system

Abstract

We provide the system. [Solution] A means for obtaining information entered by the user, A means for generating a user's learning profile based on acquired information, A means of automatically generating and providing a learning program tailored to the user's learning profile, A means of recording the user's learning progress, A means of analyzing recorded learning progress data and optimizing the next learning content, A means of providing users with feedback and suggesting additional learning content, A system that includes this.

Description

Technical Field

[0005] ,

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance as a response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Conventional educational support systems have difficulty in providing individualized support according to users' learning needs and progress, and it has been an issue to provide equal learning opportunities regardless of income, region, or individual handicaps. Also, when taking measures for a specific qualification exam, the provision of individual curricula and mock exams has been limited, making it difficult to maximize the learning effect of users. The development of a system to solve such problems has been demanded.

Means for Solving the Problems

[0005] This invention provides a system that acquires information entered by a user, generates a learning profile based on that information, and automatically generates and provides a learning program tailored to the user's profile. Furthermore, this system can record the user's learning progress, analyze the data to optimize the next learning content, and suggest feedback and additional learning content to the user. It also includes means for specifying a qualification exam, generating a curriculum corresponding to the specified exam, conducting a mock exam, analyzing the results, and suggesting additional learning content. This enables personalized support for users and provides equal learning opportunities regardless of income, region, or personal handicaps.

[0006] "Means of acquisition" refers to the interface and process for electronically collecting information entered by the user.

[0007] A "learning profile" is a data structure created based on personal information such as the user's age, grade level, subjects of interest, and learning objectives, and is used to determine learning content and curriculum that are appropriate for each user.

[0008] A "learning program" refers to the specific content of learning materials, exercises, and learning activities that are automatically generated based on the user's learning profile.

[0009] "Means of provision" refers to the functions of display devices and software used to present learning programs and other learning resources to users.

[0010] "Learning progress" refers to data that shows how much progress a user has made through their learning activities, and includes things like comprehension level and grades.

[0011] "Means of recording" refers to a function for saving details of the user's learning activities (e.g., answer results, study time, etc.) to a database.

[0012] "Means of analysis" refer to algorithms and processes that process recorded learning progress data to identify areas where the user needs improvement and what they should learn next.

[0013] "Optimizing" means adjusting the learning plan to select and provide learning content and materials that are best suited to the user's needs and progress.

[0014] "Feedback" refers to providing information and evaluation results regarding a user's learning activities, along with advice and suggestions to help them improve their future learning.

[0015] "Additional learning content" refers to supplementary materials and practice problems provided based on the user's learning progress and analysis results.

[0016] "Means for specifying qualification exams" refers to an interface for users to input the type and goals of the qualification exams they wish to take into the system.

[0017] A "curriculum" is a set of learning content and materials planned to achieve specific learning objectives.

[0018] "Methods for conducting mock exams" refer to tools that provide and administer exam-format questions in a way that allows users to check their level of understanding in accordance with the actual exam.

[0019] "Means of time management" refer to functions and tools that help users use their time efficiently during mock exams and study activities. [Brief explanation of the drawing]

[0020] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of the data processing device and smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Embodiments for Carrying Out the Invention

[0021] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described according to the accompanying drawings.

[0022] First, the language used in the following description will be explained.

[0023] In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), and APU (Accelerated Processing Unit).

[0024] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0025] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0026] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0027] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0028] [First Embodiment]

[0029] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0030] As shown in Figure 1, the 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.

[0031] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0032] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0033] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0034] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0035] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0036] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0037] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0038] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0039] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0040] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0041] This invention is an educational support system designed to ensure that users have equal learning opportunities regardless of income, location, or personal disadvantages. The system supports effective learning by providing individualized support based on the user's learning needs, managing learning progress, and offering feedback.

[0042] System Configuration

[0043] This system has the following main functions:

[0044] 1. Means of obtaining information entered by the user

[0045] 2. Generating a learning profile

[0046] 3. Automatic generation and provision of learning programs

[0047] 4. Recording and analyzing learning progress

[0048] 5. Feedback and suggestions for additional learning content

[0049] 6. Designation of qualification examinations and curriculum development

[0050] 7. Implementation and analysis of mock exams

[0051] Specific operation of the system

[0052] User registration and information retrieval

[0053] The terminal displays a form for first-time users to enter their name, age, grade level, and desired subjects.

[0054] The user enters this information and presses the register button.

[0055] The server receives the entered information, stores it in the database, and generates a user ID and password.

[0056] Generating a learning profile

[0057] The server generates a learning profile based on the registered user information. For example, a profile might be created for a second-year high school student who wants to improve their math skills.

[0058] Automatic generation and provision of learning programs

[0059] The server automatically generates a customized learning program based on the generated learning profile and displays it on the user's dashboard.

[0060] The device allows users to access the learning program from the dashboard and begin learning.

[0061] Recording and analyzing learning progress

[0062] As the user progresses through the learning process, the device records the user's progress.

[0063] The server receives the recorded learning progress data and analyzes it. For example, it might identify that the user makes many mistakes on trigonometry problems.

[0064] Feedback and suggestions for additional learning content

[0065] The server optimizes the next learning objectives based on the analysis results and provides feedback to the user.

[0066] The device displays information that allows the user to receive feedback and suggests additional learning content.

[0067] Designation of qualification exams and curriculum generation

[0068] If a user wants to take a specific certification exam, they specify that exam in the system.

[0069] The server generates a curriculum corresponding to the specified certification exam and adds it to the user's dashboard.

[0070] Implementation and analysis of mock exams

[0071] The device allows the user to start the practice exam and manages the exam time.

[0072] Users take a practice test and submit their answers.

[0073] The server analyzes the results of the practice test and suggests additional learning content for areas that require particular improvement.

[0074] Specific example

[0075] For example, if a user is a 15-year-old high school sophomore and wants to improve their math skills, the system will work as follows:

[0076] 1. The user enters and submits user information on the terminal, and the server generates a profile.

[0077] 2. The server automatically generates math materials and practice problems for second-year high school students and displays them on the user's dashboard.

[0078] 3. The user begins learning, and the device records their progress.

[0079] 4. The server analyzes the progress data and, for example, if it determines that there is a lack of understanding of trigonometry, it generates additional problems to strengthen that area and adds them to the dashboard.

[0080] 5. The user solves additional problems, the results are further analyzed, and appropriate feedback and suggestions for the next learning activities are provided.

[0081] With the above configuration and operation, this system can provide learning support tailored to the individual needs of users, thereby improving the efficiency and effectiveness of learning.

[0082] The following describes the processing flow.

[0083] Step 1:

[0084] When a user accesses the system for the first time, the device displays a registration form for them to enter their name, age, grade level, and desired subjects.

[0085] Step 2:

[0086] The user fills in the required information on the form and clicks "Register".

[0087] Step 3:

[0088] The terminal sends the entered information to the server.

[0089] Step 4:

[0090] The server receives the transmitted information and stores it in the database.

[0091] Step 5:

[0092] The server generates a user ID and password and sends them to the user.

[0093] Step 6:

[0094] The device displays the user ID and password and redirects the user to the dashboard screen.

[0095] Step 7:

[0096] The server generates a learning profile based on user profile information. For example, this includes information such as "high school sophomore" and "desire to improve math skills."

[0097] Step 8:

[0098] The server automatically generates a customized learning program based on the user's learning profile and displays it on the user's dashboard.

[0099] Step 9:

[0100] The device allows the user to access the learning program from the dashboard and begin learning.

[0101] Step 10:

[0102] Once a user begins learning, the device records the user's progress (e.g., answer results, learning time, etc.).

[0103] Step 11:

[0104] The terminal sends the recorded progress data to the server.

[0105] Step 12:

[0106] The server analyzes progress data and identifies areas where the user should focus their efforts. For example, it might extract data such as "there are many mistakes in trigonometry problems."

[0107] Step 13:

[0108] Based on the analysis results, the server optimizes the content for the next lesson and generates additional supplementary materials and practice problems.

[0109] Step 14:

[0110] The server displays the generated additional learning materials and practice problems on the user's dashboard.

[0111] Step 15:

[0112] The device notifies the user of updated learning programs and displays them as feedback.

[0113] Step 16:

[0114] The user reviews the feedback and sets their next learning goals.

[0115] Step 17:

[0116] If a user wishes to take a certification exam, the device provides a form for entering exam information.

[0117] Step 18:

[0118] The user enters the desired qualification exam (e.g., "TOEIC") and submits it.

[0119] Step 19:

[0120] The server receives the entered qualification exam information, generates the corresponding curriculum, and adds it to the dashboard.

[0121] Step 20:

[0122] The device is configured to allow the user to start a practice exam and provides time management tools for the exam.

[0123] Step 21:

[0124] Users take a practice test and submit their answers.

[0125] Step 22:

[0126] The server analyzes the results of the practice test and evaluates the level of understanding and proficiency in specific areas.

[0127] Step 23:

[0128] Based on the results of the practice test, the server suggests additional learning content for areas where the user needs to improve, and reflects this on the dashboard.

[0129] Step 24:

[0130] The device notifies the user of additional learning content and guides them to proceed to the next learning step.

[0131] By following these steps, the system can continuously provide the most suitable content for the user's learning needs and progress.

[0132] (Example 1)

[0133] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0134] Modern education systems struggle to meet the individual learning needs of users, particularly due to unequal access to learning opportunities caused by income, location, and personal disadvantages. Furthermore, traditional learning systems often fail to effectively track learning progress and provide feedback, making it difficult to offer optimal learning programs for individual users. As a result, users are unable to learn efficiently and achieve their goals.

[0135] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0136] In this invention, the server includes means for acquiring information entered by the user, means for generating a user learning profile based on the acquired information, means for automatically generating and providing a learning program according to the user's learning profile, means for recording the user's learning progress, means for analyzing the recorded learning progress data and optimizing the next learning content, means for suggesting feedback and additional learning content to the user, means for storing user information and learning progress data in a database, means for reflecting the learning program and feedback on the user's dashboard, means for the user to take a mock exam and submit the results, and means for analyzing the results of the mock exam and suggesting improvements in specific areas. This enables users to learn fairly and efficiently and provides optimal educational support tailored to each individual's learning needs.

[0137] "Means of acquiring user-inputted information" refers to devices and software that collect and store information that users input into the system, such as their name, age, grade level, and subjects they wish to study.

[0138] "Means for generating a user's learning profile based on acquired information" refers to algorithms and programs that create a learning profile that reflects the individual user's learning needs and goals, based on the information provided by the user.

[0139] "Means for automatically generating and providing learning programs tailored to a user's learning profile" refers to a system that automatically creates and provides optimal learning content and activities to the user based on the generated learning profile.

[0140] "Means for recording user learning progress" refers to devices or programs that have the function of continuously recording the progress and answer results achieved by a user during the learning process.

[0141] "Means for analyzing recorded learning progress data and optimizing the next learning content" refers to algorithms and programs that analyze collected learning progress data to understand the user's level of comprehension and weaknesses, and determine the optimal content for the next learning session.

[0142] "Means of providing users with feedback and suggesting additional learning content" refers to devices or software that have the functionality to provide users with specific feedback based on analyzed learning progress data and to suggest any additional learning content they may need.

[0143] "Means for storing user information and learning progress data in a database" refers to a system that records user-entered information and learning progress data in a database and manages it so that it can be referenced later as needed.

[0144] "Means of reflecting learning programs and feedback on the user's dashboard" refers to a system that has an interface on the dashboard that allows users to see their learning progress and feedback at a glance.

[0145] "Means for users to take a practice test and submit the results" refers to devices or programs that have the function of allowing users to take a practice test and submit the results to a system.

[0146] "Methods for analyzing mock exam results and suggesting improvements in specific areas" refers to algorithms or programs that scrutinize the results of mock exams taken by users, identify specific areas that need improvement, and suggest additional learning content for those areas.

[0147] This invention is an educational support system designed to ensure that users have equal learning opportunities regardless of income, location, or personal disadvantages. The system has the following main functions:

[0148] User registration and information retrieval

[0149] The terminal displays a form for new users to enter information such as their name, age, grade level, and desired subjects. This form is accessed via a web browser or a dedicated application.

[0150] The user enters the required information and presses the "Register" button to submit the information.

[0151] The server receives the transmitted information and stores it in a database (for example, MySQL® or PostgreSQL). It also generates a user ID and initial password and notifies the user.

[0152] Generating a learning profile

[0153] The server generates a learning profile based on registered user information. This profile reflects the user's learning needs and goals.

[0154] For example, you can generate a profile using machine learning techniques with Python libraries (pandas, scikit-learn).

[0155] Automatic generation and provision of learning programs

[0156] The server automatically generates a customized learning program based on the generated profile. This program consists of appropriate learning materials and problem sets.

[0157] The server displays programs generated using a template engine (such as Jinja2) on the user's dashboard.

[0158] The device allows users to access the dashboard, view the learning program, and begin.

[0159] Recording and analyzing learning progress

[0160] As the user progresses through the learning process, the device records their progress in real time (e.g., answer status and accuracy rate). This record is temporarily stored using HTML5 local storage or JavaScript®.

[0161] The device periodically sends this progress data to the server.

[0162] The server receives progress data and analyzes it using Python's pandas and numpy. For example, if a user makes many mistakes in a particular area (e.g., trigonometry), the server identifies that area.

[0163] Feedback and suggestions for additional learning content

[0164] The server optimizes the next learning content based on the analysis of progress data. This includes additional problems and materials to strengthen the user's weaknesses.

[0165] The device displays feedback and suggested additional learning content on the user's dashboard.

[0166] Designation of qualification exams and curriculum generation

[0167] If a user wants to take a specific certification exam (e.g., TOEIC), they specify that exam in the system.

[0168] The server generates a curriculum corresponding to the specified certification exam and provides it to the user's dashboard.

[0169] Implementation and analysis of mock exams

[0170] The device allows the user to start a practice test and manages the test time using a JavaScript timer function.

[0171] After taking a practice test, the user submits their answers.

[0172] The server analyzes the results and suggests additional learning content, particularly in areas that need strengthening.

[0173] Examples and prompts for generative AI models

[0174] For example, if a 15-year-old high school sophomore wants to improve their math skills, it would work as follows:

[0175] The user enters their information on the terminal, and the server generates a profile.

[0176] The server generates math materials and practice problems for second-year high school students and displays them on the user's dashboard.

[0177] The user begins learning, and the device records the learning progress and sends it to the server.

[0178] The server analyzes the progress data and, for example, if it determines that there is a lack of understanding of trigonometry, it generates additional problems and adds them to the dashboard.

[0179] The user solves additional problems, the results are analyzed, and the next learning objectives are suggested.

[0180] Examples of prompts for a generative AI model:

[0181] "I have a 15-year-old high school sophomore who wants to improve his math skills. Please create a customized learning program for him based on his current learning progress, with a particular focus on trigonometry."

[0182] In this way, the system provides comprehensive learning support tailored to the individual needs of users, thereby improving the efficiency and outcomes of their learning.

[0183] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0184] Step 1:

[0185] User registration and information retrieval

[0186] The device displays a form for the user to enter information such as their name, age, grade level, and the subjects they wish to study.

[0187] Input: User information (name, age, grade level, subject you want to study)

[0188] Output: Information entered by the user

[0189] The user enters the required information and presses the "Register" button to submit the information.

[0190] Input: User actions

[0191] Output: Sent user information

[0192] The server receives the transmitted user information and stores it in the database.

[0193] Input: Submitted user information

[0194] Data processing: Converting user information into a database format.

[0195] Output: User information stored in the database

[0196] The server generates a user ID and initial password and notifies the user.

[0197] Input: Saved user information

[0198] Data calculation: Generation of user ID and initial password

[0199] Output: User ID and initial password

[0200] Step 2:

[0201] Generating a learning profile

[0202] The server generates a learning profile based on the registered user information.

[0203] Input: User information stored in the database

[0204] Data processing: Generate profiles based on learning needs and grade level (e.g., using Python libraries pandas and scikit-learn).

[0205] Output: Generation of training profile

[0206] The server saves the generated profile to the database.

[0207] Input: Generated training profile

[0208] Data processing: Convert profile to database format

[0209] Output: Learning profiles stored in the database

[0210] Step 3:

[0211] Automatic generation and provision of learning programs

[0212] The server automatically generates a customized learning program based on the generated learning profile.

[0213] Input: Learning Profile

[0214] Data processing: Select appropriate teaching materials and problem sets, and design a learning program (using the Jinja2 template engine).

[0215] Output: Customized learning program

[0216] The server displays the generated learning program on the user's dashboard.

[0217] Input: Customized learning program

[0218] Output: The program reflected in the user's dashboard.

[0219] The device allows users to access the dashboard, view their learning programs, and begin.

[0220] Input: User actions

[0221] Output: Learning program displayed to the user

[0222] Step 4:

[0223] Recording and analyzing learning progress

[0224] As the user progresses through the learning process, the device records their progress in real time.

[0225] Input: User's learning activity data (answer results, progress)

[0226] Data processing: Save to local storage in real time.

[0227] Output: Recorded progress

[0228] The device periodically sends progress data to the server.

[0229] Input: Progress data stored in local storage

[0230] Output: Progress data sent to the server

[0231] The server receives and analyzes the progress data.

[0232] Input: Submitted progress data

[0233] Data processing: Analysis using data analysis tools (pandas, numpy).

[0234] Output: Analysis results (e.g., identification of weaknesses in a specific field)

[0235] Step 5:

[0236] Feedback and suggestions for additional learning content

[0237] The server optimizes the next learning steps based on the analysis results of the progress data.

[0238] Input: Analysis results of progress data

[0239] Data processing: Generating feedback content and additional learning content.

[0240] Output: Next learning content

[0241] The device displays feedback and additional learning content on the user's dashboard.

[0242] Input: Generated feedback content and additional learning content

[0243] Output: Feedback and additional learning content displayed on the dashboard

[0244] Step 6:

[0245] Designation of qualification exams and curriculum generation

[0246] If a user wants to take a specific certification exam, they specify that exam in the system.

[0247] Input: Specified information for the qualification exam

[0248] Output: Qualification exam information set in the system

[0249] The server generates a curriculum corresponding to the specified certification exam and provides it to the user's dashboard.

[0250] Input: Specified information for the qualification exam

[0251] Data processing: Automatic generation of curriculum

[0252] Output: Curriculum added to the user's dashboard

[0253] Step 7:

[0254] Implementation and analysis of mock exams

[0255] The device allows the user to start the practice exam and manages the exam time.

[0256] Input: User action (start of mock exam)

[0257] Data calculation: Using JavaScript's timer function

[0258] Output: Start of mock exam and time management

[0259] Users take a practice test and submit their answers.

[0260] Input: User's answer

[0261] Output: Submitted answer data

[0262] The server analyzes the results of the practice test and suggests additional learning content for areas that require particular improvement.

[0263] Input: Submitted answer data

[0264] Data processing: Analysis of answer data

[0265] Output: Suggestions for strengthening specific areas and additional learning content

[0266] (Application Example 1)

[0267] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0268] Traditional education systems failed to adequately address users' diverse learning needs, lacking sufficient feedback based on learning progress and insufficient suggestions for optimal additional learning content. Furthermore, the provision of learning materials and progress management were not centralized, and there were challenges in conducting mock exams and effectively addressing weaknesses based on the results. Additionally, the lack of immediate feedback and suggestions for additional learning content prevented users from learning efficiently.

[0269] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0270] In this invention, the server includes means for acquiring information entered by the user, means for generating a user learning profile based on the acquired information, means for automatically generating and providing a learning program according to the user's learning profile, means for recording the user's learning progress, means for analyzing the recorded learning progress data and optimizing the next learning content, means for suggesting feedback and additional learning content to the user, means for providing learning materials and online courses from a virtual store, means for generating a customized learning program based on purchased materials, means for analyzing the results of mock exams and suggesting a curriculum to reinforce weaknesses, and means for allowing the user to view their learning progress and feedback. As a result, the user can receive an optimal learning program tailored to their individual learning needs, easily acquire a variety of learning materials through the virtual store, and manage and improve their learning progress more efficiently and effectively.

[0271] "Means for obtaining user input" refers to an interface that allows users to input information such as their name, age, grade level, and subjects they wish to study, and then transmit this information to the system.

[0272] "Means for generating a user's learning profile based on acquired information" refers to a system that analyzes the acquired personal information of a user and creates a profile that takes into account the user's learning needs.

[0273] "A means of automatically generating and providing a learning program tailored to the user's learning profile" refers to a system that automatically creates an individualized learning plan based on the learning profile and provides it to the user.

[0274] A "means for recording user learning progress" refers to a system that records progress data such as how far a user has progressed during their learning and which tasks have been completed.

[0275] "A means of analyzing recorded learning progress data and optimizing the next learning content" refers to a system that analyzes collected learning progress data and adjusts the content to be learned next according to the user's level of understanding and weaknesses.

[0276] A "means of providing users with feedback and suggesting additional learning content" is a system that provides users with feedback based on their progress data, indicating which parts they understand and which parts they need to improve, and then suggests the necessary additional learning content.

[0277] "A means of providing learning materials and online courses from a virtual store" refers to a system that allows users to purchase and access various learning materials and online courses through an online store.

[0278] "A means of generating a customized learning program based on purchased learning materials" refers to a system that individually creates an optimal learning plan using the learning materials purchased by the user in a virtual store.

[0279] "A method for analyzing mock exam results and proposing a curriculum to strengthen weaknesses" refers to a system that thoroughly analyzes the results of mock exams taken by users, identifies their weaknesses, and then provides an additional curriculum to strengthen those weaknesses.

[0280] "Means for users to view their learning progress and feedback" refers to the interface that users use to check their learning progress and feedback from the system.

[0281] This invention is an educational support system for acquiring information entered by a user and generating, providing, and managing individualized learning programs based on that information. This system supports efficient learning by recording and analyzing the user's learning progress and optimizing the next learning content.

[0282] System Configuration

[0283] 1. User Registration and Information Acquisition

[0284] When a user first accesses, the server displays a personal information input form on the terminal. The user inputs and sends information such as name, age, grade, and subjects to study. The server saves the received information in the database and generates a user ID and password.

[0285] 2. Generation of Learning Profile

[0286] Based on the registered user information, the server generates a personalized learning profile for each user. For example, a profile indicating a high motivation to learn a specific subject is created.

[0287] 3. Automatic Generation and Provision of Learning Programs

[0288] Based on the generated learning profile, the server automatically generates a customized learning program for each user and reflects it on the user's dashboard. The user accesses the learning program through the terminal and starts learning.

[0289] 4. Recording and Analysis of Learning Progress

[0290] During the process of the user's learning progress, the terminal records the user's progress. The server receives the recorded learning progress data and analyzes the data. For example, if the user makes many incorrect answers in a specific field, that data is extracted.

[0291] 5. Feedback and Proposal of Additional Learning Content

[0292] Based on the analysis results, the server optimizes the next learning content and provides feedback to the user. The terminal displays the feedback so that the user can receive it and proposes additional learning content.

[0293] 6. Provision of Teaching Materials from Virtual Stores

[0294] The server provides users with learning materials and online courses tailored to their needs through a virtual store. Users can purchase these within the app and incorporate them into their learning programs.

[0295] 7. Generating a customized learning program

[0296] The server generates a customized learning program based on the purchased learning materials and provides it to the user.

[0297] 8. Analysis of mock exam results and strengthening of weak points

[0298] The server receives the results of the mock exam and analyzes them in detail. Based on this, it identifies the user's weaknesses and proposes a curriculum to strengthen those weaknesses.

[0299] 9. View learning progress and feedback

[0300] Users can view their learning progress and feedback from the system through their device.

[0301] Specific example

[0302] For example, if a high school sophomore user wants to improve their math skills, the system will work as follows:

[0303] 1. The user enters and submits personal information on their device. The server generates a learning profile.

[0304] 2. The server automatically generates math materials and practice problems for second-year high school students and displays them on the user's dashboard.

[0305] 3. The user purchases learning materials and proceeds with their studies. The device records their progress.

[0306] 4. The server analyzes the progress data and identifies areas where understanding is particularly lacking. For example, if the acquisition of trigonometric functions is insufficient, additional questions to strengthen that area are generated and added to the dashboard.

[0307] 5. The user solves the additional questions, and the results are analyzed, and appropriate feedback and the next learning content are proposed.

[0308] Examples of prompt sentences for the generative AI model

[0309] "When a user who is a second-year high school student is advancing in math learning, due to many incorrect answers in a specific area, generate additional questions to strengthen that area and reflect them on the dashboard."

[0310] The flow of specific processing in Application Example 1 will be described using FIG. 12.

[0311] Step 1:

[0312] When the user first accesses, the server displays a personal information input form on the terminal. The user inputs information such as name, age, grade, and subject to study, and then sends it. The input information is sent from the terminal to the server. The server saves the received information in the database and generates a user ID and password.

[0313] Step 2:

[0314] Based on the registered user information, the server generates a user-specific learning profile. This profile includes the user's age, grade, and subjects of interest. The generated profile is saved in the database.

[0315] Step 3:

[0316] The server automatically generates a personalized learning program based on the generated learning profile. This program includes learning materials and practice exercises tailored to the user's grade level and interests. This learning program is reflected in the user's dashboard and provided to the user through their device.

[0317] Step 4:

[0318] The user accesses the learning program provided through the device and begins learning. The device records the user's learning progress in real time and sends this data to the server. The recorded progress data includes completed assignments and the accuracy of answers.

[0319] Step 5:

[0320] The server performs data analysis based on recorded learning progress data. The analysis identifies areas where the user frequently makes mistakes or where their understanding is lacking. The analysis results are stored in a database.

[0321] Step 6:

[0322] The server executes an algorithm to optimize the next learning content based on the analysis results. For example, if there is a lack of understanding in a particular area, it generates additional problems or learning materials related to that area. The generated learning content is added to the user's dashboard.

[0323] Step 7:

[0324] The device displays an interface that allows the user to view newly suggested learning content and feedback. The user then continues learning based on this information, and their progress is recorded and analyzed again.

[0325] Step 8:

[0326] The server provides users with various learning materials and online courses through a virtual store. Users purchase these materials through their devices, and the content is reflected in their learning programs.

[0327] Step 9:

[0328] The server generates a customized learning program based on the purchased learning materials. This generated program is reflected in the user's dashboard and provided as additional learning content.

[0329] Step 10:

[0330] The server analyzes the results of the practice exams taken by the user in detail. Based on the analysis, it identifies areas where the user's understanding is lacking and generates a curriculum to reinforce those weaknesses. This curriculum is also added to the user's dashboard.

[0331] Step 11:

[0332] The device allows users to view their learning progress and system feedback in real time. Users can then refer to this information to learn more efficiently.

[0333] Examples of prompts for generative AI models

[0334] "When a high school sophomore user was studying mathematics, they made many mistakes in a specific area. Therefore, additional problems are generated to strengthen that area, and these are reflected in the dashboard."

[0335] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0336] This invention is an educational support system designed to ensure that users have equal learning opportunities regardless of income, location, or personal disadvantages. The system supports effective learning by providing individualized support based on the user's learning needs, managing learning progress, and offering feedback. Furthermore, the invention incorporates an emotion engine that recognizes the user's emotions and provides feedback and adjustments accordingly.

[0337] System Configuration

[0338] This system has the following main functions:

[0339] 1. Means of obtaining information entered by the user

[0340] 2. Generating a learning profile

[0341] 3. Automatic generation and provision of learning programs

[0342] 4. Recording and analyzing learning progress

[0343] 5. Feedback and suggestions for additional learning content

[0344] 6. Designation of qualification examinations and curriculum development

[0345] 7. Implementation and analysis of mock exams

[0346] 8. Emotion engine that recognizes user emotions

[0347] 9. Adjusting learning content using emotional data

[0348] Specific operation of the system

[0349] User registration and information retrieval

[0350] The terminal displays a form for first-time users to enter their name, age, grade level, and desired subjects.

[0351] The user enters this information and presses the register button.

[0352] The server receives the entered information, stores it in the database, and generates a user ID and password.

[0353] Generating a learning profile

[0354] The server generates a learning profile based on the registered user information. For example, a profile might be created stating, "I want to improve my math skills as a second-year high school student."

[0355] Automatic generation and provision of learning programs

[0356] The server automatically generates a customized learning program based on the generated learning profile and displays it on the user's dashboard.

[0357] The device allows the user to access the learning program from the dashboard and begin learning.

[0358] Recording and analyzing learning progress

[0359] Once a user begins learning, the device records the user's progress (e.g., answer results, learning time, etc.).

[0360] The server receives the recorded learning progress data and analyzes it. For example, it might identify that the user makes many mistakes on trigonometry problems.

[0361] Feedback and suggestions for additional learning content

[0362] The server optimizes the next learning objectives based on the analysis results and provides feedback to the user.

[0363] The device displays information that allows the user to receive feedback and suggests additional learning content.

[0364] Designation of qualification exams and curriculum generation

[0365] If a user wants to take a specific certification exam, they specify that exam in the system.

[0366] The server generates a curriculum corresponding to the specified certification exam and adds it to the user's dashboard.

[0367] Implementation and analysis of mock exams

[0368] The device allows the user to start the practice exam and manages the exam time.

[0369] Users take a practice test and submit their answers.

[0370] The server analyzes the results of the practice test and suggests additional learning content for areas that require particular improvement.

[0371] Using an Emotion Engine

[0372] The device uses user input information and behavioral data (facial expressions, voice, etc.) to send data to the emotion engine.

[0373] The server uses an emotion engine to recognize the user's emotions and stores the results.

[0374] The server adjusts the content of the learning program and the feedback based on the recognized emotion data. For example, if the user is feeling stressed, it will suggest a break to help them relax.

[0375] The device displays emotion-based learning content and feedback to the user.

[0376] Specific example

[0377] For example, if a 15-year-old high school sophomore wants to improve their math skills and experiences stress while learning, the system will work as follows:

[0378] 1. The user enters and submits user information on the terminal, and the server generates a profile.

[0379] 2. The server automatically generates math materials and practice problems for second-year high school students and displays them on the user's dashboard.

[0380] 3. The user begins learning, and the device records their progress and emotional data.

[0381] 4. The server analyzes progress data and emotional data, and if it determines, for example, that the user is feeling stressed, it suggests additional problems to strengthen that area, along with a break to help them relax.

[0382] 5. The server reflects the generated additional learning materials and break times on the dashboard.

[0383] 6. The user reviews the feedback and sets the next learning objectives.

[0384] With the above configuration and operation, this system can continuously provide optimal content according to the user's learning needs and emotional state.

[0385] The following describes the processing flow.

[0386] Step 1:

[0387] The device displays a registration form for users to enter their name, age, grade level, and desired subjects when they first access the system.

[0388] Step 2:

[0389] The user enters the required information into the registration form and clicks "Register".

[0390] Step 3:

[0391] The terminal sends the entered information to the server.

[0392] Step 4:

[0393] The server receives the transmitted information and stores it in the database.

[0394] Step 5:

[0395] The server generates a user ID and password and sends them to the terminal.

[0396] Step 6:

[0397] The device displays the user ID and password and redirects the user to the dashboard screen.

[0398] Step 7:

[0399] The server generates a learning profile based on registered user information. Example: "High school sophomore," "Want to improve math skills."

[0400] Step 8:

[0401] The server automatically generates a customized learning program based on the user's learning profile and displays it on the user's dashboard.

[0402] Step 9:

[0403] The device allows the user to access the learning program from the dashboard and begin learning.

[0404] Step 10:

[0405] Once a user begins learning, the device records the user's progress (answers, study time, etc.).

[0406] Step 11:

[0407] The device transmits recorded progress data, along with the user's facial expressions and voice data, to the server.

[0408] Step 12:

[0409] The server receives progress data and sentiment data analyzed by the sentiment engine, and then analyzes that data. For example, it might identify that the user is making many mistakes on trigonometry problems or that they are feeling stressed.

[0410] Step 13:

[0411] The server optimizes the next learning session based on the analysis results and generates additional supplementary materials and practice problems. It also generates relaxation suggestions and motivational messages based on emotional data.

[0412] Step 14:

[0413] The server displays the generated additional learning materials, practice problems, and suggested breaks and messages on the user's dashboard.

[0414] Step 15:

[0415] The device notifies the user of updated learning programs, suggested breaks, and messages, and displays them as feedback.

[0416] Step 16:

[0417] The user reviews the feedback and sets their next learning goals.

[0418] Step 17:

[0419] If a user wants to take a certification exam, the device provides a form for them to enter their exam information.

[0420] Step 18:

[0421] The user enters the desired qualification exam (e.g., "TOEIC") and submits it.

[0422] Step 19:

[0423] The server receives the entered qualification exam information, generates the corresponding curriculum, and adds it to the dashboard.

[0424] Step 20:

[0425] The device is configured to allow users to start a practice test and also provides a time management tool for the test.

[0426] Step 21:

[0427] Users take a practice test and submit their answers.

[0428] Step 22:

[0429] The server analyzes the results of the practice test and evaluates the level of understanding and proficiency in specific areas.

[0430] Step 23:

[0431] Based on the results of the practice test and the user's sentiment data, the server suggests additional learning content for areas where the user needs to improve, and reflects this on the dashboard.

[0432] Step 24:

[0433] The device notifies the user of additional learning content and guides them to proceed to the next learning step.

[0434] Through these steps, the system provides optimal learning support tailored to the user's learning needs and emotional state.

[0435] (Example 2)

[0436] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0437] In modern education systems, there is a challenge in ensuring that users have equal learning opportunities regardless of income, location, or personal disadvantages. Furthermore, there is a need to automatically generate learning programs tailored to each learner's progress and understanding, and to provide appropriate feedback. Additionally, there is a lack of technology to provide flexible learning support that considers learners' emotional states and reduces stress and fatigue.

[0438] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring information input by the user, means for generating a user learning profile based on the acquired information, means for automatically generating and providing a learning program according to the user's learning profile, means for recording the user's learning progress, means for analyzing the recorded learning progress data and optimizing the next learning content, means for suggesting feedback and additional learning content to the user, means for acquiring the user's emotional data, and means for adjusting the learning content based on the acquired emotional data. This makes it possible to provide optimal learning support that is tailored to the individual user's learning needs and emotional state.

[0439] "Means for obtaining user-inputted information" refers to the interface and related technologies used to collect data from users who input information such as their name, age, grade level, and desired subjects of study.

[0440] "Means for generating a user's learning profile based on acquired information" refers to technologies and methods for analyzing and processing acquired user information to create a profile based on individual learning needs.

[0441] "Means for automatically generating and providing learning programs tailored to a user's learning profile" refers to a system and technology for automatically generating optimal learning materials and assignments based on each user's learning profile and providing them to the user.

[0442] "Means for recording user learning progress" refers to technologies and methods for recording progress information such as learning activities performed by the user, answer results, and learning time.

[0443] "Means for analyzing recorded learning progress data and optimizing the next learning content" refers to technologies and methods that analyze recorded learning progress data and optimize the next learning content based on the user's level of understanding and progress.

[0444] "Means for providing users with feedback and suggesting additional learning content" refers to techniques and methods for providing users with appropriate feedback based on analysis results and for suggesting any additional learning content they may need.

[0445] "Means for acquiring user emotional data" refers to technologies and methods for analyzing a user's facial expressions, voice, etc., to recognize their emotional state and collect that emotional data.

[0446] "Means for adjusting learning content based on acquired emotional data" refers to technologies and methods for adjusting learning programs and feedback content based on acquired user emotional data.

[0447] "Means for specifying qualification exams" refers to the interface and related technologies for users to select and specify the qualification exams they wish to take.

[0448] "Means for generating and providing a curriculum corresponding to a specified qualification examination" refers to a system and technology for generating a curriculum corresponding to a qualification examination specified by the user and providing it to the user.

[0449] "Means of conducting a mock exam" refers to the technology and methods for a user to start a mock exam and take the test.

[0450] "Methods for analyzing mock exam results and proposing additional learning content" refers to techniques and methods for analyzing mock exam results and proposing additional learning content, particularly in areas that require strengthening.

[0451] "Means for managing the time of a mock exam" refers to the technology and methods for managing the exam time during a mock exam and notifying the user at the appropriate time.

[0452] This invention is an educational support system designed to ensure that users have equal learning opportunities regardless of income, location, or personal disadvantages. The system supports effective learning by providing individualized support based on the user's learning needs, managing learning progress, and offering feedback. Furthermore, it incorporates an emotion engine to recognize the user's emotions and provide feedback and adjustments accordingly.

[0453] System Configuration

[0454] This system has the following main functions:

[0455] 1. Means of obtaining information entered by the user

[0456] 2. Generating a learning profile

[0457] 3. Automatic generation and provision of learning programs

[0458] 4. Recording and analyzing learning progress

[0459] 5. Feedback and suggestions for additional learning content

[0460] 6. Designation of qualification examinations and curriculum development

[0461] 7. Implementation and analysis of mock exams

[0462] 8. Emotion engine that recognizes user emotions

[0463] 9. Adjusting learning content using emotional data

[0464] Specific operation of the system

[0465] User registration and information retrieval

[0466] The terminal displays a form for first-time users to enter their name, age, grade level, and desired subjects. For example, an HTML form could be used to allow users to input this information.

[0467] The user enters this information and presses the register button.

[0468] The server receives the input information using PHP or Node.js, stores it in a database such as MySQL or PostgreSQL, and generates a user ID and password.

[0469] Generating a learning profile

[0470] The server uses libraries such as Python's scikit-learn and pandas to generate learning profiles based on registered user information. For example, it might generate a profile for someone who says, "I'm a second-year high school student and I want to improve my math skills."

[0471] Automatic generation and provision of learning programs

[0472] The server automatically generates individually customized training programs based on the generated training profiles. This is achieved using a Python generative AI model.

[0473] The device uses front-end frameworks such as React.js or Vue.js to display the generated learning program on the user's dashboard, allowing the user to begin learning.

[0474] Recording and analyzing learning progress

[0475] When a user begins learning, the device uses JavaScript or HTML5's LocalStorage to record the user's progress, such as answer results and learning time, in real time.

[0476] The server receives recorded learning progress data and analyzes it using data analysis tools such as Python or R. For example, it saves data on when a user made a mistake on a particular problem and analyzes the patterns using a machine learning model.

[0477] Feedback and suggestions for additional learning content

[0478] The server uses a machine learning model to generate feedback based on the analysis results. This feedback includes suggestions for improvement and additional learning content for the user.

[0479] The device displays the feedback to the user in real time.

[0480] Designation of qualification exams and curriculum generation

[0481] The user selects the certification they wish to take from a list of certification exams configured within the system.

[0482] The server generates a curriculum corresponding to the selected qualification and adds it to the user's dashboard.

[0483] Implementation and analysis of mock exams

[0484] The device displays an interface for starting the mock exam and also supports time management. It records the progress of the exam in real time.

[0485] Users take a practice test and submit their results to the server.

[0486] The server analyzes the test results, identifies areas for improvement, and proposes revised learning content.

[0487] Using an Emotion Engine

[0488] The device captures the user's facial expressions with its camera and collects audio data. This data is then sent to the emotion engine.

[0489] The server analyzes the user's emotions using an emotion engine and stores the results. For example, it might use Google Cloud Emotion AI.

[0490] The server adjusts the learning program and feedback based on the analysis results. For example, if the user is feeling stressed, it suggests content to help them relax.

[0491] The device displays adjusted feedback and learning content to the user.

[0492] Specific example

[0493] For example, if a 15-year-old high school sophomore wants to improve their math skills and experiences stress while learning, the system will work as follows:

[0494] 1. The user enters and submits user information on the terminal, and the server generates a profile.

[0495] 2. The server automatically generates math materials and practice problems for second-year high school students and displays them on the user's dashboard.

[0496] 3. The user begins learning, and the device records their progress and emotional data.

[0497] 4. The server analyzes progress data and emotional data, and if it determines, for example, that the user is feeling stressed, it suggests additional problems to strengthen that area, along with a break to help them relax.

[0498] 5. The server reflects the generated additional learning materials and break times on the dashboard.

[0499] 6. The user reviews the feedback and sets the next learning objective.

[0500] Example of a prompt

[0501] "A 15-year-old high school sophomore wants to improve their math skills. They are experiencing stress while learning; please generate prompts explaining how the system can help them."

[0502] As described above, the educational support system of the present invention can provide optimal content according to the user's learning needs and emotional state.

[0503] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0504] Step 1:

[0505] The terminal displays a form for first-time users to enter their name, age, grade level, and desired subjects. Once the user enters information into the form, that data is sent to the server using JavaScript (input: user information, output: sent data).

[0506] Step 2:

[0507] The server stores the received user information in a database and generates a user ID and password. For example, you can access the database and save the information using PHP or Node.js (input: user information, output: user ID and password).

[0508] Step 3:

[0509] The server uses Python libraries such as scikit-learn and pandas to generate learning profiles based on registered user information. This uses data such as the user's grade level and the subjects they want to strengthen (input: user information, output: learning profile).

[0510] Step 4:

[0511] The server automatically generates individually customized learning programs based on the generated learning profiles. Here, a generative AI model (e.g., GPT-3®) is used to generate learning plans and learning materials (input: learning profile, output: learning program).

[0512] Step 5:

[0513] The terminal displays the generated learning program on the user's dashboard, allowing the user to begin learning. Frontend frameworks such as React.js and Vue.js are used (input: learning program, output: dashboard display).

[0514] Step 6:

[0515] When a user begins learning, the device uses JavaScript or HTML5's LocalStorage to record the user's progress in real time, including their answers and learning time (input: user's learning activity, output: progress data).

[0516] Step 7:

[0517] The server receives recorded learning progress data and analyzes it using data analysis tools such as Python or R. For example, it can analyze if a user repeatedly makes mistakes on a particular problem (input: progress data, output: analysis results).

[0518] Step 8:

[0519] The server uses a machine learning model to generate feedback based on the analysis results. This feedback includes points to check and areas for improvement (input: analysis results, output: feedback).

[0520] Step 9:

[0521] The device displays the feedback content to the user in real time (input: feedback, output: feedback display).

[0522] Step 10:

[0523] The user selects the qualification they wish to take from a list of qualification exams within the system (Input: Selection of qualification exam, Output: Specified qualification exam).

[0524] Step 11:

[0525] The server generates a curriculum corresponding to the selected qualification and adds it to the user's dashboard (input: specified qualification exam, output: curriculum).

[0526] Step 12:

[0527] The terminal displays an interface for starting the mock exam and manages the exam progress and time in real time (input: start of mock exam, output: progress of mock exam).

[0528] Step 13:

[0529] Users take a practice test and submit their results to the server (input: practice test answers, output: practice test results).

[0530] Step 14:

[0531] The server analyzes the results of the mock exam and suggests additional learning content for areas that need improvement (Input: Mock exam results, Output: Suggested additional learning content).

[0532] Step 15:

[0533] The device captures the user's facial expressions with its camera and collects audio data. This data is then sent to the emotion engine (input: facial expressions and audio data, output: emotion data).

[0534] Step 16:

[0535] The server uses an emotion engine to analyze the user's emotions and stores the results in a database (input: emotion data, output: analysis results).

[0536] Step 17:

[0537] The server adjusts the learning program and feedback based on the acquired emotional data. If stress is detected, it suggests content to help the user relax (input: analysis results, output: adjusted learning program and feedback).

[0538] Step 18:

[0539] The device displays the user with adjusted feedback and learning content (input: adjusted learning program and feedback, output: feedback display).

[0540] (Application Example 2)

[0541] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0542] Traditional learning support systems have the drawback of not maximizing learning effectiveness because they provide uniform learning programs and feedback without considering the learner's emotional state. Furthermore, there was no way to determine in real time how much stress or fatigue a learner was experiencing with each subject. These challenges made it difficult to provide optimal learning support based on the individual characteristics and emotional state of each learner.

[0543] The specific processing performed 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 means for acquiring information input by the user, means for generating a user learning profile based on the acquired information, means for automatically generating and providing a learning program according to the user's learning profile, means for recording the user's learning progress, means for analyzing the recorded learning progress data and optimizing the next learning content, means for suggesting feedback and additional learning content to the user, means for recognizing the user's emotions, and means for adjusting the learning content using the recognized emotion data. This makes it possible to grasp the learner's emotional state in real time and flexibly adjust the learning program and feedback based on that.

[0544] "User information acquisition method" refers to a means of acquiring basic information such as the learner's name, age, grade level, and desired subjects to study.

[0545] A "learning profile generation means" is a means for generating an optimal learning profile for each individual learner based on acquired user information.

[0546] A "learning program generation means" is a means for automatically generating and providing a learning program that is individually customized according to the generated learning profile.

[0547] A "learning progress recording device" is a means of recording a learner's learning activities and progress.

[0548] A "learning progress analysis tool" is a means of analyzing recorded learning progress data to optimize the content of the next learning session.

[0549] A "feedback suggestion method" is a means of providing learners with feedback on the next learning steps or areas for improvement based on the analysis results.

[0550] "Means of emotional recognition" are means of recognizing a learner's emotional state from their facial expressions, voice, etc.

[0551] "Emotional data adjustment means" refers to a means of adjusting learning content and feedback using recognized emotional data.

[0552] A "means of designating a qualification examination" refers to a means by which learners can designate a specific qualification examination.

[0553] A "curriculum generation method" is a means for generating and providing a curriculum corresponding to a designated qualification examination.

[0554] "Methods for conducting mock examinations" refers to the means for conducting mock examinations and recording and analyzing the results.

[0555] "Time management methods" refer to the means by which learners manage the time they spend taking practice exams.

[0556] The system that realizes this invention generates a user's learning profile, provides a customized learning program, and optimizes the learning experience by utilizing emotion recognition. The system mainly consists of the following elements:

[0557] 1. Obtaining user information

[0558] Users enter basic information such as their name, age, grade level, and desired subjects using their smartphones or tablets. The device retrieves this information and sends it to a cloud server. This information is stored in a database on the server (e.g., MySQL, MongoDB, etc.).

[0559] 2. Generating a learning profile

[0560] The server generates a learning profile based on the acquired user information. This profile reflects specific learning needs, such as "I want to improve my math skills as a second-year high school student." A user ID and password are also generated using Python or the Django framework.

[0561] 3. Automatic generation and provision of learning programs

[0562] The server automatically generates a customized learning program based on the generated learning profile. This learning program is reflected in the user's dashboard, and the user can access it to begin learning. Custom algorithms and generative AI models can be used to create the learning program.

[0563] 4. Recording and analyzing learning progress

[0564] Users progress through the learning process using their devices, and their progress data (such as answer results and learning time) is recorded. The devices send this data to a server, which analyzes it using Python and Pandas. Based on specific problem areas and progress, the server optimizes the next learning content.

[0565] 5. Feedback and suggestions for additional learning content

[0566] Based on the analysis results, the server suggests optimal feedback and additional learning content to the user. This is displayed on the user's dashboard to assist with the next learning steps.

[0567] 6. Optimization through emotion recognition

[0568] The device uses its camera and microphone to capture facial expressions and voice to recognize the user's emotional state. This data is analyzed by an emotion recognition model (e.g., TENSORFLOW®) and the emotional state is sent to a server. The server uses this emotional data to adjust the learning program and provide feedback.

[0569] Specific example

[0570] For example, suppose a 15-year-old high school sophomore is using this system to improve their math skills. The user first enters their name, grade level, and desired subjects via smartphone, and a learning profile is generated based on this information. As the user progresses, the system records and analyzes their progress. Furthermore, if the user is experiencing stress during their studies, an emotion recognition engine identifies this, and the server suggests a break to help them relax.

[0571] Example of a prompt

[0572] The following prompts are used when configuring the emotion recognition engine:

[0573] python

[0574] Import necessary

[0575] import cv2

[0576] import tensorflow as tf

[0577] Load pre-trained model

[0578] model = tf.keras.models.load_model('emotion_recognition_model.h5')

[0579] Capture video from webcam

[0580] cap = cv2.VideoCapture(0)

[0581] while True:

[0582] ret, frame = cap.read()

[0583] if not ret:

[0584] break

[0585] Process frame for emotion recognition

[0586] gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

[0587] face = cv2.resize(gray, (48, 48))

[0588] face = face.reshape(1, 48, 48, 1) / 255.0

[0589] Predict emotion

[0590] emotion = model.predict(face)

[0591] print(f"Detected emotion: {emotion}")

[0592] Display the frame

[0593] cv2.imshow('Emotion Recognition', frame)

[0594] if cv2.waitKey(1) & 0xFF == ord('q'):

[0595] break

[0596] cap.release()

[0597] cv2.destroyAllWindows()

[0598] In this way, a learning support system that combines emotion recognition can provide individualized and flexible support to learners.

[0599] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0600] Step 1:

[0601] Users enter basic information such as their name, age, grade level, and desired subjects using their smartphones or tablets. This information is then sent from the device to a cloud server. The server stores the received information in a database (e.g., MySQL, MongoDB). The input is the user's basic information, and the output is the storage of user information on the cloud server.

[0602] Step 2:

[0603] The server generates a learning profile based on stored user information. This learning profile includes details such as the student's grade level and subject level. This allows for the creation of a specific profile, such as "I'm a second-year high school student and I want to improve my math skills." The input is the user's basic information, and the output is the generated learning profile.

[0604] Step 3:

[0605] The server automatically generates a customized learning program based on the generated learning profile. During this process, it creates optimal learning content using custom algorithms and generative AI models. The generated learning program is reflected in the user's dashboard. The input is the learning profile, and the output is the customized learning program.

[0606] Step 4:

[0607] Users access the learning program from the dashboard and proceed with their studies. The device records the user's learning progress data (e.g., answer results, study time) and sends it to the cloud server. The server receives this data and stores it in a database. The input is the user's learning progress data, and the output is the transmission and storage of data to the server.

[0608] Step 5:

[0609] The server analyzes the recorded learning progress data using Python or Pandas. This analysis identifies specific problem areas and areas of progress for the user. For example, it identifies areas where many incorrect answers are observed. The input is the recorded learning progress data, and the output is the analysis results.

[0610] Step 6:

[0611] Based on the analysis results, the server suggests optimal feedback and additional learning content to the user. This content is displayed on the user's dashboard. The input is the analysis results, and the output is the feedback and additional learning content.

[0612] Step 7:

[0613] The device uses its camera and microphone to capture facial expressions and voice to recognize the user's emotional state. The captured data is analyzed by an emotion recognition model (e.g., TensorFlow) to identify the emotional state. The input is facial expression and voice data, and the output is recognized emotion data.

[0614] Step 8:

[0615] The server adjusts its learning content and feedback based on the recognized emotion data. For example, if the user is feeling stressed, it suggests taking a break to relax. The input is the recognized emotion data, and the output is the adjusted learning content and feedback.

[0616] Step 9:

[0617] The user reviews feedback and adjusted learning content from their device and sets the next learning step. This makes learning more effective. The input is the adjusted learning content and feedback, and the output is the setting of the next learning step.

[0618] The above describes the specific processing flow of the system that realizes this invention.

[0619] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0620] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0621] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0622] [Second Embodiment]

[0623] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0624] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0625] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0626] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0627] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0628] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0629] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0630] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0631] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0632] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0633] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0634] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0635] This invention is an educational support system designed to ensure that users have equal learning opportunities regardless of income, location, or personal disadvantages. The system supports effective learning by providing individualized support based on the user's learning needs, managing learning progress, and offering feedback.

[0636] System Configuration

[0637] This system has the following main functions:

[0638] 1. Means of obtaining information entered by the user

[0639] 2. Generating a learning profile

[0640] 3. Automatic generation and provision of learning programs

[0641] 4. Recording and analyzing learning progress

[0642] 5. Feedback and suggestions for additional learning content

[0643] 6. Designation of qualification examinations and curriculum development

[0644] 7. Implementation and analysis of mock exams

[0645] Specific operation of the system

[0646] User registration and information retrieval

[0647] The terminal displays a form for first-time users to enter their name, age, grade level, and desired subjects.

[0648] The user enters this information and presses the register button.

[0649] The server receives the entered information, stores it in the database, and generates a user ID and password.

[0650] Generating a learning profile

[0651] The server generates a learning profile based on the registered user information. For example, a profile might be created for a second-year high school student who wants to improve their math skills.

[0652] Automatic generation and provision of learning programs

[0653] The server automatically generates a customized learning program based on the generated learning profile and displays it on the user's dashboard.

[0654] The device allows users to access the learning program from the dashboard and begin learning.

[0655] Recording and analyzing learning progress

[0656] As the user progresses through the learning process, the device records the user's progress.

[0657] The server receives the recorded learning progress data and analyzes it. For example, it might identify that the user makes many mistakes on trigonometry problems.

[0658] Feedback and suggestions for additional learning content

[0659] The server optimizes the next learning objectives based on the analysis results and provides feedback to the user.

[0660] The device displays information that allows the user to receive feedback and suggests additional learning content.

[0661] Designation of qualification exams and curriculum generation

[0662] If a user wants to take a specific certification exam, they specify that exam in the system.

[0663] The server generates a curriculum corresponding to the specified certification exam and adds it to the user's dashboard.

[0664] Implementation and analysis of mock exams

[0665] The device allows the user to start the practice exam and manages the exam time.

[0666] Users take a practice test and submit their answers.

[0667] The server analyzes the results of the practice test and suggests additional learning content for areas that require particular improvement.

[0668] Specific example

[0669] For example, if a user is a 15-year-old high school sophomore and wants to improve their math skills, the system will work as follows:

[0670] 1. The user enters and submits user information on the terminal, and the server generates a profile.

[0671] 2. The server automatically generates math materials and practice problems for second-year high school students and displays them on the user's dashboard.

[0672] 3. The user begins learning, and the device records their progress.

[0673] 4. The server analyzes the progress data and, for example, if it determines that there is a lack of understanding of trigonometry, it generates additional problems to strengthen that area and adds them to the dashboard.

[0674] 5. The user solves additional problems, the results are further analyzed, and appropriate feedback and suggestions for the next learning activities are provided.

[0675] With the above configuration and operation, this system can provide learning support tailored to the individual needs of users, thereby improving the efficiency and effectiveness of learning.

[0676] The following describes the processing flow.

[0677] Step 1:

[0678] When a user accesses the system for the first time, the device displays a registration form for them to enter their name, age, grade level, and desired subjects.

[0679] Step 2:

[0680] The user fills in the required information on the form and clicks "Register".

[0681] Step 3:

[0682] The terminal sends the entered information to the server.

[0683] Step 4:

[0684] The server receives the transmitted information and stores it in the database.

[0685] Step 5:

[0686] The server generates a user ID and password and sends them to the user.

[0687] Step 6:

[0688] The device displays the user ID and password and redirects the user to the dashboard screen.

[0689] Step 7:

[0690] The server generates a learning profile based on user profile information. For example, this includes information such as "high school sophomore" and "desire to improve math skills."

[0691] Step 8:

[0692] The server automatically generates a customized learning program based on the user's learning profile and displays it on the user's dashboard.

[0693] Step 9:

[0694] The device allows the user to access the learning program from the dashboard and begin learning.

[0695] Step 10:

[0696] Once a user begins learning, the device records the user's progress (e.g., answer results, learning time, etc.).

[0697] Step 11:

[0698] The terminal sends the recorded progress data to the server.

[0699] Step 12:

[0700] The server analyzes progress data and identifies areas where the user should focus their efforts. For example, it might extract data such as "there are many mistakes in trigonometry problems."

[0701] Step 13:

[0702] Based on the analysis results, the server optimizes the content for the next lesson and generates additional supplementary materials and practice problems.

[0703] Step 14:

[0704] The server displays the generated additional learning materials and practice problems on the user's dashboard.

[0705] Step 15:

[0706] The device notifies the user of updated learning programs and displays them as feedback.

[0707] Step 16:

[0708] The user reviews the feedback and sets their next learning goals.

[0709] Step 17:

[0710] If a user wishes to take a certification exam, the device provides a form for entering exam information.

[0711] Step 18:

[0712] The user enters the desired qualification exam (e.g., "TOEIC") and submits it.

[0713] Step 19:

[0714] The server receives the entered qualification exam information, generates the corresponding curriculum, and adds it to the dashboard.

[0715] Step 20:

[0716] The device is configured to allow the user to start a practice exam and provides time management tools for the exam.

[0717] Step 21:

[0718] Users take a practice test and submit their answers.

[0719] Step 22:

[0720] The server analyzes the results of the practice test and evaluates the level of understanding and proficiency in specific areas.

[0721] Step 23:

[0722] Based on the results of the practice test, the server suggests additional learning content for areas where the user needs to improve, and reflects this on the dashboard.

[0723] Step 24:

[0724] The device notifies the user of additional learning content and guides them to proceed to the next learning step.

[0725] By following these steps, the system can continuously provide the most suitable content for the user's learning needs and progress.

[0726] (Example 1)

[0727] Next, we will describe Example 1. 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".

[0728] Modern education systems struggle to meet the individual learning needs of users, particularly due to unequal access to learning opportunities caused by income, location, and personal disadvantages. Furthermore, traditional learning systems often fail to effectively track learning progress and provide feedback, making it difficult to offer optimal learning programs for individual users. As a result, users are unable to learn efficiently and achieve their goals.

[0729] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0730] In this invention, the server includes means for acquiring information entered by the user, means for generating a user learning profile based on the acquired information, means for automatically generating and providing a learning program according to the user's learning profile, means for recording the user's learning progress, means for analyzing the recorded learning progress data and optimizing the next learning content, means for suggesting feedback and additional learning content to the user, means for storing user information and learning progress data in a database, means for reflecting the learning program and feedback on the user's dashboard, means for the user to take a mock exam and submit the results, and means for analyzing the results of the mock exam and suggesting improvements in specific areas. This enables users to learn fairly and efficiently and provides optimal educational support tailored to each individual's learning needs.

[0731] "Means of acquiring user-inputted information" refers to devices and software that collect and store information that users input into the system, such as their name, age, grade level, and subjects they wish to study.

[0732] "Means for generating a user's learning profile based on acquired information" refers to algorithms and programs that create a learning profile that reflects the individual user's learning needs and goals, based on the information provided by the user.

[0733] "Means for automatically generating and providing learning programs tailored to a user's learning profile" refers to a system that automatically creates and provides optimal learning content and activities to the user based on the generated learning profile.

[0734] "Means for recording user learning progress" refers to devices or programs that have the function of continuously recording the progress and answer results achieved by a user during the learning process.

[0735] "Means for analyzing recorded learning progress data and optimizing the next learning content" refers to algorithms and programs that analyze collected learning progress data to understand the user's level of comprehension and weaknesses, and determine the optimal content for the next learning session.

[0736] "Means of providing users with feedback and suggesting additional learning content" refers to devices or software that have the functionality to provide users with specific feedback based on analyzed learning progress data and to suggest any additional learning content they may need.

[0737] "Means for storing user information and learning progress data in a database" refers to a system that records user-entered information and learning progress data in a database and manages it so that it can be referenced later as needed.

[0738] "Means of reflecting learning programs and feedback on the user's dashboard" refers to a system that has an interface on the dashboard that allows users to see their learning progress and feedback at a glance.

[0739] "Means for users to take a practice test and submit the results" refers to devices or programs that have the function of allowing users to take a practice test and submit the results to a system.

[0740] "Methods for analyzing mock exam results and suggesting improvements in specific areas" refers to algorithms or programs that scrutinize the results of mock exams taken by users, identify specific areas that need improvement, and suggest additional learning content for those areas.

[0741] This invention is an educational support system designed to ensure that users have equal learning opportunities regardless of income, location, or personal disadvantages. The system has the following main functions:

[0742] User registration and information retrieval

[0743] The terminal displays a form for new users to enter information such as their name, age, grade level, and desired subjects. This form is accessed via a web browser or a dedicated application.

[0744] The user enters the required information and presses the "Register" button to submit the information.

[0745] The server receives the transmitted information and stores it in a database (such as MySQL or PostgreSQL). It also generates a user ID and initial password and notifies the user.

[0746] Generating a learning profile

[0747] The server generates a learning profile based on registered user information. This profile reflects the user's learning needs and goals.

[0748] For example, you can generate a profile using machine learning techniques with Python libraries (pandas, scikit-learn).

[0749] Automatic generation and provision of learning programs

[0750] The server automatically generates a customized learning program based on the generated profile. This program consists of appropriate learning materials and problem sets.

[0751] The server displays programs generated using a template engine (such as Jinja2) on the user's dashboard.

[0752] The device allows users to access the dashboard, view the learning program, and begin.

[0753] Recording and analyzing learning progress

[0754] As the user progresses through the learning process, the device records their progress in real time (e.g., answer status and accuracy rate). This record is temporarily saved using HTML5 local storage and JavaScript.

[0755] The device periodically sends this progress data to the server.

[0756] The server receives progress data and analyzes it using Python's pandas and numpy. For example, if a user makes many mistakes in a particular area (e.g., trigonometry), the server identifies that area.

[0757] Feedback and suggestions for additional learning content

[0758] The server optimizes the next learning content based on the analysis of progress data. This includes additional problems and materials to strengthen the user's weaknesses.

[0759] The device displays feedback and suggested additional learning content on the user's dashboard.

[0760] Designation of qualification exams and curriculum generation

[0761] If a user wants to take a specific certification exam (e.g., TOEIC), they specify that exam in the system.

[0762] The server generates a curriculum corresponding to the specified certification exam and provides it to the user's dashboard.

[0763] Implementation and analysis of mock exams

[0764] The device allows the user to start a practice test and manages the test time using a JavaScript timer function.

[0765] After taking a practice test, the user submits their answers.

[0766] The server analyzes the results and suggests additional learning content, particularly in areas that need strengthening.

[0767] Examples and prompts for generative AI models

[0768] For example, if a 15-year-old high school sophomore wants to improve their math skills, it would work as follows:

[0769] The user enters their information on the terminal, and the server generates a profile.

[0770] The server generates math materials and practice problems for second-year high school students and displays them on the user's dashboard.

[0771] The user begins learning, and the device records the learning progress and sends it to the server.

[0772] The server analyzes the progress data and, for example, if it determines that there is a lack of understanding of trigonometry, it generates additional problems and adds them to the dashboard.

[0773] The user solves additional problems, the results are analyzed, and the next learning objectives are suggested.

[0774] Examples of prompts for a generative AI model:

[0775] "I have a 15-year-old high school sophomore who wants to improve his math skills. Please create a customized learning program for him based on his current learning progress, with a particular focus on trigonometry."

[0776] In this way, the system provides comprehensive learning support tailored to the individual needs of users, thereby improving the efficiency and outcomes of their learning.

[0777] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0778] Step 1:

[0779] User registration and information retrieval

[0780] The device displays a form for the user to enter information such as their name, age, grade level, and the subjects they wish to study.

[0781] Input: User information (name, age, grade level, subject you want to study)

[0782] Output: Information entered by the user

[0783] The user enters the required information and presses the "Register" button to submit the information.

[0784] Input: User actions

[0785] Output: Sent user information

[0786] The server receives the transmitted user information and stores it in the database.

[0787] Input: Submitted user information

[0788] Data processing: Converting user information into a database format.

[0789] Output: User information stored in the database

[0790] The server generates a user ID and initial password and notifies the user.

[0791] Input: Saved user information

[0792] Data calculation: Generation of user ID and initial password

[0793] Output: User ID and initial password

[0794] Step 2:

[0795] Generating a learning profile

[0796] The server generates a learning profile based on the registered user information.

[0797] Input: User information stored in the database

[0798] Data processing: Generate profiles based on learning needs and grade level (e.g., using Python libraries pandas and scikit-learn).

[0799] Output: Generation of training profile

[0800] The server saves the generated profile to the database.

[0801] Input: Generated training profile

[0802] Data processing: Convert profile to database format

[0803] Output: Learning profiles stored in the database

[0804] Step 3:

[0805] Automatic generation and provision of learning programs

[0806] The server automatically generates a customized learning program based on the generated learning profile.

[0807] Input: Learning Profile

[0808] Data processing: Select appropriate teaching materials and problem sets, and design a learning program (using the Jinja2 template engine).

[0809] Output: Customized learning program

[0810] The server displays the generated learning program on the user's dashboard.

[0811] Input: Customized learning program

[0812] Output: The program reflected in the user's dashboard.

[0813] The device allows users to access the dashboard, view their learning programs, and begin.

[0814] Input: User actions

[0815] Output: Learning program displayed to the user

[0816] Step 4:

[0817] Recording and analyzing learning progress

[0818] As the user progresses through the learning process, the device records their progress in real time.

[0819] Input: User's learning activity data (answer results, progress)

[0820] Data processing: Save to local storage in real time.

[0821] Output: Recorded progress

[0822] The device periodically sends progress data to the server.

[0823] Input: Progress data stored in local storage

[0824] Output: Progress data sent to the server

[0825] The server receives and analyzes the progress data.

[0826] Input: Submitted progress data

[0827] Data processing: Analysis using data analysis tools (pandas, numpy).

[0828] Output: Analysis results (e.g., identification of weaknesses in a specific field)

[0829] Step 5:

[0830] Feedback and suggestions for additional learning content

[0831] The server optimizes the next learning steps based on the analysis results of the progress data.

[0832] Input: Analysis results of progress data

[0833] Data processing: Generating feedback content and additional learning content.

[0834] Output: Next learning content

[0835] The device displays feedback and additional learning content on the user's dashboard.

[0836] Input: Generated feedback content and additional learning content

[0837] Output: Feedback and additional learning content displayed on the dashboard

[0838] Step 6:

[0839] Designation of qualification exams and curriculum generation

[0840] If a user wants to take a specific certification exam, they specify that exam in the system.

[0841] Input: Specified information for the qualification exam

[0842] Output: Qualification exam information set in the system

[0843] The server generates a curriculum corresponding to the specified certification exam and provides it to the user's dashboard.

[0844] Input: Specified information for the qualification exam

[0845] Data processing: Automatic generation of curriculum

[0846] Output: Curriculum added to the user's dashboard

[0847] Step 7:

[0848] Implementation and analysis of mock exams

[0849] The device allows the user to start the practice exam and manages the exam time.

[0850] Input: User action (start of mock exam)

[0851] Data calculation: Using JavaScript's timer function

[0852] Output: Start of mock exam and time management

[0853] Users take a practice test and submit their answers.

[0854] Input: User's answer

[0855] Output: Submitted answer data

[0856] The server analyzes the results of the practice test and suggests additional learning content for areas that require particular improvement.

[0857] Input: Submitted answer data

[0858] Data processing: Analysis of answer data

[0859] Output: Suggestions for strengthening specific areas and additional learning content

[0860] (Application Example 1)

[0861] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0862] Traditional education systems failed to adequately address users' diverse learning needs, lacking sufficient feedback based on learning progress and insufficient suggestions for optimal additional learning content. Furthermore, the provision of learning materials and progress management were not centralized, and there were challenges in conducting mock exams and effectively addressing weaknesses based on the results. Additionally, the lack of immediate feedback and suggestions for additional learning content prevented users from learning efficiently.

[0863] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0864] In this invention, the server includes means for acquiring information entered by the user, means for generating a user learning profile based on the acquired information, means for automatically generating and providing a learning program according to the user's learning profile, means for recording the user's learning progress, means for analyzing the recorded learning progress data and optimizing the next learning content, means for suggesting feedback and additional learning content to the user, means for providing learning materials and online courses from a virtual store, means for generating a customized learning program based on purchased materials, means for analyzing the results of mock exams and suggesting a curriculum to reinforce weaknesses, and means for allowing the user to view their learning progress and feedback. As a result, the user can receive an optimal learning program tailored to their individual learning needs, easily acquire a variety of learning materials through the virtual store, and manage and improve their learning progress more efficiently and effectively.

[0865] "Means for obtaining user input" refers to an interface that allows users to input information such as their name, age, grade level, and subjects they wish to study, and then transmit this information to the system.

[0866] "Means for generating a user's learning profile based on acquired information" refers to a system that analyzes the acquired personal information of a user and creates a profile that takes into account the user's learning needs.

[0867] "A means of automatically generating and providing a learning program tailored to the user's learning profile" refers to a system that automatically creates an individualized learning plan based on the learning profile and provides it to the user.

[0868] A "means for recording user learning progress" refers to a system that records progress data such as how far a user has progressed during their learning and which tasks have been completed.

[0869] "A means of analyzing recorded learning progress data and optimizing the next learning content" refers to a system that analyzes collected learning progress data and adjusts the content to be learned next according to the user's level of understanding and weaknesses.

[0870] A "means of providing users with feedback and suggesting additional learning content" is a system that provides users with feedback based on their progress data, indicating which parts they understand and which parts they need to improve, and then suggests the necessary additional learning content.

[0871] "A means of providing learning materials and online courses from a virtual store" refers to a system that allows users to purchase and access various learning materials and online courses through an online store.

[0872] "A means of generating a customized learning program based on purchased learning materials" refers to a system that individually creates an optimal learning plan using the learning materials purchased by the user in a virtual store.

[0873] "A method for analyzing mock exam results and proposing a curriculum to strengthen weaknesses" refers to a system that thoroughly analyzes the results of mock exams taken by users, identifies their weaknesses, and then provides an additional curriculum to strengthen those weaknesses.

[0874] "Means for users to view their learning progress and feedback" refers to the interface that users use to check their learning progress and feedback from the system.

[0875] This invention is an educational support system for acquiring information entered by a user and generating, providing, and managing individualized learning programs based on that information. This system supports efficient learning by recording and analyzing the user's learning progress and optimizing the next learning content.

[0876] System Configuration

[0877] 1. User registration and information acquisition

[0878] When a user accesses the server for the first time, it displays a personal information input form on the user's device. The user enters information such as their name, age, grade level, and desired subjects, and submits the form. The server stores the received information in a database and generates a user ID and password.

[0879] 2. Generating a learning profile

[0880] The server generates individual learning profiles for each user based on the registered user information. For example, a profile might be created that indicates a high level of motivation to learn a particular subject.

[0881] 3. Automatic generation and provision of learning programs

[0882] The server automatically generates a personalized learning program based on the generated learning profile and displays it on the user's dashboard. The user accesses the learning program through their device and begins learning.

[0883] 4. Recording and analyzing learning progress

[0884] As the user progresses through the learning process, the device records the user's progress. The server receives the recorded learning progress data and analyzes it. For example, if a user makes many incorrect answers in a particular area, that data will be extracted.

[0885] 5. Feedback and suggestions for additional learning content

[0886] The server optimizes the next learning content based on the analysis results and provides feedback to the user. The terminal displays the feedback to the user and suggests additional learning content.

[0887] 6. Provision of educational materials from virtual stores

[0888] The server provides users with learning materials and online courses tailored to their needs through a virtual store. Users can purchase these within the app and incorporate them into their learning programs.

[0889] 7. Generating a customized learning program

[0890] The server generates a customized learning program based on the purchased learning materials and provides it to the user.

[0891] 8. Analysis of mock exam results and strengthening of weak points

[0892] The server receives the results of the mock exam and analyzes them in detail. Based on this, it identifies the user's weaknesses and proposes a curriculum to strengthen those weaknesses.

[0893] 9. View learning progress and feedback

[0894] Users can view their learning progress and feedback from the system through their device.

[0895] Specific example

[0896] For example, if a high school sophomore user wants to improve their math skills, the system will work as follows:

[0897] 1. The user enters and submits personal information on their device. The server generates a learning profile.

[0898] 2. The server automatically generates math materials and practice problems for second-year high school students and displays them on the user's dashboard.

[0899] 3. The user purchases learning materials and proceeds with their studies. The device records their progress.

[0900] 4. The server analyzes the progress data and identifies areas where understanding is particularly lacking. For example, if mastery of trigonometry is insufficient, it generates additional problems to reinforce that area and adds them to the dashboard.

[0901] 5. The user solves additional problems, the results are analyzed, and appropriate feedback and suggestions for the next learning activities are provided.

[0902] Examples of prompts for generative AI models

[0903] "When a high school sophomore user was studying mathematics, they made many mistakes in a specific area. Therefore, additional problems are generated to strengthen that area, and these are reflected in the dashboard."

[0904] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0905] Step 1:

[0906] When a user accesses the server for the first time, it displays a personal information input form on the terminal. The user enters information such as their name, age, grade level, and desired subjects, and submits the form. This input information is sent from the terminal to the server. The server stores the received information in a database and generates a user ID and password.

[0907] Step 2:

[0908] The server generates individual learning profiles for each user based on the registered user information. These profiles include the user's age, grade level, and areas of interest. The generated profiles are stored in a database.

[0909] Step 3:

[0910] The server automatically generates a personalized learning program based on the generated learning profile. This program includes learning materials and practice exercises tailored to the user's grade level and interests. This learning program is reflected in the user's dashboard and provided to the user through their device.

[0911] Step 4:

[0912] The user accesses the learning program provided through the device and begins learning. The device records the user's learning progress in real time and sends this data to the server. The recorded progress data includes completed assignments and the accuracy of answers.

[0913] Step 5:

[0914] The server performs data analysis based on recorded learning progress data. The analysis identifies areas where the user frequently makes mistakes or where their understanding is lacking. The analysis results are stored in a database.

[0915] Step 6:

[0916] The server executes an algorithm to optimize the next learning content based on the analysis results. For example, if there is a lack of understanding in a particular area, it generates additional problems or learning materials related to that area. The generated learning content is added to the user's dashboard.

[0917] Step 7:

[0918] The device displays an interface that allows the user to view newly suggested learning content and feedback. The user then continues learning based on this information, and their progress is recorded and analyzed again.

[0919] Step 8:

[0920] The server provides users with various learning materials and online courses through a virtual store. Users purchase these materials through their devices, and the content is reflected in their learning programs.

[0921] Step 9:

[0922] The server generates a customized learning program based on the purchased learning materials. This generated program is reflected in the user's dashboard and provided as additional learning content.

[0923] Step 10:

[0924] The server analyzes the results of the practice exams taken by the user in detail. Based on the analysis, it identifies areas where the user's understanding is lacking and generates a curriculum to reinforce those weaknesses. This curriculum is also added to the user's dashboard.

[0925] Step 11:

[0926] The device allows users to view their learning progress and system feedback in real time. Users can then refer to this information to learn more efficiently.

[0927] Examples of prompts for generative AI models

[0928] "When a high school sophomore user was studying mathematics, they made many mistakes in a specific area. Therefore, additional problems are generated to strengthen that area, and these are reflected in the dashboard."

[0929] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0930] This invention is an educational support system designed to ensure that users have equal learning opportunities regardless of income, location, or personal disadvantages. The system supports effective learning by providing individualized support based on the user's learning needs, managing learning progress, and offering feedback. Furthermore, the invention incorporates an emotion engine that recognizes the user's emotions and provides feedback and adjustments accordingly.

[0931] System Configuration

[0932] This system has the following main functions:

[0933] 1. Means of obtaining information entered by the user

[0934] 2. Generating a learning profile

[0935] 3. Automatic generation and provision of learning programs

[0936] 4. Recording and analyzing learning progress

[0937] 5. Feedback and suggestions for additional learning content

[0938] 6. Designation of qualification examinations and curriculum development

[0939] 7. Implementation and analysis of mock exams

[0940] 8. Emotion engine that recognizes user emotions

[0941] 9. Adjusting learning content using emotional data

[0942] Specific operation of the system

[0943] User registration and information retrieval

[0944] The terminal displays a form for first-time users to enter their name, age, grade level, and desired subjects.

[0945] The user enters this information and presses the register button.

[0946] The server receives the entered information, stores it in the database, and generates a user ID and password.

[0947] Generating a learning profile

[0948] The server generates a learning profile based on the registered user information. For example, a profile might be created stating, "I want to improve my math skills as a second-year high school student."

[0949] Automatic generation and provision of learning programs

[0950] The server automatically generates a customized learning program based on the generated learning profile and displays it on the user's dashboard.

[0951] The device allows the user to access the learning program from the dashboard and begin learning.

[0952] Recording and analyzing learning progress

[0953] Once a user begins learning, the device records the user's progress (e.g., answer results, learning time, etc.).

[0954] The server receives the recorded learning progress data and analyzes it. For example, it might identify that the user makes many mistakes on trigonometry problems.

[0955] Feedback and suggestions for additional learning content

[0956] The server optimizes the next learning objectives based on the analysis results and provides feedback to the user.

[0957] The device displays information that allows the user to receive feedback and suggests additional learning content.

[0958] Designation of qualification exams and curriculum generation

[0959] If a user wants to take a specific certification exam, they specify that exam in the system.

[0960] The server generates a curriculum corresponding to the specified certification exam and adds it to the user's dashboard.

[0961] Implementation and analysis of mock exams

[0962] The device allows the user to start the practice exam and manages the exam time.

[0963] Users take a practice test and submit their answers.

[0964] The server analyzes the results of the practice test and suggests additional learning content for areas that require particular improvement.

[0965] Using an Emotion Engine

[0966] The device uses user input information and behavioral data (facial expressions, voice, etc.) to send data to the emotion engine.

[0967] The server uses an emotion engine to recognize the user's emotions and stores the results.

[0968] The server adjusts the content of the learning program and the feedback based on the recognized emotion data. For example, if the user is feeling stressed, it will suggest a break to help them relax.

[0969] The device displays emotion-based learning content and feedback to the user.

[0970] Specific example

[0971] For example, if a 15-year-old high school sophomore wants to improve their math skills and experiences stress while learning, the system will work as follows:

[0972] 1. The user enters and submits user information on the terminal, and the server generates a profile.

[0973] 2. The server automatically generates math materials and practice problems for second-year high school students and displays them on the user's dashboard.

[0974] 3. The user begins learning, and the device records their progress and emotional data.

[0975] 4. The server analyzes progress data and emotional data, and if it determines, for example, that the user is feeling stressed, it suggests additional problems to strengthen that area, along with a break to help them relax.

[0976] 5. The server reflects the generated additional learning materials and break times on the dashboard.

[0977] 6. The user reviews the feedback and sets the next learning objectives.

[0978] With the above configuration and operation, this system can continuously provide optimal content according to the user's learning needs and emotional state.

[0979] The following describes the processing flow.

[0980] Step 1:

[0981] The device displays a registration form for users to enter their name, age, grade level, and desired subjects when they first access the system.

[0982] Step 2:

[0983] The user enters the required information into the registration form and clicks "Register".

[0984] Step 3:

[0985] The terminal sends the entered information to the server.

[0986] Step 4:

[0987] The server receives the transmitted information and stores it in the database.

[0988] Step 5:

[0989] The server generates a user ID and password and sends them to the terminal.

[0990] Step 6:

[0991] The device displays the user ID and password and redirects the user to the dashboard screen.

[0992] Step 7:

[0993] The server generates a learning profile based on registered user information. Example: "High school sophomore," "Want to improve math skills."

[0994] Step 8:

[0995] The server automatically generates a customized learning program based on the user's learning profile and displays it on the user's dashboard.

[0996] Step 9:

[0997] The device allows the user to access the learning program from the dashboard and begin learning.

[0998] Step 10:

[0999] Once a user begins learning, the device records the user's progress (answers, study time, etc.).

[1000] Step 11:

[1001] The device transmits recorded progress data, along with the user's facial expressions and voice data, to the server.

[1002] Step 12:

[1003] The server receives progress data and sentiment data analyzed by the sentiment engine, and then analyzes that data. For example, it might identify that the user is making many mistakes on trigonometry problems or that they are feeling stressed.

[1004] Step 13:

[1005] The server optimizes the next learning session based on the analysis results and generates additional supplementary materials and practice problems. It also generates relaxation suggestions and motivational messages based on emotional data.

[1006] Step 14:

[1007] The server displays the generated additional learning materials, practice problems, and suggested breaks and messages on the user's dashboard.

[1008] Step 15:

[1009] The device notifies the user of updated learning programs, suggested breaks, and messages, and displays them as feedback.

[1010] Step 16:

[1011] The user reviews the feedback and sets their next learning goals.

[1012] Step 17:

[1013] If a user wants to take a certification exam, the device provides a form for them to enter their exam information.

[1014] Step 18:

[1015] The user enters the desired qualification exam (e.g., "TOEIC") and submits it.

[1016] Step 19:

[1017] The server receives the entered qualification exam information, generates the corresponding curriculum, and adds it to the dashboard.

[1018] Step 20:

[1019] The device is configured to allow users to start a practice test and also provides a time management tool for the test.

[1020] Step 21:

[1021] Users take a practice test and submit their answers.

[1022] Step 22:

[1023] The server analyzes the results of the practice test and evaluates the level of understanding and proficiency in specific areas.

[1024] Step 23:

[1025] Based on the results of the practice test and the user's sentiment data, the server suggests additional learning content for areas where the user needs to improve, and reflects this on the dashboard.

[1026] Step 24:

[1027] The device notifies the user of additional learning content and guides them to proceed to the next learning step.

[1028] Through these steps, the system provides optimal learning support tailored to the user's learning needs and emotional state.

[1029] (Example 2)

[1030] Next, we will describe Example 2. 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".

[1031] In modern education systems, there is a challenge in ensuring that users have equal learning opportunities regardless of income, location, or personal disadvantages. Furthermore, there is a need to automatically generate learning programs tailored to each learner's progress and understanding, and to provide appropriate feedback. Additionally, there is a lack of technology to provide flexible learning support that considers learners' emotional states and reduces stress and fatigue.

[1032] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring information input by the user, means for generating a user learning profile based on the acquired information, means for automatically generating and providing a learning program according to the user's learning profile, means for recording the user's learning progress, means for analyzing the recorded learning progress data and optimizing the next learning content, means for suggesting feedback and additional learning content to the user, means for acquiring the user's emotional data, and means for adjusting the learning content based on the acquired emotional data. This makes it possible to provide optimal learning support that is tailored to the individual user's learning needs and emotional state.

[1033] "Means for obtaining user-inputted information" refers to the interface and related technologies used to collect data from users who input information such as their name, age, grade level, and desired subjects of study.

[1034] "Means for generating a user's learning profile based on acquired information" refers to technologies and methods for analyzing and processing acquired user information to create a profile based on individual learning needs.

[1035] "Means for automatically generating and providing learning programs tailored to a user's learning profile" refers to a system and technology for automatically generating optimal learning materials and assignments based on each user's learning profile and providing them to the user.

[1036] "Means for recording user learning progress" refers to technologies and methods for recording progress information such as learning activities performed by the user, answer results, and learning time.

[1037] "Means for analyzing recorded learning progress data and optimizing the next learning content" refers to technologies and methods that analyze recorded learning progress data and optimize the next learning content based on the user's level of understanding and progress.

[1038] "Means for providing users with feedback and suggesting additional learning content" refers to techniques and methods for providing users with appropriate feedback based on analysis results and for suggesting any additional learning content they may need.

[1039] "Means for acquiring user emotional data" refers to technologies and methods for analyzing a user's facial expressions, voice, etc., to recognize their emotional state and collect that emotional data.

[1040] "Means for adjusting learning content based on acquired emotional data" refers to technologies and methods for adjusting learning programs and feedback content based on acquired user emotional data.

[1041] "Means for specifying qualification exams" refers to the interface and related technologies for users to select and specify the qualification exams they wish to take.

[1042] "Means for generating and providing a curriculum corresponding to a specified qualification examination" refers to a system and technology for generating a curriculum corresponding to a qualification examination specified by the user and providing it to the user.

[1043] "Means of conducting a mock exam" refers to the technology and methods for a user to start a mock exam and take the test.

[1044] "Methods for analyzing mock exam results and proposing additional learning content" refers to techniques and methods for analyzing mock exam results and proposing additional learning content, particularly in areas that require strengthening.

[1045] "Means for managing the time of a mock exam" refers to the technology and methods for managing the exam time during a mock exam and notifying the user at the appropriate time.

[1046] This invention is an educational support system designed to ensure that users have equal learning opportunities regardless of income, location, or personal disadvantages. The system supports effective learning by providing individualized support based on the user's learning needs, managing learning progress, and offering feedback. Furthermore, it incorporates an emotion engine to recognize the user's emotions and provide feedback and adjustments accordingly.

[1047] System Configuration

[1048] This system has the following main functions:

[1049] 1. Means of obtaining information entered by the user

[1050] 2. Generating a learning profile

[1051] 3. Automatic generation and provision of learning programs

[1052] 4. Recording and analyzing learning progress

[1053] 5. Feedback and suggestions for additional learning content

[1054] 6. Designation of qualification examinations and curriculum development

[1055] 7. Implementation and analysis of mock exams

[1056] 8. Emotion engine that recognizes user emotions

[1057] 9. Adjusting learning content using emotional data

[1058] Specific operation of the system

[1059] User registration and information retrieval

[1060] The terminal displays a form for first-time users to enter their name, age, grade level, and desired subjects. For example, an HTML form could be used to allow users to input this information.

[1061] The user enters this information and presses the register button.

[1062] The server receives the input information using PHP or Node.js, stores it in a database such as MySQL or PostgreSQL, and generates a user ID and password.

[1063] Generating a learning profile

[1064] The server uses libraries such as Python's scikit-learn and pandas to generate learning profiles based on registered user information. For example, it might generate a profile for someone who says, "I'm a second-year high school student and I want to improve my math skills."

[1065] Automatic generation and provision of learning programs

[1066] The server automatically generates individually customized training programs based on the generated training profiles. This is achieved using a Python generative AI model.

[1067] The device uses front-end frameworks such as React.js or Vue.js to display the generated learning program on the user's dashboard, allowing the user to begin learning.

[1068] Recording and analyzing learning progress

[1069] When a user begins learning, the device uses JavaScript or HTML5's LocalStorage to record the user's progress, such as answer results and learning time, in real time.

[1070] The server receives recorded learning progress data and analyzes it using data analysis tools such as Python or R. For example, it saves data on when a user made a mistake on a particular problem and analyzes the patterns using a machine learning model.

[1071] Feedback and suggestions for additional learning content

[1072] The server uses a machine learning model to generate feedback based on the analysis results. This feedback includes suggestions for improvement and additional learning content for the user.

[1073] The device displays the feedback to the user in real time.

[1074] Designation of qualification exams and curriculum generation

[1075] The user selects the certification they wish to take from a list of certification exams configured within the system.

[1076] The server generates a curriculum corresponding to the selected qualification and adds it to the user's dashboard.

[1077] Implementation and analysis of mock exams

[1078] The device displays an interface for starting the mock exam and also supports time management. It records the progress of the exam in real time.

[1079] Users take a practice test and submit their results to the server.

[1080] The server analyzes the test results, identifies areas for improvement, and proposes revised learning content.

[1081] Using an Emotion Engine

[1082] The device captures the user's facial expressions with its camera and collects audio data. This data is then sent to the emotion engine.

[1083] The server analyzes the user's emotions using an emotion engine and stores the results. For example, it might use Google Cloud Emotion AI.

[1084] The server adjusts the learning program and feedback based on the analysis results. For example, if the user is feeling stressed, it suggests content to help them relax.

[1085] The device displays adjusted feedback and learning content to the user.

[1086] Specific example

[1087] For example, if a 15-year-old high school sophomore wants to improve their math skills and experiences stress while learning, the system will work as follows:

[1088] 1. The user enters and submits user information on the terminal, and the server generates a profile.

[1089] 2. The server automatically generates math materials and practice problems for second-year high school students and displays them on the user's dashboard.

[1090] 3. The user begins learning, and the device records their progress and emotional data.

[1091] 4. The server analyzes progress data and emotional data, and if it determines, for example, that the user is feeling stressed, it suggests additional problems to strengthen that area, along with a break to help them relax.

[1092] 5. The server reflects the generated additional learning materials and break times on the dashboard.

[1093] 6. The user reviews the feedback and sets the next learning objective.

[1094] Example of a prompt

[1095] "A 15-year-old high school sophomore wants to improve their math skills. They are experiencing stress while learning; please generate prompts explaining how the system can help them."

[1096] As described above, the educational support system of the present invention can provide optimal content according to the user's learning needs and emotional state.

[1097] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1098] Step 1:

[1099] The terminal displays a form for first-time users to enter their name, age, grade level, and desired subjects. Once the user enters information into the form, that data is sent to the server using JavaScript (input: user information, output: sent data).

[1100] Step 2:

[1101] The server stores the received user information in a database and generates a user ID and password. For example, you can access the database and save the information using PHP or Node.js (input: user information, output: user ID and password).

[1102] Step 3:

[1103] The server uses Python libraries such as scikit-learn and pandas to generate learning profiles based on registered user information. This uses data such as the user's grade level and the subjects they want to strengthen (input: user information, output: learning profile).

[1104] Step 4:

[1105] The server automatically generates individually customized learning programs based on the generated learning profiles. Here, a generative AI model (e.g., GPT-3) is used to generate the learning plan and learning materials (input: learning profile, output: learning program).

[1106] Step 5:

[1107] The terminal displays the generated learning program on the user's dashboard, allowing the user to begin learning. Frontend frameworks such as React.js and Vue.js are used (input: learning program, output: dashboard display).

[1108] Step 6:

[1109] When a user begins learning, the device uses JavaScript or HTML5's LocalStorage to record the user's progress in real time, including their answers and learning time (input: user's learning activity, output: progress data).

[1110] Step 7:

[1111] The server receives recorded learning progress data and analyzes it using data analysis tools such as Python or R. For example, it can analyze if a user repeatedly makes mistakes on a particular problem (input: progress data, output: analysis results).

[1112] Step 8:

[1113] The server uses a machine learning model to generate feedback based on the analysis results. This feedback includes points to check and areas for improvement (input: analysis results, output: feedback).

[1114] Step 9:

[1115] The device displays the feedback content to the user in real time (input: feedback, output: feedback display).

[1116] Step 10:

[1117] The user selects the qualification they wish to take from a list of qualification exams within the system (Input: Selection of qualification exam, Output: Specified qualification exam).

[1118] Step 11:

[1119] The server generates a curriculum corresponding to the selected qualification and adds it to the user's dashboard (input: specified qualification exam, output: curriculum).

[1120] Step 12:

[1121] The terminal displays an interface for starting the mock exam and manages the exam progress and time in real time (input: start of mock exam, output: progress of mock exam).

[1122] Step 13:

[1123] Users take a practice test and submit their results to the server (input: practice test answers, output: practice test results).

[1124] Step 14:

[1125] The server analyzes the results of the mock exam and suggests additional learning content for areas that need improvement (Input: Mock exam results, Output: Suggested additional learning content).

[1126] Step 15:

[1127] The device captures the user's facial expressions with its camera and collects audio data. This data is then sent to the emotion engine (input: facial expressions and audio data, output: emotion data).

[1128] Step 16:

[1129] The server uses an emotion engine to analyze the user's emotions and stores the results in a database (input: emotion data, output: analysis results).

[1130] Step 17:

[1131] The server adjusts the learning program and feedback based on the acquired emotional data. If stress is detected, it suggests content to help the user relax (input: analysis results, output: adjusted learning program and feedback).

[1132] Step 18:

[1133] The device displays the user with adjusted feedback and learning content (input: adjusted learning program and feedback, output: feedback display).

[1134] (Application Example 2)

[1135] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[1136] Traditional learning support systems have the drawback of not maximizing learning effectiveness because they provide uniform learning programs and feedback without considering the learner's emotional state. Furthermore, there was no way to determine in real time how much stress or fatigue a learner was experiencing with each subject. These challenges made it difficult to provide optimal learning support based on the individual characteristics and emotional state of each learner.

[1137] The specific processing performed 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 means for acquiring information input by the user, means for generating a user learning profile based on the acquired information, means for automatically generating and providing a learning program according to the user's learning profile, means for recording the user's learning progress, means for analyzing the recorded learning progress data and optimizing the next learning content, means for suggesting feedback and additional learning content to the user, means for recognizing the user's emotions, and means for adjusting the learning content using the recognized emotion data. This makes it possible to grasp the learner's emotional state in real time and flexibly adjust the learning program and feedback based on that.

[1138] "User information acquisition method" refers to a means of acquiring basic information such as the learner's name, age, grade level, and desired subjects to study.

[1139] A "learning profile generation means" is a means for generating an optimal learning profile for each individual learner based on acquired user information.

[1140] A "learning program generation means" is a means for automatically generating and providing a learning program that is individually customized according to the generated learning profile.

[1141] A "learning progress recording device" is a means of recording a learner's learning activities and progress.

[1142] A "learning progress analysis tool" is a means of analyzing recorded learning progress data to optimize the content of the next learning session.

[1143] A "feedback suggestion method" is a means of providing learners with feedback on the next learning steps or areas for improvement based on the analysis results.

[1144] "Means of emotional recognition" are means of recognizing a learner's emotional state from their facial expressions, voice, etc.

[1145] "Emotional data adjustment means" refers to a means of adjusting learning content and feedback using recognized emotional data.

[1146] A "means of designating a qualification examination" refers to a means by which learners can designate a specific qualification examination.

[1147] A "curriculum generation method" is a means for generating and providing a curriculum corresponding to a designated qualification examination.

[1148] "Methods for conducting mock examinations" refers to the means for conducting mock examinations and recording and analyzing the results.

[1149] "Time management methods" refer to the means by which learners manage the time they spend taking practice exams.

[1150] The system that realizes this invention generates a user's learning profile, provides a customized learning program, and optimizes the learning experience by utilizing emotion recognition. The system mainly consists of the following elements:

[1151] 1. Obtaining user information

[1152] Users enter basic information such as their name, age, grade level, and desired subjects using their smartphones or tablets. The device retrieves this information and sends it to a cloud server. This information is stored in a database on the server (e.g., MySQL, MongoDB, etc.).

[1153] 2. Generating a learning profile

[1154] The server generates a learning profile based on the acquired user information. This profile reflects specific learning needs, such as "I want to improve my math skills as a second-year high school student." A user ID and password are also generated using Python or the Django framework.

[1155] 3. Automatic generation and provision of learning programs

[1156] The server automatically generates a customized learning program based on the generated learning profile. This learning program is reflected in the user's dashboard, and the user can access it to begin learning. Custom algorithms and generative AI models can be used to create the learning program.

[1157] 4. Recording and analyzing learning progress

[1158] Users progress through the learning process using their devices, and their progress data (such as answer results and learning time) is recorded. The devices send this data to a server, which analyzes it using Python and Pandas. Based on specific problem areas and progress, the server optimizes the next learning content.

[1159] 5. Feedback and suggestions for additional learning content

[1160] Based on the analysis results, the server suggests optimal feedback and additional learning content to the user. This is displayed on the user's dashboard to assist with the next learning steps.

[1161] 6. Optimization through emotion recognition

[1162] The device uses its camera and microphone to capture facial expressions and voice to recognize the user's emotional state. This data is analyzed by an emotion recognition model (e.g., TensorFlow) and the emotional state is sent to a server. The server uses this emotional data to adjust the learning program and provide feedback.

[1163] Specific example

[1164] For example, suppose a 15-year-old high school sophomore is using this system to improve their math skills. The user first enters their name, grade level, and desired subjects via smartphone, and a learning profile is generated based on this information. As the user progresses, the system records and analyzes their progress. Furthermore, if the user is experiencing stress during their studies, an emotion recognition engine identifies this, and the server suggests a break to help them relax.

[1165] Example of a prompt

[1166] The following prompts are used when configuring the emotion recognition engine:

[1167] python

[1168] Import necessary

[1169] import cv2

[1170] import tensorflow as tf

[1171] Load pre-trained model

[1172] model = tf.keras.models.load_model('emotion_recognition_model.h5')

[1173] Capture video from webcam

[1174] cap = cv2.VideoCapture(0)

[1175] while True:

[1176] ret, frame = cap.read()

[1177] if not ret:

[1178] break

[1179] Process frame for emotion recognition

[1180] gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

[1181] face = cv2.resize(gray, (48, 48))

[1182] face = face.reshape(1, 48, 48, 1) / 255.0

[1183] Predict emotion

[1184] emotion = model.predict(face)

[1185] print(f"Detected emotion: {emotion}")

[1186] Display the frame

[1187] cv2.imshow('Emotion Recognition', frame)

[1188] if cv2.waitKey(1) & 0xFF == ord('q'):

[1189] break

[1190] cap.release()

[1191] cv2.destroyAllWindows()

[1192] In this way, a learning support system that combines emotion recognition can provide individualized and flexible support to learners.

[1193] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1194] Step 1:

[1195] Users enter basic information such as their name, age, grade level, and desired subjects using their smartphones or tablets. This information is then sent from the device to a cloud server. The server stores the received information in a database (e.g., MySQL, MongoDB). The input is the user's basic information, and the output is the storage of user information on the cloud server.

[1196] Step 2:

[1197] The server generates a learning profile based on stored user information. This learning profile includes details such as the student's grade level and subject level. This allows for the creation of a specific profile, such as "I'm a second-year high school student and I want to improve my math skills." The input is the user's basic information, and the output is the generated learning profile.

[1198] Step 3:

[1199] The server automatically generates a customized learning program based on the generated learning profile. During this process, it creates optimal learning content using custom algorithms and generative AI models. The generated learning program is reflected in the user's dashboard. The input is the learning profile, and the output is the customized learning program.

[1200] Step 4:

[1201] Users access the learning program from the dashboard and proceed with their studies. The device records the user's learning progress data (e.g., answer results, study time) and sends it to the cloud server. The server receives this data and stores it in a database. The input is the user's learning progress data, and the output is the transmission and storage of data to the server.

[1202] Step 5:

[1203] The server analyzes the recorded learning progress data using Python or Pandas. This analysis identifies specific problem areas and areas of progress for the user. For example, it identifies areas where many incorrect answers are observed. The input is the recorded learning progress data, and the output is the analysis results.

[1204] Step 6:

[1205] Based on the analysis results, the server suggests optimal feedback and additional learning content to the user. This content is displayed on the user's dashboard. The input is the analysis results, and the output is the feedback and additional learning content.

[1206] Step 7:

[1207] The device uses its camera and microphone to capture facial expressions and voice to recognize the user's emotional state. The captured data is analyzed by an emotion recognition model (e.g., TensorFlow) to identify the emotional state. The input is facial expression and voice data, and the output is recognized emotion data.

[1208] Step 8:

[1209] The server adjusts its learning content and feedback based on the recognized emotion data. For example, if the user is feeling stressed, it suggests taking a break to relax. The input is the recognized emotion data, and the output is the adjusted learning content and feedback.

[1210] Step 9:

[1211] The user reviews feedback and adjusted learning content from their device and sets the next learning step. This makes learning more effective. The input is the adjusted learning content and feedback, and the output is the setting of the next learning step.

[1212] The above describes the specific processing flow of the system that realizes this invention.

[1213] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1214] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1215] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[1216] [Third Embodiment]

[1217] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[1218] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1219] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1220] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[1221] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1222] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1223] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1224] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1225] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[1226] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1227] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1228] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[1229] This invention is an educational support system designed to ensure that users have equal learning opportunities regardless of income, location, or personal disadvantages. The system supports effective learning by providing individualized support based on the user's learning needs, managing learning progress, and offering feedback.

[1230] System Configuration

[1231] This system has the following main functions:

[1232] 1. Means of obtaining information entered by the user

[1233] 2. Generating a learning profile

[1234] 3. Automatic generation and provision of learning programs

[1235] 4. Recording and analyzing learning progress

[1236] 5. Feedback and suggestions for additional learning content

[1237] 6. Designation of qualification examinations and curriculum development

[1238] 7. Implementation and analysis of mock exams

[1239] Specific operation of the system

[1240] User registration and information retrieval

[1241] The terminal displays a form for first-time users to enter their name, age, grade level, and desired subjects.

[1242] The user enters this information and presses the register button.

[1243] The server receives the entered information, stores it in the database, and generates a user ID and password.

[1244] Generating a learning profile

[1245] The server generates a learning profile based on the registered user information. For example, a profile might be created for a second-year high school student who wants to improve their math skills.

[1246] Automatic generation and provision of learning programs

[1247] The server automatically generates a customized learning program based on the generated learning profile and displays it on the user's dashboard.

[1248] The device allows users to access the learning program from the dashboard and begin learning.

[1249] Recording and analyzing learning progress

[1250] As the user progresses through the learning process, the device records the user's progress.

[1251] The server receives the recorded learning progress data and analyzes it. For example, it might identify that the user makes many mistakes on trigonometry problems.

[1252] Feedback and suggestions for additional learning content

[1253] The server optimizes the next learning objectives based on the analysis results and provides feedback to the user.

[1254] The device displays information that allows the user to receive feedback and suggests additional learning content.

[1255] Designation of qualification exams and curriculum generation

[1256] If a user wants to take a specific certification exam, they specify that exam in the system.

[1257] The server generates a curriculum corresponding to the specified certification exam and adds it to the user's dashboard.

[1258] Implementation and analysis of mock exams

[1259] The device allows the user to start the practice exam and manages the exam time.

[1260] Users take a practice test and submit their answers.

[1261] The server analyzes the results of the practice test and suggests additional learning content for areas that require particular improvement.

[1262] Specific example

[1263] For example, if a user is a 15-year-old high school sophomore and wants to improve their math skills, the system will work as follows:

[1264] 1. The user enters and submits user information on the terminal, and the server generates a profile.

[1265] 2. The server automatically generates math materials and practice problems for second-year high school students and displays them on the user's dashboard.

[1266] 3. The user begins learning, and the device records their progress.

[1267] 4. The server analyzes the progress data and, for example, if it determines that there is a lack of understanding of trigonometry, it generates additional problems to strengthen that area and adds them to the dashboard.

[1268] 5. The user solves additional problems, the results are further analyzed, and appropriate feedback and suggestions for the next learning activities are provided.

[1269] With the above configuration and operation, this system can provide learning support tailored to the individual needs of users, thereby improving the efficiency and effectiveness of learning.

[1270] The following describes the processing flow.

[1271] Step 1:

[1272] When a user accesses the system for the first time, the device displays a registration form for them to enter their name, age, grade level, and desired subjects.

[1273] Step 2:

[1274] The user fills in the required information on the form and clicks "Register".

[1275] Step 3:

[1276] The terminal sends the entered information to the server.

[1277] Step 4:

[1278] The server receives the transmitted information and stores it in the database.

[1279] Step 5:

[1280] The server generates a user ID and password and sends them to the user.

[1281] Step 6:

[1282] The device displays the user ID and password and redirects the user to the dashboard screen.

[1283] Step 7:

[1284] The server generates a learning profile based on user profile information. For example, this includes information such as "high school sophomore" and "desire to improve math skills."

[1285] Step 8:

[1286] The server automatically generates a customized learning program based on the user's learning profile and displays it on the user's dashboard.

[1287] Step 9:

[1288] The device allows the user to access the learning program from the dashboard and begin learning.

[1289] Step 10:

[1290] Once a user begins learning, the device records the user's progress (e.g., answer results, learning time, etc.).

[1291] Step 11:

[1292] The terminal sends the recorded progress data to the server.

[1293] Step 12:

[1294] The server analyzes progress data and identifies areas where the user should focus their efforts. For example, it might extract data such as "there are many mistakes in trigonometry problems."

[1295] Step 13:

[1296] Based on the analysis results, the server optimizes the content for the next lesson and generates additional supplementary materials and practice problems.

[1297] Step 14:

[1298] The server displays the generated additional learning materials and practice problems on the user's dashboard.

[1299] Step 15:

[1300] The device notifies the user of updated learning programs and displays them as feedback.

[1301] Step 16:

[1302] The user reviews the feedback and sets their next learning goals.

[1303] Step 17:

[1304] If a user wishes to take a certification exam, the device provides a form for entering exam information.

[1305] Step 18:

[1306] The user enters the desired qualification exam (e.g., "TOEIC") and submits it.

[1307] Step 19:

[1308] The server receives the entered qualification exam information, generates the corresponding curriculum, and adds it to the dashboard.

[1309] Step 20:

[1310] The device is configured to allow the user to start a practice exam and provides time management tools for the exam.

[1311] Step 21:

[1312] Users take a practice test and submit their answers.

[1313] Step 22:

[1314] The server analyzes the results of the practice test and evaluates the level of understanding and proficiency in specific areas.

[1315] Step 23:

[1316] Based on the results of the practice test, the server suggests additional learning content for areas where the user needs to improve, and reflects this on the dashboard.

[1317] Step 24:

[1318] The device notifies the user of additional learning content and guides them to proceed to the next learning step.

[1319] By following these steps, the system can continuously provide the most suitable content for the user's learning needs and progress.

[1320] (Example 1)

[1321] Next, we will describe Example 1. 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."

[1322] Modern education systems struggle to meet the individual learning needs of users, particularly due to unequal access to learning opportunities caused by income, location, and personal disadvantages. Furthermore, traditional learning systems often fail to effectively track learning progress and provide feedback, making it difficult to offer optimal learning programs for individual users. As a result, users are unable to learn efficiently and achieve their goals.

[1323] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1324] In this invention, the server includes means for acquiring information entered by the user, means for generating a user learning profile based on the acquired information, means for automatically generating and providing a learning program according to the user's learning profile, means for recording the user's learning progress, means for analyzing the recorded learning progress data and optimizing the next learning content, means for suggesting feedback and additional learning content to the user, means for storing user information and learning progress data in a database, means for reflecting the learning program and feedback on the user's dashboard, means for the user to take a mock exam and submit the results, and means for analyzing the results of the mock exam and suggesting improvements in specific areas. This enables users to learn fairly and efficiently and provides optimal educational support tailored to each individual's learning needs.

[1325] "Means of acquiring user-inputted information" refers to devices and software that collect and store information that users input into the system, such as their name, age, grade level, and subjects they wish to study.

[1326] "Means for generating a user's learning profile based on acquired information" refers to algorithms and programs that create a learning profile that reflects the individual user's learning needs and goals, based on the information provided by the user.

[1327] "Means for automatically generating and providing learning programs tailored to a user's learning profile" refers to a system that automatically creates and provides optimal learning content and activities to the user based on the generated learning profile.

[1328] "Means for recording user learning progress" refers to devices or programs that have the function of continuously recording the progress and answer results achieved by a user during the learning process.

[1329] "Means for analyzing recorded learning progress data and optimizing the next learning content" refers to algorithms and programs that analyze collected learning progress data to understand the user's level of comprehension and weaknesses, and determine the optimal content for the next learning session.

[1330] "Means of providing users with feedback and suggesting additional learning content" refers to devices or software that have the functionality to provide users with specific feedback based on analyzed learning progress data and to suggest any additional learning content they may need.

[1331] "Means for storing user information and learning progress data in a database" refers to a system that records user-entered information and learning progress data in a database and manages it so that it can be referenced later as needed.

[1332] "Means of reflecting learning programs and feedback on the user's dashboard" refers to a system that has an interface on the dashboard that allows users to see their learning progress and feedback at a glance.

[1333] "Means for users to take a practice test and submit the results" refers to devices or programs that have the function of allowing users to take a practice test and submit the results to a system.

[1334] "Methods for analyzing mock exam results and suggesting improvements in specific areas" refers to algorithms or programs that scrutinize the results of mock exams taken by users, identify specific areas that need improvement, and suggest additional learning content for those areas.

[1335] This invention is an educational support system designed to ensure that users have equal learning opportunities regardless of income, location, or personal disadvantages. The system has the following main functions:

[1336] User registration and information retrieval

[1337] The terminal displays a form for new users to enter information such as their name, age, grade level, and desired subjects. This form is accessed via a web browser or a dedicated application.

[1338] The user enters the required information and presses the "Register" button to submit the information.

[1339] The server receives the transmitted information and stores it in a database (such as MySQL or PostgreSQL). It also generates a user ID and initial password and notifies the user.

[1340] Generating a learning profile

[1341] The server generates a learning profile based on registered user information. This profile reflects the user's learning needs and goals.

[1342] For example, you can generate a profile using machine learning techniques with Python libraries (pandas, scikit-learn).

[1343] Automatic generation and provision of learning programs

[1344] The server automatically generates a customized learning program based on the generated profile. This program consists of appropriate learning materials and problem sets.

[1345] The server displays programs generated using a template engine (such as Jinja2) on the user's dashboard.

[1346] The device allows users to access the dashboard, view the learning program, and begin.

[1347] Recording and analyzing learning progress

[1348] As the user progresses through the learning process, the device records their progress in real time (e.g., answer status and accuracy rate). This record is temporarily saved using HTML5 local storage and JavaScript.

[1349] The device periodically sends this progress data to the server.

[1350] The server receives progress data and analyzes it using Python's pandas and numpy. For example, if a user makes many mistakes in a particular area (e.g., trigonometry), the server identifies that area.

[1351] Feedback and suggestions for additional learning content

[1352] The server optimizes the next learning content based on the analysis of progress data. This includes additional problems and materials to strengthen the user's weaknesses.

[1353] The device displays feedback and suggested additional learning content on the user's dashboard.

[1354] Designation of qualification exams and curriculum generation

[1355] If a user wants to take a specific certification exam (e.g., TOEIC), they specify that exam in the system.

[1356] The server generates a curriculum corresponding to the specified certification exam and provides it to the user's dashboard.

[1357] Implementation and analysis of mock exams

[1358] The device allows the user to start a practice test and manages the test time using a JavaScript timer function.

[1359] After taking a practice test, the user submits their answers.

[1360] The server analyzes the results and suggests additional learning content, particularly in areas that need strengthening.

[1361] Examples and prompts for generative AI models

[1362] For example, if a 15-year-old high school sophomore wants to improve their math skills, it would work as follows:

[1363] The user enters their information on the terminal, and the server generates a profile.

[1364] The server generates math materials and practice problems for second-year high school students and displays them on the user's dashboard.

[1365] The user begins learning, and the device records the learning progress and sends it to the server.

[1366] The server analyzes the progress data and, for example, if it determines that there is a lack of understanding of trigonometry, it generates additional problems and adds them to the dashboard.

[1367] The user solves additional problems, the results are analyzed, and the next learning objectives are suggested.

[1368] Examples of prompts for a generative AI model:

[1369] "I have a 15-year-old high school sophomore who wants to improve his math skills. Please create a customized learning program for him based on his current learning progress, with a particular focus on trigonometry."

[1370] In this way, the system provides comprehensive learning support tailored to the individual needs of users, thereby improving the efficiency and outcomes of their learning.

[1371] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1372] Step 1:

[1373] User registration and information retrieval

[1374] The device displays a form for the user to enter information such as their name, age, grade level, and the subjects they wish to study.

[1375] Input: User information (name, age, grade level, subject you want to study)

[1376] Output: Information entered by the user

[1377] The user enters the required information and presses the "Register" button to submit the information.

[1378] Input: User actions

[1379] Output: Sent user information

[1380] The server receives the transmitted user information and stores it in the database.

[1381] Input: Submitted user information

[1382] Data processing: Converting user information into a database format.

[1383] Output: User information stored in the database

[1384] The server generates a user ID and initial password and notifies the user.

[1385] Input: Saved user information

[1386] Data calculation: Generation of user ID and initial password

[1387] Output: User ID and initial password

[1388] Step 2:

[1389] Generating a learning profile

[1390] The server generates a learning profile based on the registered user information.

[1391] Input: User information stored in the database

[1392] Data processing: Generate profiles based on learning needs and grade level (e.g., using Python libraries pandas and scikit-learn).

[1393] Output: Generation of training profile

[1394] The server saves the generated profile to the database.

[1395] Input: Generated training profile

[1396] Data processing: Convert profile to database format

[1397] Output: Learning profiles stored in the database

[1398] Step 3:

[1399] Automatic generation and provision of learning programs

[1400] The server automatically generates a customized learning program based on the generated learning profile.

[1401] Input: Learning Profile

[1402] Data processing: Select appropriate teaching materials and problem sets, and design a learning program (using the Jinja2 template engine).

[1403] Output: Customized learning program

[1404] The server displays the generated learning program on the user's dashboard.

[1405] Input: Customized learning program

[1406] Output: The program reflected in the user's dashboard.

[1407] The device allows users to access the dashboard, view their learning programs, and begin.

[1408] Input: User actions

[1409] Output: Learning program displayed to the user

[1410] Step 4:

[1411] Recording and analyzing learning progress

[1412] As the user progresses through the learning process, the device records their progress in real time.

[1413] Input: User's learning activity data (answer results, progress)

[1414] Data processing: Save to local storage in real time.

[1415] Output: Recorded progress

[1416] The device periodically sends progress data to the server.

[1417] Input: Progress data stored in local storage

[1418] Output: Progress data sent to the server

[1419] The server receives and analyzes the progress data.

[1420] Input: Submitted progress data

[1421] Data processing: Analysis using data analysis tools (pandas, numpy).

[1422] Output: Analysis results (e.g., identification of weaknesses in a specific field)

[1423] Step 5:

[1424] Feedback and suggestions for additional learning content

[1425] The server optimizes the next learning steps based on the analysis results of the progress data.

[1426] Input: Analysis results of progress data

[1427] Data processing: Generating feedback content and additional learning content.

[1428] Output: Next learning content

[1429] The device displays feedback and additional learning content on the user's dashboard.

[1430] Input: Generated feedback content and additional learning content

[1431] Output: Feedback and additional learning content displayed on the dashboard

[1432] Step 6:

[1433] Designation of qualification exams and curriculum generation

[1434] If a user wants to take a specific certification exam, they specify that exam in the system.

[1435] Input: Specified information for the qualification exam

[1436] Output: Qualification exam information set in the system

[1437] The server generates a curriculum corresponding to the specified certification exam and provides it to the user's dashboard.

[1438] Input: Specified information for the qualification exam

[1439] Data processing: Automatic generation of curriculum

[1440] Output: Curriculum added to the user's dashboard

[1441] Step 7:

[1442] Implementation and analysis of mock exams

[1443] The device allows the user to start the practice exam and manages the exam time.

[1444] Input: User action (start of mock exam)

[1445] Data calculation: Using JavaScript's timer function

[1446] Output: Start of mock exam and time management

[1447] Users take a practice test and submit their answers.

[1448] Input: User's answer

[1449] Output: Submitted answer data

[1450] The server analyzes the results of the practice test and suggests additional learning content for areas that require particular improvement.

[1451] Input: Submitted answer data

[1452] Data processing: Analysis of answer data

[1453] Output: Suggestions for strengthening specific areas and additional learning content

[1454] (Application Example 1)

[1455] Next, we will explain Application Example 1. In the following explanation, 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."

[1456] Traditional education systems failed to adequately address users' diverse learning needs, lacking sufficient feedback based on learning progress and insufficient suggestions for optimal additional learning content. Furthermore, the provision of learning materials and progress management were not centralized, and there were challenges in conducting mock exams and effectively addressing weaknesses based on the results. Additionally, the lack of immediate feedback and suggestions for additional learning content prevented users from learning efficiently.

[1457] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1458] In this invention, the server includes means for acquiring information entered by the user, means for generating a user learning profile based on the acquired information, means for automatically generating and providing a learning program according to the user's learning profile, means for recording the user's learning progress, means for analyzing the recorded learning progress data and optimizing the next learning content, means for suggesting feedback and additional learning content to the user, means for providing learning materials and online courses from a virtual store, means for generating a customized learning program based on purchased materials, means for analyzing the results of mock exams and suggesting a curriculum to reinforce weaknesses, and means for allowing the user to view their learning progress and feedback. As a result, the user can receive an optimal learning program tailored to their individual learning needs, easily acquire a variety of learning materials through the virtual store, and manage and improve their learning progress more efficiently and effectively.

[1459] "Means for obtaining user input" refers to an interface that allows users to input information such as their name, age, grade level, and subjects they wish to study, and then transmit this information to the system.

[1460] "Means for generating a user's learning profile based on acquired information" refers to a system that analyzes the acquired personal information of a user and creates a profile that takes into account the user's learning needs.

[1461] "A means of automatically generating and providing a learning program tailored to the user's learning profile" refers to a system that automatically creates an individualized learning plan based on the learning profile and provides it to the user.

[1462] A "means for recording user learning progress" refers to a system that records progress data such as how far a user has progressed during their learning and which tasks have been completed.

[1463] "A means of analyzing recorded learning progress data and optimizing the next learning content" refers to a system that analyzes collected learning progress data and adjusts the content to be learned next according to the user's level of understanding and weaknesses.

[1464] A "means of providing users with feedback and suggesting additional learning content" is a system that provides users with feedback based on their progress data, indicating which parts they understand and which parts they need to improve, and then suggests the necessary additional learning content.

[1465] "A means of providing learning materials and online courses from a virtual store" refers to a system that allows users to purchase and access various learning materials and online courses through an online store.

[1466] "A means of generating a customized learning program based on purchased learning materials" refers to a system that individually creates an optimal learning plan using the learning materials purchased by the user in a virtual store.

[1467] "A method for analyzing mock exam results and proposing a curriculum to strengthen weaknesses" refers to a system that thoroughly analyzes the results of mock exams taken by users, identifies their weaknesses, and then provides an additional curriculum to strengthen those weaknesses.

[1468] "Means for users to view their learning progress and feedback" refers to the interface that users use to check their learning progress and feedback from the system.

[1469] This invention is an educational support system for acquiring information entered by a user and generating, providing, and managing individualized learning programs based on that information. This system supports efficient learning by recording and analyzing the user's learning progress and optimizing the next learning content.

[1470] System Configuration

[1471] 1. User registration and information acquisition

[1472] When a user accesses the server for the first time, it displays a personal information input form on the user's device. The user enters information such as their name, age, grade level, and desired subjects, and submits the form. The server stores the received information in a database and generates a user ID and password.

[1473] 2. Generating a learning profile

[1474] The server generates individual learning profiles for each user based on the registered user information. For example, a profile might be created that indicates a high level of motivation to learn a particular subject.

[1475] 3. Automatic generation and provision of learning programs

[1476] The server automatically generates a personalized learning program based on the generated learning profile and displays it on the user's dashboard. The user accesses the learning program through their device and begins learning.

[1477] 4. Recording and analyzing learning progress

[1478] As the user progresses through the learning process, the device records the user's progress. The server receives the recorded learning progress data and analyzes it. For example, if a user makes many incorrect answers in a particular area, that data will be extracted.

[1479] 5. Feedback and suggestions for additional learning content

[1480] The server optimizes the next learning content based on the analysis results and provides feedback to the user. The terminal displays the feedback to the user and suggests additional learning content.

[1481] 6. Provision of educational materials from virtual stores

[1482] The server provides users with learning materials and online courses tailored to their needs through a virtual store. Users can purchase these within the app and incorporate them into their learning programs.

[1483] 7. Generating a customized learning program

[1484] The server generates a customized learning program based on the purchased learning materials and provides it to the user.

[1485] 8. Analysis of mock exam results and strengthening of weak points

[1486] The server receives the results of the mock exam and analyzes them in detail. Based on this, it identifies the user's weaknesses and proposes a curriculum to strengthen those weaknesses.

[1487] 9. View learning progress and feedback

[1488] Users can view their learning progress and feedback from the system through their device.

[1489] Specific example

[1490] For example, if a high school sophomore user wants to improve their math skills, the system will work as follows:

[1491] 1. The user enters and submits personal information on their device. The server generates a learning profile.

[1492] 2. The server automatically generates math materials and practice problems for second-year high school students and displays them on the user's dashboard.

[1493] 3. The user purchases learning materials and proceeds with their studies. The device records their progress.

[1494] 4. The server analyzes the progress data and identifies areas where understanding is particularly lacking. For example, if mastery of trigonometry is insufficient, it generates additional problems to reinforce that area and adds them to the dashboard.

[1495] 5. The user solves additional problems, the results are analyzed, and appropriate feedback and suggestions for the next learning activities are provided.

[1496] Examples of prompts for generative AI models

[1497] "When a high school sophomore user was studying mathematics, they made many mistakes in a specific area. Therefore, additional problems are generated to strengthen that area, and these are reflected in the dashboard."

[1498] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1499] Step 1:

[1500] When a user accesses the server for the first time, it displays a personal information input form on the terminal. The user enters information such as their name, age, grade level, and desired subjects, and submits the form. This input information is sent from the terminal to the server. The server stores the received information in a database and generates a user ID and password.

[1501] Step 2:

[1502] The server generates individual learning profiles for each user based on the registered user information. These profiles include the user's age, grade level, and areas of interest. The generated profiles are stored in a database.

[1503] Step 3:

[1504] The server automatically generates a personalized learning program based on the generated learning profile. This program includes learning materials and practice exercises tailored to the user's grade level and interests. This learning program is reflected in the user's dashboard and provided to the user through their device.

[1505] Step 4:

[1506] The user accesses the learning program provided through the device and begins learning. The device records the user's learning progress in real time and sends this data to the server. The recorded progress data includes completed assignments and the accuracy of answers.

[1507] Step 5:

[1508] The server performs data analysis based on recorded learning progress data. The analysis identifies areas where the user frequently makes mistakes or where their understanding is lacking. The analysis results are stored in a database.

[1509] Step 6:

[1510] The server executes an algorithm to optimize the next learning content based on the analysis results. For example, if there is a lack of understanding in a particular area, it generates additional problems or learning materials related to that area. The generated learning content is added to the user's dashboard.

[1511] Step 7:

[1512] The device displays an interface that allows the user to view newly suggested learning content and feedback. The user then continues learning based on this information, and their progress is recorded and analyzed again.

[1513] Step 8:

[1514] The server provides users with various learning materials and online courses through a virtual store. Users purchase these materials through their devices, and the content is reflected in their learning programs.

[1515] Step 9:

[1516] The server generates a customized learning program based on the purchased learning materials. This generated program is reflected in the user's dashboard and provided as additional learning content.

[1517] Step 10:

[1518] The server analyzes the results of the practice exams taken by the user in detail. Based on the analysis, it identifies areas where the user's understanding is lacking and generates a curriculum to reinforce those weaknesses. This curriculum is also added to the user's dashboard.

[1519] Step 11:

[1520] The device allows users to view their learning progress and system feedback in real time. Users can then refer to this information to learn more efficiently.

[1521] Examples of prompts for generative AI models

[1522] "When a high school sophomore user was studying mathematics, they made many mistakes in a specific area. Therefore, additional problems are generated to strengthen that area, and these are reflected in the dashboard."

[1523] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1524] This invention is an educational support system designed to ensure that users have equal learning opportunities regardless of income, location, or personal disadvantages. The system supports effective learning by providing individualized support based on the user's learning needs, managing learning progress, and offering feedback. Furthermore, the invention incorporates an emotion engine that recognizes the user's emotions and provides feedback and adjustments accordingly.

[1525] System Configuration

[1526] This system has the following main functions:

[1527] 1. Means of obtaining information entered by the user

[1528] 2. Generating a learning profile

[1529] 3. Automatic generation and provision of learning programs

[1530] 4. Recording and analyzing learning progress

[1531] 5. Feedback and suggestions for additional learning content

[1532] 6. Designation of qualification examinations and curriculum development

[1533] 7. Implementation and analysis of mock exams

[1534] 8. Emotion engine that recognizes user emotions

[1535] 9. Adjusting learning content using emotional data

[1536] Specific operation of the system

[1537] User registration and information retrieval

[1538] The terminal displays a form for first-time users to enter their name, age, grade level, and desired subjects.

[1539] The user enters this information and presses the register button.

[1540] The server receives the entered information, stores it in the database, and generates a user ID and password.

[1541] Generating a learning profile

[1542] The server generates a learning profile based on the registered user information. For example, a profile might be created stating, "I want to improve my math skills as a second-year high school student."

[1543] Automatic generation and provision of learning programs

[1544] The server automatically generates a customized learning program based on the generated learning profile and displays it on the user's dashboard.

[1545] The device allows the user to access the learning program from the dashboard and begin learning.

[1546] Recording and analyzing learning progress

[1547] Once a user begins learning, the device records the user's progress (e.g., answer results, learning time, etc.).

[1548] The server receives the recorded learning progress data and analyzes it. For example, it might identify that the user makes many mistakes on trigonometry problems.

[1549] Feedback and suggestions for additional learning content

[1550] The server optimizes the next learning objectives based on the analysis results and provides feedback to the user.

[1551] The device displays information that allows the user to receive feedback and suggests additional learning content.

[1552] Designation of qualification exams and curriculum generation

[1553] If a user wants to take a specific certification exam, they specify that exam in the system.

[1554] The server generates a curriculum corresponding to the specified certification exam and adds it to the user's dashboard.

[1555] Implementation and analysis of mock exams

[1556] The device allows the user to start the practice exam and manages the exam time.

[1557] Users take a practice test and submit their answers.

[1558] The server analyzes the results of the practice test and suggests additional learning content for areas that require particular improvement.

[1559] Using an Emotion Engine

[1560] The device uses user input information and behavioral data (facial expressions, voice, etc.) to send data to the emotion engine.

[1561] The server uses an emotion engine to recognize the user's emotions and stores the results.

[1562] The server adjusts the content of the learning program and the feedback based on the recognized emotion data. For example, if the user is feeling stressed, it will suggest a break to help them relax.

[1563] The device displays emotion-based learning content and feedback to the user.

[1564] Specific example

[1565] For example, if a 15-year-old high school sophomore wants to improve their math skills and experiences stress while learning, the system will work as follows:

[1566] 1. The user enters and submits user information on the terminal, and the server generates a profile.

[1567] 2. The server automatically generates math materials and practice problems for second-year high school students and displays them on the user's dashboard.

[1568] 3. The user begins learning, and the device records their progress and emotional data.

[1569] 4. The server analyzes progress data and emotional data, and if it determines, for example, that the user is feeling stressed, it suggests additional problems to strengthen that area, along with a break to help them relax.

[1570] 5. The server reflects the generated additional learning materials and break times on the dashboard.

[1571] 6. The user reviews the feedback and sets the next learning objectives.

[1572] With the above configuration and operation, this system can continuously provide optimal content according to the user's learning needs and emotional state.

[1573] The following describes the processing flow.

[1574] Step 1:

[1575] The device displays a registration form for users to enter their name, age, grade level, and desired subjects when they first access the system.

[1576] Step 2:

[1577] The user enters the required information into the registration form and clicks "Register".

[1578] Step 3:

[1579] The terminal sends the entered information to the server.

[1580] Step 4:

[1581] The server receives the transmitted information and stores it in the database.

[1582] Step 5:

[1583] The server generates a user ID and password and sends them to the terminal.

[1584] Step 6:

[1585] The device displays the user ID and password and redirects the user to the dashboard screen.

[1586] Step 7:

[1587] The server generates a learning profile based on registered user information. Example: "High school sophomore," "Want to improve math skills."

[1588] Step 8:

[1589] The server automatically generates a customized learning program based on the user's learning profile and displays it on the user's dashboard.

[1590] Step 9:

[1591] The device allows the user to access the learning program from the dashboard and begin learning.

[1592] Step 10:

[1593] Once a user begins learning, the device records the user's progress (answers, study time, etc.).

[1594] Step 11:

[1595] The device transmits recorded progress data, along with the user's facial expressions and voice data, to the server.

[1596] Step 12:

[1597] The server receives progress data and sentiment data analyzed by the sentiment engine, and then analyzes that data. For example, it might identify that the user is making many mistakes on trigonometry problems or that they are feeling stressed.

[1598] Step 13:

[1599] The server optimizes the next learning session based on the analysis results and generates additional supplementary materials and practice problems. It also generates relaxation suggestions and motivational messages based on emotional data.

[1600] Step 14:

[1601] The server displays the generated additional learning materials, practice problems, and suggested breaks and messages on the user's dashboard.

[1602] Step 15:

[1603] The device notifies the user of updated learning programs, suggested breaks, and messages, and displays them as feedback.

[1604] Step 16:

[1605] The user reviews the feedback and sets their next learning goals.

[1606] Step 17:

[1607] If a user wants to take a certification exam, the device provides a form for them to enter their exam information.

[1608] Step 18:

[1609] The user enters the desired qualification exam (e.g., "TOEIC") and submits it.

[1610] Step 19:

[1611] The server receives the entered qualification exam information, generates the corresponding curriculum, and adds it to the dashboard.

[1612] Step 20:

[1613] The device is configured to allow users to start a practice test and also provides a time management tool for the test.

[1614] Step 21:

[1615] Users take a practice test and submit their answers.

[1616] Step 22:

[1617] The server analyzes the results of the practice test and evaluates the level of understanding and proficiency in specific areas.

[1618] Step 23:

[1619] Based on the results of the practice test and the user's sentiment data, the server suggests additional learning content for areas where the user needs to improve, and reflects this on the dashboard.

[1620] Step 24:

[1621] The device notifies the user of additional learning content and guides them to proceed to the next learning step.

[1622] Through these steps, the system provides optimal learning support tailored to the user's learning needs and emotional state.

[1623] (Example 2)

[1624] Next, we will describe Example 2. 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."

[1625] In modern education systems, there is a challenge in ensuring that users have equal learning opportunities regardless of income, location, or personal disadvantages. Furthermore, there is a need to automatically generate learning programs tailored to each learner's progress and understanding, and to provide appropriate feedback. Additionally, there is a lack of technology to provide flexible learning support that considers learners' emotional states and reduces stress and fatigue.

[1626] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring information input by the user, means for generating a user learning profile based on the acquired information, means for automatically generating and providing a learning program according to the user's learning profile, means for recording the user's learning progress, means for analyzing the recorded learning progress data and optimizing the next learning content, means for suggesting feedback and additional learning content to the user, means for acquiring the user's emotional data, and means for adjusting the learning content based on the acquired emotional data. This makes it possible to provide optimal learning support that is tailored to the individual user's learning needs and emotional state.

[1627] "Means for obtaining user-inputted information" refers to the interface and related technologies used to collect data from users who input information such as their name, age, grade level, and desired subjects of study.

[1628] "Means for generating a user's learning profile based on acquired information" refers to technologies and methods for analyzing and processing acquired user information to create a profile based on individual learning needs.

[1629] "Means for automatically generating and providing learning programs tailored to a user's learning profile" refers to a system and technology for automatically generating optimal learning materials and assignments based on each user's learning profile and providing them to the user.

[1630] "Means for recording user learning progress" refers to technologies and methods for recording progress information such as learning activities performed by the user, answer results, and learning time.

[1631] "Means for analyzing recorded learning progress data and optimizing the next learning content" refers to technologies and methods that analyze recorded learning progress data and optimize the next learning content based on the user's level of understanding and progress.

[1632] "Means for providing users with feedback and suggesting additional learning content" refers to techniques and methods for providing users with appropriate feedback based on analysis results and for suggesting any additional learning content they may need.

[1633] "Means for acquiring user emotional data" refers to technologies and methods for analyzing a user's facial expressions, voice, etc., to recognize their emotional state and collect that emotional data.

[1634] "Means for adjusting learning content based on acquired emotional data" refers to technologies and methods for adjusting learning programs and feedback content based on acquired user emotional data.

[1635] "Means for specifying qualification exams" refers to the interface and related technologies for users to select and specify the qualification exams they wish to take.

[1636] "Means for generating and providing a curriculum corresponding to a specified qualification examination" refers to a system and technology for generating a curriculum corresponding to a qualification examination specified by the user and providing it to the user.

[1637] "Means of conducting a mock exam" refers to the technology and methods for a user to start a mock exam and take the test.

[1638] "Methods for analyzing mock exam results and proposing additional learning content" refers to techniques and methods for analyzing mock exam results and proposing additional learning content, particularly in areas that require strengthening.

[1639] "Means for managing the time of a mock exam" refers to the technology and methods for managing the exam time during a mock exam and notifying the user at the appropriate time.

[1640] This invention is an educational support system designed to ensure that users have equal learning opportunities regardless of income, location, or personal disadvantages. The system supports effective learning by providing individualized support based on the user's learning needs, managing learning progress, and offering feedback. Furthermore, it incorporates an emotion engine to recognize the user's emotions and provide feedback and adjustments accordingly.

[1641] System Configuration

[1642] This system has the following main functions:

[1643] 1. Means of obtaining information entered by the user

[1644] 2. Generating a learning profile

[1645] 3. Automatic generation and provision of learning programs

[1646] 4. Recording and analyzing learning progress

[1647] 5. Feedback and suggestions for additional learning content

[1648] 6. Designation of qualification examinations and curriculum development

[1649] 7. Implementation and analysis of mock exams

[1650] 8. Emotion engine that recognizes user emotions

[1651] 9. Adjusting learning content using emotional data

[1652] Specific operation of the system

[1653] User registration and information retrieval

[1654] The terminal displays a form for first-time users to enter their name, age, grade level, and desired subjects. For example, an HTML form could be used to allow users to input this information.

[1655] The user enters this information and presses the register button.

[1656] The server receives the input information using PHP or Node.js, stores it in a database such as MySQL or PostgreSQL, and generates a user ID and password.

[1657] Generating a learning profile

[1658] The server uses libraries such as Python's scikit-learn and pandas to generate learning profiles based on registered user information. For example, it might generate a profile for someone who says, "I'm a second-year high school student and I want to improve my math skills."

[1659] Automatic generation and provision of learning programs

[1660] The server automatically generates individually customized training programs based on the generated training profiles. This is achieved using a Python generative AI model.

[1661] The device uses front-end frameworks such as React.js or Vue.js to display the generated learning program on the user's dashboard, allowing the user to begin learning.

[1662] Recording and analyzing learning progress

[1663] When a user begins learning, the device uses JavaScript or HTML5's LocalStorage to record the user's progress, such as answer results and learning time, in real time.

[1664] The server receives recorded learning progress data and analyzes it using data analysis tools such as Python or R. For example, it saves data on when a user made a mistake on a particular problem and analyzes the patterns using a machine learning model.

[1665] Feedback and suggestions for additional learning content

[1666] The server uses a machine learning model to generate feedback based on the analysis results. This feedback includes suggestions for improvement and additional learning content for the user.

[1667] The device displays the feedback to the user in real time.

[1668] Designation of qualification exams and curriculum generation

[1669] The user selects the certification they wish to take from a list of certification exams configured within the system.

[1670] The server generates a curriculum corresponding to the selected qualification and adds it to the user's dashboard.

[1671] Implementation and analysis of mock exams

[1672] The device displays an interface for starting the mock exam and also supports time management. It records the progress of the exam in real time.

[1673] Users take a practice test and submit their results to the server.

[1674] The server analyzes the test results, identifies areas for improvement, and proposes revised learning content.

[1675] Using an Emotion Engine

[1676] The device captures the user's facial expressions with its camera and collects audio data. This data is then sent to the emotion engine.

[1677] The server analyzes the user's emotions using an emotion engine and stores the results. For example, it might use Google Cloud Emotion AI.

[1678] The server adjusts the learning program and feedback based on the analysis results. For example, if the user is feeling stressed, it suggests content to help them relax.

[1679] The device displays adjusted feedback and learning content to the user.

[1680] Specific example

[1681] For example, if a 15-year-old high school sophomore wants to improve their math skills and experiences stress while learning, the system will work as follows:

[1682] 1. The user enters and submits user information on the terminal, and the server generates a profile.

[1683] 2. The server automatically generates math materials and practice problems for second-year high school students and displays them on the user's dashboard.

[1684] 3. The user begins learning, and the device records their progress and emotional data.

[1685] 4. The server analyzes progress data and emotional data, and if it determines, for example, that the user is feeling stressed, it suggests additional problems to strengthen that area, along with a break to help them relax.

[1686] 5. The server reflects the generated additional learning materials and break times on the dashboard.

[1687] 6. The user reviews the feedback and sets the next learning objective.

[1688] Example of a prompt

[1689] "A 15-year-old high school sophomore wants to improve their math skills. They are experiencing stress while learning; please generate prompts explaining how the system can help them."

[1690] As described above, the educational support system of the present invention can provide optimal content according to the user's learning needs and emotional state.

[1691] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1692] Step 1:

[1693] The terminal displays a form for first-time users to enter their name, age, grade level, and desired subjects. Once the user enters information into the form, that data is sent to the server using JavaScript (input: user information, output: sent data).

[1694] Step 2:

[1695] The server stores the received user information in a database and generates a user ID and password. For example, you can access the database and save the information using PHP or Node.js (input: user information, output: user ID and password).

[1696] Step 3:

[1697] The server uses Python libraries such as scikit-learn and pandas to generate learning profiles based on registered user information. This uses data such as the user's grade level and the subjects they want to strengthen (input: user information, output: learning profile).

[1698] Step 4:

[1699] The server automatically generates individually customized learning programs based on the generated learning profiles. Here, a generative AI model (e.g., GPT-3) is used to generate the learning plan and learning materials (input: learning profile, output: learning program).

[1700] Step 5:

[1701] The terminal displays the generated learning program on the user's dashboard, allowing the user to begin learning. Frontend frameworks such as React.js and Vue.js are used (input: learning program, output: dashboard display).

[1702] Step 6:

[1703] When a user begins learning, the device uses JavaScript or HTML5's LocalStorage to record the user's progress in real time, including their answers and learning time (input: user's learning activity, output: progress data).

[1704] Step 7:

[1705] The server receives recorded learning progress data and analyzes it using data analysis tools such as Python or R. For example, it can analyze if a user repeatedly makes mistakes on a particular problem (input: progress data, output: analysis results).

[1706] Step 8:

[1707] The server uses a machine learning model to generate feedback based on the analysis results. This feedback includes points to check and areas for improvement (input: analysis results, output: feedback).

[1708] Step 9:

[1709] The device displays the feedback content to the user in real time (input: feedback, output: feedback display).

[1710] Step 10:

[1711] The user selects the qualification they wish to take from a list of qualification exams within the system (Input: Selection of qualification exam, Output: Specified qualification exam).

[1712] Step 11:

[1713] The server generates a curriculum corresponding to the selected qualification and adds it to the user's dashboard (input: specified qualification exam, output: curriculum).

[1714] Step 12:

[1715] The terminal displays an interface for starting the mock exam and manages the exam progress and time in real time (input: start of mock exam, output: progress of mock exam).

[1716] Step 13:

[1717] Users take a practice test and submit their results to the server (input: practice test answers, output: practice test results).

[1718] Step 14:

[1719] The server analyzes the results of the mock exam and suggests additional learning content for areas that need improvement (Input: Mock exam results, Output: Suggested additional learning content).

[1720] Step 15:

[1721] The device captures the user's facial expressions with its camera and collects audio data. This data is then sent to the emotion engine (input: facial expressions and audio data, output: emotion data).

[1722] Step 16:

[1723] The server uses an emotion engine to analyze the user's emotions and stores the results in a database (input: emotion data, output: analysis results).

[1724] Step 17:

[1725] The server adjusts the learning program and feedback based on the acquired emotional data. If stress is detected, it suggests content to help the user relax (input: analysis results, output: adjusted learning program and feedback).

[1726] Step 18:

[1727] The device displays the user with adjusted feedback and learning content (input: adjusted learning program and feedback, output: feedback display).

[1728] (Application Example 2)

[1729] Next, we will explain application example 2. In the following explanation, 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."

[1730] Traditional learning support systems have the drawback of not maximizing learning effectiveness because they provide uniform learning programs and feedback without considering the learner's emotional state. Furthermore, there was no way to determine in real time how much stress or fatigue a learner was experiencing with each subject. These challenges made it difficult to provide optimal learning support based on the individual characteristics and emotional state of each learner.

[1731] The specific processing performed 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 means for acquiring information input by the user, means for generating a user learning profile based on the acquired information, means for automatically generating and providing a learning program according to the user's learning profile, means for recording the user's learning progress, means for analyzing the recorded learning progress data and optimizing the next learning content, means for suggesting feedback and additional learning content to the user, means for recognizing the user's emotions, and means for adjusting the learning content using the recognized emotion data. This makes it possible to grasp the learner's emotional state in real time and flexibly adjust the learning program and feedback based on that.

[1732] "User information acquisition method" refers to a means of acquiring basic information such as the learner's name, age, grade level, and desired subjects to study.

[1733] A "learning profile generation means" is a means for generating an optimal learning profile for each individual learner based on acquired user information.

[1734] A "learning program generation means" is a means for automatically generating and providing a learning program that is individually customized according to the generated learning profile.

[1735] A "learning progress recording device" is a means of recording a learner's learning activities and progress.

[1736] A "learning progress analysis tool" is a means of analyzing recorded learning progress data to optimize the content of the next learning session.

[1737] A "feedback suggestion method" is a means of providing learners with feedback on the next learning steps or areas for improvement based on the analysis results.

[1738] "Means of emotional recognition" are means of recognizing a learner's emotional state from their facial expressions, voice, etc.

[1739] "Emotional data adjustment means" refers to a means of adjusting learning content and feedback using recognized emotional data.

[1740] A "means of designating a qualification examination" refers to a means by which learners can designate a specific qualification examination.

[1741] A "curriculum generation method" is a means for generating and providing a curriculum corresponding to a designated qualification examination.

[1742] "Methods for conducting mock examinations" refers to the means for conducting mock examinations and recording and analyzing the results.

[1743] "Time management methods" refer to the means by which learners manage the time they spend taking practice exams.

[1744] The system that realizes this invention generates a user's learning profile, provides a customized learning program, and optimizes the learning experience by utilizing emotion recognition. The system mainly consists of the following elements:

[1745] 1. Obtaining user information

[1746] Users enter basic information such as their name, age, grade level, and desired subjects using their smartphones or tablets. The device retrieves this information and sends it to a cloud server. This information is stored in a database on the server (e.g., MySQL, MongoDB, etc.).

[1747] 2. Generating a learning profile

[1748] The server generates a learning profile based on the acquired user information. This profile reflects specific learning needs, such as "I want to improve my math skills as a second-year high school student." A user ID and password are also generated using Python or the Django framework.

[1749] 3. Automatic generation and provision of learning programs

[1750] The server automatically generates a customized learning program based on the generated learning profile. This learning program is reflected in the user's dashboard, and the user can access it to begin learning. Custom algorithms and generative AI models can be used to create the learning program.

[1751] 4. Recording and analyzing learning progress

[1752] Users progress through the learning process using their devices, and their progress data (such as answer results and learning time) is recorded. The devices send this data to a server, which analyzes it using Python and Pandas. Based on specific problem areas and progress, the server optimizes the next learning content.

[1753] 5. Feedback and suggestions for additional learning content

[1754] Based on the analysis results, the server suggests optimal feedback and additional learning content to the user. This is displayed on the user's dashboard to assist with the next learning steps.

[1755] 6. Optimization through emotion recognition

[1756] The device uses its camera and microphone to capture facial expressions and voice to recognize the user's emotional state. This data is analyzed by an emotion recognition model (e.g., TensorFlow) and the emotional state is sent to a server. The server uses this emotional data to adjust the learning program and provide feedback.

[1757] Specific example

[1758] For example, suppose a 15-year-old high school sophomore is using this system to improve their math skills. The user first enters their name, grade level, and desired subjects via smartphone, and a learning profile is generated based on this information. As the user progresses, the system records and analyzes their progress. Furthermore, if the user is experiencing stress during their studies, an emotion recognition engine identifies this, and the server suggests a break to help them relax.

[1759] Example of a prompt

[1760] The following prompts are used when configuring the emotion recognition engine:

[1761] python

[1762] Import necessary

[1763] import cv2

[1764] import tensorflow as tf

[1765] Load pre-trained model

[1766] model = tf.keras.models.load_model('emotion_recognition_model.h5')

[1767] Capture video from webcam

[1768] cap = cv2.VideoCapture(0)

[1769] while True:

[1770] ret, frame = cap.read()

[1771] if not ret:

[1772] break

[1773] Process frame for emotion recognition

[1774] gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

[1775] face = cv2.resize(gray, (48, 48))

[1776] face = face.reshape(1, 48, 48, 1) / 255.0

[1777] Predict emotion

[1778] emotion = model.predict(face)

[1779] print(f"Detected emotion: {emotion}")

[1780] Display the frame

[1781] cv2.imshow('Emotion Recognition', frame)

[1782] if cv2.waitKey(1) & 0xFF == ord('q'):

[1783] break

[1784] cap.release()

[1785] cv2.destroyAllWindows()

[1786] In this way, a learning support system that combines emotion recognition can provide individualized and flexible support to learners.

[1787] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1788] Step 1:

[1789] Users enter basic information such as their name, age, grade level, and desired subjects using their smartphones or tablets. This information is then sent from the device to a cloud server. The server stores the received information in a database (e.g., MySQL, MongoDB). The input is the user's basic information, and the output is the storage of user information on the cloud server.

[1790] Step 2:

[1791] The server generates a learning profile based on stored user information. This learning profile includes details such as the student's grade level and subject level. This allows for the creation of a specific profile, such as "I'm a second-year high school student and I want to improve my math skills." The input is the user's basic information, and the output is the generated learning profile.

[1792] Step 3:

[1793] The server automatically generates a customized learning program based on the generated learning profile. During this process, it creates optimal learning content using custom algorithms and generative AI models. The generated learning program is reflected in the user's dashboard. The input is the learning profile, and the output is the customized learning program.

[1794] Step 4:

[1795] Users access the learning program from the dashboard and proceed with their studies. The device records the user's learning progress data (e.g., answer results, study time) and sends it to the cloud server. The server receives this data and stores it in a database. The input is the user's learning progress data, and the output is the transmission and storage of data to the server.

[1796] Step 5:

[1797] The server analyzes the recorded learning progress data using Python or Pandas. This analysis identifies specific problem areas and areas of progress for the user. For example, it identifies areas where many incorrect answers are observed. The input is the recorded learning progress data, and the output is the analysis results.

[1798] Step 6:

[1799] Based on the analysis results, the server suggests optimal feedback and additional learning content to the user. This content is displayed on the user's dashboard. The input is the analysis results, and the output is the feedback and additional learning content.

[1800] Step 7:

[1801] The device uses its camera and microphone to capture facial expressions and voice to recognize the user's emotional state. The captured data is analyzed by an emotion recognition model (e.g., TensorFlow) to identify the emotional state. The input is facial expression and voice data, and the output is recognized emotion data.

[1802] Step 8:

[1803] The server adjusts its learning content and feedback based on the recognized emotion data. For example, if the user is feeling stressed, it suggests taking a break to relax. The input is the recognized emotion data, and the output is the adjusted learning content and feedback.

[1804] Step 9:

[1805] The user reviews feedback and adjusted learning content from their device and sets the next learning step. This makes learning more effective. The input is the adjusted learning content and feedback, and the output is the setting of the next learning step.

[1806] The above describes the specific processing flow of the system that realizes this invention.

[1807] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1808] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio 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 specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1810] [Fourth Embodiment]

[1811] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1812] As shown in Figure 7, the 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 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is 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 interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1815] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the 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 image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1817] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1818] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1819] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1820] The specific processing program 56 is an example of a "program" relating to the technology of this 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 the data generation model 58 and the 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 robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1823] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1824] This invention is an educational support system designed to ensure that users have equal learning opportunities regardless of income, location, or personal disadvantages. The system supports effective learning by providing individualized support based on users' learning needs, managing learning progress, and offering feedback.

[1825] System Configuration

[1826] This system has the following main functions:

[1827] 1. Means of obtaining information entered by the user

[1828] 2. Generating a learning profile

[1829] 3. Automatic generation and provision of learning programs

[1830] 4. Recording and analyzing learning progress

[1831] 5. Feedback and suggestions for additional learning content

[1832] 6. Designation of qualification examinations and curriculum development

[1833] 7. Implementation and analysis of mock exams

[1834] Specific operation of the system

[1835] User registration and information retrieval

[1836] The terminal displays a form for first-time users to enter their name, age, grade level, and desired subjects.

[1837] The user enters this information and presses the register button.

[1838] The server receives the entered information, stores it in the database, and generates a user ID and password.

[1839] Generating a learning profile

[1840] The server generates a learning profile based on the registered user information. For example, a profile might be created for a second-year high school student who wants to improve their math skills.

[1841] Automatic generation and provision of learning programs

[1842] The server automatically generates a customized learning program based on the generated learning profile and displays it on the user's dashboard.

[1843] The device allows users to access the learning program from the dashboard and begin learning.

[1844] Recording and analyzing learning progress

[1845] As the user progresses through the learning process, the device records the user's progress.

[1846] The server receives the recorded learning progress data and analyzes it. For example, it might identify that the user makes many mistakes on trigonometry problems.

[1847] Feedback and suggestions for additional learning content

[1848] The server optimizes the next learning objectives based on the analysis results and provides feedback to the user.

[1849] The device displays information that allows the user to receive feedback and suggests additional learning content.

[1850] Designation of qualification exams and curriculum generation

[1851] If a user wants to take a specific certification exam, they specify that exam in the system.

[1852] The server generates a curriculum corresponding to the specified certification exam and adds it to the user's dashboard.

[1853] Implementation and analysis of mock exams

[1854] The device allows the user to start the practice exam and manages the exam time.

[1855] Users take a practice test and submit their answers.

[1856] The server analyzes the results of the practice test and suggests additional learning content for areas that require particular improvement.

[1857] Specific example

[1858] For example, if a user is a 15-year-old high school sophomore and wants to improve their math skills, the system will work as follows:

[1859] 1. The user enters and submits user information on the terminal, and the server generates a profile.

[1860] 2. The server automatically generates math materials and practice problems for second-year high school students and displays them on the user's dashboard.

[1861] 3. The user begins learning, and the device records their progress.

[1862] 4. The server analyzes the progress data and, for example, if it determines that there is a lack of understanding of trigonometry, it generates additional problems to strengthen that area and adds them to the dashboard.

[1863] 5. The user solves additional problems, the results are further analyzed, and appropriate feedback and suggestions for the next learning activities are provided.

[1864] With the above configuration and operation, this system can provide learning support tailored to the individual needs of users, thereby improving the efficiency and effectiveness of learning.

[1865] The following describes the processing flow.

[1866] Step 1:

[1867] When a user accesses the system for the first time, the device displays a registration form for them to enter their name, age, grade level, and desired subjects.

[1868] Step 2:

[1869] The user fills in the required information on the form and clicks "Register".

[1870] Step 3:

[1871] The terminal sends the entered information to the server.

[1872] Step 4:

[1873] The server receives the transmitted information and stores it in the database.

[1874] Step 5:

[1875] The server generates a user ID and password and sends them to the user.

[1876] Step 6:

[1877] The device displays the user ID and password and redirects the user to the dashboard screen.

[1878] Step 7:

[1879] The server generates a learning profile based on user profile information. For example, this includes information such as "high school sophomore" and "desire to improve math skills."

[1880] Step 8:

[1881] The server automatically generates a customized learning program based on the user's learning profile and displays it on the user's dashboard.

[1882] Step 9:

[1883] The device allows the user to access the learning program from the dashboard and begin learning.

[1884] Step 10:

[1885] Once a user begins learning, the device records the user's progress (e.g., answer results, learning time, etc.).

[1886] Step 11:

[1887] The terminal sends the recorded progress data to the server.

[1888] Step 12:

[1889] The server analyzes progress data and identifies areas where the user should focus their efforts. For example, it might extract data such as "there are many mistakes in trigonometry problems."

[1890] Step 13:

[1891] Based on the analysis results, the server optimizes the content for the next lesson and generates additional supplementary materials and practice problems.

[1892] Step 14:

[1893] The server displays the generated additional learning materials and practice problems on the user's dashboard.

[1894] Step 15:

[1895] The device notifies the user of updated learning programs and displays them as feedback.

[1896] Step 16:

[1897] The user reviews the feedback and sets their next learning goals.

[1898] Step 17:

[1899] If a user wishes to take a certification exam, the device provides a form for entering exam information.

[1900] Step 18:

[1901] The user enters the desired qualification exam (e.g., "TOEIC") and submits it.

[1902] Step 19:

[1903] The server receives the entered qualification exam information, generates the corresponding curriculum, and adds it to the dashboard.

[1904] Step 20:

[1905] The device is configured to allow the user to start a practice exam and provides time management tools for the exam.

[1906] Step 21:

[1907] Users take a practice test and submit their answers.

[1908] Step 22:

[1909] The server analyzes the results of the practice test and evaluates the level of understanding and proficiency in specific areas.

[1910] Step 23:

[1911] Based on the results of the practice test, the server suggests additional learning content for areas where the user needs to improve, and reflects this on the dashboard.

[1912] Step 24:

[1913] The device notifies the user of additional learning content and guides them to proceed to the next learning step.

[1914] By following these steps, the system can continuously provide the most suitable content for the user's learning needs and progress.

[1915] (Example 1)

[1916] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1917] Modern education systems struggle to meet the individual learning needs of users, particularly due to unequal access to learning opportunities caused by income, location, and personal disadvantages. Furthermore, traditional learning systems often fail to effectively track learning progress and provide feedback, making it difficult to offer optimal learning programs for individual users. As a result, users are unable to learn efficiently and achieve their goals.

[1918] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1919] In this invention, the server includes means for acquiring information entered by the user, means for generating a user learning profile based on the acquired information, means for automatically generating and providing a learning program according to the user's learning profile, means for recording the user's learning progress, means for analyzing the recorded learning progress data and optimizing the next learning content, means for suggesting feedback and additional learning content to the user, means for storing user information and learning progress data in a database, means for reflecting the learning program and feedback on the user's dashboard, means for the user to take a mock exam and submit the results, and means for analyzing the results of the mock exam and suggesting improvements in specific areas. This enables users to learn fairly and efficiently and provides optimal educational support tailored to each individual's learning needs.

[1920] "Means of acquiring user-inputted information" refers to devices and software that collect and store information that users input into the system, such as their name, age, grade level, and subjects they wish to study.

[1921] "Means for generating a user's learning profile based on acquired information" refers to algorithms and programs that create a learning profile that reflects the individual user's learning needs and goals, based on the information provided by the user.

[1922] "Means for automatically generating and providing learning programs tailored to a user's learning profile" refers to a system that automatically creates and provides optimal learning content and activities to the user based on the generated learning profile.

[1923] "Means for recording user learning progress" refers to devices or programs that have the function of continuously recording the progress and answer results achieved by a user during the learning process.

[1924] "Means for analyzing recorded learning progress data and optimizing the next learning content" refers to algorithms and programs that analyze collected learning progress data to understand the user's level of comprehension and weaknesses, and determine the optimal content for the next learning session.

[1925] "Means of providing users with feedback and suggesting additional learning content" refers to devices or software that have the functionality to provide users with specific feedback based on analyzed learning progress data and to suggest any additional learning content they may need.

[1926] "Means for storing user information and learning progress data in a database" refers to a system that records user-entered information and learning progress data in a database and manages it so that it can be referenced later as needed.

[1927] "Means of reflecting learning programs and feedback on the user's dashboard" refers to a system that has an interface on the dashboard that allows users to see their learning progress and feedback at a glance.

[1928] "Means for users to take a practice test and submit the results" refers to devices or programs that have the function of allowing users to take a practice test and submit the results to a system.

[1929] "Methods for analyzing mock exam results and suggesting improvements in specific areas" refers to algorithms or programs that scrutinize the results of mock exams taken by users, identify specific areas that need improvement, and suggest additional learning content for those areas.

[1930] This invention is an educational support system designed to ensure that users have equal learning opportunities regardless of income, location, or personal disadvantages. The system has the following main functions:

[1931] User registration and information retrieval

[1932] The terminal displays a form for new users to enter information such as their name, age, grade level, and desired subjects. This form is accessed via a web browser or a dedicated application.

[1933] The user enters the required information and presses the "Register" button to submit the information.

[1934] The server receives the transmitted information and stores it in a database (such as MySQL or PostgreSQL). It also generates a user ID and initial password and notifies the user.

[1935] Generating a learning profile

[1936] The server generates a learning profile based on the registered user information. This profile reflects the user's learning needs and goals.

[1937] For example, you can generate a profile using machine learning techniques with Python libraries (pandas, scikit-learn).

[1938] Automatic generation and provision of learning programs

[1939] The server automatically generates a customized learning program based on the generated profile. This program consists of appropriate learning materials and problem sets.

[1940] The server displays programs generated using a template engine (such as Jinja2) on the user's dashboard.

[1941] The device allows users to access the dashboard, view the learning program, and begin.

[1942] Recording and analyzing learning progress

[1943] As the user progresses through the learning process, the device records their progress in real time (e.g., answer status and accuracy rate). This record is temporarily saved using HTML5 local storage and JavaScript.

[1944] The device periodically sends this progress data to the server.

[1945] The server receives progress data and analyzes it using Python's pandas and numpy. For example, if a user makes many mistakes in a particular area (e.g., trigonometry), the server identifies that area.

[1946] Feedback and suggestions for additional learning content

[1947] The server optimizes the next learning content based on the analysis of progress data. This includes additional problems and materials to strengthen the user's weaknesses.

[1948] The device displays feedback and suggested additional learning content on the user's dashboard.

[1949] Designation of qualification exams and curriculum generation

[1950] If a user wants to take a specific certification exam (e.g., TOEIC), they specify that exam in the system.

[1951] The server generates a curriculum corresponding to the specified certification exam and provides it to the user's dashboard.

[1952] Implementation and analysis of mock exams

[1953] The device allows the user to start a practice test and manages the test time using a JavaScript timer function.

[1954] After taking a practice test, the user submits their answers.

[1955] The server analyzes the results and suggests additional learning content, particularly in areas that need strengthening.

[1956] Examples and prompts for generative AI models

[1957] For example, if a 15-year-old high school sophomore wants to improve their math skills, it would work as follows:

[1958] The user enters their information on the terminal, and the server generates a profile.

[1959] The server generates math materials and practice problems for second-year high school students and displays them on the user's dashboard.

[1960] The user begins learning, and the device records the learning progress and sends it to the server.

[1961] The server analyzes the progress data and, for example, if it determines that there is a lack of understanding of trigonometry, it generates additional problems and adds them to the dashboard.

[1962] The user solves additional problems, the results are analyzed, and the next learning objectives are suggested.

[1963] Examples of prompts for a generative AI model:

[1964] "I have a 15-year-old high school sophomore who wants to improve his math skills. Please create a customized learning program for him based on his current learning progress, with a particular focus on trigonometry."

[1965] In this way, the system provides comprehensive learning support tailored to the individual needs of users, thereby improving the efficiency and outcomes of their learning.

[1966] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1967] Step 1:

[1968] User registration and information retrieval

[1969] The device displays a form for the user to enter information such as their name, age, grade level, and the subjects they wish to study.

[1970] Input: User information (name, age, grade level, subject you want to study)

[1971] Output: Information entered by the user

[1972] The user enters the required information and presses the "Register" button to submit the information.

[1973] Input: User actions

[1974] Output: Sent user information

[1975] The server receives the transmitted user information and stores it in the database.

[1976] Input: Submitted user information

[1977] Data processing: Converting user information into a database format.

[1978] Output: User information stored in the database

[1979] The server generates a user ID and initial password and notifies the user.

[1980] Input: Saved user information

[1981] Data calculation: Generation of user ID and initial password

[1982] Output: User ID and initial password

[1983] Step 2:

[1984] Generating a learning profile

[1985] The server generates a learning profile based on the registered user information.

[1986] Input: User information stored in the database

[1987] Data processing: Generate profiles based on learning needs and grade level (e.g., using Python libraries pandas and scikit-learn).

[1988] Output: Generation of training profile

[1989] The server saves the generated profile to the database.

[1990] Input: Generated training profile

[1991] Data processing: Convert profile to database format

[1992] Output: Learning profiles stored in the database

[1993] Step 3:

[1994] Automatic generation and provision of learning programs

[1995] The server automatically generates a customized learning program based on the generated learning profile.

[1996] Input: Learning Profile

[1997] Data processing: Select appropriate teaching materials and problem sets, and design a learning program (using the Jinja2 template engine).

[1998] Output: Customized learning program

[1999] The server displays the generated learning program on the user's dashboard.

[2000] Input: Customized learning program

[2001] Output: The program reflected in the user's dashboard.

[2002] The device allows users to access the dashboard, view their learning programs, and begin.

[2003] Input: User actions

[2004] Output: Learning program displayed to the user

[2005] Step 4:

[2006] Recording and analyzing learning progress

[2007] As the user progresses through the learning process, the device records their progress in real time.

[2008] Input: User's learning activity data (answer results, progress)

[2009] Data processing: Save to local storage in real time.

[2010] Output: Recorded progress

[2011] The device periodically sends progress data to the server.

[2012] Input: Progress data stored in local storage

[2013] Output: Progress data sent to the server

[2014] The server receives and analyzes the progress data.

[2015] Input: Submitted progress data

[2016] Data processing: Analysis using data analysis tools (pandas, numpy).

[2017] Output: Analysis results (e.g., identification of weaknesses in a specific field)

[2018] Step 5:

[2019] Feedback and suggestions for additional learning content

[2020] The server optimizes the next learning steps based on the analysis results of the progress data.

[2021] Input: Analysis results of progress data

[2022] Data processing: Generating feedback content and additional learning content.

[2023] Output: Next learning content

[2024] The device displays feedback and additional learning content on the user's dashboard.

[2025] Input: Generated feedback content and additional learning content

[2026] Output: Feedback and additional learning content displayed on the dashboard

[2027] Step 6:

[2028] Designation of qualification exams and curriculum generation

[2029] If a user wants to take a specific certification exam, they specify that exam in the system.

[2030] Input: Specified information for the qualification exam

[2031] Output: Qualification exam information set in the system

[2032] The server generates a curriculum corresponding to the specified certification exam and provides it to the user's dashboard.

[2033] Input: Specified information for the qualification exam

[2034] Data processing: Automatic generation of curriculum

[2035] Output: Curriculum added to the user's dashboard

[2036] Step 7:

[2037] Implementation and analysis of mock exams

[2038] The device allows the user to start the practice exam and manages the exam time.

[2039] Input: User action (start of mock exam)

[2040] Data calculation: Using JavaScript's timer function

[2041] Output: Start of mock exam and time management

[2042] Users take a practice test and submit their answers.

[2043] Input: User's answer

[2044] Output: Submitted answer data

[2045] The server analyzes the results of the practice test and suggests additional learning content for areas that require particular improvement.

[2046] Input: Submitted answer data

[2047] Data processing: Analysis of answer data

[2048] Output: Suggestions for strengthening specific areas and additional learning content

[2049] (Application Example 1)

[2050] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2051] Traditional education systems failed to adequately address users' diverse learning needs, lacking sufficient feedback based on learning progress and insufficient suggestions for optimal additional learning content. Furthermore, the provision of learning materials and progress management were not centralized, and there were challenges in conducting mock exams and effectively addressing weaknesses based on the results. Additionally, the lack of immediate feedback and suggestions for additional learning content prevented users from learning efficiently.

[2052] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[2053] In this invention, the server includes means for acquiring information entered by the user, means for generating a user learning profile based on the acquired information, means for automatically generating and providing a learning program according to the user's learning profile, means for recording the user's learning progress, means for analyzing the recorded learning progress data and optimizing the next learning content, means for suggesting feedback and additional learning content to the user, means for providing learning materials and online courses from a virtual store, means for generating a customized learning program based on purchased materials, means for analyzing the results of mock exams and suggesting a curriculum to reinforce weaknesses, and means for allowing the user to view their learning progress and feedback. As a result, the user can receive an optimal learning program tailored to their individual learning needs, easily acquire a variety of learning materials through the virtual store, and manage and improve their learning progress more efficiently and effectively.

[2054] "Means for obtaining user input" refers to an interface that allows users to input information such as their name, age, grade level, and subjects they wish to study, and then transmit that information to the system.

[2055] "Means for generating a user's learning profile based on acquired information" refers to a system that analyzes the acquired personal information of a user and creates a profile that takes into account the user's learning needs.

[2056] "A means of automatically generating and providing a learning program tailored to the user's learning profile" refers to a system that automatically creates an individualized learning plan based on the learning profile and provides it to the user.

[2057] A "means for recording user learning progress" refers to a system that records progress data such as how far a user has progressed during their learning and which tasks have been completed.

[2058] "A means of analyzing recorded learning progress data and optimizing the next learning content" refers to a system that analyzes collected learning progress data and adjusts the content to be learned next according to the user's level of understanding and weaknesses.

[2059] A "means of providing users with feedback and suggesting additional learning content" is a system that provides users with feedback based on their progress data, indicating which parts they understand and which parts they need to improve, and then suggests the necessary additional learning content.

[2060] "A means of providing learning materials and online courses from a virtual store" refers to a system that allows users to purchase and access various learning materials and online courses through an online store.

[2061] "A means of generating a customized learning program based on purchased learning materials" refers to a system that individually creates an optimal learning plan using the learning materials purchased by the user in a virtual store.

[2062] "A method for analyzing mock exam results and proposing a curriculum to strengthen weaknesses" refers to a system that thoroughly analyzes the results of mock exams taken by users, identifies their weaknesses, and then provides an additional curriculum to strengthen those weaknesses.

[2063] "Means for users to view their learning progress and feedback" refers to the interface that users use to check their learning progress and feedback from the system.

[2064] This invention is an educational support system for acquiring information entered by a user and generating, providing, and managing individualized learning programs based on that information. This system supports efficient learning by recording and analyzing the user's learning progress and optimizing the next learning content.

[2065] System Configuration

[2066] 1. User registration and information acquisition

[2067] When a user accesses the server for the first time, it displays a personal information input form on the user's device. The user enters information such as their name, age, grade level, and desired subjects, and submits the form. The server stores the received information in a database and generates a user ID and password.

[2068] 2. Generating a learning profile

[2069] The server generates individual learning profiles for each user based on the registered user information. For example, a profile might be created that indicates a high level of motivation to learn a particular subject.

[2070] 3. Automatic generation and provision of learning programs

[2071] The server automatically generates a customized learning program based on the generated learning profile and displays it on the user's dashboard. The user accesses the learning program through their terminal and begins learning.

[2072] 4. Recording and analyzing learning progress

[2073] As the user progresses through the learning process, the device records the user's progress. The server receives the recorded learning progress data and analyzes it. For example, if a user makes many incorrect answers in a particular area, that data will be extracted.

[2074] 5. Feedback and suggestions for additional learning content

[2075] The server optimizes the next learning content based on the analysis results and provides feedback to the user. The terminal displays the feedback to the user and suggests additional learning content.

[2076] 6. Provision of educational materials from virtual stores

[2077] The server provides users with learning materials and online courses tailored to their needs through a virtual store. Users can purchase these within the app and incorporate them into their learning programs.

[2078] 7. Generating a customized learning program

[2079] The server generates a customized learning program based on the purchased learning materials and provides it to the user.

[2080] 8. Analysis of mock exam results and strengthening of weak points

[2081] The server receives the results of the mock exam and analyzes them in detail. Based on this, it identifies the user's weaknesses and proposes a curriculum to strengthen those weaknesses.

[2082] 9. View learning progress and feedback

[2083] Users can view their learning progress and feedback from the system through their device.

[2084] Specific example

[2085] For example, if a high school sophomore user wants to improve their math skills, the system will work as follows:

[2086] 1. The user enters and submits personal information on their device. The server generates a learning profile.

[2087] 2. The server automatically generates math materials and practice problems for second-year high school students and displays them on the user's dashboard.

[2088] 3. The user purchases learning materials and proceeds with their studies. The device records their progress.

[2089] 4. The server analyzes the progress data and identifies areas where understanding is particularly lacking. For example, if mastery of trigonometry is insufficient, it generates additional problems to reinforce that area and adds them to the dashboard.

[2090] 5. The user solves additional problems, the results are analyzed, and appropriate feedback and suggestions for the next learning activities are provided.

[2091] Examples of prompts for generative AI models

[2092] "When a high school sophomore user was studying mathematics, they made many mistakes in a specific area. Therefore, additional problems are generated to strengthen that area, and these are reflected in the dashboard."

[2093] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[2094] Step 1:

[2095] When a user accesses the server for the first time, it displays a personal information input form on the terminal. The user enters information such as their name, age, grade level, and desired subjects, and submits the form. This input information is sent from the terminal to the server. The server stores the received information in a database and generates a user ID and password.

[2096] Step 2:

[2097] The server generates individual learning profiles for each user based on registered user information. These profiles include the user's age, grade level, and areas of interest. The generated profiles are stored in a database.

[2098] Step 3:

[2099] The server automatically generates a personalized learning program based on the generated learning profile. This program includes learning materials and practice exercises tailored to the user's grade level and interests. This learning program is reflected in the user's dashboard and provided to the user through their device.

[2100] Step 4:

[2101] The user accesses the learning program provided through the device and begins learning. The device records the user's learning progress in real time and sends this data to the server. The recorded progress data includes completed assignments and the accuracy of answers.

[2102] Step 5:

[2103] The server performs data analysis based on recorded learning progress data. The analysis identifies areas where the user frequently makes mistakes or where their understanding is lacking. The analysis results are stored in a database.

[2104] Step 6:

[2105] The server executes an algorithm to optimize the next learning content based on the analysis results. For example, if there is a lack of understanding in a particular area, it generates additional problems or learning materials related to that area. The generated learning content is added to the user's dashboard.

[2106] Step 7:

[2107] The device displays an interface that allows the user to view newly suggested learning content and feedback. The user then continues learning based on this information, and their progress is recorded and analyzed again.

[2108] Step 8:

[2109] The server provides users with various learning materials and online courses through a virtual store. Users purchase these materials through their devices, and the content is reflected in their learning programs.

[2110] Step 9:

[2111] The server generates a customized learning program based on the purchased learning materials. This generated program is reflected in the user's dashboard and provided as additional learning content.

[2112] Step 10:

[2113] The server analyzes the results of the practice exams taken by the user in detail. Based on the analysis, it identifies areas where the user's understanding is lacking and generates a curriculum to reinforce those weaknesses. This curriculum is also added to the user's dashboard.

[2114] Step 11:

[2115] The device allows users to view their learning progress and system feedback in real time. Users can then refer to this information to learn more efficiently.

[2116] Examples of prompts for generative AI models

[2117] "When a high school sophomore user was studying mathematics, they made many mistakes in a specific area. Therefore, additional problems are generated to strengthen that area, and these are reflected in the dashboard."

[2118] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[2119] This invention is an educational support system designed to ensure that users have equal learning opportunities regardless of income, location, or personal disadvantages. The system supports effective learning by providing individualized support based on the user's learning needs, managing learning progress, and offering feedback. Furthermore, the invention incorporates an emotion engine that recognizes the user's emotions and provides feedback and adjustments accordingly.

[2120] System Configuration

[2121] This system has the following main functions:

[2122] 1. Means of obtaining information entered by the user

[2123] 2. Generating a learning profile

[2124] 3. Automatic generation and provision of learning programs

[2125] 4. Recording and analyzing learning progress

[2126] 5. Feedback and suggestions for additional learning content

[2127] 6. Designation of qualification examinations and curriculum development

[2128] 7. Implementation and analysis of mock exams

[2129] 8. Emotion engine that recognizes user emotions

[2130] 9. Adjusting learning content using emotional data

[2131] Specific operation of the system

[2132] User registration and information retrieval

[2133] The terminal displays a form for first-time users to enter their name, age, grade level, and desired subjects.

[2134] The user enters this information and presses the register button.

[2135] The server receives the entered information, stores it in the database, and generates a user ID and password.

[2136] Generating a learning profile

[2137] The server generates a learning profile based on the registered user information. For example, a profile might be created stating, "I want to improve my math skills as a second-year high school student."

[2138] Automatic generation and provision of learning programs

[2139] The server automatically generates a customized learning program based on the generated learning profile and displays it on the user's dashboard.

[2140] The device allows the user to access the learning program from the dashboard and begin learning.

[2141] Recording and analyzing learning progress

[2142] Once a user begins learning, the device records the user's progress (e.g., answer results, learning time, etc.).

[2143] The server receives the recorded learning progress data and analyzes it. For example, it might identify that the user makes many mistakes on trigonometry problems.

[2144] Feedback and suggestions for additional learning content

[2145] The server optimizes the next learning objectives based on the analysis results and provides feedback to the user.

[2146] The device displays information that allows the user to receive feedback and suggests additional learning content.

[2147] Designation of qualification exams and curriculum generation

[2148] If a user wants to take a specific certification exam, they specify that exam in the system.

[2149] The server generates a curriculum corresponding to the specified certification exam and adds it to the user's dashboard.

[2150] Implementation and analysis of mock exams

[2151] The device allows the user to start the practice exam and manages the exam time.

[2152] Users take a practice test and submit their answers.

[2153] The server analyzes the results of the practice test and suggests additional learning content for areas that require particular improvement.

[2154] Using an Emotion Engine

[2155] The device uses user input information and behavioral data (facial expressions, voice, etc.) to send data to the emotion engine.

[2156] The server uses an emotion engine to recognize the user's emotions and stores the results.

[2157] The server adjusts the content of the learning program and the feedback based on the recognized emotion data. For example, if the user is feeling stressed, it will suggest a break to help them relax.

[2158] The device displays emotion-based learning content and feedback to the user.

[2159] Specific example

[2160] For example, if a 15-year-old high school sophomore wants to improve their math skills and experiences stress while learning, the system will work as follows:

[2161] 1. The user enters and submits user information on the terminal, and the server generates a profile.

[2162] 2. The server automatically generates math materials and practice problems for second-year high school students and displays them on the user's dashboard.

[2163] 3. The user begins learning, and the device records their progress and emotional data.

[2164] 4. The server analyzes progress data and emotional data, and if it determines, for example, that the user is feeling stressed, it suggests additional problems to strengthen that area, along with a break to help them relax.

[2165] 5. The server reflects the generated additional learning materials and break times on the dashboard.

[2166] 6. The user reviews the feedback and sets the next learning objectives.

[2167] With the above configuration and operation, this system can continuously provide optimal content according to the user's learning needs and emotional state.

[2168] The following describes the processing flow.

[2169] Step 1:

[2170] The device displays a registration form for users to enter their name, age, grade level, and desired subjects when they first access the system.

[2171] Step 2:

[2172] The user enters the required information into the registration form and clicks "Register".

[2173] Step 3:

[2174] The terminal sends the entered information to the server.

[2175] Step 4:

[2176] The server receives the transmitted information and stores it in the database.

[2177] Step 5:

[2178] The server generates a user ID and password and sends them to the terminal.

[2179] Step 6:

[2180] The device displays the user ID and password and redirects the user to the dashboard screen.

[2181] Step 7:

[2182] The server generates a learning profile based on registered user information. Example: "High school sophomore," "Want to improve math skills."

[2183] Step 8:

[2184] The server automatically generates a customized learning program based on the user's learning profile and displays it on the user's dashboard.

[2185] Step 9:

[2186] The device allows the user to access the learning program from the dashboard and begin learning.

[2187] Step 10:

[2188] Once a user begins learning, the device records the user's progress (answers, study time, etc.).

[2189] Step 11:

[2190] The device transmits recorded progress data, along with the user's facial expressions and voice data, to the server.

[2191] Step 12:

[2192] The server receives progress data and sentiment data analyzed by the sentiment engine, and then analyzes that data. For example, it might identify that the user is making many mistakes on trigonometry problems or is feeling stressed.

[2193] Step 13:

[2194] The server optimizes the next learning session based on the analysis results and generates additional supplementary materials and practice problems. It also generates relaxation suggestions and motivational messages based on emotional data.

[2195] Step 14:

[2196] The server displays the generated additional learning materials, practice problems, and suggested breaks and messages on the user's dashboard.

[2197] Step 15:

[2198] The device notifies the user of updated learning programs, suggested breaks, and messages, and displays them as feedback.

[2199] Step 16:

[2200] The user reviews the feedback and sets their next learning goals.

[2201] Step 17:

[2202] If a user wants to take a certification exam, the device provides a form for them to enter their exam information.

[2203] Step 18:

[2204] The user enters the desired qualification exam (e.g., "TOEIC") and submits it.

[2205] Step 19:

[2206] The server receives the entered qualification exam information, generates the corresponding curriculum, and adds it to the dashboard.

[2207] Step 20:

[2208] The device is configured to allow users to start a practice test and also provides a time management tool for the test.

[2209] Step 21:

[2210] Users take a practice test and submit their answers.

[2211] Step 22:

[2212] The server analyzes the results of the practice test and evaluates the level of understanding and proficiency in specific areas.

[2213] Step 23:

[2214] Based on the results of the practice test and the user's sentiment data, the server suggests additional learning content for areas where the user needs to improve, and reflects this on the dashboard.

[2215] Step 24:

[2216] The device notifies the user of additional learning content and guides them to proceed to the next learning step.

[2217] Through these steps, the system provides optimal learning support tailored to the user's learning needs and emotional state.

[2218] (Example 2)

[2219] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2220] In modern education systems, there is a challenge in ensuring that users have equal learning opportunities regardless of income, location, or personal disadvantages. Furthermore, there is a need to automatically generate learning programs tailored to each learner's progress and understanding, and to provide appropriate feedback. Additionally, there is a lack of technology to provide flexible learning support that considers learners' emotional states and reduces stress and fatigue.

[2221] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring information input by the user, means for generating a user learning profile based on the acquired information, means for automatically generating and providing a learning program according to the user's learning profile, means for recording the user's learning progress, means for analyzing the recorded learning progress data and optimizing the next learning content, means for suggesting feedback and additional learning content to the user, means for acquiring the user's emotional data, and means for adjusting the learning content based on the acquired emotional data. This makes it possible to provide optimal learning support that is tailored to the individual user's learning needs and emotional state.

[2222] "Means for obtaining user-inputted information" refers to the interface and related technologies used to collect data from users who input information such as their name, age, grade level, and desired subjects of study.

[2223] "Means for generating a user's learning profile based on acquired information" refers to technologies and methods for analyzing and processing acquired user information to create a profile based on individual learning needs.

[2224] "Means for automatically generating and providing learning programs tailored to a user's learning profile" refers to a system and technology for automatically generating optimal learning materials and assignments based on each user's learning profile and providing them to the user.

[2225] "Means for recording user learning progress" refers to technologies and methods for recording progress information such as learning activities performed by the user, answer results, and learning time.

[2226] "Means for analyzing recorded learning progress data and optimizing the next learning content" refers to technologies and methods that analyze recorded learning progress data and optimize the next learning content based on the user's level of understanding and progress.

[2227] "Means for providing users with feedback and suggesting additional learning content" refers to techniques and methods for providing users with appropriate feedback based on analysis results and for suggesting any additional learning content they may need.

[2228] "Means for acquiring user emotional data" refers to technologies and methods for analyzing a user's facial expressions, voice, etc., to recognize their emotional state and collect that emotional data.

[2229] "Means for adjusting learning content based on acquired emotional data" refers to technologies and methods for adjusting learning programs and feedback content based on acquired user emotional data.

[2230] "Means for specifying qualification exams" refers to the interface and related technologies for users to select and specify the qualification exams they wish to take.

[2231] "Means for generating and providing a curriculum corresponding to a specified qualification examination" refers to a system and technology for generating a curriculum corresponding to a qualification examination specified by the user and providing it to the user.

[2232] "Means of conducting a mock exam" refers to the technology and methods for a user to start a mock exam and take the test.

[2233] "Methods for analyzing mock exam results and proposing additional learning content" refers to techniques and methods for analyzing mock exam results and proposing additional learning content, particularly in areas that require strengthening.

[2234] "Means for managing the time of a mock exam" refers to the technology and methods for managing the exam time during a mock exam and notifying the user at the appropriate time.

[2235] This invention is an educational support system designed to ensure that users have equal learning opportunities regardless of income, location, or personal disadvantages. The system supports effective learning by providing individualized support based on the user's learning needs, managing learning progress, and offering feedback. Furthermore, it incorporates an emotion engine to recognize the user's emotions and provide feedback and adjustments accordingly.

[2236] System Configuration

[2237] This system has the following main functions:

[2238] 1. Means of obtaining information entered by the user

[2239] 2. Generating a learning profile

[2240] 3. Automatic generation and provision of learning programs

[2241] 4. Recording and analyzing learning progress

[2242] 5. Feedback and suggestions for additional learning content

[2243] 6. Designation of qualification examinations and curriculum development

[2244] 7. Implementation and analysis of mock exams

[2245] 8. Emotion engine that recognizes user emotions

[2246] 9. Adjusting learning content using emotional data

[2247] Specific operation of the system

[2248] User registration and information retrieval

[2249] The terminal displays a form for first-time users to enter their name, age, grade level, and desired subjects. For example, an HTML form could be used to allow users to input this information.

[2250] The user enters this information and presses the register button.

[2251] The server receives the input information using PHP or Node.js, stores it in a database such as MySQL or PostgreSQL, and generates a user ID and password.

[2252] Generating a learning profile

[2253] The server uses libraries such as Python's scikit-learn and pandas to generate learning profiles based on registered user information. For example, it might generate a profile for someone who says, "I'm a second-year high school student and I want to improve my math skills."

[2254] Automatic generation and provision of learning programs

[2255] The server automatically generates individually customized training programs based on the generated training profiles. This is achieved using a Python generative AI model.

[2256] The device uses front-end frameworks such as React.js or Vue.js to display the generated learning program on the user's dashboard, allowing the user to begin learning.

[2257] Recording and analyzing learning progress

[2258] When a user begins learning, the device uses JavaScript or HTML5's LocalStorage to record the user's progress, such as answer results and learning time, in real time.

[2259] The server receives recorded learning progress data and analyzes it u...

Claims

1. Means of obtaining information entered by the user, A means for generating a user's learning profile based on acquired information, A means of automatically generating and providing a learning program tailored to the user's learning profile, A means of recording the user's learning progress, A means of analyzing recorded learning progress data and optimizing the next learning content, A means of providing users with feedback and suggesting additional learning content, A system that includes this.

2. A means for the user to specify the qualification exam, A means of generating and providing a curriculum corresponding to a specified qualification examination, Methods for conducting mock exams, The system according to claim 1, further comprising means for analyzing the results of a mock exam and suggesting additional learning content.

3. The system according to claim 1, further comprising means for managing the time taken by the user during a mock exam.

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