When the user finishes the learning content, a quiz is displayed. When the user answers the quiz, the device sends the answer to the server, which compares it with the correct answer data and calculates a score. A feedback message is generated based on this score and displayed to the user via the device. The user's score is also reflected in the generation of the next learning path.

[1780] Introducing the Emotion Engine

[1781] The server utilizes an emotion engine that analyzes the user's emotional state in real time using the smart device's camera and microphone. For example, if the emotion engine detects that the user is stressed, it can adjust the difficulty of the learning content or suggest a break. Feedback messages are also adjusted based on the user's emotional state.

[1782] A points system to increase motivation to learn

[1783] The server awards points and coupons based on the user's learning progress and quiz scores. These points are displayed on the user's device and can be used to exchange for rewards. In particular, if the emotion engine detects a decline in the user's motivation, it can award special bonus points to improve the user's motivation to learn.

[1784] Specific examples

[1785] For example, when a user creates a new account and begins studying and taking a quiz, the emotion engine detects a decline in concentration from the user's facial expressions. In this case, the difficulty level of the learning content is automatically lowered to allow the user to continue studying at a comfortable pace. The feedback message provided after the quiz is graded is also adjusted to include words of encouragement or additional explanation.

[1786] Prompt Sentence Examples

[1787] Generate new quiz questions below to prompt your AI model with the right feedback to help users overcome emotional disorders.

[1788] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1789] Step 1:

[1790] A user registers by entering their name, email address, and password on their terminal. They provide their name, email address, and password as input and send them from the terminal to the server. The server stores this information in a database and sends a "Registration successful" message to the terminal as output, which is displayed to the user.

[1791] Step 2:

[1792] A user logs in by entering an email address and password on the terminal. The email address and password are provided as input and sent from the terminal to the server. The server compares them with the user information in the database and performs authentication. If authentication is successful, a "Login successful" message is output and sent to the terminal. If authentication fails, a "Login failed" message is displayed.

[1793] Step 3:

[1794] After logging in, the user clicks the "Start Learning" button. The device sends a request to the server, providing the user's authentication information as input. The server retrieves the user's learning history from the database and uses generative AI to generate an optimal learning path. Online learning content based on this learning path is sent to the device as output and displayed to the user.

[1795] Step 4:

[1796] Users study according to the learning content provided on their devices. While studying, the smart device's camera and microphone capture the user's facial expressions and voice, collecting emotional data as input. The server's emotion engine analyzes this data and recognizes the user's emotional state in real time. For example, if stress or fatigue is detected, the difficulty level will be adjusted or a break will be suggested.

[1797] Step 5:

[1798] After completing the study, the user answers the quiz on the device. The user's answers are provided as input and sent from the device to the server. The server compares the user's answers with the correct answers in the database and calculates a score. A feedback message is generated based on the score, and the feedback message and score are sent as output to the device and displayed to the user.

[1799] Step 6:

[1800] The server determines the next learning content based on the user's latest learning history and score. This information is taken as input from the database, and the optimal next learning step is output and sent to the terminal. The user then performs the next learning activity based on this.

[1801] Step 7:

[1802] The server calculates points and coupons according to the user's learning progress and quiz scores. The server uses the user's learning history and score as input, and the calculated points and coupons are added to the user's account as output. A message about the points earned is sent to the terminal, which then displays it to the user.

[1803] Step 8:

[1804] While the user continues learning, the emotion engine continuously collects and analyzes the user's emotional data. Feedback messages and learning content are dynamically adjusted according to the user's emotional state. For example, a confused user may be provided with detailed explanations, and a user with low motivation may be awarded extra bonus points.

[1805] Example prompt

[1806] Generate new quiz questions below to prompt your AI model with the right feedback to help users overcome emotional disorders.

[1807] 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.

[1808] 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.

[1809] 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.

[1810] [Fourth embodiment]

[1811] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1812] 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.

[1813] 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).

[1814] 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.

[1815] 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.

[1816] 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).

[1817] 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.

[1818] 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.

[1819] 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.

[1820] 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.

[1821] 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.

[1822] 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.

[1823] 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."

[1824] The present invention provides an online learning system that utilizes generative AI to enable users to learn IT and programming knowledge in a fun and efficient manner. Specific embodiments of this system are described in detail below.

[1825] User Registration and Login

[1826] User Registration

[1827] The user enters the required information, such as name, email address, and password, and sends it from the device to the server. The server stores this information in a database and returns a message to the user indicating successful registration. The user can then create an account and begin learning.

[1828] User Login

[1829] When logging in, a registered user enters their username and password and sends them from their terminal to the server. The server compares them with the information in the database and determines whether authentication is successful. If authentication is successful, a login success message is returned and the user can access the system. If authentication is unsuccessful, a login failure message is displayed.

[1830] Providing learning content

[1831] Obtaining learning history and displaying content

[1832] After logging in, the user clicks the "Start Learning" button, which sends a request from the device to the server. The server retrieves the user's learning history from the database and generates an optimal learning path based on that information. The online learning content corresponding to this learning path is sent to the device and displayed to the user.

[1833] Quiz grading and feedback

[1834] Take the quiz and submit your answers

[1835] After completing the learning content, the user answers the provided quiz, and the device sends the user's answers to the server.

[1836] Grade quizzes and provide feedback

[1837] The server compares the user's answer with the correct answer data in the database and calculates a score. It generates a feedback message based on the score and sends it to the terminal. At the same time, it records the user's score in the database. The terminal displays the score and feedback to the user.

[1838] Suggested next steps

[1839] Suggestions for next learning content

[1840] The server determines the next learning content based on the user's most recent learning history and score. This information is sent to the device and displayed as the user's next learning step. This allows the user to always know the appropriate next learning task.

[1841] Points and coupons

[1842] Points awarded based on learning outcomes

[1843] The server calculates the points to be awarded based on the user's latest score and learning progress. The calculated points are added to the user's account, and a message informing the user that the points have been earned is sent to the device. The device then displays the message to the user, encouraging them to learn.

[1844] Specific examples

[1845] Example 1: When a user creates a new account

[1846] The user enters their name, email address, and password and clicks the Register button. The device sends this information to the server, which stores it in a database. If registration is successful, the device displays a "Registration successful" message to the user.

[1847] Example 2: When a user takes a quiz

[1848] Users complete learning content and answer quizzes. The device sends the user's answers to the server, which scores them. Feedback and scores are generated and sent to the device, which displays them to the user. Users can instantly check their learning progress and receive advice on how to proceed to the next step.

[1849] This completes the embodiment of the present invention. This system allows users to acquire IT and programming knowledge efficiently and enjoyably.

[1850] The processing flow will be explained below.

[1851] User Registration and Login

[1852] User Registration

[1853] Step 1:

[1854] The user enters their name, email address, and password and clicks the "Register" button.

[1855] Step 2:

[1856] The terminal transmits the user's input information to the server.

[1857] Step 3:

[1858] The server stores the received user information in a database.

[1859] Step 4:

[1860] The server returns a message to the terminal indicating successful registration.

[1861] Step 5:

[1862] The terminal displays a "Registration successful" message to the user.

[1863] User Login

[1864] Step 1:

[1865] The user enters their username and password and clicks the "Login" button.

[1866] Step 2:

[1867] The device sends the authentication information to the server.

[1868] Step 3:

[1869] The server checks the authentication information against the information in its database to verify its accuracy.

[1870] Step 4:

[1871] If the server is successful in authentication, it returns a "Login successful" message to the terminal. If it fails, it returns a "Login failed" message.

[1872] Step 5:

[1873] The terminal displays a "Login successful" or "Login unsuccessful" message to the user.

[1874] Providing learning content

[1875] Obtaining learning history and displaying content

[1876] Step 1:

[1877] After logging in, the user clicks the "Start learning" button.

[1878] Step 2:

[1879] The device sends a request to the server.

[1880] Step 3:

[1881] The server retrieves the user's learning history from the database.

[1882] Step 4:

[1883] The server generates a new learning path based on the learning history.

[1884] Step 5:

[1885] The server transmits the generated learning content to the terminal.

[1886] Step 6:

[1887] The device displays the learning content to the user.

[1888] Quiz grading and feedback

[1889] Take the quiz and submit your answers

[1890] Step 1:

[1891] Users study learning content and take quizzes.

[1892] Step 2:

[1893] The terminal sends the user's response to the server.

[1894] Grade quizzes and provide feedback

[1895] Step 1:

[1896] The server retrieves the correct answer data from the database.

[1897] Step 2:

[1898] The server compares the user's answer with the correct answer data and calculates a score.

[1899] Step 3:

[1900] The server generates a feedback message based on the score.

[1901] Step 4:

[1902] The server sends a feedback message and a score to the device.

[1903] Step 5:

[1904] The device displays feedback and a score to the user.

[1905] Step 6:

[1906] The server records the user's score in a database.

[1907] Suggested next steps

[1908] Suggestions for next learning content

[1909] Step 1:

[1910] The server identifies the next learning step based on the user's latest learning history and score.

[1911] Step 2:

[1912] The server sends the next learning step content to the terminal.

[1913] Step 3:

[1914] The terminal displays the next learning step to the user.

[1915] Points and coupons

[1916] Points awarded based on learning outcomes

[1917] Step 1:

[1918] The server calculates the points to be awarded based on the user's learning progress and score.

[1919] Step 2:

[1920] The server adds the calculated points to the user's account.

[1921] Step 3:

[1922] The server sends a message to the terminal indicating that points have been earned.

[1923] Step 4:

[1924] The terminal displays a points acquisition message to the user.

[1925] Example 1

[1926] 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."

[1927] The present invention aims to solve the problem that, in an online system that allows users to learn IT and programming knowledge efficiently and enjoyably, it is difficult to provide appropriate learning steps according to the user's learning progress, provide feedback based on individual learning history, and issue points and rewards to increase motivation to learn.

[1928] 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.

[1929] In this invention, the server includes means for managing registration information entered by the user, means for authenticating the user based on the registration information, means for acquiring the learning history of the authenticated user, means for generating adaptive learning content based on the learning history, means for displaying the generated content to the user, means for scoring the results of quizzes answered by the user and generating feedback, means for automatically suggesting the next learning step based on the user's learning progress, and means for calculating points and rewards according to the learning progress and notifying the user. This allows the user to continuously receive appropriate learning content according to their learning progress, enabling them to effectively acquire knowledge while maintaining their motivation to learn.

[1930] "User" refers to an individual or corporation that uses the online learning system to learn.

[1931] "Registration Information" refers to information such as name, email address, and password provided by a User to the System.

[1932] "Study history" refers to data that records the learning content that a user has done on the system, as well as their progress and scores.

[1933] "Adaptive learning content" refers to optimal learning materials and question sets that are generated based on a user's individual learning history and scores.

[1934] "Quiz" refers to questions or assignments provided to users who have completed learning content.

[1935] "Feedback" refers to evaluations and advice for the user that are generated based on the results of the quiz.

[1936] "Points" are a type of reward given by the system based on the user's learning progress and results, and refer to a numerical value used to increase motivation to learn.

[1937] "Rewards" refers to incentives such as points or coupons that users can earn as they progress with their studies.

[1938] "Next learning step" refers to the next learning content or task that the system automatically suggests based on the user's current learning situation and history.

[1939] "Authentication" refers to the process of verifying a user's identity based on registration information in order to properly access a system.

[1940] "Generative AI model" refers to an artificial intelligence model used to generate optimal learning content and feedback based on a user's learning history and quiz results.

[1941] "Database" refers to a data management system for storing and managing users' learning history, registration information, etc.

[1942] "Content display" refers to the process of displaying the generated learning materials and question sets on the user's device.

[1943] "Customization" refers to individually adjusting the next learning content and steps based on the user's learning history and score.

[1944] This invention details the technology for building an online learning system, which allows users to acquire IT and programming knowledge efficiently and enjoyably.

[1945] User Registration and Login

[1946] User Registration

[1947] 1. The user enters information such as their name, email address, and password, and sends it from their device to the server.

[1948] 2. The server receives this information and stores it in a MySQL database, using Python's Flask framework and SQLAlchemy.

[1949] 3. The server returns a "Registration successful" message to the terminal, which the terminal displays to the user.

[1950] User Login

[1951] 1. The registered user enters their email address and password and sends them from their device to the server.

[1952] 2. The server authenticates the user against information stored in a database.

[1953] 3. If authentication is successful, the server returns a "Login successful" message, which the terminal displays to the user. If authentication is unsuccessful, a "Login failed" message is displayed.

[1954] Providing learning content

[1955] Obtaining learning history and displaying content

[1956] 1. After logging in, the user clicks the "Start learning" button, and the device sends a request to the server.

[1957] 2. The server retrieves the user's learning history from the database.

[1958] 3. Based on the acquired history, the server uses a generative AI model to generate adaptive learning content.

[1959] 4. The generated learning content is sent to the device and displayed to the user.

[1960] Run and grade quizzes

[1961] Take the quiz and submit your answers

[1962] 1. The user completes the learning content and answers the provided quiz. The device sends the user's answers to the server.

[1963] 2. The server receives the answer, compares it with the correct answers in the database, and calculates a score.

[1964] Grade quizzes and provide feedback

[1965] 1. The server generates a feedback message based on the score, possibly using a generative AI model.

[1966] 2. Feedback and scores are sent to the device and displayed to the user.

[1967] Suggested next steps

[1968] 1. The server determines what the user should learn next based on their most recent learning history and scores. This process is also carried out using a generative AI model.

[1969] 2. The server sends the next learning step to the terminal and displays it to the user.

[1970] Points and coupons

[1971] 1. The server calculates the points to be awarded based on the user's learning progress and achievements.

[1972] 2. The calculated points are added to the user's account, and the server sends a message to the terminal indicating that the points have been earned.

[1973] 3. The device displays a message to the user about earning points, encouraging them to study.

[1974] Specific examples

[1975] Example 1: When a user creates a new account

[1976] 1. The user enters their name, email address, and password and clicks the Register button.

[1977] 2. The device sends this information to the server as an HTTP POST request.

[1978] 3. The server stores the received data in a database and sends a success message to the terminal.

[1979] 4. The terminal displays a "Registration successful" message to the user.

[1980] Example 2: When a user takes a quiz

[1981] Users complete learning content and take quizzes.

[1982] The device sends the user's response to the server as an HTTP POST request.

[1983] The server scores the answers and generates a score and feedback message that is sent to the device.

[1984] The device displays the score and feedback to the user, allowing them to see their progress and receive advice on how to proceed.

[1985] This invention enables users to efficiently acquire knowledge of IT and programming, and allows them to continue learning while maintaining their motivation to learn.

[1986] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1987] Detailed explanation of the processing steps

[1988] User Registration

[1989] Step 1:

[1990] The user enters their name, email address, and password and clicks the register button. This sends the input information from the device to the server. The data format sent is JSON.

[1991] Step 2:

[1992] The server receives the received user information using the Flask framework and processes the data appropriately (for example, hashing the password).

[1993] Step 3:

[1994] The server uses SQLAlchemy to store the processed data in a database (MySQL), which includes the user's name, email address, and hashed password.

[1995] Step 4:

[1996] The server generates a message indicating successful registration and returns it to the terminal as an HTTP response. The terminal displays this message to the user to notify them that registration was successful.

[1997] User Login

[1998] Step 1:

[1999] The user enters their email address and password and clicks the login button. The entered information is sent from the terminal to the server. The data format sent is JSON.

[2000] Step 2:

[2001] The server queries the database using SQLAlchemy to match the login information received with the registration information retrieved from the database. The password entered is hashed and compared to the hash value in the database.

[2002] Step 3:

[2003] The server judges the authentication result, and if successful, generates a "Login successful" message and returns it to the terminal. If unsuccessful, it generates a "Login failed" message and returns it to the terminal. The terminal displays the received message to the user.

[2004] Providing learning content

[2005] Step 1:

[2006] After logging in, when the user clicks the "Start learning" button, the device sends a request including the user ID to the server.

[2007] Step 2:

[2008] The server executes a query using SQLAlchemy to retrieve the learning history from the database based on the received user ID.

[2009] Step 3:

[2010] The server inputs the acquired learning history into the generative AI model as prompt sentences to generate an optimal learning path. This input includes the user's past learning history and current score.

[2011] Step 4:

[2012] The server selects the corresponding learning content based on the generated learning path and sends it to the terminal, which then displays the received content to the user.

[2013] Run and grade quizzes

[2014] Step 1:

[2015] The user completes the learning content and answers the provided quizzes, and the device records the user's answers.

[2016] Step 2:

[2017] The device sends the recorded quiz answers to the server as an HTTP POST request in JSON format.

[2018] Step 3:

[2019] The server compares the received answers with the correct answers in the database and calculates a score, using SQLAlchemy.

[2020] Step 4:

[2021] The server generates a feedback message based on the score, possibly using a generative AI model in the generation process.

[2022] Step 5:

[2023] The server sends the feedback and score to the device, which then displays it to the user, allowing the user to check their learning progress.

[2024] Suggested next steps

[2025] Step 1:

[2026] The server retrieves the latest learning history and quiz scores from the database, using SQLAlchemy.

[2027] Step 2:

[2028] The server uses the information it has acquired to determine what to learn next, a step that uses a generative AI model.

[2029] Step 3:

[2030] The server sends the next learning step to the terminal, which then displays it to the user, allowing the user to continue learning to the next step.

[2031] Points and coupons

[2032] Step 1:

[2033] The server calculates the points to be awarded based on the user's learning progress and achievements, and this calculation may use a generative AI model.

[2034] Step 2:

[2035] The calculated points are added to the user's account, and the server generates a message notifying the user of the points being earned and sends it to the terminal.

[2036] Step 3:

[2037] The device displays a message to the user that they have earned points, allowing them to maintain their motivation to study while continuing to study.

[2038] (Application example 1)

[2039] 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."

[2040] Conventional online learning systems offer features such as automatically suggesting the next learning step based on the user's learning progress, automatically scoring quizzes, providing feedback, and awarding points and coupons. However, these systems are often implemented through standard displays, which often lack a sense of realism and immersion. Furthermore, user interaction is limited, with real-time feedback and voice and gesture control underutilized. This leads to issues such as a decline in motivation and a lack of engagement.

[2041] 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.

[2042] In this invention, the server includes a device that displays online learning content provided by using generative AI to the user, a device that allows learning in a virtual space using a wearable device such as smart glasses, a device that automatically suggests the user's next learning step based on their learning progress, a device that scores the results of quizzes answered by the user and generates feedback, a device that recognizes voice and gesture inputs and sends quiz answers to the server, and a device that awards points and coupons according to the user's learning progress.This allows users to have a more realistic and immersive learning experience, and can increase their motivation and engagement in learning through real-time feedback and interactive operations.

[2043] "Generative AI" is a type of artificial intelligence that automatically generates and provides learning content for users.

[2044] "Online learning content" means digital educational materials provided via the Internet.

[2045] "Smart glasses" are wearable devices that use display technology to overlay virtual information onto the real world.

[2046] "Wearable devices" is a general term for electronic devices worn by users.

[2047] A "virtual space" is a virtual environment generated by computer simulation.

[2048] "Study progress" is information indicating the process by which the user advances in their studies and the state of progress.

[2049] "Auto-suggestion" is a feature where the system presents the user with the best next steps or content based on data.

[2050] A "quiz" is a set of questions to assess the user's level of understanding.

[2051] "Scoring" is a process in which a user assigns points based on their answers to a quiz.

[2052] "Feedback" refers to information about evaluations and areas for improvement provided to users.

[2053] "Voice input" is a method of recognizing a user's speech and sending information to a system.

[2054] "Gesture input" is a method in which sensors read the user's movements and send information to the system.

[2055] A "server" is a computer system that provides services to clients over a network.

[2056] "Points" are digital evaluation units awarded based on a user's learning progress and achievements.

[2057] A "coupon" is a discount ticket or service coupon given to a user depending on the results of their learning.

[2058] This invention realizes an online learning system using generative AI in combination with wearable devices such as smart glasses, which provides users with a more immersive learning experience, allowing for real-time feedback and interactive operation.

[2059] Hardware and Software Configuration

[2060] Hardware used:

[2061] Smart glasses: A wearable device worn by the user that uses display technology to overlay a virtual space onto the real world.

[2062] Server: A computer system that provides services to clients over the Internet.

[2063] Software used:

[2064] Generative AI models: Use artificial intelligence models such as GPT-4 to generate learning content and next learning steps.

[2065] Database: Manages user learning history and scores using SQLite etc.

[2066] Flask: A Python web framework that handles server-side processing.

[2067] System Operation

[2068] 1. User Registration and Login:

[2069] The server stores the authentication information provided by the user, such as the name, email address, and password, in a database and registers the user. When logging in, the entered authentication information is compared with the information in the database to determine whether the authentication was successful.

[2070] 2. Providing online learning content:

[2071] When a user wears smart glasses and logs into the virtual space, the server uses the generative AI model to generate appropriate learning content, which is then displayed on the smart glasses' display.

[2072] 3. Track your progress and suggest next steps:

[2073] The server records the user's learning progress in a database and automatically suggests the next step to learn based on that data, ensuring that the user is always on the optimal learning path.

[2074] 4. Take the quiz and provide feedback:

[2075] After completing the learning content, the user answers a quiz using the smart glasses. The quiz is answered using voice or gesture input, and the data is sent to the server. The server scores the quiz results and generates feedback that is displayed on the smart glasses' display.

[2076] 5. Points and coupons awarded:

[2077] The server calculates points based on the user's learning progress and quiz scores, and issues coupons at appropriate times, thereby increasing the user's motivation to study.

[2078] Specific examples

[2079] Example of user registration:

[2080] The user puts on the smart glasses and executes the "Register" command using voice commands. When the user enters their name, email address, and password by voice, the smart glasses recognize it and send it to the server, completing the registration.

[2081] A concrete example of running a quiz:

[2082] After completing the learning content, users answer quizzes displayed on the smart glasses display using voice or gestures. The answers are recognized by the smart glasses' sensors and sent to the server.

[2083] Example of an input prompt for a generative AI model:

[2084] Generate the next best learning content based on the user's learning history data. Below is the user's learning history.

[2085] Lesson 1: ... (detail)

[2086] Lesson 2: ... (detail)

[2087] Generate what content is best for you next.

[2088] Unlike traditional display learning, this system allows users to enjoy a more interactive and realistic learning experience. By utilizing real-time feedback and voice and gesture input, learning motivation and engagement are significantly improved.

[2089] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2090] Step 1:

[2091] The user puts on the smart glasses and executes the "Register" command with a voice command. The voice recognition system of the smart glasses receives the name, email address, and password, and sends this data to the server. The server stores the received data in a database, and returns a "Register Successful" message to the user if registration is successful. The input is the name, email address, and password, and the output is the registration success message.

[2092] Step 2:

[2093] To log in, a user enters their username and password via voice commands through the smart glasses. The smart glasses then send this authentication information to the server, which checks it against the information in its database. If the authentication is successful, the server returns a "login successful" message, and the user can enter the virtual space. The input is the username and password, and the output is the login successful message.

[2094] Step 3:

[2095] When a user logs into the virtual space, the server generates a prompt based on the user's learning history data and sends a request to the generative AI model to generate the next optimal learning content. The generative AI model generates the learning content and returns the data to the server. The server sends the content to the smart glasses and displays it to the user. The input is the user's learning history data, and the output is the learning content.

[2096] Step 4:

[2097] After the user has completed the learning content, the server generates a quiz and displays it on the smart glasses' display. The user answers the quiz through voice or gestures, and the answer data is sent to the server by the smart glasses. The input is the user's quiz answer, and the output is the quiz answer data.

[2098] Step 5:

[2099] The server compares the received quiz answer data with the correct answer data in the database and calculates a score. Based on this score, the server generates a feedback message and sends it to the smart glasses. The smart glasses display the feedback and score to the user. The input is the quiz answer data and correct answer data, and the output is the score and feedback message.

[2100] Step 6:

[2101] The server records the user's latest learning history and score in a database and requests the generative AI model to suggest the next learning content. The generative AI model generates the next learning step and returns that information to the server. The server then sends the next learning step to the smart glasses and displays it to the user. The input is the user's latest learning history and score, and the output is the next learning content.

[2102] Step 7:

[2103] The server calculates points based on the user's learning progress and quiz scores, and issues coupons in a timely manner. The points and coupon information are sent to the smart glasses and displayed to the user. The input is the learning progress and score, and the output is the points and coupon information.

[2104] 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.

[2105] The present invention provides an online learning system that utilizes generative AI and an emotion engine to enable users to effectively learn IT and programming knowledge. Specific embodiments of this system are described in detail below.

[2106] User Registration and Login

[2107] User Registration

[2108] The user enters the required information, such as name, email address, and password, and sends it from the device to the server. The server stores this information in a database and returns a message to the user indicating successful registration. The user can then create an account and begin learning.

[2109] User Login

[2110] When logging in, a registered user enters their username and password and sends them from their terminal to the server. The server compares them with the information in the database and determines whether authentication is successful. If authentication is successful, a login success message is returned and the user can access the system. If authentication is unsuccessful, a login failure message is displayed.

[2111] Providing learning content

[2112] Obtaining learning history and displaying content

[2113] After logging in, the user clicks the "Start Learning" button, which sends a request from the device to the server. The server retrieves the user's learning history from the database and generates an optimal learning path based on that information. The online learning content corresponding to this learning path is sent to the device and displayed to the user.

[2114] Quiz grading and feedback

[2115] Take the quiz and submit your answers

[2116] After completing the learning content, the user answers the provided quiz, and the device sends the user's answers to the server.

[2117] Grade quizzes and provide feedback

[2118] The server compares the user's answer with the correct answer data in the database and calculates a score. It generates a feedback message based on the score and sends it to the terminal. At the same time, it records the user's score in the database. The terminal displays the score and feedback to the user.

[2119] Suggested next steps

[2120] Suggestions for next learning content

[2121] The server determines the next learning content based on the user's most recent learning history and score. This information is sent to the device and displayed as the user's next learning step. This allows the user to always know the appropriate next learning task.

[2122] Points and coupons

[2123] Points awarded based on learning outcomes

[2124] The server calculates the points to be awarded based on the user's latest score and learning progress. The calculated points are added to the user's account, and a message informing the user that the points have been earned is sent to the device. The device then displays the message to the user, encouraging them to learn.

[2125] Introducing the Emotion Engine

[2126] Emotion Engine Functions

[2127] The emotion engine has the function of recognizing the user's emotional state in real time through facial expression and voice analysis. This recognized emotional information is integrated into various functions of the system as follows:

[2128] Adjusting content based on emotions

[2129] The emotion engine recognizes the user's emotional state and adjusts the difficulty of the learning content if it detects stress, for example: if the user is relaxed, more challenging content can be provided.

[2130] Modifying feedback based on emotions

[2131] An emotion engine recognizes the user's emotional state and adjusts feedback messages accordingly, for example, providing more detailed explanations or encouraging messages if the user is confused.

[2132] Adjusted the points system to increase motivation to learn

[2133] The emotional engine recognizes the user's emotional state and adjusts the criteria for awarding points and coupons. If the user is tired or unmotivated, it will award extra bonus points to encourage learning.

[2134] Suggesting a break

[2135] If the emotion engine detects stress or fatigue in the user, the system will suggest a break, allowing the user to continue learning without straining themselves.

[2136] Specific examples

[2137] Example 1: When a user creates a new account

[2138] The user enters their name, email address, and password and clicks the Register button. The device sends this information to the server, which stores it in a database. If registration is successful, the device displays a "Registration successful" message to the user.

[2139] Example 2: When a user takes a quiz

[2140] Users complete learning content and answer quizzes. The device sends the user's answers to the server, which scores them. Feedback and scores are generated and sent to the device, which displays them to the user. Users can instantly check their learning progress and receive advice on how to proceed to the next step.

[2141] This concludes the description of the embodiment of the present invention. This system allows users to acquire IT and programming knowledge efficiently and enjoyably. The introduction of an emotion engine is expected to provide a learning experience that is tailored to each individual user, further improving learning effectiveness.

[2142] The processing flow will be explained below.

[2143] User Registration and Login

[2144] User Registration

[2145] Step 1:

[2146] The user enters their name, email address, and password and clicks the "Register" button.

[2147] Step 2:

[2148] The terminal transmits the user's input information to the server.

[2149] Step 3:

[2150] The server stores the received user information in a database.

[2151] Step 4:

[2152] The server returns a message to the terminal indicating successful registration.

[2153] Step 5:

[2154] The terminal displays a "Registration successful" message to the user.

[2155] User Login

[2156] Step 1:

[2157] The user enters their username and password and clicks the "Login" button.

[2158] Step 2:

[2159] The device sends the authentication information to the server.

[2160] Step 3:

[2161] The server checks the authentication information against the information in its database to verify its accuracy.

[2162] Step 4:

[2163] If the server is successful in authentication, it returns a "Login successful" message to the terminal. If it fails, it returns a "Login failed" message.

[2164] Step 5:

[2165] The terminal displays a "Login successful" or "Login unsuccessful" message to the user.

[2166] Providing learning content

[2167] Obtaining learning history and displaying content

[2168] Step 1:

[2169] After logging in, the user clicks the "Start learning" button.

[2170] Step 2:

[2171] The device sends a request to the server.

[2172] Step 3:

[2173] The server retrieves the user's learning history from the database.

[2174] Step 4:

[2175] The server generates a new learning path based on the learning history.

[2176] Step 5:

[2177] The server transmits the generated learning content to the terminal.

[2178] Step 6:

[2179] The device displays the learning content to the user.

[2180] Quiz grading and feedback

[2181] Take the quiz and submit your answers

[2182] Step 1:

[2183] Users study learning content and take quizzes.

[2184] Step 2:

[2185] The terminal sends the user's response to the server.

[2186] Grade quizzes and provide feedback

[2187] Step 1:

[2188] The server retrieves the correct answer data from the database.

[2189] Step 2:

[2190] The server compares the user's answer with the correct answer data and calculates a score.

[2191] Step 3:

[2192] The server generates a feedback message based on the score.

[2193] Step 4:

[2194] The server sends a feedback message and a score to the device.

[2195] Step 5:

[2196] The device displays feedback and a score to the user.

[2197] Step 6:

[2198] The server records the user's score in a database.

[2199] Suggested next steps

[2200] Suggestions for next learning content

[2201] Step 1:

[2202] The server identifies the next learning step based on the user's latest learning history and score.

[2203] Step 2:

[2204] The server sends the next learning step content to the terminal.

[2205] Step 3:

[2206] The terminal displays the next learning step to the user.

[2207] Points and coupons

[2208] Points awarded based on learning outcomes

[2209] Step 1:

[2210] The server calculates the points to be awarded based on the user's learning progress and score.

[2211] Step 2:

[2212] The server adds the calculated points to the user's account.

[2213] Step 3:

[2214] The server sends a message to the terminal indicating that points have been earned.

[2215] Step 4:

[2216] The terminal displays a points acquisition message to the user.

[2217] Introducing the Emotion Engine

[2218] Emotion Engine Functions

[2219] Step 1:

[2220] The emotion engine analyzes the user's facial expressions and voice in real time.

[2221] Step 2:

[2222] The emotion engine transmits the analyzed emotion data to the server.

[2223] Step 3:

[2224] The emotional data received by the server is stored in a database and used to adjust current learning content and feedback.

[2225] Adjusting content based on emotions

[2226] Step 1:

[2227] The server determines the user's emotional state based on data from the emotion engine.

[2228] Step 2:

[2229] The server adjusts the difficulty of the learning content according to the emotional state.

[2230] Step 3:

[2231] The adapted learning content is sent to the device.

[2232] Step 4:

[2233] The device displays the tailored content to the user.

[2234] Modifying feedback based on emotions

[2235] Step 1:

[2236] The server determines the user's emotional state based on data from the emotion engine.

[2237] Step 2:

[2238] The server generates a feedback message according to the emotional state.

[2239] Step 3:

[2240] The generated feedback is sent to the device.

[2241] Step 4:

[2242] The device displays tailored feedback to the user.

[2243] Adjusted the points system to increase motivation to learn

[2244] Step 1:

[2245] The server determines the user's emotional state based on data from the emotion engine.

[2246] Step 2:

[2247] The server adjusts the criteria for awarding points and coupons depending on the emotional state of the user.

[2248] Step 3:

[2249] Calculate adjusted points or coupons and add them to the user's account.

[2250] Step 4:

[2251] A message about points being earned is sent to the terminal.

[2252] Step 5:

[2253] The terminal displays the tailored points earning message to the user.

[2254] Suggesting a break

[2255] Step 1:

[2256] The server detects the user's stress and fatigue state based on data from the emotion engine.

[2257] Step 2:

[2258] The server generates a message suggesting a break and sends it to the terminal.

[2259] Step 3:

[2260] The terminal displays a message suggesting that the user take a break.

[2261] Example 2

[2262] 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."

[2263] While existing online learning systems offer basic functions such as tracking users' learning progress, scoring quizzes, and suggesting next steps, they lack consideration for the user's emotional state, which means the effectiveness of learning is not maximized. Furthermore, due to complex authentication processes and lack of break suggestions based on progress, there is a risk that users' motivation to learn will decrease. Furthermore, the inability to provide emotional feedback or adjust point allocation makes it difficult to provide an optimal learning experience tailored to each individual user.

[2264] 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.

[2265] In this invention, the server includes a means for displaying online learning content provided by a generation AI to the user, a means for automatically suggesting the next learning step based on the user's learning progress, a means for scoring the results of quizzes answered by the user and generating feedback, a means for awarding points or coupons according to the user's learning progress, a means for recognizing the user's emotions in real time and adjusting the difficulty level of the learning content, and a means for adjusting feedback messages based on the user's emotions. This enables the provision of adaptive learning content that takes into account the user's emotional state and the adjustment of the point system to maintain motivation while continuing to learn. Furthermore, the server can improve learning efficiency by suggesting breaks when fatigue or stress is detected.

[2266] "Generative AI" is a technology that uses artificial intelligence to automatically generate content such as text, images, and audio.

[2267] "Online learning content" refers to educational teaching materials and resources provided via the Internet.

[2268] "User's learning progress" is information indicating the results the user has achieved through their learning activities and their current level of achievement.

[2269] The "next learning step" refers to the next learning task or learning material that the user should tackle after completing the current learning content.

[2270] "Scoring the quiz results" means calculating and evaluating the percentage of correct answers and scores for the quiz answers given by the user.

[2271] "Generating feedback" means providing advice and comments based on the user's learning progress and quiz results.

[2272] "Giving points or coupons" means giving points or discount coupons as a reward for the user's learning activities.

[2273] "Real-time emotion recognition" means instantly analyzing and understanding a user's emotional state based on their facial expressions, voice, and behavior.

[2274] "Adjusting the difficulty level of learning content" means changing the difficulty level of the learning materials according to the user's emotions and learning progress.

[2275] "Adjusting the feedback message" means providing feedback whose content is in accordance with the user's emotional state.

[2276] "Performing authentication based on authentication information" means checking the username and password provided by the user and verifying their validity.

[2277] "Retrieving learning history from database" means searching and retrieving records of the user's past learning activities from the database.

[2278] "Generating an adaptive learning path" means determining the optimal learning order and learning materials based on the user's learning history and progress.

[2279] "Recording answers and reflecting them in the next study" means that the results of the user's answers to quizzes and tests are saved and used the next time they study.

[2280] "Suggest a break" means encouraging the user to temporarily stop studying when they feel tired or stressed.

[2281] "Individually customizing" means adjusting the content and progress to suit each user's individual situation.

[2282] "Calculating points" means calculating the points acquired based on the user's learning activities.

[2283] "Adjusting points and coupons" means changing the content and amount of rewards given depending on the user's emotional state and effort.

[2284] The present invention provides an online learning system that utilizes generative AI and an emotion engine to enable users to effectively learn IT and programming knowledge. Specific embodiments of this system are described in detail below.

[2285] User Registration and Login

[2286] This system requires user registration first. The user enters their name, email address, and password, and sends them from their terminal to the server. The server stores this information in a database and sends a message to the user indicating successful registration to the terminal. The database used in this process is a relational database management system such as MySQL.

[2287] Next, the user logs in using the registered information. They enter their username and password and send them from the terminal to the server. The server compares them with the information in the database and determines whether the authentication was successful. If successful, a login success message is returned and the user can access the system. If unsuccessful, a login failure message is displayed.

[2288] Providing learning content

[2289] When a logged-in user clicks the "Start Learning" button, a request is sent from the device to the server. The server retrieves the user's learning history from a database and generates an optimal learning path based on that information. A generative AI model (e.g., GPT-3) is used in this process. Online learning content corresponding to the generated learning path is sent to the device and displayed to the user.

[2290] Quiz grading and feedback

[2291] After completing the learning content, the user answers the provided quiz. The device sends the user's answers to the server. The server compares the user's answers with the correct answers in the database and calculates a score. A feedback message is generated based on the score and sent to the device. At the same time, the user's score is recorded in the database. The device displays the score and feedback to the user.

[2292] Suggested next steps

[2293] The server determines the next learning content based on the user's most recent learning history and score. This information is sent to the device and displayed as the user's next learning step. This allows the user to always know the appropriate next learning task.

[2294] Points and coupons

[2295] The server calculates the points to be awarded based on the user's latest score and learning progress. The calculated points are added to the user's account, and a message informing the user that the points have been earned is sent to the device. The device then displays the message to the user, encouraging them to learn.

[2296] Introducing the Emotion Engine

[2297] The emotion engine has the ability to recognize the user's emotional state in real time through facial expression and voice analysis. This recognized emotional information is integrated into various functions of the system as follows: If the emotion engine recognizes the user's emotional state and detects, for example, stress, it can adjust the difficulty of the learning content. If the user is relaxed, it can provide more challenging content.

[2298] The emotion engine also adjusts feedback messages based on the user's emotional state. If the user is confused, it will provide more detailed explanations or encouraging messages. Furthermore, the emotion engine recognizes the user's emotional state and adjusts the criteria for awarding points and coupons. If the user is tired or unmotivated, it can award extra bonus points to motivate them to continue learning.

[2299] If the emotion engine detects stress or fatigue in the user, the system will suggest a break, allowing the user to continue learning without straining themselves.

[2300] Specific examples

[2301] Example 1: When a user creates a new account

[2302] The user enters their name, email address, and password and clicks the Register button. The device sends this information to the server, which stores it in a database (e.g., MySQL). If registration is successful, the device displays a "Registration successful" message to the user.

[2303] Example 2: When a user takes a quiz

[2304] Users complete learning content and answer quizzes. The device sends the user's answers to the server, which scores them. Feedback and scores are generated and sent to the device, which displays them to the user. Users can instantly check their learning progress and receive advice on how to proceed to the next step.

[2305] Prompt Sentence Examples

[2306] By inputting the prompt sentence "Generate a prompt to suggest the next learning step," the generative AI model can suggest appropriate learning steps.

[2307] The above is a specific embodiment of the online learning system of the present invention. This system allows users to acquire IT and programming knowledge efficiently and enjoyably. The introduction of an emotion engine is expected to provide users with a personalized learning experience, further improving learning effectiveness.

[2308] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2309] Step 1: User Registration

[2310] The user enters their name, email address, and password and clicks the Register button.

[2311] The terminal sends this information to the server using the HTTPS protocol.

[2312] The server performs validation checks on the transmitted information (checking the format, password strength, etc.).

[2313] If validation passes, the server saves the information in a database (e.g. MySQL) and generates a registration success message.

[2314] The server sends a registration success message to the terminal, and the terminal displays the message "Registration successful" to the user.

[2315] Input: Name, email address, password, Output: Registration successful message.

[2316] Step 2: User Login

[2317] The user enters their username (or email address) and password and clicks the login button.

[2318] The terminal transmits this information to the server.

[2319] The server authenticates the user by checking the information in the database, for example by comparing the hash value of the entered password with the hash value in the database.

[2320] If authentication is successful, the server generates a token (e.g., a JWT token) and sends it to the terminal.

[2321] The terminal receives the token and starts the user's session. It displays a success message to the user.

[2322] Input: Username (or email address), password. Output: Authentication token, login success message.

[2323] Step 3: Provide learning content

[2324] The user clicks the "Start Learning" button.

[2325] The terminal sends a request to the server.

[2326] The server retrieves the user's learning history from the database and processes the information.

[2327] The server uses a generative AI model (e.g., GPT-3) to generate the optimal learning path.

[2328] The server transmits the generated learning content to the terminal, which displays it to the user.

[2329] Input: Learning start request, Output: Optimal learning content.

[2330] Step 4: Run and grade the quiz

[2331] Users complete learning content and take quizzes.

[2332] The terminal transmits the user's answer to the server.

[2333] The server compares the user's answer with the correct answer data in the database and calculates a score.

[2334] The server generates a feedback message based on the calculated score and sends it to the terminal.

[2335] The terminal displays a feedback message and score to the user.

[2336] Input: quiz answers, Output: scores, feedback messages.

[2337] Step 5: Suggest next learning steps

[2338] The server determines what to study next based on the most recent learning history and score.

[2339] The server uses the generative AI model to generate prompts (e.g., "Generate a prompt that suggests the next learning step") and determine the next learning path.

[2340] The server sends the next learning content to the terminal, which then displays it to the user.

[2341] Input: Latest learning history and score, Output: Next learning content.

[2342] Step 6: Points and coupons awarded

[2343] The server calculates the points to be awarded based on the latest score and learning progress.

[2344] The calculated points are recorded in a database by the server.

[2345] The server sends a points acquisition message to the terminal, which displays it to the user.

[2346] Input: Latest score, Output: Calculated points, Points earned message.

[2347] Step 7: Use the Emotion Engine

[2348] The emotion engine analyzes the user's facial expressions and voice to recognize emotions in real time.

[2349] Based on the emotional information recognized by the emotion engine, the server adjusts the difficulty level of the learning content.

[2350] The server also adjusts the feedback message according to the emotional state and sends it to the terminal.

[2351] If the emotion engine detects stress or fatigue, the server generates a message suggesting a break and sends it to the terminal.

[2352] The terminal displays these messages to the user.

[2353] Input: User's facial expressions and voice, Output: Tailored learning content, feedback messages, break suggestion messages.

[2354] (Application example 2)

[2355] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2356] Conventional online learning systems provide learning paths and quiz feedback based on a user's learning progress and history, but lack the ability to analyze the user's emotional state in real time and dynamically adjust learning content and feedback. As a result, users' motivation tends to drop and learning efficiency declines. In addition, point systems to improve motivation to learn are limited, making continuity of learning an issue.

[2357] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for displaying online learning content provided to the user using a generation AI, a means for automatically suggesting the next learning step based on the user's learning progress, a means for scoring the results of quizzes answered by the user and generating feedback, a means for awarding points or coupons according to the learning progress, a means for analyzing the user's emotional state using the camera and microphone of the smart device, and a means for adjusting the learning content based on the analysis results. This makes it possible to provide a dynamic learning experience that corresponds to the user's emotional state, increasing motivation to learn and enabling effective knowledge acquisition.

[2358] "Learning Content" means educational content created using generative AI and made available to users through an online platform.

[2359] "Generative AI" is a type of artificial intelligence that generates optimal learning paths and feedback based on a user's learning history and response results.

[2360] A "quiz" is a question-based test presented to a user after completing learning content, and is a means of assessing the user's level of understanding of the learning.

[2361] "Points" are rewards given to users according to their progress and achievements in learning, and are used to increase the user's motivation to learn.

[2362] A "coupon" is something that is given to a user as a reward for learning activities, and can be exchanged for a specific service or product.

[2363] A "smart device" is a device equipped with a camera and a microphone and used to analyze the emotional state of a user.

[2364] The "emotion engine" is a technology that analyzes the user's facial expressions and voice to recognize their emotional state in real time.

[2365] An "adaptive learning path" is an individually customized learning path that is generated based on a user's learning history and current learning progress.

[2366] A "feedback message" is a message for learning support that is provided according to the user's quiz results and emotional state.

[2367] "Break suggestion" is a function that suggests to the user that they take a break if the emotion engine detects stress or fatigue in the user.

[2368] System Overview

[2369] This invention is an online learning system that utilizes generative AI and an emotion engine to enable users to effectively learn IT and programming knowledge. This system provides learning content to users via smart devices (such as smartphones and tablets) and dynamically adjusts the learning experience according to the user's learning progress and emotional state.

[2370] User Registration and Login

[2371] The server stores the authentication information provided by the user, such as name, email address, and password, in a database, which allows the user to access the learning system. After registration and login, the server manages the user's learning history and provides an adaptive learning path for the next time the user studies.

[2372] Providing learning content

[2373] The server uses generative AI to generate online learning content and displays it on the user's device. When the user clicks the "Start Learning" button, the server retrieves the user's learning history from the database and generates an optimal learning path based on that information. The content corresponding to that learning path is sent to the device and displayed to the user.

[2374] Quiz grading and feedback

[2375] When the user finishes the learning content, a quiz is displayed. When the user answers the quiz, the device sends the answer to the server, which compares it with the correct answer data and calculates a score. A feedback message is generated based on this score and displayed to the user via the device. The user's score is also reflected in the generation of the next learning path.

[2376] Introducing the Emotion Engine

[2377] The server utilizes an emotion engine that analyzes the user's emotional state in real time using the smart device's camera and microphone. For example, if the emotion engine detects that the user is stressed, it can adjust the difficulty of the learning content or suggest a break. Feedback messages are also adjusted based on the user's emotional state.

[2378] A points system to increase motivation to learn

[2379] The server awards points and coupons based on the user's learning progress and quiz scores. These points are displayed on the user's device and can be used to exchange for rewards. In particular, if the emotion engine detects a decline in the user's motivation, it can award special bonus points to improve the user's motivation to learn.

[2380] Specific examples

[2381] For example, when a user creates a new account and begins studying and taking a quiz, the emotion engine detects a decline in concentration from the user's facial expressions. In this case, the difficulty level of the learning content is automatically lowered to allow the user to continue studying at a comfortable pace. The feedback message provided after the quiz is graded is also adjusted to include words of encouragement or additional explanation.

[2382] Prompt Sentence Examples

[2383] Generate new quiz questions below to prompt your AI model with the right feedback to help users overcome emotional disorders.

[2384] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2385] Step 1:

[2386] A user registers by entering their name, email address, and password on their terminal. They provide their name, email address, and password as input and send them from the terminal to the server. The server stores this information in a database and sends a "Registration successful" message to the terminal as output, which is displayed to the user.

[2387] Step 2:

[2388] A user logs in by entering an email address and password on the terminal. The email address and password are provided as input and sent from the terminal to the server. The server compares them with the user information in the database and performs authentication. If authentication is successful, a "Login successful" message is output and sent to the terminal. If authentication fails, a "Login failed" message is displayed.

[2389] Step 3:

[2390] After logging in, the user clicks the "Start Learning" button. The device sends a request to the server, providing the user's authentication information as input. The server retrieves the user's learning history from the database and uses generative AI to generate an optimal learning path. Online learning content based on this learning path is sent to the device as output and displayed to the user.

[2391] Step 4:

[2392] Users study according to the learning content provided on their devices. While studying, the smart device's camera and microphone capture the user's facial expressions and voice, collecting emotional data as input. The server's emotion engine analyzes this data and recognizes the user's emotional state in real time. For example, if stress or fatigue is detected, the difficulty level will be adjusted or a break will be suggested.

[2393] Step 5:

[2394] After completing the study, the user answers the quiz on the device. The user's answers are provided as input and sent from the device to the server. The server compares the user's answers with the correct answers in the database and calculates a score. A feedback message is generated based on the score, and the feedback message and score are sent as output to the device and displayed to the user.

[2395] Step 6:

[2396] The server determines the next learning content based on the user's latest learning history and score. This information is taken as input from the database, and the optimal next learning step is output and sent to the terminal. The user then performs the next learning activity based on this.

[2397] Step 7:

[2398] The server calculates points and coupons according to the user's learning progress and quiz scores. The server uses the user's learning history and score as input, and the calculated points and coupons are added to the user's ...

Claims

1. a means for displaying online learning content provided using the generative AI to a user; means for automatically suggesting a next learning step based on the user's learning progress; means for scoring the results of the quiz answered by the user and generating feedback; A method to award points and coupons according to the progress of learning, A system including:

2. means for performing authentication based on user-provided authentication information; A means for retrieving a user's learning history from a database; means for generating an adaptive learning path based on a user's learning history; A means to record the user's answers and reflect them in the next lesson. The system of claim 1 further comprising:

3. A means for customizing the next learning step for each user based on their learning history and scores; a means for calculating points and issuing coupons to increase the user's motivation to learn; a means for displaying earned points and coupons to the user; The system of claim 1 further comprising:

Images