System

Abstract

A system is provided.SOLUTION: A system comprising: means for inputting basic information of a subject; means for determining cognitive traits of the subject; means for suggesting an optimal learning method based on the determination; means for providing learning content; means for tracking learning progress and conducting comprehension tests; means for providing personalized feedback to the subject; and means for solving questions during learning in real-time.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In the conventional education system, a uniform learning method centered on textbooks is the norm, making it difficult to select a learning method that suits the characteristics of each individual student. This has led to problems such as a decline in motivation to learn and low learning effectiveness. Furthermore, it has not adequately addressed social issues such as educational disparities, school absenteeism, and support for people with disabilities. To solve these problems, it is necessary to propose optimal learning methods based on students' cognitive characteristics and provide a flexible learning environment that responds to each student's individual progress. [Means for solving the problem]

[0005] The present invention solves these problems by the following means. First, it provides a means for inputting basic information about the subject, followed by a means for assessing the subject's cognitive characteristics. Next, it provides a means for proposing the optimal learning method based on the assessment results, and further includes a means for providing learning content. In addition, it incorporates a means for tracking learning progress and conducting comprehension tests, thereby providing individual feedback to the subject. By utilizing these means in a comprehensive manner, it is possible to provide an optimal educational experience tailored to individual learning needs, solving the problems faced by conventional education systems. Furthermore, by adding a means for proposing discussion topics to the subject and encouraging the exchange of opinions between the subject, it is possible to stimulate mutual communication.

[0006] The "means for inputting basic information about the subject" is an interface that allows the user to collect basic information such as their name, age, grade, and areas of interest, and input it into the system.

[0007] The "means for determining the cognitive characteristics of a subject" is a system that presents questions and tasks to determine whether the subject has a visual, verbal, or auditory dominance, and collects and analyzes the subject's responses.

[0008] The "means for proposing the optimal learning method" is a system that selects and proposes the most suitable learning method (video materials, text materials, audio materials, etc.) for each subject based on the results of the cognitive characteristics determined.

[0009] "Means for providing learning content" refers to a system that provides relevant educational materials and learning materials (video, text, audio, etc.) to the target person based on the learning method proposed.

[0010] A "means for tracking learning progress" is a system that records and analyzes the learning content and progress of the subject in real time.

[0011] "Means for conducting comprehension tests" refers to a system for periodically administering quizzes on the content that the subject has learned to measure their level of comprehension.

[0012] The "means of providing individualized feedback" is a system that suggests learning advice and next assignments specific to each individual based on the results of a comprehension test.

[0013] "A means of resolving questions during learning in real time" is a system that provides immediate answers to questions or doubts that students have while learning.

[0014] The "means for suggesting discussion topics" is an interface that periodically suggests topics to encourage discussion among the participants, and promotes the exchange of opinions among the participants. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9]1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0016] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0019] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0020] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0021] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0026] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0028] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0035] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0036] This invention is an AI system for educational support that maximizes learning effectiveness by determining the cognitive characteristics of each individual and proposing individually appropriate learning methods, thereby addressing educational disparities, school absenteeism, and support for people with disabilities. This system functions among three parties: a server, a terminal, and a user.

[0037] Overall system overview

[0038] This system provides educational support tailored to the target individual by performing the following processes.

[0039] 1. Obtain basic information about the subject.

[0040] 2. Determine the cognitive characteristics of the subject.

[0041] 3. Based on the results of the assessment, the optimal learning method is proposed.

[0042] 4. Provide learning content.

[0043] 5. Track your progress and test your comprehension.

[0044] 6. Provide personalized feedback.

[0045] 7. Resolve your doubts while studying in real time.

[0046] 8. Suggest discussion topics and encourage exchange of ideas.

[0047] Program processing

[0048] Below, the program processing at each step of this system will be explained in natural language.

[0049] 1. User Registration

[0050] The server provides a user registration page.

[0051] Users use the terminal to enter basic information such as name, age, grade, and areas of interest.

[0052] The server stores basic information about the user in a database.

[0053] 2. Cognitive trait assessment test

[0054] The server displays the interface for the cognitive characteristics assessment test on the terminal.

[0055] The user clicks the Start Test button to begin the test.

[0056] The server sends a series of questions or tasks to the terminal in sequence.

[0057] The terminal displays each question or task to the user and accepts responses.

[0058] The user answers each question at the terminal.

[0059] The server receives the user's responses and stores them in a database in real time.

[0060] The server analyzes the collected data and determines the user's visual, linguistic, and auditory cognitive characteristics.

[0061] 3. Learning method suggestions

[0062] Based on the results of the judgment, the server selects the most suitable learning method for the user.

[0063] The server presents the selected learning method and related learning materials to the terminal.

[0064] The device displays learning method suggestions and introductions to learning materials to the user.

[0065] 4. Providing learning content

[0066] The server provides users with learning content (video, text, audio materials, etc.) appropriate for their needs.

[0067] The user checks the learning content on the device and begins learning.

[0068] The device records the user's learning progress in real time.

[0069] 5. Real-time support

[0070] The server provides an interface that accepts questions from users during their studies via the terminal.

[0071] The user inputs a question into the terminal and sends it.

[0072] The server analyzes the question and provides an appropriate answer instantly.

[0073] The terminal displays the response from the server to the user.

[0074] 6. Progress Tracking and Comprehension Testing

[0075] The server periodically displays an interface on the terminal that allows users to take comprehension tests.

[0076] The user takes the test at the terminal.

[0077] The terminal transmits the user's answer to the server.

[0078] The server scores the answers, stores the results in a database, and provides feedback to the user.

[0079] 7. Personalized feedback and suggestions for next steps

[0080] The server analyzes the results of the user's comprehension test and suggests the next learning content and assignments.

[0081] The device displays feedback and new challenges to the user.

[0082] The user works on the proposed tasks on the device.

[0083] 8. Facilitating discussion and communication

[0084] The server periodically provides discussion topics.

[0085] The terminal displays discussion topics to the user and provides a form where responses and opinions can be entered.

[0086] Users input their opinions on the terminal and exchange opinions with other users.

[0087] Specific examples

[0088] For example, let's say Mr. C is a second-year junior high school student who wants to study history.

[0089] 1. User Registration

[0090] Mr. C types into his terminal, "Second year junior high school student, interested in history."

[0091] The server stores this information.

[0092] 2. Cognitive trait assessment test

[0093] Mr. C clicks the start test button on his device.

[0094] The server begins the validation test.

[0095] The device will display questions such as, "Is it easy to remember with an image?"

[0096] C answers the questions.

[0097] The server analyzes Mr. C's answers and determines that he is visually dominant.

[0098] 3. Learning method suggestions

[0099] "Learn about historical events through videos," suggests the server.

[0100] A link to the video material will be displayed on the device.

[0101] 4. Providing learning content

[0102] Mr. C starts watching the video on his device.

[0103] 5. Real-time support

[0104] Mr. C types the question into his terminal: "I don't understand the background of this war."

[0105] The server provides the answer, which is displayed on the terminal.

[0106] 6. Progress Tracking and Comprehension Testing

[0107] After watching the video, the server conducts a comprehension test.

[0108] Mr. C takes the test on a terminal.

[0109] 7. Personalized feedback and suggestions for next steps

[0110] The server analyzes the test results and suggests, "Next, let's learn more about the causes of this war."

[0111] The next learning content will be displayed to Mr. C on his terminal.

[0112] 8. Facilitating discussion and communication

[0113] The server suggests that next week's theme will be "Important Figures in Modern History," and provides a platform where users can exchange opinions.

[0114] Mr. C can input his opinions on the device and discuss them with his classmates.

[0115] In this way, the AI ​​system can provide an optimal educational experience tailored to individual learning needs, creating an environment in which Mr. C can learn independently.

[0116] The processing flow will be explained below.

[0117] Step 1:

[0118] The server provides a user registration page, where users use their terminals to enter basic information such as name, age, grade, and areas of interest, and the server stores the entered basic information in a database.

[0119] Step 2:

[0120] The server displays the cognitive characteristics assessment test interface on the terminal, and the user clicks the test start button to start the test.

[0121] Step 3:

[0122] The server sequentially sends a series of questions or tasks to the terminal, which displays the questions or tasks to the user and accepts answers. The user answers each question on the terminal.

[0123] Step 4:

[0124] The server receives the user's responses and stores them in a database in real time. The server analyzes the collected data to determine the user's visual, linguistic, and auditory cognitive characteristics.

[0125] Step 5:

[0126] Based on the results of the assessment, the server selects the optimal learning method for the user. The server then presents the selected learning method and related learning materials to the terminal. The terminal then displays suggested learning methods and introductions to the learning materials to the user.

[0127] Step 6:

[0128] The server provides learning content (video, text, audio, etc.) appropriate for the user. The user checks the learning content on the device and begins learning. The device records the user's learning progress in real time.

[0129] Step 7:

[0130] The server provides an interface that accepts questions from users during their studies via their terminal. The user inputs and submits a question on the terminal. The server analyzes the question and instantly generates and provides an appropriate answer. The terminal displays the answer from the server to the user.

[0131] Step 8:

[0132] The server periodically displays an interface on the device that conducts comprehension tests. The user takes the test on the device. The device sends the user's answers to the server. The server grades the answers, stores the results in a database, and provides feedback to the user.

[0133] Step 9:

[0134] The server analyzes the results of the user's comprehension test and suggests the next learning content and assignments. The device displays feedback and new assignments to the user. The user then works on the suggested assignments.

[0135] Step 10:

[0136] The server periodically provides discussion topics. The terminal displays the discussion topics to the user and provides a form in which the user can enter their answers and opinions. The user enters their opinions on the terminal and exchanges opinions with other users.

[0137] Example 1

[0138] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0139] Modern education demands optimal learning methods based on individual cognitive characteristics. However, many current educational systems only provide uniform learning methods, making it difficult to address individual cognitive characteristics. Furthermore, they lack features such as learning progress tracking, comprehension tests, and real-time question resolution, making it difficult to adequately address individual learning needs. Furthermore, there are few systems that automatically suggest learning content and provide feedback, preventing the effectiveness of education from being maximized.

[0140] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0141] In this invention, the server includes means for inputting basic information about the subject, means for determining the cognitive characteristics of the subject, means for proposing an optimal learning method based on the determination results, means for providing learning content, means for tracking learning progress and conducting comprehension tests, means for providing individual feedback to the subject, means for resolving questions during learning in real time, means for saving the subject's input and learning progress in a database, means for collecting questions from the subject and generating answers using a generative AI model, and means for evaluating the subject's answers and dynamically proposing the next learning content. This makes it possible to provide an optimal learning method according to individual cognitive characteristics, track learning progress, resolve questions in real time, and dynamically suggest learning content.

[0142] "Target" refers to an individual who uses an educational support AI system to advance their learning.

[0143] "Basic information" refers to basic information necessary for education, such as the subject's name, age, grade, and areas of interest.

[0144] "Cognitive characteristics" are the information processing characteristics of a subject, such as vision, language, and hearing, and indicate individual characteristics in learning.

[0145] "Learning methods" are optimal learning methods or approaches suggested based on cognitive characteristics, including learning materials and learning formats.

[0146] "Learning content" refers to learning videos, texts, audio materials, etc. provided to the target audience, and is an information resource to support learning.

[0147] "Study progress" refers to the progress that a subject makes as they progress through their studies.

[0148] A "comprehension test" is a test used to measure the subject's level of comprehension of the learning content.

[0149] "Individual feedback" refers to specific assessments and guidance provided to students based on the results of comprehension tests and their learning progress.

[0150] "Real-time question resolution" means providing immediate and appropriate answers to questions that students have while studying.

[0151] A "database" is a system that stores and manages data such as basic information about the subject, their learning progress, and the content of their responses.

[0152] A "generative AI model" is an artificial intelligence model used to generate appropriate answers to user questions.

[0153] "Dynamic suggestions" means generating and suggesting the next content or tasks to be learned on an ongoing basis based on the student's learning progress and level of understanding.

[0154] This invention relates to an AI system for supporting education, which maximizes learning effectiveness by providing optimal learning methods based on individual cognitive characteristics, and addresses educational disparities, school absenteeism, and support for people with disabilities. The system functions among three parties: a server, a terminal, and a user.

[0155] Overall system overview

[0156] The system provides tailored educational support by:

[0157] 1. Obtain basic information about the subject.

[0158] 2. Determine the cognitive characteristics of the subject.

[0159] 3. Based on the results of the assessment, the optimal learning method is proposed.

[0160] 4. Provide learning content.

[0161] 5. Track your progress and test your comprehension.

[0162] 6. Provide personalized feedback.

[0163] 7. Resolve your doubts while studying in real time.

[0164] 8. Suggest discussion topics and encourage exchange of ideas.

[0165] Hardware and software used

[0166] The hardware used includes a server and user devices. The server uses a database (e.g., MySQL, PostgreSQL) for managing and analyzing user information, an execution environment for machine learning models (e.g., Python, Scikit-learn), a real-time chat system (e.g., Node.js), and a generative AI model (e.g., OpenAI GPT-3).

[0167] The user device provides an interface that runs on a web browser and processes user operations and learning progress using HTML, CSS, JavaScript, React, etc.

[0168] Program processing overview

[0169] User Registration

[0170] The server generates a user registration page using HTML and CSS and sends it to the device. The user enters basic information such as name, age, grade, and areas of interest on the device and submits it. The server receives the information in JSON format and stores it in a database.

[0171] Cognitive trait assessment test

[0172] The server generates the cognitive trait assessment test interface using JavaScript and React and displays it on the device. The user starts the test and answers a series of questions. The server receives the answers, stores them in a database, and uses a Python machine learning model to analyze the data and determine cognitive traits.

[0173] Learning method suggestions

[0174] The server determines the optimal learning method based on the cognitive characteristics and selects relevant learning materials, which are then sent to the terminal, which then presents them to the user.

[0175] Providing learning content

[0176] The server provides the selected learning content, which the user uses on their device to progress through the learning process. The device records the learning progress in real time and sends it to the server.

[0177] Real-time Support

[0178] The server receives the user's question through the device, generates an appropriate answer using the generative AI model, and sends it to the device for display.

[0179] Progress tracking and comprehension tests

[0180] The server periodically conducts comprehension tests and stores the results in a database, providing feedback to the user and suggesting what to study next.

[0181] Individual feedback and suggestions for next steps

[0182] The server analyzes the next learning content based on the test results and provides feedback and new challenges to the user, thereby presenting the optimal learning path for each individual user.

[0183] Facilitating discussion and communication

[0184] The server periodically generates new discussion topics and presents them to users, who can then input their opinions on their terminals and exchange opinions with other users.

[0185] Specific examples

[0186] For example, consider the case where Mr. C is a second-year junior high school student who wants to study history.

[0187] 1. Mr. C enters "I'm a second-year junior high school student and I'm interested in history" on his device and sends the information. The server saves this information.

[0188] 2. Person C starts the cognitive ability assessment test on his terminal. The server displays questions, and Person C inputs answers. The server analyzes the answers and determines that Person C is visually dominant.

[0189] 3. The server suggests, "Let's learn about historical events through videos," and displays a link to the video material on the device.

[0190] 4. Mr. C starts watching the video on his device. The device records his learning progress and sends it to the server.

[0191] 5. When Mr. C enters a question such as "I don't understand the background of this war," the server uses a generative AI model to generate and display an answer.

[0192] 6. After watching the video, the server conducts a comprehension test, and Mr. C takes the test. The results are sent to the server, which then suggests the next learning content.

[0193] 7. The server suggests a new task: "Next, let's learn more about the causes of this war," and displays it on the device.

[0194] 8. The server suggests that next week’s topic is “Important Figures in Modern History” and provides a discussion platform. C can input his opinions and discuss them with his classmates.

[0195] Prompt Sentence Examples

[0196] "If you have a second-year junior high school student who wants to study history, how would you use AI to suggest the best way to learn it? Please explain the specific process."

[0197] In this way, AI systems can provide optimal educational experiences tailored to individual learning needs and create an environment in which participants can learn independently.

[0198] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0199] Step 1:

[0200] User Registration

[0201] The server generates a user registration page using HTML and CSS and sends it to the device. The user enters basic information such as name, age, grade, and areas of interest on the device and submits it. The server receives the received information in JSON format and saves it in the database. This registers the user's basic information in the database. The input is the user's basic information, and the output is the user's basic information saved in the database.

[0202] Step 2:

[0203] Cognitive trait assessment test

[0204] The server uses JavaScript and React to generate an interface for the cognitive trait assessment test and displays it on the device. The user clicks a button to start the test and answers a series of questions. The device displays each question and accepts the user's answers. The server stores the received answers in a database and analyzes the data using a Python machine learning model to determine the user's cognitive traits. The input is the user's answers and the output is the assessed cognitive traits. This reveals the user's cognitive traits.

[0205] Step 3:

[0206] Learning method suggestions

[0207] The server selects the optimal learning method based on cognitive characteristics and selects related learning materials. The server sends the selected learning method and learning materials to the terminal via REST API. The terminal displays this to the user. The input is cognitive characteristics and a learning material database, and the output is a link between the learning method and learning materials presented to the user. This allows the optimal learning method to be presented to the user.

[0208] Step 4:

[0209] Providing learning content

[0210] The server dynamically generates learning content appropriate for the user and sends it to the device. The user checks the learning content on the device and begins learning. The device records learning progress and periodically sends it to the server. The input is the user's cognitive characteristics and progress, and the output is the learning content provided and a record of learning progress. This allows the user to study with content that is appropriate for them.

[0211] Step 5:

[0212] Real-time Support

[0213] The server provides an interface that accepts user questions via the terminal. The user inputs a question on the terminal and sends it to the server. The server analyzes the question and generates the optimal answer using a generative AI model. The server sends the answer to the terminal, which displays it to the user. The input is the user's question, and the output is the generated answer. This allows the user's question to be resolved instantly.

[0214] Step 6:

[0215] Progress tracking and comprehension tests

[0216] The server periodically displays an interface on the terminal that conducts comprehension tests. The user takes the test on the terminal and sends the answers to the server. The server scores the answers and stores the results in a database. It then generates feedback based on the results and sends it to the terminal. The input is the answers to the comprehension test, and the output is the test results and feedback. This evaluates the user's level of understanding and determines the next learning content.

[0217] Step 7:

[0218] Individual feedback and suggestions for next steps

[0219] The server analyzes the test results and determines the next learning content. The server sends feedback and new assignments to the device, which displays them to the user. The user then works on the suggested assignments. The input is the test results and learning objectives, and the output is feedback and new suggested assignments. This allows the user to continuously work on appropriate assignments.

[0220] Step 8:

[0221] Facilitating discussion and communication

[0222] The server periodically generates discussion topics and sends them to the terminals. Users input their opinions on their terminals and send them to the server. The server collects the opinions and displays them to other users, allowing for an exchange of opinions. The input is the user's opinion, and the output is the shared opinion and discussion results. This promotes communication between users and leads to deeper understanding.

[0223] (Application example 1)

[0224] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0225] With conventional educational systems, it has been difficult to efficiently grasp the cognitive characteristics of each individual student and propose optimal learning methods based on that.In addition, there is a lack of educational support for industrial product operation methods and control technologies in industrial workplaces, and automatic and effective measures are needed as a means of improving engineers' skills.

[0226] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0227] In this invention, the server includes means for inputting basic information about the subject, means for determining the cognitive characteristics of the subject, means for proposing an optimal learning method based on the determination results, means for providing learning content, means for tracking learning progress and conducting comprehension tests, means for providing individual feedback and proposing next tasks to the subject, means for resolving questions during learning in real time, means for promoting the exchange of opinions between subjects, and means for supporting learning of industrial product operation methods and control technology. This makes it possible to propose a learning method optimal for the cognitive characteristics of each subject, and to automatically and effectively provide education on industrial product operation methods and control technology.

[0228] 1. "Basic information of the subject" refers to personal information such as the subject's name, age, years of experience, and field of expertise.

[0229] 2. "Cognitive characteristics" refers to the individual characteristics of how a subject receives, processes, and understands information, such as visual dominance, auditory dominance, or verbal dominance.

[0230] 3. "Optimal learning method" refers to the most effective learning method based on the cognitive characteristics of the individual.

[0231] 4. "Learning Content" refers to the learning materials and information provided to a target audience for learning, including video, text, and audio materials.

[0232] 5. "Tracking learning progress" refers to recording and managing the learning progress of a student in real time.

[0233] 6. "Comprehension test" refers to a test to assess the extent to which a subject has understood the learning content.

[0234] 7. "Individualized feedback" refers to specific advice and next steps provided based on the learner's learning progress and level of understanding.

[0235] 8. "Resolving questions during learning in real time" refers to providing immediate answers to questions that arise during learning.

[0236] 9. "Promoting exchange of opinions" refers to support provided to stimulate information sharing and discussion among participants.

[0237] 10. "Supporting learning about the operation methods and control techniques of industrial products" refers to educational support to promote understanding of the correct operation methods and control techniques of industrial products and equipment used in industry.

[0238] Overall system configuration

[0239] This invention describes a specific embodiment for implementing an educational support system consisting of a server, a terminal, and a user. This system proposes optimal learning methods based on the cognitive characteristics of each individual and supports education on industrial product operation methods and control technologies.

[0240] Hardware and software used

[0241] The present invention uses the following hardware and software.

[0242] Server: High-performance server (e.g. AWS, Google Cloud)

[0243] Terminals: Smartphones, factory robot HMI (Human-Machine Interface), PCs

[0244] Frontend: Angular, HTML5, CSS3, JavaScript

[0245] Backend: Node.js, MySQL

[0246] AI modeling: Python, TensorFlow, Socket.IO

[0247] Program processing

[0248] 1. User Registration

[0249] The server serves a user registration page in Angular on the front end.

[0250] The user uses a terminal to enter basic information such as name, age, years of experience, and field of expertise.

[0251] The server receives this information via Node.js and stores it in a MySQL database.

[0252] 2. Assessment of cognitive characteristics

[0253] The server uses an Angular front-end to provide an interface for questions and tasks to assess cognitive characteristics.

[0254] The user starts the test at the terminal and answers the questions.

[0255] The server receives the responses and uses Python and TensorFlow to analyze the data and determine cognitive traits.

[0256] 3. Learning method suggestions

[0257] Based on the analysis results, the server selects the optimal learning method and suggests corresponding learning materials.

[0258] The terminal displays the suggestions and educational materials to the user.

[0259] 4. Providing learning content

[0260] The server provides learning content (video, audio, text) that best suits the user's cognitive characteristics.

[0261] Users can view this content on their devices and progress as they study, with their progress recorded in real time.

[0262] 5. Real-time support

[0263] If a user has a question while studying, they can enter it using their smartphone or tablet.

[0264] The server uses Socket.IO to receive questions in real time, processes them in Python, and provides instant answers.

[0265] 6. Progress Tracking and Comprehension Testing

[0266] The server periodically conducts comprehension tests, analyzes the results, stores them in a database, and provides feedback to the user.

[0267] 7. Personalized feedback and suggestions for next steps

[0268] The server suggests the next learning task based on the test results and provides related learning content.

[0269] 8. Facilitating discussion and communication

[0270] The server periodically provides discussion topics and provides an interface that encourages the exchange of ideas between users.

[0271] Users can input their opinions on the terminal and hold discussions with other users.

[0272] Examples and prompts

[0273] As a concrete example, consider the case where engineer A is learning how to operate a new industrial robot.

[0274] If engineer A enters "years of experience: 5 years, specialty: industrial robot control" and has visually dominant cognitive characteristics, the system will suggest, "Let's learn the basic operation of industrial robots through video materials." Engineer A will begin learning by watching the video materials, and if he has any questions, he can ask, "Please tell me more about how the sensors on this robot work." The server will immediately provide an appropriate answer to this question.

[0275] An example of a prompt is:

[0276] "For an engineer with five years of experience operating robots, please propose an industrial robot operation method that is easy for a person with visually dominant cognitive characteristics to learn. Also, please suggest related video teaching materials."

[0277] Possible possibilities include:

[0278] In this way, it is possible to propose a learning method that is optimal for the cognitive characteristics of each individual, and to automatically and effectively educate the student on how to operate industrial products and control technology.

[0279] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0280] Step 1:

[0281] User Registration

[0282] The server serves a user registration page in Angular on the front end.

[0283] The user uses a terminal to enter basic information such as name, age, years of experience, and field of expertise.

[0284] The basic information entered is sent from the terminal to the server, which receives this information via Node.js and stores it in a MySQL database.

[0285] Input: Basic information such as name, age, years of experience, field of expertise, etc.

[0286] Output: Basic user information stored in the database

[0287] Step 2:

[0288] Determining cognitive characteristics

[0289] The server uses an Angular front-end to provide an interface for questions and tasks to assess cognitive characteristics.

[0290] The user starts the test at the terminal and answers the questions.

[0291] The server receives the response data and analyzes it using Python and TensorFlow to determine the user's cognitive characteristics, such as visual, auditory, and language.

[0292] Input: User response data

[0293] Output: Cognitive characteristics (visual, auditory, language, etc.)

[0294] Step 3:

[0295] Learning method suggestions

[0296] Based on the results of the analysis of cognitive characteristics, the server selects the optimal learning method and suggests corresponding learning materials.

[0297] The terminal displays the suggestions and educational materials to the user.

[0298] For example, video instructional materials are suggested to visually dominant users.

[0299] Input: Cognitive characteristic analysis results

[0300] Output: Suggested learning methods and materials

[0301] Step 4:

[0302] Providing learning content

[0303] The server provides learning content (video, audio, text) that best suits the user's cognitive characteristics.

[0304] Users can check this content on their devices and progress through their studies, with their progress recorded in real time on the server.

[0305] Input: Suggested learning methods and materials

[0306] Output: Providing learning content and recording progress

[0307] Step 5:

[0308] Real-time Support

[0309] If a user has a question while studying, they can enter it using their smartphone or tablet.

[0310] The server uses Socket.IO to receive questions in real time, processes them in Python, and provides instant answers.

[0311] Input: User question

[0312] Output: Answers provided in real time

[0313] Step 6:

[0314] Progress tracking and comprehension tests

[0315] The server periodically conducts comprehension tests, analyzes the results, stores them in a database, and provides feedback to the user.

[0316] The terminal displays the test results to the user.

[0317] Input: Comprehension test response data

[0318] Output: Test result analysis and feedback

[0319] Step 7:

[0320] Individual feedback and suggestions for next steps

[0321] Based on the results of the comprehension test, the server suggests the next learning task and provides related learning content.

[0322] The terminal displays the next assignment and related content to the user.

[0323] Input: Comprehension test results

[0324] Output: Providing next assignments and related learning content

[0325] Step 8:

[0326] Facilitating discussion and communication

[0327] The server periodically provides discussion topics and provides an interface that encourages the exchange of ideas between users.

[0328] Users can input their opinions on the terminal and hold discussions with other users.

[0329] Input: Discussion topics and user opinions

[0330] Output: Facilitated exchange of ideas and shared opinions

[0331] In this way, the educational support system is designed to function effectively by clarifying the roles of the server, terminal, and user at each step and organizing the specific operations and inputs and outputs.

[0332] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0333] This invention is an AI system for educational support that maximizes learning effectiveness by determining the cognitive characteristics of each individual and proposing individually appropriate learning methods, and by combining it with an emotion engine, provides an optimal learning experience by taking into account the emotional state of the individual. This system functions among four parties: a server, a terminal, a user, and an emotion engine.

[0334] Overall system overview

[0335] This system provides educational support tailored to the target individual by performing the following processes.

[0336] 1. Obtain basic information about the subject.

[0337] 2. Determine the cognitive characteristics of the subject.

[0338] 3. Based on the results of the assessment, the optimal learning method is proposed.

[0339] 4. Provide learning content.

[0340] 5. Track your progress and test your comprehension.

[0341] 6. Provide personalized feedback.

[0342] 7. Resolve your doubts while studying in real time.

[0343] 8. Use an emotion engine to recognize and respond to the subject's emotional state.

[0344] 9. Suggest discussion topics and encourage exchange of ideas.

[0345] Program processing

[0346] Below, the program processing at each step of this system will be explained in natural language.

[0347] 1. User Registration

[0348] The server provides a user registration page.

[0349] Users use the terminal to enter basic information such as name, age, grade, and areas of interest.

[0350] The server stores the entered basic information in a database.

[0351] 2. Cognitive trait assessment test

[0352] The server displays the interface for the cognitive characteristics assessment test on the terminal.

[0353] The user clicks the Start Test button to begin the test.

[0354] 3. Conducting a cognitive assessment test

[0355] The server sends a series of questions or tasks to the terminal in sequence.

[0356] The terminal displays questions and tasks to the user and accepts answers.

[0357] The user answers each question on the terminal.

[0358] The server receives the user's responses and stores them in a database in real time.

[0359] The server analyzes the collected data and determines the user's visual, linguistic, and auditory cognitive characteristics.

[0360] 4. Learning method suggestions

[0361] Based on the judgment results, the server selects the most suitable learning method for the user.

[0362] The server presents the selected learning method and related learning materials to the terminal.

[0363] The device displays learning method suggestions and introductions to learning materials to the user.

[0364] 5. Provision of learning content

[0365] The server provides users with learning content (video, text, audio materials, etc.) appropriate for their needs.

[0366] The user checks the learning content on the device and begins learning.

[0367] The device records the user's learning progress in real time.

[0368] 6. Real-time support

[0369] The server provides an interface that accepts questions from users during their studies via the terminal.

[0370] The user inputs a question into the terminal and sends it.

[0371] The server analyzes the question and instantly generates and provides the appropriate answer.

[0372] The terminal displays the response from the server to the user.

[0373] 7. Progress Tracking and Comprehension Testing

[0374] The server periodically displays an interface on the terminal that allows users to take comprehension tests.

[0375] The user takes the test at the terminal.

[0376] The terminal transmits the user's answer to the server.

[0377] The server scores the answers, stores the results in a database, and provides feedback to the user.

[0378] 8. Personalized feedback and suggestions for next steps

[0379] The server analyzes the results of the user's comprehension test and suggests the next learning content and assignments.

[0380] The device displays feedback and new challenges to the user.

[0381] The user tackles the proposed task.

[0382] 9. Emotion Recognition and Response

[0383] The server uses an emotion engine to monitor the user's emotional state during learning in real time through the terminal.

[0384] The emotion engine identifies emotions from the user's facial expressions and tone of voice, and stores the emotional state in a database.

[0385] The server adjusts the optimal feedback and learning content based on the user's emotional state.

[0386] 10. Facilitating discussion and communication

[0387] The server periodically provides discussion topics.

[0388] The terminal displays discussion topics to the user and provides a form where responses and opinions can be entered.

[0389] Users input their opinions on the terminal and exchange opinions with other users.

[0390] Specific examples

[0391] For example, let's say Mr. D is a first-year high school student who wants to study mathematics.

[0392] 1. User Registration

[0393] Mr. D types into his terminal, "First year high school student, interested in mathematics."

[0394] The server stores this information.

[0395] 2. Cognitive trait assessment test

[0396] Mr. D clicks the start test button on his device.

[0397] The server begins the validation test.

[0398] The device will display questions such as, "Is it easy to remember with an image?"

[0399] D answers the questions.

[0400] The server analyzes Mr. D's answers and determines that he is visually dominant.

[0401] 3. Learning method suggestions

[0402] "Learn math concepts through videos," suggests Thurber.

[0403] A link to the video material will be displayed on the device.

[0404] 4. Providing learning content

[0405] Mr. D starts watching the video on his device.

[0406] 5. Real-time support

[0407] Mr. D types a question into his terminal: "I don't know how to use this formula."

[0408] The server provides the answer, which is displayed on the terminal.

[0409] 6. Progress Tracking and Comprehension Testing

[0410] After watching the video, the server conducts a comprehension test.

[0411] Mr. D takes the test on a terminal.

[0412] 7. Personalized feedback and suggestions for next steps

[0413] The server analyzes the test results and suggests, "Next, try solving some real problems."

[0414] The next learning content will be displayed to Mr. D on his device.

[0415] 8. Emotion Recognition and Response

[0416] The server uses an emotion engine to analyze Mr. D's facial expressions and tone of voice while he is studying.

[0417] If the server identifies Mr. D as feeling tired, it will display a message on his device saying, "Let's take a short break."

[0418] Also, if Mr. D is in a state of joy or adaptation, the teacher will give him feedback such as "That's good enough" and encourage him to continue learning.

[0419] 9. Facilitating discussion and communication

[0420] The server suggests that next week's theme is "Application of Functions," and provides a platform where users can exchange opinions.

[0421] Mr. D can input his opinions on the device and discuss them with his classmates.

[0422] In this way, the AI ​​system can provide an optimal educational experience tailored to individual learning needs, creating an environment in which Mr. D can learn independently. By combining it with an emotion engine, it is possible to respond according to the user's emotional state, further improving learning effectiveness.

[0423] The processing flow will be explained below.

[0424] Step 1:

[0425] The server provides a user registration page, where users use their terminals to enter basic information such as name, age, grade, and areas of interest, and the server stores the entered basic information in a database.

[0426] Step 2:

[0427] The server displays the cognitive characteristics assessment test interface on the terminal, and the user clicks the test start button to start the test.

[0428] Step 3:

[0429] The server sequentially sends a series of questions or tasks to the terminal, which displays the questions or tasks to the user and accepts answers. The user answers each question on the terminal.

[0430] Step 4:

[0431] The server receives the user's responses and stores them in a database in real time. The server analyzes the collected data to determine the user's visual, linguistic, and auditory cognitive characteristics.

[0432] Step 5:

[0433] Based on the results of the assessment, the server selects the optimal learning method for the user. The server then presents the selected learning method and related learning materials to the terminal. The terminal then displays suggested learning methods and introductions to the learning materials to the user.

[0434] Step 6:

[0435] The server provides learning content (video, text, audio, etc.) appropriate for the user. The user checks the learning content on the device and begins learning. The device records the user's learning progress in real time.

[0436] Step 7:

[0437] The server provides an interface that accepts questions from users during their studies via their terminal. The user inputs and submits a question on the terminal. The server analyzes the question and instantly generates and provides an appropriate answer. The terminal displays the answer from the server to the user.

[0438] Step 8:

[0439] The server periodically displays an interface on the device that conducts comprehension tests. The user takes the test on the device. The device sends the user's answers to the server. The server grades the answers, stores the results in a database, and provides feedback to the user.

[0440] Step 9:

[0441] The server analyzes the results of the user's comprehension test and suggests the next learning content and assignments. The device displays feedback and new assignments to the user. The user then works on the suggested assignments.

[0442] Step 10:

[0443] The server uses an emotion engine to monitor the user's emotional state in real time through the device while they are learning. The emotion engine identifies emotions from the user's facial expressions and tone of voice, and stores the emotional state in a database. The server then provides optimal feedback and adjusts the learning content based on the user's emotional state.

[0444] Step 11:

[0445] The server periodically provides discussion topics. The terminal displays the discussion topics to the user and provides a form in which the user can enter their answers and opinions. The user enters their opinions on the terminal and exchanges opinions with other users.

[0446] Example 2

[0447] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0448] Conventional educational systems have had difficulty providing learning methods that fully consider the cognitive characteristics and emotional state of each individual student. Furthermore, they lacked functionality for real-time resolution of questions that arise during learning and for easy exchange of opinions between students. This made it difficult to provide an optimal learning experience for each student, resulting in a lack of maximization of learning effectiveness.

[0449] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for inputting basic information about the subject, a means for determining the cognitive characteristics of the subject, a means for proposing an optimal learning method based on the determination results, a means for providing learning content, a means for tracking learning progress and conducting comprehension tests, a means for providing individual feedback to the subject, a means for resolving questions during learning in real time, and a means for recognizing and responding to the subject's emotional state using an emotion engine. This makes it possible to provide an optimal learning experience tailored to the subject's individual needs and maximize learning effectiveness. Furthermore, by encouraging the exchange of opinions between subjects as needed, the quality of learning can be expected to improve.

[0450] "Target audience" refers to learners who use the education system.

[0451] "Basic information" refers to basic data such as the subject's name, age, grade, and areas of interest.

[0452] "Cognitive characteristics" refers to the subject's cognitive style, such as visual, linguistic, and auditory.

[0453] A "judgment test" refers to a series of questions or tasks designed to assess a subject's cognitive characteristics.

[0454] "Feedback" refers to individual evaluations and advice provided based on the subject's learning results.

[0455] "Learning method" refers to the learning process and techniques proposed based on the cognitive characteristics of the subject.

[0456] "Learning content" includes learning materials and resources used for learning, such as videos, texts, and audio materials.

[0457] An "emotion engine" refers to a system that has the ability to recognize a subject's emotional state and process that data.

[0458] "Real-time support" refers to the function of providing immediate responses to questions or concerns that students may have while studying.

[0459] "Discussion Topics" refers to topics that are periodically provided by the server for the purpose of exchanging opinions among participants.

[0460] "Opinion exchange" refers to the activity of sharing opinions and thoughts among participants.

[0461] "Server" refers to a central computer that runs the entire system and provides each function.

[0462] "Device" means the computer or mobile device used by a Subject to access the System.

[0463] This invention is an AI system for educational support that maximizes learning effectiveness by determining the cognitive characteristics of each individual and proposing individually appropriate learning methods. Furthermore, by combining it with an emotion engine, it provides an optimal learning experience by taking into account the emotional state of each individual. This system functions among four parties: a server, a terminal, a user, and an emotion engine.

[0464] Overall system overview

[0465] This system provides educational support tailored to each individual through the following steps:

[0466] 1. Obtain basic information about the subject.

[0467] 2. Determine the cognitive characteristics of the subject.

[0468] 3. Based on the results of the assessment, the optimal learning method is proposed.

[0469] 4. Provide learning content.

[0470] 5. Track your progress and test your comprehension.

[0471] 6. Provide personalized feedback.

[0472] 7. Resolve your doubts while studying in real time.

[0473] 8. Use an emotion engine to recognize and respond to the subject's emotional state.

[0474] 9. Suggest discussion topics and encourage exchange of ideas.

[0475] Program processing

[0476] The processing of this system is carried out through cooperation between the server and the terminal, as detailed below.

[0477] Hardware and Software Use

[0478] The server uses a MySQL database to store and manage data.

[0479] The server uses Python to implement data analysis and decision algorithms.

[0480] The server provides a front end consisting of JavaScript and HTML.

[0481] The device accesses the server using a browser such as Google Chrome.

[0482] The emotion engine uses the camera and microphone to analyze the user's facial expressions and tone of voice.

[0483] Specific examples

[0484] For example, consider the following situation where Mr. D is a first-year high school student who wishes to study mathematics.

[0485] 1. User Registration

[0486] Mr. D enters "First year high school student, interested in mathematics" into the terminal. The form displayed on the terminal has fields for entering name, age, grade, and area of ​​interest.

[0487] When Mr. D clicks the "Register" button, the server receives the input data and saves it in the MySQL database.

[0488] 2. Cognitive trait assessment test

[0489] Mr. D clicks the start test button on his device. The server sends the UI for the assessment test, which is composed of HTML and JavaScript, to the device and asks a series of questions.

[0490] Questions such as "Is it easy to remember with an image?" are displayed on the device. Mr. D answers the questions, and the answers are saved in a database in real time.

[0491] 3. Learning method suggestions

[0492] Based on D's cognitive characteristics, the server suggests, "Let's learn mathematical concepts through videos." A link to the video material is displayed on the device.

[0493] 4. Providing learning content

[0494] Mr. D starts watching the video on his device. The server provides the video material through a video streaming service.

[0495] 5. Real-time support

[0496] During the study, Mr. D enters a question into his device, such as "I don't know how to use this formula." The server receives the question, analyzes it using natural language processing (NLP), instantly generates an appropriate answer, and displays it on the device.

[0497] 6. Progress Tracking and Comprehension Testing

[0498] After watching the video, the server periodically conducts comprehension tests. Mr. D takes the tests on his device and his answers are sent to the server. The server then uses an automatic scoring system to score the answers and stores the results in a database.

[0499] 7. Personalized feedback and suggestions for next steps

[0500] Based on the test results, the server suggests, "Next, try solving a real problem." The next learning content is displayed to Mr. D on his device.

[0501] 8. Emotion Recognition and Response

[0502] The server uses an emotion recognition algorithm to monitor Mr. D's facial expressions and tone of voice in real time while he is studying.

[0503] If D is identified as feeling tired, the server will display a message on his device saying, "Take a short break." If he is in a state of joy or adaptation, the server will provide feedback saying, "That's good," encouraging him to continue learning.

[0504] 9. Facilitating discussion and communication

[0505] The server suggests that next week's topic is "Application of Functions," and provides a platform for users to exchange opinions. D can input his opinion on his device and discuss it with his classmates.

[0506] Prompt Sentence Examples

[0507] "Please explain how to register by entering basic user information."

[0508] "Please explain with specific examples what kind of questions will be asked during the cognitive trait assessment test."

[0509] "Please explain how you handle real-time support if a user has a question while learning."

[0510] "Please explain the process of recognizing and responding to user emotions using the emotion engine."

[0511] This allows the AI ​​system to provide an optimal educational experience tailored to the user's individual learning needs, improving learning outcomes.The combination of an emotion engine enables the system to respond to the user's emotional state, further enhancing learning outcomes.

[0512] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0513] Step 1: User Registration

[0514] The server provides a user registration page. The user uses the terminal to enter basic information such as name, age, grade, and areas of interest. When the user clicks the "Register" button, the terminal sends the data to the server. The server receives the entered basic information and stores it in a database. The input here is the user's basic information, and the output is the data stored in the database.

[0515] Step 2: Cognitive trait assessment test

[0516] The server displays the cognitive ability assessment test interface on the terminal. The user clicks the test start button and answers the questions and tasks displayed on the terminal in sequence. The server receives each answer and stores them in a database one by one. Based on the collected answer data, the server uses Python to analyze the data and determine the user's visual, linguistic, and auditory cognitive abilities. The input is the user's test answers, and the output is the assessed cognitive abilities.

[0517] Step 3: Suggest a learning method

[0518] The server selects the optimal learning method and related learning materials based on the assessment results. The selected information is sent to the terminal and links to the learning methods and learning materials are displayed to the user. The input is the assessed cognitive characteristics, and the output is the suggested learning methods and links to the learning materials.

[0519] Step 4: Provide learning content

[0520] The server provides learning content such as videos, texts, and audio materials through a streaming service. The user checks the learning content on their device and begins learning. The device records the user's learning progress (e.g., video viewing time and text completion status) in real time and sends it to the server. The input is the learning content, and the output is learning progress data.

[0521] Step 5: Real-time support

[0522] The server provides an interface through the terminal for users to input questions they have while studying. The user inputs the question on the terminal and sends it. The server analyzes the question using NLP (natural language processing) functions, generates an appropriate answer, and sends it to the terminal. The terminal displays the answer to the user. The input is the user's question, and the output is the generated answer.

[0523] Step 6: Progress Tracking and Testing

[0524] The server periodically displays an interface on the terminal that conducts comprehension tests. The user takes the test on the terminal and submits their answers. The server scores the answers using an automatic scoring system and stores the results in a database. The server then provides feedback on the results to the user. The input is the test answers, and the output is the scoring results and feedback.

[0525] Step 7: Personalized feedback and next steps

[0526] The server selects the next learning content and assignment based on the results of the comprehension test. The selected information is sent to the terminal, and feedback and new assignments are displayed to the user. The user then works on the suggested assignments. The input is the test results, and the output is feedback and assignment suggestions.

[0527] Step 8: Emotion Recognition and Responding

[0528] The server uses an emotion engine to monitor the user's facial expressions and tone of voice in real time while they are studying via their device. It identifies the user's emotional state and stores it in a database. The server then provides optimal feedback and adjusts the learning content based on the user's emotional state. For example, if the server identifies the user as tired, it will suggest taking a break, and if the user is in an adaptive state, it will display an encouraging message. The input is the user's facial expression and tone of voice data, and the output is the emotion analysis results and feedback based on them.

[0529] Step 9: Facilitate discussion and communication

[0530] The server periodically provides discussion topics and displays them on the terminal. Users input their opinions on the topics and exchange them with other users. The server stores the posted opinions in a database and displays them to other participants in real time. The input is the discussion topic and user opinions, and the output is a log of the opinion exchange.

[0531] (Application example 2)

[0532] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0533] Conventional educational support systems have difficulty providing individual learning methods based on the cognitive characteristics of each student, and in particular, do not provide a learning experience that takes into account their emotional state, resulting in insufficient learning effectiveness. Furthermore, they are unable to effectively resolve questions in real time during learning or exchange opinions with other students, resulting in a lack of progress management and feedback provision. It is necessary to solve these issues and provide the optimal learning environment for each student.

[0534] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0535] In this invention, the server includes a means for inputting basic information about the subject, a means for determining the subject's cognitive characteristics, a means for proposing an optimal learning method based on the determination results, a means for providing learning content, a means for tracking learning progress and conducting comprehension tests, a means for providing individual feedback to the subject, a means for resolving questions during learning in real time, a means for recognizing the subject's emotional state and providing feedback accordingly, and a means for delivering educational content via a head-mounted display. This makes it possible to provide an optimal learning experience that takes into account the subject's cognitive characteristics and emotional state. Furthermore, by promoting real-time question resolution and opinion exchange, learning efficiency can be improved.

[0536] "Means for entering basic information about the subject" refers to a function for entering basic information related to learning, such as the subject's name, age, grade, and areas of interest, through a user interface and saving it in a database.

[0537] "Means for assessing the cognitive characteristics of subjects" refers to a function that provides questions and tasks to assess the cognitive features and characteristics of subjects, and collects and analyzes the responses.

[0538] "Means for proposing optimal learning methods based on assessment results" is a function that recommends the most suitable learning style and learning materials for each individual based on the assessment results of their cognitive characteristics.

[0539] "Means for providing learning content" refers to the function of selecting and distributing learning materials, such as videos, texts, and audio materials, to target users.

[0540] "Means for tracking learning progress and conducting comprehension tests" refers to a function that monitors the learning progress of the subject and periodically conducts tests to assess comprehension.

[0541] "Means for providing individual feedback to the subject" refers to a function for providing appropriate advice and guidance to the subject individually based on the subject's learning outcomes and progress.

[0542] "Means for resolving questions during learning in real time" refers to a function that provides immediate answers to questions or queries that students encounter while learning.

[0543] "Means for recognizing the emotional state of the subject and providing feedback accordingly" refers to a function that monitors the subject's facial expressions, tone of voice, etc. in real time, analyzes their emotional state, and provides appropriate feedback.

[0544] "Means for delivering educational content through a head-mounted display" refers to a function for effectively delivering visual and auditory educational content to a target audience using a head-mounted display (HMD).

[0545] This invention is an AI system for educational support that determines the cognitive characteristics and emotional state of the subject and provides optimal learning methods and content based on that. This system functions among four parties: a server, a terminal, a user, and an emotion engine.

[0546] First, the user enters basic information, such as name, age, grade, and areas of interest, through a user interface provided by the server. The entered information is stored using a database management system such as SQLite. This information is used to assess cognitive characteristics and customize learning content.

[0547] Next, a cognitive test is administered to determine the subject's cognitive characteristics. The CognitiveTest module uses a series of questions and tasks displayed in the user interface. The user answers these questions, and the responses are collected and analyzed by the server. This identifies visual, verbal, and auditory cognitive characteristics.

[0548] Based on the results of the assessment, the server will suggest the optimal learning method. For example, video materials may be recommended for visually dominant students, and text materials for verbally dominant students. These learning methods and content are provided via devices such as head-mounted displays (HMDs). Using an HMD makes the learning experience more visual and interactive.

[0549] As learning progresses, the server tracks learning progress and periodically conducts comprehension tests. The UserTracking module monitors the learning progress of the subject and conducts comprehension tests based on that data. The test results are stored in a database and used to adjust subsequent learning plans.

[0550] Furthermore, the emotion engine monitors the user's emotional state in real time. Using the camera and microphone installed in the HMD, the server analyzes facial expressions and tone of voice to recognize the user's emotional state. For example, if the server determines that the subject is feeling tired, it will provide feedback such as "Take a short break."

[0551] Another important feature is real-time question resolution. The server accepts questions via the device and provides immediate answers generated by AI. This is effective in immediately resolving any difficulties users may have while studying and maintaining continuity in their learning.

[0552] Finally, the server periodically provides discussion topics to encourage exchange of ideas between users. This functionality is realized through the DiscussionModule, allowing users to exchange ideas with other users about what they have learned and deepen their understanding.

[0553] Here are some example prompts:

[0554] "D is a first-year high school student who is interested in math. Please suggest the best study method for D based on his cognitive characteristics and emotional state. What should we do if D does not show interest while studying?"

[0555] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0556] Step 1:

[0557] The server provides a user interface to the terminal for inputting basic user information. The user inputs basic information such as name, age, grade, and areas of interest. This input data is sent to the server and stored in a database. The input here is the user's basic information, and the output is the user information stored in the database.

[0558] Step 2:

[0559] The server displays the cognitive characteristics assessment test interface on the terminal. The user clicks the test start button on the terminal to begin the cognitive characteristics assessment test. The terminal displays the questions received from the server to the user and accepts the user's answers. The user inputs answer data, which the server collects and analyzes in real time. The output is the user's cognitive characteristics assessment results.

[0560] Step 3:

[0561] The server proposes the optimal learning method based on the cognitive characteristic assessment results. Based on the assessment results, the server selects the most appropriate learning method from various options (video, text, audio materials, etc.). This selected learning method is displayed on the user's device from the server. The input is the cognitive characteristic assessment results, and the output is a proposal for the optimal learning method.

[0562] Step 4:

[0563] The server provides the user with optimal learning content. The user receives the video and text learning materials provided by the server through their terminal. The input here is information on the optimal learning method, and the output is the learning content itself. The learning content is delivered via a head-mounted display (HMD), which the user uses to progress through their studies.

[0564] Step 5:

[0565] The server tracks learning progress and conducts comprehension tests. Each time a user uses learning content, the server monitors their progress in real time. It also periodically presents tests to assess comprehension, which the user answers. The server evaluates the level of comprehension based on the response data and stores this in a database. The input is learning progress data and test answers, and the output is the comprehension assessment results.

[0566] Step 6:

[0567] The server provides the ability to solve questions during learning in real time. When a user inputs a question into the terminal, the question is sent to the server. The server analyzes the question, generates an answer instantly, and sends it to the terminal. The input is the user's question data, and the output is the answer to that question.

[0568] Step 7:

[0569] The server uses an emotion engine to monitor the user's emotional state in real time. The HMD's built-in camera and microphone collect the user's facial expressions and tone of voice, which are then analyzed by the emotion engine. If the server determines that the user is tired based on this, it provides feedback such as "Take a short break." The input is the user's facial expressions and voice data, and the output is the emotional state analysis results and feedback.

[0570] Step 8:

[0571] The server periodically provides users with discussion topics and promotes the exchange of opinions between users. The server selects topics and displays them on the user's device. Users use their devices to exchange opinions with other users, and the content is sent to the server. The input is the discussion topic and user opinion data, and the output is the result of the exchange of opinions.

[0572] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0573] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0574] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0575] [Second embodiment]

[0576] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0577] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0578] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0579] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0580] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0581] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0582] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0583] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0584] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0585] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0586] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0587] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0588] This invention is an AI system for educational support that maximizes learning effectiveness by determining the cognitive characteristics of each individual and proposing individually appropriate learning methods, thereby addressing educational disparities, school absenteeism, and support for people with disabilities. This system functions among three parties: a server, a terminal, and a user.

[0589] Overall system overview

[0590] This system provides educational support tailored to the target individual by performing the following processes.

[0591] 1. Obtain basic information about the subject.

[0592] 2. Determine the cognitive characteristics of the subject.

[0593] 3. Based on the results of the assessment, the optimal learning method is proposed.

[0594] 4. Provide learning content.

[0595] 5. Track your progress and test your comprehension.

[0596] 6. Provide personalized feedback.

[0597] 7. Resolve your doubts while studying in real time.

[0598] 8. Suggest discussion topics and encourage exchange of ideas.

[0599] Program processing

[0600] Below, the program processing at each step of this system will be explained in natural language.

[0601] 1. User Registration

[0602] The server provides a user registration page.

[0603] Users use the terminal to enter basic information such as name, age, grade, and areas of interest.

[0604] The server stores basic information about the user in a database.

[0605] 2. Cognitive trait assessment test

[0606] The server displays the interface for the cognitive characteristics assessment test on the terminal.

[0607] The user clicks the Start Test button to begin the test.

[0608] The server sends a series of questions or tasks to the terminal in sequence.

[0609] The terminal displays each question or task to the user and accepts responses.

[0610] The user answers each question at the terminal.

[0611] The server receives the user's responses and stores them in a database in real time.

[0612] The server analyzes the collected data and determines the user's visual, linguistic, and auditory cognitive characteristics.

[0613] 3. Learning method suggestions

[0614] Based on the results of the judgment, the server selects the most suitable learning method for the user.

[0615] The server presents the selected learning method and related learning materials to the terminal.

[0616] The device displays learning method suggestions and introductions to learning materials to the user.

[0617] 4. Providing learning content

[0618] The server provides users with learning content (video, text, audio materials, etc.) appropriate for their needs.

[0619] The user checks the learning content on the device and begins learning.

[0620] The device records the user's learning progress in real time.

[0621] 5. Real-time support

[0622] The server provides an interface that accepts questions from users during their studies via the terminal.

[0623] The user inputs a question into the terminal and sends it.

[0624] The server analyzes the question and provides an appropriate answer instantly.

[0625] The terminal displays the response from the server to the user.

[0626] 6. Progress Tracking and Comprehension Testing

[0627] The server periodically displays an interface on the terminal that allows users to take comprehension tests.

[0628] The user takes the test at the terminal.

[0629] The terminal transmits the user's answer to the server.

[0630] The server scores the answers, stores the results in a database, and provides feedback to the user.

[0631] 7. Personalized feedback and suggestions for next steps

[0632] The server analyzes the results of the user's comprehension test and suggests the next learning content and assignments.

[0633] The device displays feedback and new challenges to the user.

[0634] The user works on the proposed tasks on the device.

[0635] 8. Facilitating discussion and communication

[0636] The server periodically provides discussion topics.

[0637] The terminal displays discussion topics to the user and provides a form where responses and opinions can be entered.

[0638] Users input their opinions on the terminal and exchange opinions with other users.

[0639] Specific examples

[0640] For example, let's say Mr. C is a second-year junior high school student who wants to study history.

[0641] 1. User Registration

[0642] Mr. C types into his terminal, "Second year junior high school student, interested in history."

[0643] The server stores this information.

[0644] 2. Cognitive trait assessment test

[0645] Mr. C clicks the start test button on his device.

[0646] The server begins the validation test.

[0647] The device will display questions such as, "Is it easy to remember with an image?"

[0648] C answers the questions.

[0649] The server analyzes Mr. C's answers and determines that he is visually dominant.

[0650] 3. Learning method suggestions

[0651] "Learn about historical events through videos," suggests the server.

[0652] A link to the video material will be displayed on the device.

[0653] 4. Providing learning content

[0654] Mr. C starts watching the video on his device.

[0655] 5. Real-time support

[0656] Mr. C types the question into his terminal: "I don't understand the background of this war."

[0657] The server provides the answer, which is displayed on the terminal.

[0658] 6. Progress Tracking and Comprehension Testing

[0659] After watching the video, the server conducts a comprehension test.

[0660] Mr. C takes the test on a terminal.

[0661] 7. Personalized feedback and suggestions for next steps

[0662] The server analyzes the test results and suggests, "Next, let's learn more about the causes of this war."

[0663] The next learning content will be displayed to Mr. C on his terminal.

[0664] 8. Facilitating discussion and communication

[0665] The server suggests that next week's theme will be "Important Figures in Modern History," and provides a platform where users can exchange opinions.

[0666] Mr. C can input his opinions on the device and discuss them with his classmates.

[0667] In this way, the AI ​​system can provide an optimal educational experience tailored to individual learning needs, creating an environment in which Mr. C can learn independently.

[0668] The processing flow will be explained below.

[0669] Step 1:

[0670] The server provides a user registration page, where users use their terminals to enter basic information such as name, age, grade, and areas of interest, and the server stores the entered basic information in a database.

[0671] Step 2:

[0672] The server displays the cognitive characteristics assessment test interface on the terminal, and the user clicks the test start button to start the test.

[0673] Step 3:

[0674] The server sequentially sends a series of questions or tasks to the terminal, which displays the questions or tasks to the user and accepts answers. The user answers each question on the terminal.

[0675] Step 4:

[0676] The server receives the user's responses and stores them in a database in real time. The server analyzes the collected data to determine the user's visual, linguistic, and auditory cognitive characteristics.

[0677] Step 5:

[0678] Based on the results of the assessment, the server selects the optimal learning method for the user. The server then presents the selected learning method and related learning materials to the terminal. The terminal then displays suggested learning methods and introductions to the learning materials to the user.

[0679] Step 6:

[0680] The server provides learning content (video, text, audio, etc.) appropriate for the user. The user checks the learning content on the device and begins learning. The device records the user's learning progress in real time.

[0681] Step 7:

[0682] The server provides an interface that accepts questions from users during their studies via their terminal. The user inputs and submits a question on the terminal. The server analyzes the question and instantly generates and provides an appropriate answer. The terminal displays the answer from the server to the user.

[0683] Step 8:

[0684] The server periodically displays an interface on the device that conducts comprehension tests. The user takes the test on the device. The device sends the user's answers to the server. The server grades the answers, stores the results in a database, and provides feedback to the user.

[0685] Step 9:

[0686] The server analyzes the results of the user's comprehension test and suggests the next learning content and assignments. The device displays feedback and new assignments to the user. The user then works on the suggested assignments.

[0687] Step 10:

[0688] The server periodically provides discussion topics. The terminal displays the discussion topics to the user and provides a form in which the user can enter their answers and opinions. The user enters their opinions on the terminal and exchanges opinions with other users.

[0689] Example 1

[0690] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0691] Modern education demands optimal learning methods based on individual cognitive characteristics. However, many current educational systems only provide uniform learning methods, making it difficult to address individual cognitive characteristics. Furthermore, they lack features such as learning progress tracking, comprehension tests, and real-time question resolution, making it difficult to adequately address individual learning needs. Furthermore, there are few systems that automatically suggest learning content and provide feedback, preventing the effectiveness of education from being maximized.

[0692] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0693] In this invention, the server includes means for inputting basic information about the subject, means for determining the cognitive characteristics of the subject, means for proposing an optimal learning method based on the determination results, means for providing learning content, means for tracking learning progress and conducting comprehension tests, means for providing individual feedback to the subject, means for resolving questions during learning in real time, means for saving the subject's input and learning progress in a database, means for collecting questions from the subject and generating answers using a generative AI model, and means for evaluating the subject's answers and dynamically proposing the next learning content. This makes it possible to provide an optimal learning method according to individual cognitive characteristics, track learning progress, resolve questions in real time, and dynamically suggest learning content.

[0694] "Target" refers to an individual who uses an educational support AI system to advance their learning.

[0695] "Basic information" refers to basic information necessary for education, such as the subject's name, age, grade, and areas of interest.

[0696] "Cognitive characteristics" are the information processing characteristics of a subject, such as vision, language, and hearing, and indicate individual characteristics in learning.

[0697] "Learning methods" are optimal learning methods or approaches suggested based on cognitive characteristics, including learning materials and learning formats.

[0698] "Learning content" refers to learning videos, texts, audio materials, etc. provided to the target audience, and is an information resource to support learning.

[0699] "Study progress" refers to the progress that a subject makes as they progress through their studies.

[0700] A "comprehension test" is a test used to measure the subject's level of comprehension of the learning content.

[0701] "Individual feedback" refers to specific assessments and guidance provided to students based on the results of comprehension tests and their learning progress.

[0702] "Real-time question resolution" means providing immediate and appropriate answers to questions that students have while studying.

[0703] A "database" is a system that stores and manages data such as basic information about the subject, their learning progress, and the content of their responses.

[0704] A "generative AI model" is an artificial intelligence model used to generate appropriate answers to user questions.

[0705] "Dynamic suggestions" means generating and suggesting the next content or tasks to be learned on an ongoing basis based on the student's learning progress and level of understanding.

[0706] This invention relates to an AI system for supporting education, which maximizes learning effectiveness by providing optimal learning methods based on individual cognitive characteristics, and addresses educational disparities, school absenteeism, and support for people with disabilities. The system functions among three parties: a server, a terminal, and a user.

[0707] Overall system overview

[0708] The system provides tailored educational support by:

[0709] 1. Obtain basic information about the subject.

[0710] 2. Determine the cognitive characteristics of the subject.

[0711] 3. Based on the results of the assessment, the optimal learning method is proposed.

[0712] 4. Provide learning content.

[0713] 5. Track your progress and test your comprehension.

[0714] 6. Provide personalized feedback.

[0715] 7. Resolve your doubts while studying in real time.

[0716] 8. Suggest discussion topics and encourage exchange of ideas.

[0717] Hardware and software used

[0718] The hardware used includes a server and user devices. The server uses a database (e.g., MySQL, PostgreSQL) for managing and analyzing user information, an execution environment for machine learning models (e.g., Python, Scikit-learn), a real-time chat system (e.g., Node.js), and a generative AI model (e.g., OpenAI GPT-3).

[0719] The user device provides an interface that runs on a web browser and processes user operations and learning progress using HTML, CSS, JavaScript, React, etc.

[0720] Program processing overview

[0721] User Registration

[0722] The server generates a user registration page using HTML and CSS and sends it to the device. The user enters basic information such as name, age, grade, and areas of interest on the device and submits it. The server receives the information in JSON format and stores it in a database.

[0723] Cognitive trait assessment test

[0724] The server generates the cognitive trait assessment test interface using JavaScript and React and displays it on the device. The user starts the test and answers a series of questions. The server receives the answers, stores them in a database, and uses a Python machine learning model to analyze the data and determine cognitive traits.

[0725] Learning method suggestions

[0726] The server determines the optimal learning method based on the cognitive characteristics and selects relevant learning materials, which are then sent to the terminal, which then presents them to the user.

[0727] Providing learning content

[0728] The server provides the selected learning content, which the user uses on their device to progress through the learning process. The device records the learning progress in real time and sends it to the server.

[0729] Real-time Support

[0730] The server receives the user's question through the device, generates an appropriate answer using the generative AI model, and sends it to the device for display.

[0731] Progress tracking and comprehension tests

[0732] The server periodically conducts comprehension tests and stores the results in a database, providing feedback to the user and suggesting what to study next.

[0733] Individual feedback and suggestions for next steps

[0734] The server analyzes the next learning content based on the test results and provides feedback and new challenges to the user, thereby presenting the optimal learning path for each individual user.

[0735] Facilitating discussion and communication

[0736] The server periodically generates new discussion topics and presents them to users, who can then input their opinions on their terminals and exchange opinions with other users.

[0737] Specific examples

[0738] For example, consider the case where Mr. C is a second-year junior high school student who wants to study history.

[0739] 1. Mr. C enters "I'm a second-year junior high school student and I'm interested in history" on his device and sends the information. The server saves this information.

[0740] 2. Person C starts the cognitive ability assessment test on his terminal. The server displays questions, and Person C inputs answers. The server analyzes the answers and determines that Person C is visually dominant.

[0741] 3. The server suggests, "Let's learn about historical events through videos," and displays a link to the video material on the device.

[0742] 4. Mr. C starts watching the video on his device. The device records his learning progress and sends it to the server.

[0743] 5. When Mr. C enters a question such as "I don't understand the background of this war," the server uses a generative AI model to generate and display an answer.

[0744] 6. After watching the video, the server conducts a comprehension test, and Mr. C takes the test. The results are sent to the server, which then suggests the next learning content.

[0745] 7. The server suggests a new task: "Next, let's learn more about the causes of this war," and displays it on the device.

[0746] 8. The server suggests that next week’s topic is “Important Figures in Modern History” and provides a discussion platform. C can input his opinions and discuss them with his classmates.

[0747] Prompt Sentence Examples

[0748] "If you have a second-year junior high school student who wants to study history, how would you use AI to suggest the best way to learn it? Please explain the specific process."

[0749] In this way, AI systems can provide optimal educational experiences tailored to individual learning needs and create an environment in which participants can learn independently.

[0750] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0751] Step 1:

[0752] User Registration

[0753] The server generates a user registration page using HTML and CSS and sends it to the device. The user enters basic information such as name, age, grade, and areas of interest on the device and submits it. The server receives the received information in JSON format and saves it in the database. This registers the user's basic information in the database. The input is the user's basic information, and the output is the user's basic information saved in the database.

[0754] Step 2:

[0755] Cognitive trait assessment test

[0756] The server uses JavaScript and React to generate an interface for the cognitive trait assessment test and displays it on the device. The user clicks a button to start the test and answers a series of questions. The device displays each question and accepts the user's answers. The server stores the received answers in a database and analyzes the data using a Python machine learning model to determine the user's cognitive traits. The input is the user's answers and the output is the assessed cognitive traits. This reveals the user's cognitive traits.

[0757] Step 3:

[0758] Learning method suggestions

[0759] The server selects the optimal learning method based on cognitive characteristics and selects related learning materials. The server sends the selected learning method and learning materials to the terminal via REST API. The terminal displays this to the user. The input is cognitive characteristics and a learning material database, and the output is a link between the learning method and learning materials presented to the user. This allows the optimal learning method to be presented to the user.

[0760] Step 4:

[0761] Providing learning content

[0762] The server dynamically generates learning content appropriate for the user and sends it to the device. The user checks the learning content on the device and begins learning. The device records learning progress and periodically sends it to the server. The input is the user's cognitive characteristics and progress, and the output is the learning content provided and a record of learning progress. This allows the user to study with content that is appropriate for them.

[0763] Step 5:

[0764] Real-time Support

[0765] The server provides an interface that accepts user questions via the terminal. The user inputs a question on the terminal and sends it to the server. The server analyzes the question and generates the optimal answer using a generative AI model. The server sends the answer to the terminal, which displays it to the user. The input is the user's question, and the output is the generated answer. This allows the user's question to be resolved instantly.

[0766] Step 6:

[0767] Progress tracking and comprehension tests

[0768] The server periodically displays an interface on the terminal that conducts comprehension tests. The user takes the test on the terminal and sends the answers to the server. The server scores the answers and stores the results in a database. It then generates feedback based on the results and sends it to the terminal. The input is the answers to the comprehension test, and the output is the test results and feedback. This evaluates the user's level of understanding and determines the next learning content.

[0769] Step 7:

[0770] Individual feedback and suggestions for next steps

[0771] The server analyzes the test results and determines the next learning content. The server sends feedback and new assignments to the device, which displays them to the user. The user then works on the suggested assignments. The input is the test results and learning objectives, and the output is feedback and new suggested assignments. This allows the user to continuously work on appropriate assignments.

[0772] Step 8:

[0773] Facilitating discussion and communication

[0774] The server periodically generates discussion topics and sends them to the terminals. Users input their opinions on their terminals and send them to the server. The server collects the opinions and displays them to other users, allowing for an exchange of opinions. The input is the user's opinion, and the output is the shared opinion and discussion results. This promotes communication between users and leads to deeper understanding.

[0775] (Application example 1)

[0776] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0777] With conventional educational systems, it has been difficult to efficiently grasp the cognitive characteristics of each individual student and propose optimal learning methods based on that.In addition, there is a lack of educational support for industrial product operation methods and control technologies in industrial workplaces, and automatic and effective measures are needed as a means of improving engineers' skills.

[0778] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0779] In this invention, the server includes means for inputting basic information about the subject, means for determining the cognitive characteristics of the subject, means for proposing an optimal learning method based on the determination results, means for providing learning content, means for tracking learning progress and conducting comprehension tests, means for providing individual feedback and proposing next tasks to the subject, means for resolving questions during learning in real time, means for promoting the exchange of opinions between subjects, and means for supporting learning of industrial product operation methods and control technology. This makes it possible to propose a learning method optimal for the cognitive characteristics of each subject, and to automatically and effectively provide education on industrial product operation methods and control technology.

[0780] 1. "Basic information of the subject" refers to personal information such as the subject's name, age, years of experience, and field of expertise.

[0781] 2. "Cognitive characteristics" refers to the individual characteristics of how a subject receives, processes, and understands information, such as visual dominance, auditory dominance, or verbal dominance.

[0782] 3. "Optimal learning method" refers to the most effective learning method based on the cognitive characteristics of the individual.

[0783] 4. "Learning Content" refers to the learning materials and information provided to a target audience for learning, including video, text, and audio materials.

[0784] 5. "Tracking learning progress" refers to recording and managing the learning progress of a student in real time.

[0785] 6. "Comprehension test" refers to a test to assess the extent to which a subject has understood the learning content.

[0786] 7. "Individualized feedback" refers to specific advice and next steps provided based on the learner's learning progress and level of understanding.

[0787] 8. "Resolving questions during learning in real time" refers to providing immediate answers to questions that arise during learning.

[0788] 9. "Promoting exchange of opinions" refers to support provided to stimulate information sharing and discussion among participants.

[0789] 10. "Supporting learning about the operation methods and control techniques of industrial products" refers to educational support to promote understanding of the correct operation methods and control techniques of industrial products and equipment used in industry.

[0790] Overall system configuration

[0791] This invention describes a specific embodiment for implementing an educational support system consisting of a server, a terminal, and a user. This system proposes optimal learning methods based on the cognitive characteristics of each individual and supports education on industrial product operation methods and control technologies.

[0792] Hardware and software used

[0793] The present invention uses the following hardware and software.

[0794] Server: High-performance server (e.g. AWS, Google Cloud)

[0795] Terminals: Smartphones, factory robot HMI (Human-Machine Interface), PCs

[0796] Frontend: Angular, HTML5, CSS3, JavaScript

[0797] Backend: Node.js, MySQL

[0798] AI modeling: Python, TensorFlow, Socket.IO

[0799] Program processing

[0800] 1. User Registration

[0801] The server serves a user registration page in Angular on the front end.

[0802] The user uses a terminal to enter basic information such as name, age, years of experience, and field of expertise.

[0803] The server receives this information via Node.js and stores it in a MySQL database.

[0804] 2. Assessment of cognitive characteristics

[0805] The server uses an Angular front-end to provide an interface for questions and tasks to assess cognitive characteristics.

[0806] The user starts the test at the terminal and answers the questions.

[0807] The server receives the responses and uses Python and TensorFlow to analyze the data and determine cognitive traits.

[0808] 3. Learning method suggestions

[0809] Based on the analysis results, the server selects the optimal learning method and suggests corresponding learning materials.

[0810] The terminal displays the suggestions and educational materials to the user.

[0811] 4. Providing learning content

[0812] The server provides learning content (video, audio, text) that best suits the user's cognitive characteristics.

[0813] Users can view this content on their devices and progress as they study, with their progress recorded in real time.

[0814] 5. Real-time support

[0815] If a user has a question while studying, they can enter it using their smartphone or tablet.

[0816] The server uses Socket.IO to receive questions in real time, processes them in Python, and provides instant answers.

[0817] 6. Progress Tracking and Comprehension Testing

[0818] The server periodically conducts comprehension tests, analyzes the results, stores them in a database, and provides feedback to the user.

[0819] 7. Personalized feedback and suggestions for next steps

[0820] The server suggests the next learning task based on the test results and provides related learning content.

[0821] 8. Facilitating discussion and communication

[0822] The server periodically provides discussion topics and provides an interface that encourages the exchange of ideas between users.

[0823] Users can input their opinions on the terminal and hold discussions with other users.

[0824] Examples and prompts

[0825] As a concrete example, consider the case where engineer A is learning how to operate a new industrial robot.

[0826] If engineer A enters "years of experience: 5 years, specialty: industrial robot control" and has visually dominant cognitive characteristics, the system will suggest, "Let's learn the basic operation of industrial robots through video materials." Engineer A will begin learning by watching the video materials, and if he has any questions, he can ask, "Please tell me more about how the sensors on this robot work." The server will immediately provide an appropriate answer to this question.

[0827] An example of a prompt is:

[0828] "For an engineer with five years of experience operating robots, please propose an industrial robot operation method that is easy for a person with visually dominant cognitive characteristics to learn. Also, please suggest related video teaching materials."

[0829] Possible possibilities include:

[0830] In this way, it is possible to propose a learning method that is optimal for the cognitive characteristics of each individual, and to automatically and effectively educate the student on how to operate industrial products and control technology.

[0831] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0832] Step 1:

[0833] User Registration

[0834] The server serves a user registration page in Angular on the front end.

[0835] The user uses a terminal to enter basic information such as name, age, years of experience, and field of expertise.

[0836] The basic information entered is sent from the terminal to the server, which receives this information via Node.js and stores it in a MySQL database.

[0837] Input: Basic information such as name, age, years of experience, field of expertise, etc.

[0838] Output: Basic user information stored in the database

[0839] Step 2:

[0840] Determining cognitive characteristics

[0841] The server uses an Angular front-end to provide an interface for questions and tasks to assess cognitive characteristics.

[0842] The user starts the test at the terminal and answers the questions.

[0843] The server receives the response data and analyzes it using Python and TensorFlow to determine the user's cognitive characteristics, such as visual, auditory, and language.

[0844] Input: User response data

[0845] Output: Cognitive characteristics (visual, auditory, language, etc.)

[0846] Step 3:

[0847] Learning method suggestions

[0848] Based on the results of the analysis of cognitive characteristics, the server selects the optimal learning method and suggests corresponding learning materials.

[0849] The terminal displays the suggestions and educational materials to the user.

[0850] For example, video instructional materials are suggested to visually dominant users.

[0851] Input: Cognitive characteristic analysis results

[0852] Output: Suggested learning methods and materials

[0853] Step 4:

[0854] Providing learning content

[0855] The server provides learning content (video, audio, text) that best suits the user's cognitive characteristics.

[0856] Users can check this content on their devices and progress through their studies, with their progress recorded in real time on the server.

[0857] Input: Suggested learning methods and materials

[0858] Output: Providing learning content and recording progress

[0859] Step 5:

[0860] Real-time Support

[0861] If a user has a question while studying, they can enter it using their smartphone or tablet.

[0862] The server uses Socket.IO to receive questions in real time, processes them in Python, and provides instant answers.

[0863] Input: User question

[0864] Output: Answers provided in real time

[0865] Step 6:

[0866] Progress tracking and comprehension tests

[0867] The server periodically conducts comprehension tests, analyzes the results, stores them in a database, and provides feedback to the user.

[0868] The terminal displays the test results to the user.

[0869] Input: Comprehension test response data

[0870] Output: Test result analysis and feedback

[0871] Step 7:

[0872] Individual feedback and suggestions for next steps

[0873] Based on the results of the comprehension test, the server suggests the next learning task and provides related learning content.

[0874] The terminal displays the next assignment and related content to the user.

[0875] Input: Comprehension test results

[0876] Output: Providing next assignments and related learning content

[0877] Step 8:

[0878] Facilitating discussion and communication

[0879] The server periodically provides discussion topics and provides an interface that encourages the exchange of ideas between users.

[0880] Users can input their opinions on the terminal and hold discussions with other users.

[0881] Input: Discussion topics and user opinions

[0882] Output: Facilitated exchange of ideas and shared opinions

[0883] In this way, the educational support system is designed to function effectively by clarifying the roles of the server, terminal, and user at each step and organizing the specific operations and inputs and outputs.

[0884] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0885] This invention is an AI system for educational support that maximizes learning effectiveness by determining the cognitive characteristics of each individual and proposing individually appropriate learning methods, and by combining it with an emotion engine, provides an optimal learning experience by taking into account the emotional state of the individual. This system functions among four parties: a server, a terminal, a user, and an emotion engine.

[0886] Overall system overview

[0887] This system provides educational support tailored to the target individual by performing the following processes.

[0888] 1. Obtain basic information about the subject.

[0889] 2. Determine the cognitive characteristics of the subject.

[0890] 3. Based on the results of the assessment, the optimal learning method is proposed.

[0891] 4. Provide learning content.

[0892] 5. Track your progress and test your comprehension.

[0893] 6. Provide personalized feedback.

[0894] 7. Resolve your doubts while studying in real time.

[0895] 8. Use an emotion engine to recognize and respond to the subject's emotional state.

[0896] 9. Suggest discussion topics and encourage exchange of ideas.

[0897] Program processing

[0898] Below, the program processing at each step of this system will be explained in natural language.

[0899] 1. User Registration

[0900] The server provides a user registration page.

[0901] Users use the terminal to enter basic information such as name, age, grade, and areas of interest.

[0902] The server stores the entered basic information in a database.

[0903] 2. Cognitive trait assessment test

[0904] The server displays the interface for the cognitive characteristics assessment test on the terminal.

[0905] The user clicks the Start Test button to begin the test.

[0906] 3. Conducting a cognitive assessment test

[0907] The server sends a series of questions or tasks to the terminal in sequence.

[0908] The terminal displays questions and tasks to the user and accepts answers.

[0909] The user answers each question on the terminal.

[0910] The server receives the user's responses and stores them in a database in real time.

[0911] The server analyzes the collected data and determines the user's visual, linguistic, and auditory cognitive characteristics.

[0912] 4. Learning method suggestions

[0913] Based on the judgment results, the server selects the most suitable learning method for the user.

[0914] The server presents the selected learning method and related learning materials to the terminal.

[0915] The device displays learning method suggestions and introductions to learning materials to the user.

[0916] 5. Provision of learning content

[0917] The server provides users with learning content (video, text, audio materials, etc.) appropriate for their needs.

[0918] The user checks the learning content on the device and begins learning.

[0919] The device records the user's learning progress in real time.

[0920] 6. Real-time support

[0921] The server provides an interface that accepts questions from users during their studies via the terminal.

[0922] The user inputs a question into the terminal and sends it.

[0923] The server analyzes the question and instantly generates and provides the appropriate answer.

[0924] The terminal displays the response from the server to the user.

[0925] 7. Progress Tracking and Comprehension Testing

[0926] The server periodically displays an interface on the terminal that allows users to take comprehension tests.

[0927] The user takes the test at the terminal.

[0928] The terminal transmits the user's answer to the server.

[0929] The server scores the answers, stores the results in a database, and provides feedback to the user.

[0930] 8. Personalized feedback and suggestions for next steps

[0931] The server analyzes the results of the user's comprehension test and suggests the next learning content and assignments.

[0932] The device displays feedback and new challenges to the user.

[0933] The user tackles the proposed task.

[0934] 9. Emotion Recognition and Response

[0935] The server uses an emotion engine to monitor the user's emotional state during learning in real time through the terminal.

[0936] The emotion engine identifies emotions from the user's facial expressions and tone of voice, and stores the emotional state in a database.

[0937] The server adjusts the optimal feedback and learning content based on the user's emotional state.

[0938] 10. Facilitating discussion and communication

[0939] The server periodically provides discussion topics.

[0940] The terminal displays discussion topics to the user and provides a form where responses and opinions can be entered.

[0941] Users input their opinions on the terminal and exchange opinions with other users.

[0942] Specific examples

[0943] For example, let's say Mr. D is a first-year high school student who wants to study mathematics.

[0944] 1. User Registration

[0945] Mr. D types into his terminal, "First year high school student, interested in mathematics."

[0946] The server stores this information.

[0947] 2. Cognitive trait assessment test

[0948] Mr. D clicks the start test button on his device.

[0949] The server begins the validation test.

[0950] The device will display questions such as, "Is it easy to remember with an image?"

[0951] D answers the questions.

[0952] The server analyzes Mr. D's answers and determines that he is visually dominant.

[0953] 3. Learning method suggestions

[0954] "Learn math concepts through videos," suggests Thurber.

[0955] A link to the video material will be displayed on the device.

[0956] 4. Providing learning content

[0957] Mr. D starts watching the video on his device.

[0958] 5. Real-time support

[0959] Mr. D types a question into his terminal: "I don't know how to use this formula."

[0960] The server provides the answer, which is displayed on the terminal.

[0961] 6. Progress Tracking and Comprehension Testing

[0962] After watching the video, the server conducts a comprehension test.

[0963] Mr. D takes the test on a terminal.

[0964] 7. Personalized feedback and suggestions for next steps

[0965] The server analyzes the test results and suggests, "Next, try solving some real problems."

[0966] The next learning content will be displayed to Mr. D on his device.

[0967] 8. Emotion Recognition and Response

[0968] The server uses an emotion engine to analyze Mr. D's facial expressions and tone of voice while he is studying.

[0969] If the server identifies Mr. D as feeling tired, it will display a message on his device saying, "Let's take a short break."

[0970] Also, if Mr. D is in a state of joy or adaptation, the teacher will give him feedback such as "That's good enough" and encourage him to continue learning.

[0971] 9. Facilitating discussion and communication

[0972] The server suggests that next week's theme is "Application of Functions," and provides a platform where users can exchange opinions.

[0973] Mr. D can input his opinions on the device and discuss them with his classmates.

[0974] In this way, the AI ​​system can provide an optimal educational experience tailored to individual learning needs, creating an environment in which Mr. D can learn independently. By combining it with an emotion engine, it is possible to respond according to the user's emotional state, further improving learning effectiveness.

[0975] The processing flow will be explained below.

[0976] Step 1:

[0977] The server provides a user registration page, where users use their terminals to enter basic information such as name, age, grade, and areas of interest, and the server stores the entered basic information in a database.

[0978] Step 2:

[0979] The server displays the cognitive characteristics assessment test interface on the terminal, and the user clicks the test start button to start the test.

[0980] Step 3:

[0981] The server sequentially sends a series of questions or tasks to the terminal, which displays the questions or tasks to the user and accepts answers. The user answers each question on the terminal.

[0982] Step 4:

[0983] The server receives the user's responses and stores them in a database in real time. The server analyzes the collected data to determine the user's visual, linguistic, and auditory cognitive characteristics.

[0984] Step 5:

[0985] Based on the results of the assessment, the server selects the optimal learning method for the user. The server then presents the selected learning method and related learning materials to the terminal. The terminal then displays suggested learning methods and introductions to the learning materials to the user.

[0986] Step 6:

[0987] The server provides learning content (video, text, audio, etc.) appropriate for the user. The user checks the learning content on the device and begins learning. The device records the user's learning progress in real time.

[0988] Step 7:

[0989] The server provides an interface that accepts questions from users during their studies via their terminal. The user inputs and submits a question on the terminal. The server analyzes the question and instantly generates and provides an appropriate answer. The terminal displays the answer from the server to the user.

[0990] Step 8:

[0991] The server periodically displays an interface on the device that conducts comprehension tests. The user takes the test on the device. The device sends the user's answers to the server. The server grades the answers, stores the results in a database, and provides feedback to the user.

[0992] Step 9:

[0993] The server analyzes the results of the user's comprehension test and suggests the next learning content and assignments. The device displays feedback and new assignments to the user. The user then works on the suggested assignments.

[0994] Step 10:

[0995] The server uses an emotion engine to monitor the user's emotional state in real time through the device while they are learning. The emotion engine identifies emotions from the user's facial expressions and tone of voice, and stores the emotional state in a database. The server then provides optimal feedback and adjusts the learning content based on the user's emotional state.

[0996] Step 11:

[0997] The server periodically provides discussion topics. The terminal displays the discussion topics to the user and provides a form in which the user can enter their answers and opinions. The user enters their opinions on the terminal and exchanges opinions with other users.

[0998] Example 2

[0999] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1000] Conventional educational systems have had difficulty providing learning methods that fully consider the cognitive characteristics and emotional state of each individual student. Furthermore, they lacked functionality for real-time resolution of questions that arise during learning and for easy exchange of opinions between students. This made it difficult to provide an optimal learning experience for each student, resulting in a lack of maximization of learning effectiveness.

[1001] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for inputting basic information about the subject, a means for determining the cognitive characteristics of the subject, a means for proposing an optimal learning method based on the determination results, a means for providing learning content, a means for tracking learning progress and conducting comprehension tests, a means for providing individual feedback to the subject, a means for resolving questions during learning in real time, and a means for recognizing and responding to the subject's emotional state using an emotion engine. This makes it possible to provide an optimal learning experience tailored to the subject's individual needs and maximize learning effectiveness. Furthermore, by encouraging the exchange of opinions between subjects as needed, the quality of learning can be expected to improve.

[1002] "Target audience" refers to learners who use the education system.

[1003] "Basic information" refers to basic data such as the subject's name, age, grade, and areas of interest.

[1004] "Cognitive characteristics" refers to the subject's cognitive style, such as visual, linguistic, and auditory.

[1005] A "judgment test" refers to a series of questions or tasks designed to assess a subject's cognitive characteristics.

[1006] "Feedback" refers to individual evaluations and advice provided based on the subject's learning results.

[1007] "Learning method" refers to the learning process and techniques proposed based on the cognitive characteristics of the subject.

[1008] "Learning content" includes learning materials and resources used for learning, such as videos, texts, and audio materials.

[1009] An "emotion engine" refers to a system that has the ability to recognize a subject's emotional state and process that data.

[1010] "Real-time support" refers to the function of providing immediate responses to questions or concerns that students may have while studying.

[1011] "Discussion Topics" refers to topics that are periodically provided by the server for the purpose of exchanging opinions among participants.

[1012] "Opinion exchange" refers to the activity of sharing opinions and thoughts among participants.

[1013] "Server" refers to a central computer that runs the entire system and provides each function.

[1014] "Device" means the computer or mobile device used by a Subject to access the System.

[1015] This invention is an AI system for educational support that maximizes learning effectiveness by determining the cognitive characteristics of each individual and proposing individually appropriate learning methods. Furthermore, by combining it with an emotion engine, it provides an optimal learning experience by taking into account the emotional state of each individual. This system functions among four parties: a server, a terminal, a user, and an emotion engine.

[1016] Overall system overview

[1017] This system provides educational support tailored to each individual through the following steps:

[1018] 1. Obtain basic information about the subject.

[1019] 2. Determine the cognitive characteristics of the subject.

[1020] 3. Based on the results of the assessment, the optimal learning method is proposed.

[1021] 4. Provide learning content.

[1022] 5. Track your progress and test your comprehension.

[1023] 6. Provide personalized feedback.

[1024] 7. Resolve your doubts while studying in real time.

[1025] 8. Use an emotion engine to recognize and respond to the subject's emotional state.

[1026] 9. Suggest discussion topics and encourage exchange of ideas.

[1027] Program processing

[1028] The processing of this system is carried out through cooperation between the server and the terminal, as detailed below.

[1029] Hardware and Software Use

[1030] The server uses a MySQL database to store and manage data.

[1031] The server uses Python to implement data analysis and decision algorithms.

[1032] The server provides a front end consisting of JavaScript and HTML.

[1033] The device accesses the server using a browser such as Google Chrome.

[1034] The emotion engine uses the camera and microphone to analyze the user's facial expressions and tone of voice.

[1035] Specific examples

[1036] For example, consider the following situation where Mr. D is a first-year high school student who wishes to study mathematics.

[1037] 1. User Registration

[1038] Mr. D enters "First year high school student, interested in mathematics" into the terminal. The form displayed on the terminal has fields for entering name, age, grade, and area of ​​interest.

[1039] When Mr. D clicks the "Register" button, the server receives the input data and saves it in the MySQL database.

[1040] 2. Cognitive trait assessment test

[1041] Mr. D clicks the start test button on his device. The server sends the UI for the assessment test, which is composed of HTML and JavaScript, to the device and asks a series of questions.

[1042] Questions such as "Is it easy to remember with an image?" are displayed on the device. Mr. D answers the questions, and the answers are saved in a database in real time.

[1043] 3. Learning method suggestions

[1044] Based on D's cognitive characteristics, the server suggests, "Let's learn mathematical concepts through videos." A link to the video material is displayed on the device.

[1045] 4. Providing learning content

[1046] Mr. D starts watching the video on his device. The server provides the video material through a video streaming service.

[1047] 5. Real-time support

[1048] During the study, Mr. D enters a question into his device, such as "I don't know how to use this formula." The server receives the question, analyzes it using natural language processing (NLP), instantly generates an appropriate answer, and displays it on the device.

[1049] 6. Progress Tracking and Comprehension Testing

[1050] After watching the video, the server periodically conducts comprehension tests. Mr. D takes the tests on his device and his answers are sent to the server. The server then uses an automatic scoring system to score the answers and stores the results in a database.

[1051] 7. Personalized feedback and suggestions for next steps

[1052] Based on the test results, the server suggests, "Next, try solving a real problem." The next learning content is displayed to Mr. D on his device.

[1053] 8. Emotion Recognition and Response

[1054] The server uses an emotion recognition algorithm to monitor Mr. D's facial expressions and tone of voice in real time while he is studying.

[1055] If D is identified as feeling tired, the server will display a message on his device saying, "Take a short break." If he is in a state of joy or adaptation, the server will provide feedback saying, "That's good," encouraging him to continue learning.

[1056] 9. Facilitating discussion and communication

[1057] The server suggests that next week's topic is "Application of Functions," and provides a platform for users to exchange opinions. D can input his opinion on his device and discuss it with his classmates.

[1058] Prompt Sentence Examples

[1059] "Please explain how to register by entering basic user information."

[1060] "Please explain with specific examples what kind of questions will be asked during the cognitive trait assessment test."

[1061] "Please explain how you handle real-time support if a user has a question while learning."

[1062] "Please explain the process of recognizing and responding to user emotions using the emotion engine."

[1063] This allows the AI ​​system to provide an optimal educational experience tailored to the user's individual learning needs, improving learning outcomes.The combination of an emotion engine enables the system to respond to the user's emotional state, further enhancing learning outcomes.

[1064] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1065] Step 1: User Registration

[1066] The server provides a user registration page. The user uses the terminal to enter basic information such as name, age, grade, and areas of interest. When the user clicks the "Register" button, the terminal sends the data to the server. The server receives the entered basic information and stores it in a database. The input here is the user's basic information, and the output is the data stored in the database.

[1067] Step 2: Cognitive trait assessment test

[1068] The server displays the cognitive ability assessment test interface on the terminal. The user clicks the test start button and answers the questions and tasks displayed on the terminal in sequence. The server receives each answer and stores them in a database one by one. Based on the collected answer data, the server uses Python to analyze the data and determine the user's visual, linguistic, and auditory cognitive abilities. The input is the user's test answers, and the output is the assessed cognitive abilities.

[1069] Step 3: Suggest a learning method

[1070] The server selects the optimal learning method and related learning materials based on the assessment results. The selected information is sent to the terminal and links to the learning methods and learning materials are displayed to the user. The input is the assessed cognitive characteristics, and the output is the suggested learning methods and links to the learning materials.

[1071] Step 4: Provide learning content

[1072] The server provides learning content such as videos, texts, and audio materials through a streaming service. The user checks the learning content on their device and begins learning. The device records the user's learning progress (e.g., video viewing time and text completion status) in real time and sends it to the server. The input is the learning content, and the output is learning progress data.

[1073] Step 5: Real-time support

[1074] The server provides an interface through the terminal for users to input questions they have while studying. The user inputs the question on the terminal and sends it. The server analyzes the question using NLP (natural language processing) functions, generates an appropriate answer, and sends it to the terminal. The terminal displays the answer to the user. The input is the user's question, and the output is the generated answer.

[1075] Step 6: Progress Tracking and Testing

[1076] The server periodically displays an interface on the terminal that conducts comprehension tests. The user takes the test on the terminal and submits their answers. The server scores the answers using an automatic scoring system and stores the results in a database. The server then provides feedback on the results to the user. The input is the test answers, and the output is the scoring results and feedback.

[1077] Step 7: Personalized feedback and next steps

[1078] The server selects the next learning content and assignment based on the results of the comprehension test. The selected information is sent to the terminal, and feedback and new assignments are displayed to the user. The user then works on the suggested assignments. The input is the test results, and the output is feedback and assignment suggestions.

[1079] Step 8: Emotion Recognition and Responding

[1080] The server uses an emotion engine to monitor the user's facial expressions and tone of voice in real time while they are studying via their device. It identifies the user's emotional state and stores it in a database. The server then provides optimal feedback and adjusts the learning content based on the user's emotional state. For example, if the server identifies the user as tired, it will suggest taking a break, and if the user is in an adaptive state, it will display an encouraging message. The input is the user's facial expression and tone of voice data, and the output is the emotion analysis results and feedback based on them.

[1081] Step 9: Facilitate discussion and communication

[1082] The server periodically provides discussion topics and displays them on the terminal. Users input their opinions on the topics and exchange them with other users. The server stores the posted opinions in a database and displays them to other participants in real time. The input is the discussion topic and user opinions, and the output is a log of the opinion exchange.

[1083] (Application example 2)

[1084] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1085] Conventional educational support systems have difficulty providing individual learning methods based on the cognitive characteristics of each student, and in particular, do not provide a learning experience that takes into account their emotional state, resulting in insufficient learning effectiveness. Furthermore, they are unable to effectively resolve questions in real time during learning or exchange opinions with other students, resulting in a lack of progress management and feedback provision. It is necessary to solve these issues and provide the optimal learning environment for each student.

[1086] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1087] In this invention, the server includes a means for inputting basic information about the subject, a means for determining the subject's cognitive characteristics, a means for proposing an optimal learning method based on the determination results, a means for providing learning content, a means for tracking learning progress and conducting comprehension tests, a means for providing individual feedback to the subject, a means for resolving questions during learning in real time, a means for recognizing the subject's emotional state and providing feedback accordingly, and a means for delivering educational content via a head-mounted display. This makes it possible to provide an optimal learning experience that takes into account the subject's cognitive characteristics and emotional state. Furthermore, by promoting real-time question resolution and opinion exchange, learning efficiency can be improved.

[1088] "Means for entering basic information about the subject" refers to a function for entering basic information related to learning, such as the subject's name, age, grade, and areas of interest, through a user interface and saving it in a database.

[1089] "Means for assessing the cognitive characteristics of subjects" refers to a function that provides questions and tasks to assess the cognitive features and characteristics of subjects, and collects and analyzes the responses.

[1090] "Means for proposing optimal learning methods based on assessment results" is a function that recommends the most suitable learning style and learning materials for each individual based on the assessment results of their cognitive characteristics.

[1091] "Means for providing learning content" refers to the function of selecting and distributing learning materials, such as videos, texts, and audio materials, to target users.

[1092] "Means for tracking learning progress and conducting comprehension tests" refers to a function that monitors the learning progress of the subject and periodically conducts tests to assess comprehension.

[1093] "Means for providing individual feedback to the subject" refers to a function for providing appropriate advice and guidance to the subject individually based on the subject's learning outcomes and progress.

[1094] "Means for resolving questions during learning in real time" refers to a function that provides immediate answers to questions or queries that students encounter while learning.

[1095] "Means for recognizing the emotional state of the subject and providing feedback accordingly" refers to a function that monitors the subject's facial expressions, tone of voice, etc. in real time, analyzes their emotional state, and provides appropriate feedback.

[1096] "Means for delivering educational content through a head-mounted display" refers to a function for effectively delivering visual and auditory educational content to a target audience using a head-mounted display (HMD).

[1097] This invention is an AI system for educational support that determines the cognitive characteristics and emotional state of the subject and provides optimal learning methods and content based on that. This system functions among four parties: a server, a terminal, a user, and an emotion engine.

[1098] First, the user enters basic information, such as name, age, grade, and areas of interest, through a user interface provided by the server. The entered information is stored using a database management system such as SQLite. This information is used to assess cognitive characteristics and customize learning content.

[1099] Next, a cognitive test is administered to determine the subject's cognitive characteristics. The CognitiveTest module uses a series of questions and tasks displayed in the user interface. The user answers these questions, and the responses are collected and analyzed by the server. This identifies visual, verbal, and auditory cognitive characteristics.

[1100] Based on the results of the assessment, the server will suggest the optimal learning method. For example, video materials may be recommended for visually dominant students, and text materials for verbally dominant students. These learning methods and content are provided via devices such as head-mounted displays (HMDs). Using an HMD makes the learning experience more visual and interactive.

[1101] As learning progresses, the server tracks learning progress and periodically conducts comprehension tests. The UserTracking module monitors the learning progress of the subject and conducts comprehension tests based on that data. The test results are stored in a database and used to adjust subsequent learning plans.

[1102] Furthermore, the emotion engine monitors the user's emotional state in real time. Using the camera and microphone installed in the HMD, the server analyzes facial expressions and tone of voice to recognize the user's emotional state. For example, if the server determines that the subject is feeling tired, it will provide feedback such as "Take a short break."

[1103] Another important feature is real-time question resolution. The server accepts questions via the device and provides immediate answers generated by AI. This is effective in immediately resolving any difficulties users may have while studying and maintaining continuity in their learning.

[1104] Finally, the server periodically provides discussion topics to encourage exchange of ideas between users. This functionality is realized through the DiscussionModule, allowing users to exchange ideas with other users about what they have learned and deepen their understanding.

[1105] Here are some example prompts:

[1106] "D is a first-year high school student who is interested in math. Please suggest the best study method for D based on his cognitive characteristics and emotional state. What should we do if D does not show interest while studying?"

[1107] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1108] Step 1:

[1109] The server provides a user interface to the terminal for inputting basic user information. The user inputs basic information such as name, age, grade, and areas of interest. This input data is sent to the server and stored in a database. The input here is the user's basic information, and the output is the user information stored in the database.

[1110] Step 2:

[1111] The server displays the cognitive characteristics assessment test interface on the terminal. The user clicks the test start button on the terminal to begin the cognitive characteristics assessment test. The terminal displays the questions received from the server to the user and accepts the user's answers. The user inputs answer data, which the server collects and analyzes in real time. The output is the user's cognitive characteristics assessment results.

[1112] Step 3:

[1113] The server proposes the optimal learning method based on the cognitive characteristic assessment results. Based on the assessment results, the server selects the most appropriate learning method from various options (video, text, audio materials, etc.). This selected learning method is displayed on the user's device from the server. The input is the cognitive characteristic assessment results, and the output is a proposal for the optimal learning method.

[1114] Step 4:

[1115] The server provides the user with optimal learning content. The user receives the video and text learning materials provided by the server through their terminal. The input here is information on the optimal learning method, and the output is the learning content itself. The learning content is delivered via a head-mounted display (HMD), which the user uses to progress through their studies.

[1116] Step 5:

[1117] The server tracks learning progress and conducts comprehension tests. Each time a user uses learning content, the server monitors their progress in real time. It also periodically presents tests to assess comprehension, which the user answers. The server evaluates the level of comprehension based on the response data and stores this in a database. The input is learning progress data and test answers, and the output is the comprehension assessment results.

[1118] Step 6:

[1119] The server provides the ability to solve questions during learning in real time. When a user inputs a question into the terminal, the question is sent to the server. The server analyzes the question, generates an answer instantly, and sends it to the terminal. The input is the user's question data, and the output is the answer to that question.

[1120] Step 7:

[1121] The server uses an emotion engine to monitor the user's emotional state in real time. The HMD's built-in camera and microphone collect the user's facial expressions and tone of voice, which are then analyzed by the emotion engine. If the server determines that the user is tired based on this, it provides feedback such as "Take a short break." The input is the user's facial expressions and voice data, and the output is the emotional state analysis results and feedback.

[1122] Step 8:

[1123] The server periodically provides users with discussion topics and promotes the exchange of opinions between users. The server selects topics and displays them on the user's device. Users use their devices to exchange opinions with other users, and the content is sent to the server. The input is the discussion topic and user opinion data, and the output is the result of the exchange of opinions.

[1124] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1125] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1126] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1127] [Third embodiment]

[1128] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1129] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1130] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1131] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1132] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1133] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1134] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1135] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1136] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1137] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1138] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1139] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1140] This invention is an AI system for educational support that maximizes learning effectiveness by determining the cognitive characteristics of each individual and proposing individually appropriate learning methods, thereby addressing educational disparities, school absenteeism, and support for people with disabilities. This system functions among three parties: a server, a terminal, and a user.

[1141] Overall system overview

[1142] This system provides educational support tailored to the target individual by performing the following processes.

[1143] 1. Obtain basic information about the subject.

[1144] 2. Determine the cognitive characteristics of the subject.

[1145] 3. Based on the results of the assessment, the optimal learning method is proposed.

[1146] 4. Provide learning content.

[1147] 5. Track your progress and test your comprehension.

[1148] 6. Provide personalized feedback.

[1149] 7. Resolve your doubts while studying in real time.

[1150] 8. Suggest discussion topics and encourage exchange of ideas.

[1151] Program processing

[1152] Below, the program processing at each step of this system will be explained in natural language.

[1153] 1. User Registration

[1154] The server provides a user registration page.

[1155] Users use the terminal to enter basic information such as name, age, grade, and areas of interest.

[1156] The server stores basic information about the user in a database.

[1157] 2. Cognitive trait assessment test

[1158] The server displays the interface for the cognitive characteristics assessment test on the terminal.

[1159] The user clicks the Start Test button to begin the test.

[1160] The server sends a series of questions or tasks to the terminal in sequence.

[1161] The terminal displays each question or task to the user and accepts responses.

[1162] The user answers each question at the terminal.

[1163] The server receives the user's responses and stores them in a database in real time.

[1164] The server analyzes the collected data and determines the user's visual, linguistic, and auditory cognitive characteristics.

[1165] 3. Learning method suggestions

[1166] Based on the results of the judgment, the server selects the most suitable learning method for the user.

[1167] The server presents the selected learning method and related learning materials to the terminal.

[1168] The device displays learning method suggestions and introductions to learning materials to the user.

[1169] 4. Providing learning content

[1170] The server provides users with learning content (video, text, audio materials, etc.) appropriate for their needs.

[1171] The user checks the learning content on the device and begins learning.

[1172] The device records the user's learning progress in real time.

[1173] 5. Real-time support

[1174] The server provides an interface that accepts questions from users during their studies via the terminal.

[1175] The user inputs a question into the terminal and sends it.

[1176] The server analyzes the question and provides an appropriate answer instantly.

[1177] The terminal displays the response from the server to the user.

[1178] 6. Progress Tracking and Comprehension Testing

[1179] The server periodically displays an interface on the terminal that allows users to take comprehension tests.

[1180] The user takes the test at the terminal.

[1181] The terminal transmits the user's answer to the server.

[1182] The server scores the answers, stores the results in a database, and provides feedback to the user.

[1183] 7. Personalized feedback and suggestions for next steps

[1184] The server analyzes the results of the user's comprehension test and suggests the next learning content and assignments.

[1185] The device displays feedback and new challenges to the user.

[1186] The user works on the proposed tasks on the device.

[1187] 8. Facilitating discussion and communication

[1188] The server periodically provides discussion topics.

[1189] The terminal displays discussion topics to the user and provides a form where responses and opinions can be entered.

[1190] Users input their opinions on the terminal and exchange opinions with other users.

[1191] Specific examples

[1192] For example, let's say Mr. C is a second-year junior high school student who wants to study history.

[1193] 1. User Registration

[1194] Mr. C types into his terminal, "Second year junior high school student, interested in history."

[1195] The server stores this information.

[1196] 2. Cognitive trait assessment test

[1197] Mr. C clicks the start test button on his device.

[1198] The server begins the validation test.

[1199] The device will display questions such as, "Is it easy to remember with an image?"

[1200] C answers the questions.

[1201] The server analyzes Mr. C's answers and determines that he is visually dominant.

[1202] 3. Learning method suggestions

[1203] "Learn about historical events through videos," suggests the server.

[1204] A link to the video material will be displayed on the device.

[1205] 4. Providing learning content

[1206] Mr. C starts watching the video on his device.

[1207] 5. Real-time support

[1208] Mr. C types the question into his terminal: "I don't understand the background of this war."

[1209] The server provides the answer, which is displayed on the terminal.

[1210] 6. Progress Tracking and Comprehension Testing

[1211] After watching the video, the server conducts a comprehension test.

[1212] Mr. C takes the test on a terminal.

[1213] 7. Personalized feedback and suggestions for next steps

[1214] The server analyzes the test results and suggests, "Next, let's learn more about the causes of this war."

[1215] The next learning content will be displayed to Mr. C on his terminal.

[1216] 8. Facilitating discussion and communication

[1217] The server suggests that next week's theme will be "Important Figures in Modern History," and provides a platform where users can exchange opinions.

[1218] Mr. C can input his opinions on the device and discuss them with his classmates.

[1219] In this way, the AI ​​system can provide an optimal educational experience tailored to individual learning needs, creating an environment in which Mr. C can learn independently.

[1220] The processing flow will be explained below.

[1221] Step 1:

[1222] The server provides a user registration page, where users use their terminals to enter basic information such as name, age, grade, and areas of interest, and the server stores the entered basic information in a database.

[1223] Step 2:

[1224] The server displays the cognitive characteristics assessment test interface on the terminal, and the user clicks the test start button to start the test.

[1225] Step 3:

[1226] The server sequentially sends a series of questions or tasks to the terminal, which displays the questions or tasks to the user and accepts answers. The user answers each question on the terminal.

[1227] Step 4:

[1228] The server receives the user's responses and stores them in a database in real time. The server analyzes the collected data to determine the user's visual, linguistic, and auditory cognitive characteristics.

[1229] Step 5:

[1230] Based on the results of the assessment, the server selects the optimal learning method for the user. The server then presents the selected learning method and related learning materials to the terminal. The terminal then displays suggested learning methods and introductions to the learning materials to the user.

[1231] Step 6:

[1232] The server provides learning content (video, text, audio, etc.) appropriate for the user. The user checks the learning content on the device and begins learning. The device records the user's learning progress in real time.

[1233] Step 7:

[1234] The server provides an interface that accepts questions from users during their studies via their terminal. The user inputs and submits a question on the terminal. The server analyzes the question and instantly generates and provides an appropriate answer. The terminal displays the answer from the server to the user.

[1235] Step 8:

[1236] The server periodically displays an interface on the device that conducts comprehension tests. The user takes the test on the device. The device sends the user's answers to the server. The server grades the answers, stores the results in a database, and provides feedback to the user.

[1237] Step 9:

[1238] The server analyzes the results of the user's comprehension test and suggests the next learning content and assignments. The device displays feedback and new assignments to the user. The user then works on the suggested assignments.

[1239] Step 10:

[1240] The server periodically provides discussion topics. The terminal displays the discussion topics to the user and provides a form in which the user can enter their answers and opinions. The user enters their opinions on the terminal and exchanges opinions with other users.

[1241] Example 1

[1242] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1243] Modern education demands optimal learning methods based on individual cognitive characteristics. However, many current educational systems only provide uniform learning methods, making it difficult to address individual cognitive characteristics. Furthermore, they lack features such as learning progress tracking, comprehension tests, and real-time question resolution, making it difficult to adequately address individual learning needs. Furthermore, there are few systems that automatically suggest learning content and provide feedback, preventing the effectiveness of education from being maximized.

[1244] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1245] In this invention, the server includes means for inputting basic information about the subject, means for determining the cognitive characteristics of the subject, means for proposing an optimal learning method based on the determination results, means for providing learning content, means for tracking learning progress and conducting comprehension tests, means for providing individual feedback to the subject, means for resolving questions during learning in real time, means for saving the subject's input and learning progress in a database, means for collecting questions from the subject and generating answers using a generative AI model, and means for evaluating the subject's answers and dynamically proposing the next learning content. This makes it possible to provide an optimal learning method according to individual cognitive characteristics, track learning progress, resolve questions in real time, and dynamically suggest learning content.

[1246] "Target" refers to an individual who uses an educational support AI system to advance their learning.

[1247] "Basic information" refers to basic information necessary for education, such as the subject's name, age, grade, and areas of interest.

[1248] "Cognitive characteristics" are the information processing characteristics of a subject, such as vision, language, and hearing, and indicate individual characteristics in learning.

[1249] "Learning methods" are optimal learning methods or approaches suggested based on cognitive characteristics, including learning materials and learning formats.

[1250] "Learning content" refers to learning videos, texts, audio materials, etc. provided to the target audience, and is an information resource to support learning.

[1251] "Study progress" refers to the progress that a subject makes as they progress through their studies.

[1252] A "comprehension test" is a test used to measure the subject's level of comprehension of the learning content.

[1253] "Individual feedback" refers to specific assessments and guidance provided to students based on the results of comprehension tests and their learning progress.

[1254] "Real-time question resolution" means providing immediate and appropriate answers to questions that students have while studying.

[1255] A "database" is a system that stores and manages data such as basic information about the subject, their learning progress, and the content of their responses.

[1256] A "generative AI model" is an artificial intelligence model used to generate appropriate answers to user questions.

[1257] "Dynamic suggestions" means generating and suggesting the next content or tasks to be learned on an ongoing basis based on the student's learning progress and level of understanding.

[1258] This invention relates to an AI system for supporting education, which maximizes learning effectiveness by providing optimal learning methods based on individual cognitive characteristics, and addresses educational disparities, school absenteeism, and support for people with disabilities. The system functions among three parties: a server, a terminal, and a user.

[1259] Overall system overview

[1260] The system provides tailored educational support by:

[1261] 1. Obtain basic information about the subject.

[1262] 2. Determine the cognitive characteristics of the subject.

[1263] 3. Based on the results of the assessment, the optimal learning method is proposed.

[1264] 4. Provide learning content.

[1265] 5. Track your progress and test your comprehension.

[1266] 6. Provide personalized feedback.

[1267] 7. Resolve your doubts while studying in real time.

[1268] 8. Suggest discussion topics and encourage exchange of ideas.

[1269] Hardware and software used

[1270] The hardware used includes a server and user devices. The server uses a database (e.g., MySQL, PostgreSQL) for managing and analyzing user information, an execution environment for machine learning models (e.g., Python, Scikit-learn), a real-time chat system (e.g., Node.js), and a generative AI model (e.g., OpenAI GPT-3).

[1271] The user device provides an interface that runs on a web browser and processes user operations and learning progress using HTML, CSS, JavaScript, React, etc.

[1272] Program processing overview

[1273] User Registration

[1274] The server generates a user registration page using HTML and CSS and sends it to the device. The user enters basic information such as name, age, grade, and areas of interest on the device and submits it. The server receives the information in JSON format and stores it in a database.

[1275] Cognitive trait assessment test

[1276] The server generates the cognitive trait assessment test interface using JavaScript and React and displays it on the device. The user starts the test and answers a series of questions. The server receives the answers, stores them in a database, and uses a Python machine learning model to analyze the data and determine cognitive traits.

[1277] Learning method suggestions

[1278] The server determines the optimal learning method based on the cognitive characteristics and selects relevant learning materials, which are then sent to the terminal, which then presents them to the user.

[1279] Providing learning content

[1280] The server provides the selected learning content, which the user uses on their device to progress through the learning process. The device records the learning progress in real time and sends it to the server.

[1281] Real-time Support

[1282] The server receives the user's question through the device, generates an appropriate answer using the generative AI model, and sends it to the device for display.

[1283] Progress tracking and comprehension tests

[1284] The server periodically conducts comprehension tests and stores the results in a database, providing feedback to the user and suggesting what to study next.

[1285] Individual feedback and suggestions for next steps

[1286] The server analyzes the next learning content based on the test results and provides feedback and new challenges to the user, thereby presenting the optimal learning path for each individual user.

[1287] Facilitating discussion and communication

[1288] The server periodically generates new discussion topics and presents them to users, who can then input their opinions on their terminals and exchange opinions with other users.

[1289] Specific examples

[1290] For example, consider the case where Mr. C is a second-year junior high school student who wants to study history.

[1291] 1. Mr. C enters "I'm a second-year junior high school student and I'm interested in history" on his device and sends the information. The server saves this information.

[1292] 2. Person C starts the cognitive ability assessment test on his terminal. The server displays questions, and Person C inputs answers. The server analyzes the answers and determines that Person C is visually dominant.

[1293] 3. The server suggests, "Let's learn about historical events through videos," and displays a link to the video material on the device.

[1294] 4. Mr. C starts watching the video on his device. The device records his learning progress and sends it to the server.

[1295] 5. When Mr. C enters a question such as "I don't understand the background of this war," the server uses a generative AI model to generate and display an answer.

[1296] 6. After watching the video, the server conducts a comprehension test, and Mr. C takes the test. The results are sent to the server, which then suggests the next learning content.

[1297] 7. The server suggests a new task: "Next, let's learn more about the causes of this war," and displays it on the device.

[1298] 8. The server suggests that next week’s topic is “Important Figures in Modern History” and provides a discussion platform. C can input his opinions and discuss them with his classmates.

[1299] Prompt Sentence Examples

[1300] "If you have a second-year junior high school student who wants to study history, how would you use AI to suggest the best way to learn it? Please explain the specific process."

[1301] In this way, AI systems can provide optimal educational experiences tailored to individual learning needs and create an environment in which participants can learn independently.

[1302] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1303] Step 1:

[1304] User Registration

[1305] The server generates a user registration page using HTML and CSS and sends it to the device. The user enters basic information such as name, age, grade, and areas of interest on the device and submits it. The server receives the received information in JSON format and saves it in the database. This registers the user's basic information in the database. The input is the user's basic information, and the output is the user's basic information saved in the database.

[1306] Step 2:

[1307] Cognitive trait assessment test

[1308] The server uses JavaScript and React to generate an interface for the cognitive trait assessment test and displays it on the device. The user clicks a button to start the test and answers a series of questions. The device displays each question and accepts the user's answers. The server stores the received answers in a database and analyzes the data using a Python machine learning model to determine the user's cognitive traits. The input is the user's answers and the output is the assessed cognitive traits. This reveals the user's cognitive traits.

[1309] Step 3:

[1310] Learning method suggestions

[1311] The server selects the optimal learning method based on cognitive characteristics and selects related learning materials. The server sends the selected learning method and learning materials to the terminal via REST API. The terminal displays this to the user. The input is cognitive characteristics and a learning material database, and the output is a link between the learning method and learning materials presented to the user. This allows the optimal learning method to be presented to the user.

[1312] Step 4:

[1313] Providing learning content

[1314] The server dynamically generates learning content appropriate for the user and sends it to the device. The user checks the learning content on the device and begins learning. The device records learning progress and periodically sends it to the server. The input is the user's cognitive characteristics and progress, and the output is the learning content provided and a record of learning progress. This allows the user to study with content that is appropriate for them.

[1315] Step 5:

[1316] Real-time Support

[1317] The server provides an interface that accepts user questions via the terminal. The user inputs a question on the terminal and sends it to the server. The server analyzes the question and generates the optimal answer using a generative AI model. The server sends the answer to the terminal, which displays it to the user. The input is the user's question, and the output is the generated answer. This allows the user's question to be resolved instantly.

[1318] Step 6:

[1319] Progress tracking and comprehension tests

[1320] The server periodically displays an interface on the terminal that conducts comprehension tests. The user takes the test on the terminal and sends the answers to the server. The server scores the answers and stores the results in a database. It then generates feedback based on the results and sends it to the terminal. The input is the answers to the comprehension test, and the output is the test results and feedback. This evaluates the user's level of understanding and determines the next learning content.

[1321] Step 7:

[1322] Individual feedback and suggestions for next steps

[1323] The server analyzes the test results and determines the next learning content. The server sends feedback and new assignments to the device, which displays them to the user. The user then works on the suggested assignments. The input is the test results and learning objectives, and the output is feedback and new suggested assignments. This allows the user to continuously work on appropriate assignments.

[1324] Step 8:

[1325] Facilitating discussion and communication

[1326] The server periodically generates discussion topics and sends them to the terminals. Users input their opinions on their terminals and send them to the server. The server collects the opinions and displays them to other users, allowing for an exchange of opinions. The input is the user's opinion, and the output is the shared opinion and discussion results. This promotes communication between users and leads to deeper understanding.

[1327] (Application example 1)

[1328] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1329] With conventional educational systems, it has been difficult to efficiently grasp the cognitive characteristics of each individual student and propose optimal learning methods based on that.In addition, there is a lack of educational support for industrial product operation methods and control technologies in industrial workplaces, and automatic and effective measures are needed as a means of improving engineers' skills.

[1330] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1331] In this invention, the server includes means for inputting basic information about the subject, means for determining the cognitive characteristics of the subject, means for proposing an optimal learning method based on the determination results, means for providing learning content, means for tracking learning progress and conducting comprehension tests, means for providing individual feedback and proposing next tasks to the subject, means for resolving questions during learning in real time, means for promoting the exchange of opinions between subjects, and means for supporting learning of industrial product operation methods and control technology. This makes it possible to propose a learning method optimal for the cognitive characteristics of each subject, and to automatically and effectively provide education on industrial product operation methods and control technology.

[1332] 1. "Basic information of the subject" refers to personal information such as the subject's name, age, years of experience, and field of expertise.

[1333] 2. "Cognitive characteristics" refers to the individual characteristics of how a subject receives, processes, and understands information, such as visual dominance, auditory dominance, or verbal dominance.

[1334] 3. "Optimal learning method" refers to the most effective learning method based on the cognitive characteristics of the individual.

[1335] 4. "Learning Content" refers to the learning materials and information provided to a target audience for learning, including video, text, and audio materials.

[1336] 5. "Tracking learning progress" refers to recording and managing the learning progress of a student in real time.

[1337] 6. "Comprehension test" refers to a test to assess the extent to which a subject has understood the learning content.

[1338] 7. "Individualized feedback" refers to specific advice and next steps provided based on the learner's learning progress and level of understanding.

[1339] 8. "Resolving questions during learning in real time" refers to providing immediate answers to questions that arise during learning.

[1340] 9. "Promoting exchange of opinions" refers to support provided to stimulate information sharing and discussion among participants.

[1341] 10. "Supporting learning about the operation methods and control techniques of industrial products" refers to educational support to promote understanding of the correct operation methods and control techniques of industrial products and equipment used in industry.

[1342] Overall system configuration

[1343] This invention describes a specific embodiment for implementing an educational support system consisting of a server, a terminal, and a user. This system proposes optimal learning methods based on the cognitive characteristics of each individual and supports education on industrial product operation methods and control technologies.

[1344] Hardware and software used

[1345] The present invention uses the following hardware and software.

[1346] Server: High-performance server (e.g. AWS, Google Cloud)

[1347] Terminals: Smartphones, factory robot HMI (Human-Machine Interface), PCs

[1348] Frontend: Angular, HTML5, CSS3, JavaScript

[1349] Backend: Node.js, MySQL

[1350] AI modeling: Python, TensorFlow, Socket.IO

[1351] Program processing

[1352] 1. User Registration

[1353] The server serves a user registration page in Angular on the front end.

[1354] The user uses a terminal to enter basic information such as name, age, years of experience, and field of expertise.

[1355] The server receives this information via Node.js and stores it in a MySQL database.

[1356] 2. Assessment of cognitive characteristics

[1357] The server uses an Angular front-end to provide an interface for questions and tasks to assess cognitive characteristics.

[1358] The user starts the test at the terminal and answers the questions.

[1359] The server receives the responses and uses Python and TensorFlow to analyze the data and determine cognitive traits.

[1360] 3. Learning method suggestions

[1361] Based on the analysis results, the server selects the optimal learning method and suggests corresponding learning materials.

[1362] The terminal displays the suggestions and educational materials to the user.

[1363] 4. Providing learning content

[1364] The server provides learning content (video, audio, text) that best suits the user's cognitive characteristics.

[1365] Users can view this content on their devices and progress as they study, with their progress recorded in real time.

[1366] 5. Real-time support

[1367] If a user has a question while studying, they can enter it using their smartphone or tablet.

[1368] The server uses Socket.IO to receive questions in real time, processes them in Python, and provides instant answers.

[1369] 6. Progress Tracking and Comprehension Testing

[1370] The server periodically conducts comprehension tests, analyzes the results, stores them in a database, and provides feedback to the user.

[1371] 7. Personalized feedback and suggestions for next steps

[1372] The server suggests the next learning task based on the test results and provides related learning content.

[1373] 8. Facilitating discussion and communication

[1374] The server periodically provides discussion topics and provides an interface that encourages the exchange of ideas between users.

[1375] Users can input their opinions on the terminal and hold discussions with other users.

[1376] Examples and prompts

[1377] As a concrete example, consider the case where engineer A is learning how to operate a new industrial robot.

[1378] If engineer A enters "years of experience: 5 years, specialty: industrial robot control" and has visually dominant cognitive characteristics, the system will suggest, "Let's learn the basic operation of industrial robots through video materials." Engineer A will begin learning by watching the video materials, and if he has any questions, he can ask, "Please tell me more about how the sensors on this robot work." The server will immediately provide an appropriate answer to this question.

[1379] An example of a prompt is:

[1380] "For an engineer with five years of experience operating robots, please propose an industrial robot operation method that is easy for a person with visually dominant cognitive characteristics to learn. Also, please suggest related video teaching materials."

[1381] Possible possibilities include:

[1382] In this way, it is possible to propose a learning method that is optimal for the cognitive characteristics of each individual, and to automatically and effectively educate the student on how to operate industrial products and control technology.

[1383] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1384] Step 1:

[1385] User Registration

[1386] The server serves a user registration page in Angular on the front end.

[1387] The user uses a terminal to enter basic information such as name, age, years of experience, and field of expertise.

[1388] The basic information entered is sent from the terminal to the server, which receives this information via Node.js and stores it in a MySQL database.

[1389] Input: Basic information such as name, age, years of experience, field of expertise, etc.

[1390] Output: Basic user information stored in the database

[1391] Step 2:

[1392] Determining cognitive characteristics

[1393] The server uses an Angular front-end to provide an interface for questions and tasks to assess cognitive characteristics.

[1394] The user starts the test at the terminal and answers the questions.

[1395] The server receives the response data and analyzes it using Python and TensorFlow to determine the user's cognitive characteristics, such as visual, auditory, and language.

[1396] Input: User response data

[1397] Output: Cognitive characteristics (visual, auditory, language, etc.)

[1398] Step 3:

[1399] Learning method suggestions

[1400] Based on the results of the analysis of cognitive characteristics, the server selects the optimal learning method and suggests corresponding learning materials.

[1401] The terminal displays the suggestions and educational materials to the user.

[1402] For example, video instructional materials are suggested to visually dominant users.

[1403] Input: Cognitive characteristic analysis results

[1404] Output: Suggested learning methods and materials

[1405] Step 4:

[1406] Providing learning content

[1407] The server provides learning content (video, audio, text) that best suits the user's cognitive characteristics.

[1408] Users can check this content on their devices and progress through their studies, with their progress recorded in real time on the server.

[1409] Input: Suggested learning methods and materials

[1410] Output: Providing learning content and recording progress

[1411] Step 5:

[1412] Real-time Support

[1413] If a user has a question while studying, they can enter it using their smartphone or tablet.

[1414] The server uses Socket.IO to receive questions in real time, processes them in Python, and provides instant answers.

[1415] Input: User question

[1416] Output: Answers provided in real time

[1417] Step 6:

[1418] Progress tracking and comprehension tests

[1419] The server periodically conducts comprehension tests, analyzes the results, stores them in a database, and provides feedback to the user.

[1420] The terminal displays the test results to the user.

[1421] Input: Comprehension test response data

[1422] Output: Test result analysis and feedback

[1423] Step 7:

[1424] Individual feedback and suggestions for next steps

[1425] Based on the results of the comprehension test, the server suggests the next learning task and provides related learning content.

[1426] The terminal displays the next assignment and related content to the user.

[1427] Input: Comprehension test results

[1428] Output: Providing next assignments and related learning content

[1429] Step 8:

[1430] Facilitating discussion and communication

[1431] The server periodically provides discussion topics and provides an interface that encourages the exchange of ideas between users.

[1432] Users can input their opinions on the terminal and hold discussions with other users.

[1433] Input: Discussion topics and user opinions

[1434] Output: Facilitated exchange of ideas and shared opinions

[1435] In this way, the educational support system is designed to function effectively by clarifying the roles of the server, terminal, and user at each step and organizing the specific operations and inputs and outputs.

[1436] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1437] This invention is an AI system for educational support that maximizes learning effectiveness by determining the cognitive characteristics of each individual and proposing individually appropriate learning methods, and by combining it with an emotion engine, provides an optimal learning experience by taking into account the emotional state of the individual. This system functions among four parties: a server, a terminal, a user, and an emotion engine.

[1438] Overall system overview

[1439] This system provides educational support tailored to the target individual by performing the following processes.

[1440] 1. Obtain basic information about the subject.

[1441] 2. Determine the cognitive characteristics of the subject.

[1442] 3. Based on the results of the assessment, the optimal learning method is proposed.

[1443] 4. Provide learning content.

[1444] 5. Track your progress and test your comprehension.

[1445] 6. Provide personalized feedback.

[1446] 7. Resolve your doubts while studying in real time.

[1447] 8. Use an emotion engine to recognize and respond to the subject's emotional state.

[1448] 9. Suggest discussion topics and encourage exchange of ideas.

[1449] Program processing

[1450] Below, the program processing at each step of this system will be explained in natural language.

[1451] 1. User Registration

[1452] The server provides a user registration page.

[1453] Users use the terminal to enter basic information such as name, age, grade, and areas of interest.

[1454] The server stores the entered basic information in a database.

[1455] 2. Cognitive trait assessment test

[1456] The server displays the interface for the cognitive characteristics assessment test on the terminal.

[1457] The user clicks the Start Test button to begin the test.

[1458] 3. Conducting a cognitive assessment test

[1459] The server sends a series of questions or tasks to the terminal in sequence.

[1460] The terminal displays questions and tasks to the user and accepts answers.

[1461] The user answers each question on the terminal.

[1462] The server receives the user's responses and stores them in a database in real time.

[1463] The server analyzes the collected data and determines the user's visual, linguistic, and auditory cognitive characteristics.

[1464] 4. Learning method suggestions

[1465] Based on the judgment results, the server selects the most suitable learning method for the user.

[1466] The server presents the selected learning method and related learning materials to the terminal.

[1467] The device displays learning method suggestions and introductions to learning materials to the user.

[1468] 5. Provision of learning content

[1469] The server provides users with learning content (video, text, audio materials, etc.) appropriate for their needs.

[1470] The user checks the learning content on the device and begins learning.

[1471] The device records the user's learning progress in real time.

[1472] 6. Real-time support

[1473] The server provides an interface that accepts questions from users during their studies via the terminal.

[1474] The user inputs a question into the terminal and sends it.

[1475] The server analyzes the question and instantly generates and provides the appropriate answer.

[1476] The terminal displays the response from the server to the user.

[1477] 7. Progress Tracking and Comprehension Testing

[1478] The server periodically displays an interface on the terminal that allows users to take comprehension tests.

[1479] The user takes the test at the terminal.

[1480] The terminal transmits the user's answer to the server.

[1481] The server scores the answers, stores the results in a database, and provides feedback to the user.

[1482] 8. Personalized feedback and suggestions for next steps

[1483] The server analyzes the results of the user's comprehension test and suggests the next learning content and assignments.

[1484] The device displays feedback and new challenges to the user.

[1485] The user tackles the proposed task.

[1486] 9. Emotion Recognition and Response

[1487] The server uses an emotion engine to monitor the user's emotional state during learning in real time through the terminal.

[1488] The emotion engine identifies emotions from the user's facial expressions and tone of voice, and stores the emotional state in a database.

[1489] The server adjusts the optimal feedback and learning content based on the user's emotional state.

[1490] 10. Facilitating discussion and communication

[1491] The server periodically provides discussion topics.

[1492] The terminal displays discussion topics to the user and provides a form where responses and opinions can be entered.

[1493] Users input their opinions on the terminal and exchange opinions with other users.

[1494] Specific examples

[1495] For example, let's say Mr. D is a first-year high school student who wants to study mathematics.

[1496] 1. User Registration

[1497] Mr. D types into his terminal, "First year high school student, interested in mathematics."

[1498] The server stores this information.

[1499] 2. Cognitive trait assessment test

[1500] Mr. D clicks the start test button on his device.

[1501] The server begins the validation test.

[1502] The device will display questions such as, "Is it easy to remember with an image?"

[1503] D answers the questions.

[1504] The server analyzes Mr. D's answers and determines that he is visually dominant.

[1505] 3. Learning method suggestions

[1506] "Learn math concepts through videos," suggests Thurber.

[1507] A link to the video material will be displayed on the device.

[1508] 4. Providing learning content

[1509] Mr. D starts watching the video on his device.

[1510] 5. Real-time support

[1511] Mr. D types a question into his terminal: "I don't know how to use this formula."

[1512] The server provides the answer, which is displayed on the terminal.

[1513] 6. Progress Tracking and Comprehension Testing

[1514] After watching the video, the server conducts a comprehension test.

[1515] Mr. D takes the test on a terminal.

[1516] 7. Personalized feedback and suggestions for next steps

[1517] The server analyzes the test results and suggests, "Next, try solving some real problems."

[1518] The next learning content will be displayed to Mr. D on his device.

[1519] 8. Emotion Recognition and Response

[1520] The server uses an emotion engine to analyze Mr. D's facial expressions and tone of voice while he is studying.

[1521] If the server identifies Mr. D as feeling tired, it will display a message on his device saying, "Let's take a short break."

[1522] Also, if Mr. D is in a state of joy or adaptation, the teacher will give him feedback such as "That's good enough" and encourage him to continue learning.

[1523] 9. Facilitating discussion and communication

[1524] The server suggests that next week's theme is "Application of Functions," and provides a platform where users can exchange opinions.

[1525] Mr. D can input his opinions on the device and discuss them with his classmates.

[1526] In this way, the AI ​​system can provide an optimal educational experience tailored to individual learning needs, creating an environment in which Mr. D can learn independently. By combining it with an emotion engine, it is possible to respond according to the user's emotional state, further improving learning effectiveness.

[1527] The processing flow will be explained below.

[1528] Step 1:

[1529] The server provides a user registration page, where users use their terminals to enter basic information such as name, age, grade, and areas of interest, and the server stores the entered basic information in a database.

[1530] Step 2:

[1531] The server displays the cognitive characteristics assessment test interface on the terminal, and the user clicks the test start button to start the test.

[1532] Step 3:

[1533] The server sequentially sends a series of questions or tasks to the terminal, which displays the questions or tasks to the user and accepts answers. The user answers each question on the terminal.

[1534] Step 4:

[1535] The server receives the user's responses and stores them in a database in real time. The server analyzes the collected data to determine the user's visual, linguistic, and auditory cognitive characteristics.

[1536] Step 5:

[1537] Based on the results of the assessment, the server selects the optimal learning method for the user. The server then presents the selected learning method and related learning materials to the terminal. The terminal then displays suggested learning methods and introductions to the learning materials to the user.

[1538] Step 6:

[1539] The server provides learning content (video, text, audio, etc.) appropriate for the user. The user checks the learning content on the device and begins learning. The device records the user's learning progress in real time.

[1540] Step 7:

[1541] The server provides an interface that accepts questions from users during their studies via their terminal. The user inputs and submits a question on the terminal. The server analyzes the question and instantly generates and provides an appropriate answer. The terminal displays the answer from the server to the user.

[1542] Step 8:

[1543] The server periodically displays an interface on the device that conducts comprehension tests. The user takes the test on the device. The device sends the user's answers to the server. The server grades the answers, stores the results in a database, and provides feedback to the user.

[1544] Step 9:

[1545] The server analyzes the results of the user's comprehension test and suggests the next learning content and assignments. The device displays feedback and new assignments to the user. The user then works on the suggested assignments.

[1546] Step 10:

[1547] The server uses an emotion engine to monitor the user's emotional state in real time through the device while they are learning. The emotion engine identifies emotions from the user's facial expressions and tone of voice, and stores the emotional state in a database. The server then provides optimal feedback and adjusts the learning content based on the user's emotional state.

[1548] Step 11:

[1549] The server periodically provides discussion topics. The terminal displays the discussion topics to the user and provides a form in which the user can enter their answers and opinions. The user enters their opinions on the terminal and exchanges opinions with other users.

[1550] Example 2

[1551] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1552] Conventional educational systems have had difficulty providing learning methods that fully consider the cognitive characteristics and emotional state of each individual student. Furthermore, they lacked functionality for real-time resolution of questions that arise during learning and for easy exchange of opinions between students. This made it difficult to provide an optimal learning experience for each student, resulting in a lack of maximization of learning effectiveness.

[1553] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for inputting basic information about the subject, a means for determining the cognitive characteristics of the subject, a means for proposing an optimal learning method based on the determination results, a means for providing learning content, a means for tracking learning progress and conducting comprehension tests, a means for providing individual feedback to the subject, a means for resolving questions during learning in real time, and a means for recognizing and responding to the subject's emotional state using an emotion engine. This makes it possible to provide an optimal learning experience tailored to the subject's individual needs and maximize learning effectiveness. Furthermore, by encouraging the exchange of opinions between subjects as needed, the quality of learning can be expected to improve.

[1554] "Target audience" refers to learners who use the education system.

[1555] "Basic information" refers to basic data such as the subject's name, age, grade, and areas of interest.

[1556] "Cognitive characteristics" refers to the subject's cognitive style, such as visual, linguistic, and auditory.

[1557] A "judgment test" refers to a series of questions or tasks designed to assess a subject's cognitive characteristics.

[1558] "Feedback" refers to individual evaluations and advice provided based on the subject's learning results.

[1559] "Learning method" refers to the learning process and techniques proposed based on the cognitive characteristics of the subject.

[1560] "Learning content" includes learning materials and resources used for learning, such as videos, texts, and audio materials.

[1561] An "emotion engine" refers to a system that has the ability to recognize a subject's emotional state and process that data.

[1562] "Real-time support" refers to the function of providing immediate responses to questions or concerns that students may have while studying.

[1563] "Discussion Topics" refers to topics that are periodically provided by the server for the purpose of exchanging opinions among participants.

[1564] "Opinion exchange" refers to the activity of sharing opinions and thoughts among participants.

[1565] "Server" refers to a central computer that runs the entire system and provides each function.

[1566] "Device" means the computer or mobile device used by a Subject to access the System.

[1567] This invention is an AI system for educational support that maximizes learning effectiveness by determining the cognitive characteristics of each individual and proposing individually appropriate learning methods. Furthermore, by combining it with an emotion engine, it provides an optimal learning experience by taking into account the emotional state of each individual. This system functions among four parties: a server, a terminal, a user, and an emotion engine.

[1568] Overall system overview

[1569] This system provides educational support tailored to each individual through the following steps:

[1570] 1. Obtain basic information about the subject.

[1571] 2. Determine the cognitive characteristics of the subject.

[1572] 3. Based on the results of the assessment, the optimal learning method is proposed.

[1573] 4. Provide learning content.

[1574] 5. Track your progress and test your comprehension.

[1575] 6. Provide personalized feedback.

[1576] 7. Resolve your doubts while studying in real time.

[1577] 8. Use an emotion engine to recognize and respond to the subject's emotional state.

[1578] 9. Suggest discussion topics and encourage exchange of ideas.

[1579] Program processing

[1580] The processing of this system is carried out through cooperation between the server and the terminal, as detailed below.

[1581] Hardware and Software Use

[1582] The server uses a MySQL database to store and manage data.

[1583] The server uses Python to implement data analysis and decision algorithms.

[1584] The server provides a front end consisting of JavaScript and HTML.

[1585] The device accesses the server using a browser such as Google Chrome.

[1586] The emotion engine uses the camera and microphone to analyze the user's facial expressions and tone of voice.

[1587] Specific examples

[1588] For example, consider the following situation where Mr. D is a first-year high school student who wishes to study mathematics.

[1589] 1. User Registration

[1590] Mr. D enters "First year high school student, interested in mathematics" into the terminal. The form displayed on the terminal has fields for entering name, age, grade, and area of ​​interest.

[1591] When Mr. D clicks the "Register" button, the server receives the input data and saves it in the MySQL database.

[1592] 2. Cognitive trait assessment test

[1593] Mr. D clicks the start test button on his device. The server sends the UI for the assessment test, which is composed of HTML and JavaScript, to the device and asks a series of questions.

[1594] Questions such as "Is it easy to remember with an image?" are displayed on the device. Mr. D answers the questions, and the answers are saved in a database in real time.

[1595] 3. Learning method suggestions

[1596] Based on D's cognitive characteristics, the server suggests, "Let's learn mathematical concepts through videos." A link to the video material is displayed on the device.

[1597] 4. Providing learning content

[1598] Mr. D starts watching the video on his device. The server provides the video material through a video streaming service.

[1599] 5. Real-time support

[1600] During the study, Mr. D enters a question into his device, such as "I don't know how to use this formula." The server receives the question, analyzes it using natural language processing (NLP), instantly generates an appropriate answer, and displays it on the device.

[1601] 6. Progress Tracking and Comprehension Testing

[1602] After watching the video, the server periodically conducts comprehension tests. Mr. D takes the tests on his device and his answers are sent to the server. The server then uses an automatic scoring system to score the answers and stores the results in a database.

[1603] 7. Personalized feedback and suggestions for next steps

[1604] Based on the test results, the server suggests, "Next, try solving a real problem." The next learning content is displayed to Mr. D on his device.

[1605] 8. Emotion Recognition and Response

[1606] The server uses an emotion recognition algorithm to monitor Mr. D's facial expressions and tone of voice in real time while he is studying.

[1607] If D is identified as feeling tired, the server will display a message on his device saying, "Take a short break." If he is in a state of joy or adaptation, the server will provide feedback saying, "That's good," encouraging him to continue learning.

[1608] 9. Facilitating discussion and communication

[1609] The server suggests that next week's topic is "Application of Functions," and provides a platform for users to exchange opinions. D can input his opinion on his device and discuss it with his classmates.

[1610] Prompt Sentence Examples

[1611] "Please explain how to register by entering basic user information."

[1612] "Please explain with specific examples what kind of questions will be asked during the cognitive trait assessment test."

[1613] "Please explain how you handle real-time support if a user has a question while learning."

[1614] "Please explain the process of recognizing and responding to user emotions using the emotion engine."

[1615] This allows the AI ​​system to provide an optimal educational experience tailored to the user's individual learning needs, improving learning outcomes.The combination of an emotion engine enables the system to respond to the user's emotional state, further enhancing learning outcomes.

[1616] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1617] Step 1: User Registration

[1618] The server provides a user registration page. The user uses the terminal to enter basic information such as name, age, grade, and areas of interest. When the user clicks the "Register" button, the terminal sends the data to the server. The server receives the entered basic information and stores it in a database. The input here is the user's basic information, and the output is the data stored in the database.

[1619] Step 2: Cognitive trait assessment test

[1620] The server displays the cognitive ability assessment test interface on the terminal. The user clicks the test start button and answers the questions and tasks displayed on the terminal in sequence. The server receives each answer and stores them in a database one by one. Based on the collected answer data, the server uses Python to analyze the data and determine the user's visual, linguistic, and auditory cognitive abilities. The input is the user's test answers, and the output is the assessed cognitive abilities.

[1621] Step 3: Suggest a learning method

[1622] The server selects the optimal learning method and related learning materials based on the assessment results. The selected information is sent to the terminal and links to the learning methods and learning materials are displayed to the user. The input is the assessed cognitive characteristics, and the output is the suggested learning methods and links to the learning materials.

[1623] Step 4: Provide learning content

[1624] The server provides learning content such as videos, texts, and audio materials through a streaming service. The user checks the learning content on their device and begins learning. The device records the user's learning progress (e.g., video viewing time and text completion status) in real time and sends it to the server. The input is the learning content, and the output is learning progress data.

[1625] Step 5: Real-time support

[1626] The server provides an interface through the terminal for users to input questions they have while studying. The user inputs the question on the terminal and sends it. The server analyzes the question using NLP (natural language processing) functions, generates an appropriate answer, and sends it to the terminal. The terminal displays the answer to the user. The input is the user's question, and the output is the generated answer.

[1627] Step 6: Progress Tracking and Testing

[1628] The server periodically displays an interface on the terminal that conducts comprehension tests. The user takes the test on the terminal and submits their answers. The server scores the answers using an automatic scoring system and stores the results in a database. The server then provides feedback on the results to the user. The input is the test answers, and the output is the scoring results and feedback.

[1629] Step 7: Personalized feedback and next steps

[1630] The server selects the next learning content and assignment based on the results of the comprehension test. The selected information is sent to the terminal, and feedback and new assignments are displayed to the user. The user then works on the suggested assignments. The input is the test results, and the output is feedback and assignment suggestions.

[1631] Step 8: Emotion Recognition and Responding

[1632] The server uses an emotion engine to monitor the user's facial expressions and tone of voice in real time while they are studying via their device. It identifies the user's emotional state and stores it in a database. The server then provides optimal feedback and adjusts the learning content based on the user's emotional state. For example, if the server identifies the user as tired, it will suggest taking a break, and if the user is in an adaptive state, it will display an encouraging message. The input is the user's facial expression and tone of voice data, and the output is the emotion analysis results and feedback based on them.

[1633] Step 9: Facilitate discussion and communication

[1634] The server periodically provides discussion topics and displays them on the terminal. Users input their opinions on the topics and exchange them with other users. The server stores the posted opinions in a database and displays them to other participants in real time. The input is the discussion topic and user opinions, and the output is a log of the opinion exchange.

[1635] (Application example 2)

[1636] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1637] Conventional educational support systems have difficulty providing individual learning methods based on the cognitive characteristics of each student, and in particular, do not provide a learning experience that takes into account their emotional state, resulting in insufficient learning effectiveness. Furthermore, they are unable to effectively resolve questions in real time during learning or exchange opinions with other students, resulting in a lack of progress management and feedback provision. It is necessary to solve these issues and provide the optimal learning environment for each student.

[1638] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1639] In this invention, the server includes a means for inputting basic information about the subject, a means for determining the subject's cognitive characteristics, a means for proposing an optimal learning method based on the determination results, a means for providing learning content, a means for tracking learning progress and conducting comprehension tests, a means for providing individual feedback to the subject, a means for resolving questions during learning in real time, a means for recognizing the subject's emotional state and providing feedback accordingly, and a means for delivering educational content via a head-mounted display. This makes it possible to provide an optimal learning experience that takes into account the subject's cognitive characteristics and emotional state. Furthermore, by promoting real-time question resolution and opinion exchange, learning efficiency can be improved.

[1640] "Means for entering basic information about the subject" refers to a function for entering basic information related to learning, such as the subject's name, age, grade, and areas of interest, through a user interface and saving it in a database.

[1641] "Means for assessing the cognitive characteristics of subjects" refers to a function that provides questions and tasks to assess the cognitive features and characteristics of subjects, and collects and analyzes the responses.

[1642] "Means for proposing optimal learning methods based on assessment results" is a function that recommends the most suitable learning style and learning materials for each individual based on the assessment results of their cognitive characteristics.

[1643] "Means for providing learning content" refers to the function of selecting and distributing learning materials, such as videos, texts, and audio materials, to target users.

[1644] "Means for tracking learning progress and conducting comprehension tests" refers to a function that monitors the learning progress of the subject and periodically conducts tests to assess comprehension.

[1645] "Means for providing individual feedback to the subject" refers to a function for providing appropriate advice and guidance to the subject individually based on the subject's learning outcomes and progress.

[1646] "Means for resolving questions during learning in real time" refers to a function that provides immediate answers to questions or queries that students encounter while learning.

[1647] "Means for recognizing the emotional state of the subject and providing feedback accordingly" refers to a function that monitors the subject's facial expressions, tone of voice, etc. in real time, analyzes their emotional state, and provides appropriate feedback.

[1648] "Means for delivering educational content through a head-mounted display" refers to a function for effectively delivering visual and auditory educational content to a target audience using a head-mounted display (HMD).

[1649] This invention is an AI system for educational support that determines the cognitive characteristics and emotional state of the subject and provides optimal learning methods and content based on that. This system functions among four parties: a server, a terminal, a user, and an emotion engine.

[1650] First, the user enters basic information, such as name, age, grade, and areas of interest, through a user interface provided by the server. The entered information is stored using a database management system such as SQLite. This information is used to assess cognitive characteristics and customize learning content.

[1651] Next, a cognitive test is administered to determine the subject's cognitive characteristics. The CognitiveTest module uses a series of questions and tasks displayed in the user interface. The user answers these questions, and the responses are collected and analyzed by the server. This identifies visual, verbal, and auditory cognitive characteristics.

[1652] Based on the results of the assessment, the server will suggest the optimal learning method. For example, video materials may be recommended for visually dominant students, and text materials for verbally dominant students. These learning methods and content are provided via devices such as head-mounted displays (HMDs). Using an HMD makes the learning experience more visual and interactive.

[1653] As learning progresses, the server tracks learning progress and periodically conducts comprehension tests. The UserTracking module monitors the learning progress of the subject and conducts comprehension tests based on that data. The test results are stored in a database and used to adjust subsequent learning plans.

[1654] Furthermore, the emotion engine monitors the user's emotional state in real time. Using the camera and microphone installed in the HMD, the server analyzes facial expressions and tone of voice to recognize the user's emotional state. For example, if the server determines that the subject is feeling tired, it will provide feedback such as "Take a short break."

[1655] Another important feature is real-time question resolution. The server accepts questions via the device and provides immediate answers generated by AI. This is effective in immediately resolving any difficulties users may have while studying and maintaining continuity in their learning.

[1656] Finally, the server periodically provides discussion topics to encourage exchange of ideas between users. This functionality is realized through the DiscussionModule, allowing users to exchange ideas with other users about what they have learned and deepen their understanding.

[1657] Here are some example prompts:

[1658] "D is a first-year high school student who is interested in math. Please suggest the best study method for D based on his cognitive characteristics and emotional state. What should we do if D does not show interest while studying?"

[1659] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1660] Step 1:

[1661] The server provides a user interface to the terminal for inputting basic user information. The user inputs basic information such as name, age, grade, and areas of interest. This input data is sent to the server and stored in a database. The input here is the user's basic information, and the output is the user information stored in the database.

[1662] Step 2:

[1663] The server displays the cognitive characteristics assessment test interface on the terminal. The user clicks the test start button on the terminal to begin the cognitive characteristics assessment test. The terminal displays the questions received from the server to the user and accepts the user's answers. The user inputs answer data, which the server collects and analyzes in real time. The output is the user's cognitive characteristics assessment results.

[1664] Step 3:

[1665] The server proposes the optimal learning method based on the cognitive characteristic assessment results. Based on the assessment results, the server selects the most appropriate learning method from various options (video, text, audio materials, etc.). This selected learning method is displayed on the user's device from the server. The input is the cognitive characteristic assessment results, and the output is a proposal for the optimal learning method.

[1666] Step 4:

[1667] The server provides the user with optimal learning content. The user receives the video and text learning materials provided by the server through their terminal. The input here is information on the optimal learning method, and the output is the learning content itself. The learning content is delivered via a head-mounted display (HMD), which the user uses to progress through their studies.

[1668] Step 5:

[1669] The server tracks learning progress and conducts comprehension tests. Each time a user uses learning content, the server monitors their progress in real time. It also periodically presents tests to assess comprehension, which the user answers. The server evaluates the level of comprehension based on the response data and stores this in a database. The input is learning progress data and test answers, and the output is the comprehension assessment results.

[1670] Step 6:

[1671] The server provides the ability to solve questions during learning in real time. When a user inputs a question into the terminal, the question is sent to the server. The server analyzes the question, generates an answer instantly, and sends it to the terminal. The input is the user's question data, and the output is the answer to that question.

[1672] Step 7:

[1673] The server uses an emotion engine to monitor the user's emotional state in real time. The HMD's built-in camera and microphone collect the user's facial expressions and tone of voice, which are then analyzed by the emotion engine. If the server determines that the user is tired based on this, it provides feedback such as "Take a short break." The input is the user's facial expressions and voice data, and the output is the emotional state analysis results and feedback.

[1674] Step 8:

[1675] The server periodically provides users with discussion topics and promotes the exchange of opinions between users. The server selects topics and displays them on the user's device. Users use their devices to exchange opinions with other users, and the content is sent to the server. The input is the discussion topic and user opinion data, and the output is the result of the exchange of opinions.

[1676] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1677] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1678] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1679] [Fourth embodiment]

[1680] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1681] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1682] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1683] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1684] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1685] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1686] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1687] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1688] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1689] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1690] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1691] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1692] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1693] This invention is an AI system for educational support that maximizes learning effectiveness by determining the cognitive characteristics of each individual and proposing individually appropriate learning methods, thereby addressing educational disparities, school absenteeism, and support for people with disabilities. This system functions among three parties: a server, a terminal, and a user.

[1694] Overall system overview

[1695] This system provides educational support tailored to the target individual by performing the following processes.

[1696] 1. Obtain basic information about the subject.

[1697] 2. Determine the cognitive characteristics of the subject.

[1698] 3. Based on the results of the assessment, the optimal learning method is proposed.

[1699] 4. Provide learning content.

[1700] 5. Track your progress and test your comprehension.

[1701] 6. Provide personalized feedback.

[1702] 7. Resolve your doubts while studying in real time.

[1703] 8. Suggest discussion topics and encourage exchange of ideas.

[1704] Program processing

[1705] Below, the program processing at each step of this system will be explained in natural language.

[1706] 1. User Registration

[1707] The server provides a user registration page.

[1708] Users use the terminal to enter basic information such as name, age, grade, and areas of interest.

[1709] The server stores basic information about the user in a database.

[1710] 2. Cognitive trait assessment test

[1711] The server displays the interface for the cognitive characteristics assessment test on the terminal.

[1712] The user clicks the Start Test button to begin the test.

[1713] The server sends a series of questions or tasks to the terminal in sequence.

[1714] The terminal displays each question or task to the user and accepts responses.

[1715] The user answers each question at the terminal.

[1716] The server receives the user's responses and stores them in a database in real time.

[1717] The server analyzes the collected data and determines the user's visual, linguistic, and auditory cognitive characteristics.

[1718] 3. Learning method suggestions

[1719] Based on the results of the judgment, the server selects the most suitable learning method for the user.

[1720] The server presents the selected learning method and related learning materials to the terminal.

[1721] The device displays learning method suggestions and introductions to learning materials to the user.

[1722] 4. Providing learning content

[1723] The server provides users with learning content (video, text, audio materials, etc.) appropriate for their needs.

[1724] The user checks the learning content on the device and begins learning.

[1725] The device records the user's learning progress in real time.

[1726] 5. Real-time support

[1727] The server provides an interface that accepts questions from users during their studies via the terminal.

[1728] The user inputs a question into the terminal and sends it.

[1729] The server analyzes the question and provides an appropriate answer instantly.

[1730] The terminal displays the response from the server to the user.

[1731] 6. Progress Tracking and Comprehension Testing

[1732] The server periodically displays an interface on the terminal that allows users to take comprehension tests.

[1733] The user takes the test at the terminal.

[1734] The terminal transmits the user's answer to the server.

[1735] The server scores the answers, stores the results in a database, and provides feedback to the user.

[1736] 7. Personalized feedback and suggestions for next steps

[1737] The server analyzes the results of the user's comprehension test and suggests the next learning content and assignments.

[1738] The device displays feedback and new challenges to the user.

[1739] The user works on the proposed tasks on the device.

[1740] 8. Facilitating discussion and communication

[1741] The server periodically provides discussion topics.

[1742] The terminal displays discussion topics to the user and provides a form where responses and opinions can be entered.

[1743] Users input their opinions on the terminal and exchange opinions with other users.

[1744] Specific examples

[1745] For example, let's say Mr. C is a second-year junior high school student who wants to study history.

[1746] 1. User Registration

[1747] Mr. C types into his terminal, "Second year junior high school student, interested in history."

[1748] The server stores this information.

[1749] 2. Cognitive trait assessment test

[1750] Mr. C clicks the start test button on his device.

[1751] The server begins the validation test.

[1752] The device will display questions such as, "Is it easy to remember with an image?"

[1753] C answers the questions.

[1754] The server analyzes Mr. C's answers and determines that he is visually dominant.

[1755] 3. Learning method suggestions

[1756] "Learn about historical events through videos," suggests the server.

[1757] A link to the video material will be displayed on the device.

[1758] 4. Providing learning content

[1759] Mr. C starts watching the video on his device.

[1760] 5. Real-time support

[1761] Mr. C types the question into his terminal: "I don't understand the background of this war."

[1762] The server provides the answer, which is displayed on the terminal.

[1763] 6. Progress Tracking and Comprehension Testing

[1764] After watching the video, the server conducts a comprehension test.

[1765] Mr. C takes the test on a terminal.

[1766] 7. Personalized feedback and suggestions for next steps

[1767] The server analyzes the test results and suggests, "Next, let's learn more about the causes of this war."

[1768] The next learning content will be displayed to Mr. C on his terminal.

[1769] 8. Facilitating discussion and communication

[1770] The server suggests that next week's theme will be "Important Figures in Modern History," and provides a platform where users can exchange opinions.

[1771] Mr. C can input his opinions on the device and discuss them with his classmates.

[1772] In this way, the AI ​​system can provide an optimal educational experience tailored to individual learning needs, creating an environment in which Mr. C can learn independently.

[1773] The processing flow will be explained below.

[1774] Step 1:

[1775] The server provides a user registration page, where users use their terminals to enter basic information such as name, age, grade, and areas of interest, and the server stores the entered basic information in a database.

[1776] Step 2:

[1777] The server displays the cognitive characteristics assessment test interface on the terminal, and the user clicks the test start button to start the test.

[1778] Step 3:

[1779] The server sequentially sends a series of questions or tasks to the terminal, which displays the questions or tasks to the user and accepts answers. The user answers each question on the terminal.

[1780] Step 4:

[1781] The server receives the user's responses and stores them in a database in real time. The server analyzes the collected data to determine the user's visual, linguistic, and auditory cognitive characteristics.

[1782] Step 5:

[1783] Based on the results of the assessment, the server selects the optimal learning method for the user. The server then presents the selected learning method and related learning materials to the terminal. The terminal then displays suggested learning methods and introductions to the learning materials to the user.

[1784] Step 6:

[1785] The server provides learning content (video, text, audio, etc.) appropriate for the user. The user checks the learning content on the device and begins learning. The device records the user's learning progress in real time.

[1786] Step 7:

[1787] The server provides an interface that accepts questions from users during their studies via their terminal. The user inputs and submits a question on the terminal. The server analyzes the question and instantly generates and provides an appropriate answer. The terminal displays the answer from the server to the user.

[1788] Step 8:

[1789] The server periodically displays an interface on the device that conducts comprehension tests. The user takes the test on the device. The device sends the user's answers to the server. The server grades the answers, stores the results in a database, and provides feedback to the user.

[1790] Step 9:

[1791] The server analyzes the results of the user's comprehension test and suggests the next learning content and assignments. The device displays feedback and new assignments to the user. The user then works on the suggested assignments.

[1792] Step 10:

[1793] The server periodically provides discussion topics. The terminal displays the discussion topics to the user and provides a form in which the user can enter their answers and opinions. The user enters their opinions on the terminal and exchanges opinions with other users.

[1794] Example 1

[1795] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1796] Modern education demands optimal learning methods based on individual cognitive characteristics. However, many current educational systems only provide uniform learning methods, making it difficult to address individual cognitive characteristics. Furthermore, they lack features such as learning progress tracking, comprehension tests, and real-time question resolution, making it difficult to adequately address individual learning needs. Furthermore, there are few systems that automatically suggest learning content and provide feedback, preventing the effectiveness of education from being maximized.

[1797] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1798] In this invention, the server includes means for inputting basic information about the subject, means for determining the cognitive characteristics of the subject, means for proposing an optimal learning method based on the determination results, means for providing learning content, means for tracking learning progress and conducting comprehension tests, means for providing individual feedback to the subject, means for resolving questions during learning in real time, means for saving the subject's input and learning progress in a database, means for collecting questions from the subject and generating answers using a generative AI model, and means for evaluating the subject's answers and dynamically proposing the next learning content. This makes it possible to provide an optimal learning method according to individual cognitive characteristics, track learning progress, resolve questions in real time, and dynamically suggest learning content.

[1799] "Target" refers to an individual who uses an educational support AI system to advance their learning.

[1800] "Basic information" refers to basic information necessary for education, such as the subject's name, age, grade, and areas of interest.

[1801] "Cognitive characteristics" are the information processing characteristics of a subject, such as vision, language, and hearing, and indicate individual characteristics in learning.

[1802] "Learning methods" are optimal learning methods or approaches suggested based on cognitive characteristics, including learning materials and learning formats.

[1803] "Learning content" refers to learning videos, texts, audio materials, etc. provided to the target audience, and is an information resource to support learning.

[1804] "Study progress" refers to the progress that a subject makes as they progress through their studies.

[1805] A "comprehension test" is a test used to measure the subject's level of comprehension of the learning content.

[1806] "Individual feedback" refers to specific assessments and guidance provided to students based on the results of comprehension tests and their learning progress.

[1807] "Real-time question resolution" means providing immediate and appropriate answers to questions that students have while studying.

[1808] A "database" is a system that stores and manages data such as basic information about the subject, their learning progress, and the content of their responses.

[1809] A "generative AI model" is an artificial intelligence model used to generate appropriate answers to user questions.

[1810] "Dynamic suggestions" means generating and suggesting the next content or tasks to be learned on an ongoing basis based on the student's learning progress and level of understanding.

[1811] This invention relates to an AI system for supporting education, which maximizes learning effectiveness by providing optimal learning methods based on individual cognitive characteristics, and addresses educational disparities, school absenteeism, and support for people with disabilities. The system functions among three parties: a server, a terminal, and a user.

[1812] Overall system overview

[1813] The system provides tailored educational support by:

[1814] 1. Obtain basic information about the subject.

[1815] 2. Determine the cognitive characteristics of the subject.

[1816] 3. Based on the results of the assessment, the optimal learning method is proposed.

[1817] 4. Provide learning content.

[1818] 5. Track your progress and test your comprehension.

[1819] 6. Provide personalized feedback.

[1820] 7. Resolve your doubts while studying in real time.

[1821] 8. Suggest discussion topics and encourage exchange of ideas.

[1822] Hardware and software used

[1823] The hardware used includes a server and user devices. The server uses a database (e.g., MySQL, PostgreSQL) for managing and analyzing user information, an execution environment for machine learning models (e.g., Python, Scikit-learn), a real-time chat system (e.g., Node.js), and a generative AI model (e.g., OpenAI GPT-3).

[1824] The user device provides an interface that runs on a web browser and processes user operations and learning progress using HTML, CSS, JavaScript, React, etc.

[1825] Program processing overview

[1826] User Registration

[1827] The server generates a user registration page using HTML and CSS and sends it to the device. The user enters basic information such as name, age, grade, and areas of interest on the device and submits it. The server receives the information in JSON format and stores it in a database.

[1828] Cognitive trait assessment test

[1829] The server generates the cognitive trait assessment test interface using JavaScript and React and displays it on the device. The user starts the test and answers a series of questions. The server receives the answers, stores them in a database, and uses a Python machine learning model to analyze the data and determine cognitive traits.

[1830] Learning method suggestions

[1831] The server determines the optimal learning method based on the cognitive characteristics and selects relevant learning materials, which are then sent to the terminal, which then presents them to the user.

[1832] Providing learning content

[1833] The server provides the selected learning content, which the user uses on their device to progress through the learning process. The device records the learning progress in real time and sends it to the server.

[1834] Real-time Support

[1835] The server receives the user's question through the device, generates an appropriate answer using the generative AI model, and sends it to the device for display.

[1836] Progress tracking and comprehension tests

[1837] The server periodically conducts comprehension tests and stores the results in a database, providing feedback to the user and suggesting what to study next.

[1838] Individual feedback and suggestions for next steps

[1839] The server analyzes the next learning content based on the test results and provides feedback and new challenges to the user, thereby presenting the optimal learning path for each individual user.

[1840] Facilitating discussion and communication

[1841] The server periodically generates new discussion topics and presents them to users, who can then input their opinions on their terminals and exchange opinions with other users.

[1842] Specific examples

[1843] For example, consider the case where Mr. C is a second-year junior high school student who wants to study history.

[1844] 1. Mr. C enters "I'm a second-year junior high school student and I'm interested in history" on his device and sends the information. The server saves this information.

[1845] 2. Person C starts the cognitive ability assessment test on his terminal. The server displays questions, and Person C inputs answers. The server analyzes the answers and determines that Person C is visually dominant.

[1846] 3. The server suggests, "Let's learn about historical events through videos," and displays a link to the video material on the device.

[1847] 4. Mr. C starts watching the video on his device. The device records his learning progress and sends it to the server.

[1848] 5. When Mr. C enters a question such as "I don't understand the background of this war," the server uses a generative AI model to generate and display an answer.

[1849] 6. After watching the video, the server conducts a comprehension test, and Mr. C takes the test. The results are sent to the server, which then suggests the next learning content.

[1850] 7. The server suggests a new task: "Next, let's learn more about the causes of this war," and displays it on the device.

[1851] 8. The server suggests that next week’s topic is “Important Figures in Modern History” and provides a discussion platform. C can input his opinions and discuss them with his classmates.

[1852] Prompt Sentence Examples

[1853] "If you have a second-year junior high school student who wants to study history, how would you use AI to suggest the best way to learn it? Please explain the specific process."

[1854] In this way, AI systems can provide optimal educational experiences tailored to individual learning needs and create an environment in which participants can learn independently.

[1855] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1856] Step 1:

[1857] User Registration

[1858] The server generates a user registration page using HTML and CSS and sends it to the device. The user enters basic information such as name, age, grade, and areas of interest on the device and submits it. The server receives the received information in JSON format and saves it in the database. This registers the user's basic information in the database. The input is the user's basic information, and the output is the user's basic information saved in the database.

[1859] Step 2:

[1860] Cognitive trait assessment test

[1861] The server uses JavaScript and React to generate an interface for the cognitive trait assessment test and displays it on the device. The user clicks a button to start the test and answers a series of questions. The device displays each question and accepts the user's answers. The server stores the received answers in a database and analyzes the data using a Python machine learning model to determine the user's cognitive traits. The input is the user's answers and the output is the assessed cognitive traits. This reveals the user's cognitive traits.

[1862] Step 3:

[1863] Learning method suggestions

[1864] The server selects the optimal learning method based on cognitive characteristics and selects related learning materials. The server sends the selected learning method and learning materials to the terminal via REST API. The terminal displays this to the user. The input is cognitive characteristics and a learning material database, and the output is a link between the learning method and learning materials presented to the user. This allows the optimal learning method to be presented to the user.

[1865] Step 4:

[1866] Providing learning content

[1867] The server dynamically generates learning content appropriate for the user and sends it to the device. The user checks the learning content on the device and begins learning. The device records learning progress and periodically sends it to the server. The input is the user's cognitive characteristics and progress, and the output is the learning content provided and a record of learning progress. This allows the user to study with content that is appropriate for them.

[1868] Step 5:

[1869] Real-time Support

[1870] The server provides an interface that accepts user questions via the terminal. The user inputs a question on the terminal and sends it to the server. The server analyzes the question and generates the optimal answer using a generative AI model. The server sends the answer to the terminal, which displays it to the user. The input is the user's question, and the output is the generated answer. This allows the user's question to be resolved instantly.

[1871] Step 6:

[1872] Progress tracking and comprehension tests

[1873] The server periodically displays an interface on the terminal that conducts comprehension tests. The user takes the test on the terminal and sends the answers to the server. The server scores the answers and stores the results in a database. It then generates feedback based on the results and sends it to the terminal. The input is the answers to the comprehension test, and the output is the test results and feedback. This evaluates the user's level of understanding and determines the next learning content.

[1874] Step 7:

[1875] Individual feedback and suggestions for next steps

[1876] The server analyzes the test results and determines the next learning content. The server sends feedback and new assignments to the device, which displays them to the user. The user then works on the suggested assignments. The input is the test results and learning objectives, and the output is feedback and new suggested assignments. This allows the user to continuously work on appropriate assignments.

[1877] Step 8:

[1878] Facilitating discussion and communication

[1879] The server periodically generates discussion topics and sends them to the terminals. Users input their opinions on their terminals and send them to the server. The server collects the opinions and displays them to other users, allowing for an exchange of opinions. The input is the user's opinion, and the output is the shared opinion and discussion results. This promotes communication between users and leads to deeper understanding.

[1880] (Application example 1)

[1881] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1882] With conventional educational systems, it has been difficult to efficiently grasp the cognitive characteristics of each individual student and propose optimal learning methods based on that.In addition, there is a lack of educational support for industrial product operation methods and control technologies in industrial workplaces, and automatic and effective measures are needed as a means of improving engineers' skills.

[1883] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1884] In this invention, the server includes means for inputting basic information about the subject, means for determining the cognitive characteristics of the subject, means for proposing an optimal learning method based on the determination results, means for providing learning content, means for tracking learning progress and conducting comprehension tests, means for providing individual feedback and proposing next tasks to the subject, means for resolving questions during learning in real time, means for promoting the exchange of opinions between subjects, and means for supporting learning of industrial product operation methods and control technology. This makes it possible to propose a learning method optimal for the cognitive characteristics of each subject, and to automatically and effectively provide education on industrial product operation methods and control technology.

[1885] 1. "Basic information of the subject" refers to personal information such as the subject's name, age, years of experience, and field of expertise.

[1886] 2. "Cognitive characteristics" refers to the individual characteristics of how a subject receives, processes, and understands information, such as visual dominance, auditory dominance, or verbal dominance.

[1887] 3. "Optimal learning method" refers to the most effective learning method based on the cognitive characteristics of the individual.

[1888] 4. "Learning Content" refers to the learning materials and information provided to a target audience for learning, including video, text, and audio materials.

[1889] 5. "Tracking learning progress" refers to recording and managing the learning progress of a student in real time.

[1890] 6. "Comprehension test" refers to a test to assess the extent to which a subject has understood the learning content.

[1891] 7. "Individualized feedback" refers to specific advice and next steps provided based on the learner's learning progress and level of understanding.

[1892] 8. "Resolving questions during learning in real time" refers to providing immediate answers to questions that arise during learning.

[1893] 9. "Promoting exchange of opinions" refers to support provided to stimulate information sharing and discussion among participants.

[1894] 10. "Supporting learning about the operation methods and control techniques of industrial products" refers to educational support to promote understanding of the correct operation methods and control techniques of industrial products and equipment used in industry.

[1895] Overall system configuration

[1896] This invention describes a specific embodiment for implementing an educational support system consisting of a server, a terminal, and a user. This system proposes optimal learning methods based on the cognitive characteristics of each individual and supports education on industrial product operation methods and control technologies.

[1897] Hardware and software used

[1898] The present invention uses the following hardware and software.

[1899] Server: High-performance server (e.g. AWS, Google Cloud)

[1900] Terminals: Smartphones, factory robot HMI (Human-Machine Interface), PCs

[1901] Frontend: Angular, HTML5, CSS3, JavaScript

[1902] Backend: Node.js, MySQL

[1903] AI modeling: Python, TensorFlow, Socket.IO

[1904] Program processing

[1905] 1. User Registration

[1906] The server serves a user registration page in Angular on the front end.

[1907] The user uses a terminal to enter basic information such as name, age, years of experience, and field of expertise.

[1908] The server receives this information via Node.js and stores it in a MySQL database.

[1909] 2. Assessment of cognitive characteristics

[1910] The server uses an Angular front-end to provide an interface for questions and tasks to assess cognitive characteristics.

[1911] The user starts the test at the terminal and answers the questions.

[1912] The server receives the responses and uses Python and TensorFlow to analyze the data and determine cognitive traits.

[1913] 3. Learning method suggestions

[1914] Based on the analysis results, the server selects the optimal learning method and suggests corresponding learning materials.

[1915] The terminal displays the suggestions and educational materials to the user.

[1916] 4. Providing learning content

[1917] The server provides learning content (video, audio, text) that best suits the user's cognitive characteristics.

[1918] Users can view this content on their devices and progress as they study, with their progress recorded in real time.

[1919] 5. Real-time support

[1920] If a user has a question while studying, they can enter it using their smartphone or tablet.

[1921] The server uses Socket.IO to receive questions in real time, processes them in Python, and provides instant answers.

[1922] 6. Progress Tracking and Comprehension Testing

[1923] The server periodically conducts comprehension tests, analyzes the results, stores them in a database, and provides feedback to the user.

[1924] 7. Personalized feedback and suggestions for next steps

[1925] The server suggests the next learning task based on the test results and provides related learning content.

[1926] 8. Facilitating discussion and communication

[1927] The server periodically provides discussion topics and provides an interface that encourages the exchange of ideas between users.

[1928] Users can input their opinions on the terminal and hold discussions with other users.

[1929] Examples and prompts

[1930] As a concrete example, consider the case where engineer A is learning how to operate a new industrial robot.

[1931] If engineer A enters "years of experience: 5 years, specialty: industrial robot control" and has visually dominant cognitive characteristics, the system will suggest, "Let's learn the basic operation of industrial robots through video materials." Engineer A will begin learning by watching the video materials, and if he has any questions, he can ask, "Please tell me more about how the sensors on this robot work." The server will immediately provide an appropriate answer to this question.

[1932] An example of a prompt is:

[1933] "For an engineer with five years of experience operating robots, please propose an industrial robot operation method that is easy for a person with visually dominant cognitive characteristics to learn. Also, please suggest related video teaching materials."

[1934] Possible possibilities include:

[1935] In this way, it is possible to propose a learning method that is optimal for the cognitive characteristics of each individual, and to automatically and effectively educate the student on how to operate industrial products and control technology.

[1936] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1937] Step 1:

[1938] User Registration

[1939] The server serves a user registration page in Angular on the front end.

[1940] The user uses a terminal to enter basic information such as name, age, years of experience, and field of expertise.

[1941] The basic information entered is sent from the terminal to the server, which receives this information via Node.js and stores it in a MySQL database.

[1942] Input: Basic information such as name, age, years of experience, field of expertise, etc.

[1943] Output: Basic user information stored in the database

[1944] Step 2:

[1945] Determining cognitive characteristics

[1946] The server uses an Angular front-end to provide an interface for questions and tasks to assess cognitive characteristics.

[1947] The user starts the test at the terminal and answers the questions.

[1948] The server receives the response data and analyzes it using Python and TensorFlow to determine the user's cognitive characteristics, such as visual, auditory, and language.

[1949] Input: User response data

[1950] Output: Cognitive characteristics (visual, auditory, language, etc.)

[1951] Step 3:

[1952] Learning method suggestions

[1953] Based on the results of the analysis of cognitive characteristics, the server selects the optimal learning method and suggests corresponding learning materials.

[1954] The terminal displays the suggestions and educational materials to the user.

[1955] For example, video instructional materials are suggested to visually dominant users.

[1956] Input: Cognitive characteristic analysis results

[1957] Output: Suggested learning methods and materials

[1958] Step 4:

[1959] Providing learning content

[1960] The server provides learning content (video, audio, text) that best suits the user's cognitive characteristics.

[1961] Users can check this content on their devices and progress through their studies, with their progress recorded in real time on the server.

[1962] Input: Suggested learning methods and materials

[1963] Output: Providing learning content and recording progress

[1964] Step 5:

[1965] Real-time Support

[1966] If a user has a question while studying, they can enter it using their smartphone or tablet.

[1967] The server uses Socket.IO to receive questions in real time, processes them in Python, and provides instant answers.

[1968] Input: User question

[1969] Output: Answers provided in real time

[1970] Step 6:

[1971] Progress tracking and comprehension tests

[1972] The server periodically conducts comprehension tests, analyzes the results, stores them in a database, and provides feedback to the user.

[1973] The terminal displays the test results to the user.

[1974] Input: Comprehension test response data

[1975] Output: Test result analysis and feedback

[1976] Step 7:

[1977] Individual feedback and suggestions for next steps

[1978] Based on the results of the comprehension test, the server suggests the next learning task and provides related learning content.

[1979] The terminal displays the next assignment and related content to the user.

[1980] Input: Comprehension test results

[1981] Output: Providing next assignments and related learning content

[1982] Step 8:

[1983] Facilitating discussion and communication

[1984] The server periodically provides discussion topics and provides an interface that encourages the exchange of ideas between users.

[1985] Users can input their opinions on the terminal and hold discussions with other users.

[1986] Input: Discussion topics and user opinions

[1987] Output: Facilitated exchange of ideas and shared opinions

[1988] In this way, the educational support system is designed to function effectively by clarifying the roles of the server, terminal, and user at each step and organizing the specific operations and inputs and outputs.

[1989] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1990] This invention is an AI system for educational support that maximizes learning effectiveness by determining the cognitive characteristics of each individual and proposing individually appropriate learning methods, and by combining it with an emotion engine, provides an optimal learning experience by taking into account the emotional state of the individual. This system functions among four parties: a server, a terminal, a user, and an emotion engine.

[1991] Overall system overview

[1992] This system provides educational support tailored to the target individual by performing the following processes.

[1993] 1. Obtain basic information about the subject.

[1994] 2. Determine the cognitive characteristics of the subject.

[1995] 3. Based on the results of the assessment, the optimal learning method is proposed.

[1996] 4. Provide learning content.

[1997] 5. Track your progress and test your comprehension.

[1998] 6. Provide personalized feedback.

[1999] 7. Resolve your doubts while studying in real time.

[2000] 8. Use an emotion engine to recognize and respond to the subject's emotional state.

[2001] 9. Suggest discussion topics and encourage exchange of ideas.

[2002] Program processing

[2003] Below, the program processing at each step of this system will be explained in natural language.

[2004] 1. User Registration

[2005] The server provides a user registration page.

[2006] Users use the terminal to enter basic information such as name, age, grade, and areas of interest.

[2007] The server stores the entered basic information in a database.

[2008] 2. Cognitive trait assessment test

[2009] The server displays the interface for the cognitive characteristics assessment test on the terminal.

[2010] The user clicks the Start Test button to begin the test.

[2011] 3. Conducting a cognitive assessment test

[2012] The server sends a series of questions or tasks to the terminal in sequence.

[2013] The terminal displays questions and tasks to the user and accepts answers.

[2014] The user answers each question on the terminal.

[2015] The server receives the user's responses and stores them in a database in real time.

[2016] The server analyzes the collected data and determines the user's visual, linguistic, and auditory cognitive characteristics.

[2017] 4. Learning method suggestions

[2018] Based on the judgment results, the server selects the most suitable learning method for the user.

[2019] The server presents the selected learning method and related learning materials to the terminal.

[2020] The device displays learning method suggestions and introductions to learning materials to the user.

[2021] 5. Provision of learning content

[2022] The server provides users with learning content (video, text, audio materials, etc.) appropriate for their needs.

[2023] The user checks the learning content on the device and begins learning.

[2024] The device records the user's learning progress in real time.

[2025] 6. Real-time support

[2026] The server provides an interface that accepts questions from users during their studies via the terminal.

[2027] The user inputs a question into the terminal and sends it.

[2028] The server analyzes the question and instantly generates and provides the appropriate answer.

[2029] The terminal displays the response from the server to the user.

[2030] 7. Progress Tracking and Comprehension Testing

[2031] The server periodically displays an interface on the terminal that allows users to take comprehension tests.

[2032] The user takes the test at the terminal.

[2033] The terminal transmits the user's answer to the server.

[2034] The server scores the answers, stores the results in a database, and provides feedback to the user.

[2035] 8. Personalized feedback and suggestions for next steps

[2036] The server analyzes the results of the user's comprehension test and suggests the next learning content and assignments.

[2037] The device displays feedback and new challenges to the user.

[2038] The user tackles the proposed task.

[2039] 9. Emotion Recognition and Response

[2040] The server uses an emotion engine to monitor the user's emotional state during learning in real time through the terminal.

[2041] The emotion engine identifies emotions from the user's facial expressions and tone of voice, and stores the emotional state in a database.

[2042] The server adjusts the optimal feedback and learning content based on the user's emotional state.

[2043] 10. Facilitating discussion and communication

[2044] The server periodically provides discussion topics.

[2045] The terminal displays discussion topics to the user and provides a form where responses and opinions can be entered.

[2046] Users input their opinions on the terminal and exchange opinions with other users.

[2047] Specific examples

[2048] For example, let's say Mr. D is a first-year high school student who wants to study mathematics.

[2049] 1. User Registration

[2050] Mr. D types into his terminal, "First year high school student, interested in mathematics."

[2051] The server stores this information.

[2052] 2. Cognitive trait assessment test

[2053] Mr. D clicks the start test button on his device.

[2054] The server begins the validation test.

[2055] The device will display questions such as, "Is it easy to remember with an image?"

[2056] D answers the questions.

[2057] The server analyzes Mr. D's answers and determines that he is visually dominant.

[2058] 3. Learning method suggestions

[2059] "Learn math concepts through videos," suggests Thurber.

[2060] A link to the video material will be displayed on the device.

[2061] 4. Providing learning content

[2062] Mr. D starts watching the video on his device.

[2063] 5. Real-time support

[2064] Mr. D types a question into his terminal: "I don't know how to use this formula."

[2065] The server provides the answer, which is displayed on the terminal.

[2066] 6. Progress Tracking and Comprehension Testing

[2067] After watching the video, the server conducts a comprehension test.

[2068] Mr. D takes the test on a terminal.

[2069] 7. Personalized feedback and suggestions for next steps

[2070] The server analyzes the test results and suggests, "Next, try solving some real problems."

[2071] The next learning content will be displayed to Mr. D on his device.

[2072] 8. Emotion Recognition and Response

[2073] The server uses an emotion engine to analyze Mr. D's facial expressions and tone of voice while he is studying.

[2074] If the server identifies Mr. D as feeling tired, it will display a message on his device saying, "Let's take a short break."

[2075] Also, if Mr. D is in a state of joy or adaptation, the teacher will give him feedback such as "That's good enough" and encourage him to continue learning.

[2076] 9. Facilitating discussion and communication

[2077] The server suggests that next week's theme is "Application of Functions," and provides a platform where users can exchange opinions.

[2078] Mr. D can input his opinions on the device and discuss them with his classmates.

[2079] In this way, the AI ​​system can provide an optimal educational experience tailored to individual learning needs, creating an environment in which Mr. D can learn independently. By combining it with an emotion engine, it is possible to respond according to the user's emotional state, further improving learning effectiveness.

[2080] The processing flow will be explained below.

[2081] Step 1:

[2082] The server provides a user registration page, where users use their terminals to enter basic information such as name, age, grade, and areas of interest, and the server stores the entered basic information in a database.

[2083] Step 2:

[2084] The server displays the cognitive characteristics assessment test interface on the terminal, and the user clicks the test start button to start the test.

[2085] Step 3:

[2086] The server sequentially sends a series of questions or tasks to the terminal, which displays the questions or tasks to the user and accepts answers. The user answers each question on the terminal.

[2087] Step 4:

[2088] The server receives the user's responses and stores them in a database in real time. The server analyzes the collected data to determine the user's visual, linguistic, and auditory cognitive characteristics.

[2089] Step 5:

[2090] Based on the results of the assessment, the server selects the optimal learning method for the user. The server then presents the selected learning method and related learning materials to the terminal. The terminal then displays suggested learning methods and introductions to the learning materials to the user.

[2091] Step 6:

[2092] The server provides learning content (video, text, audio, etc.) appropriate for the user. The user checks the learning content on the device and begins learning. The device records the user's learning progress in real time.

[2093] Step 7:

[2094] The server provides an interface that accepts questions from users during their studies via their terminal. The user inputs and submits a question on the terminal. The server analyzes the question and instantly generates and provides an appropriate answer. The terminal displays the answer from the server to the user.

[2095] Step 8:

[2096] The server periodically displays an interface on the device that conducts comprehension tests. The user takes the test on the device. The device sends the user's answers to the server. The server grades the answers, stores the results in a database, and provides feedback to the user.

[2097] Step 9:

[2098] The server analyzes the results of the user's comprehension test and suggests the next learning content and assignments. The device displays feedback and new assignments to the user. The user then works on the suggested assignments.

[2099] Step 10:

[2100] The server uses an emotion engine to monitor the user's emotional state in real time through the device while they are learning. The emotion engine identifies emotions from the user's facial expressions and tone of voice, and stores the emotional state in a database. The server then provides optimal feedback and adjusts the learning content based on the user's emotional state.

[2101] Step 11:

[2102] The server periodically provides discussion topics. The terminal displays the discussion topics to the user and provides a form in which the user can enter their answers and opinions. The user enters their opinions on the terminal and exchanges opinions with other users.

[2103] Example 2

[2104] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2105] Conventional educational systems have had difficulty providing learning methods that fully consider the cognitive characteristics and emotional state of each individual student. Furthermore, they lacked functionality for real-time resolution of questions that arise during learning and for easy exchange of opinions between students. This made it difficult to provide an optimal learning experience for each student, resulting in a lack of maximization of learning effectiveness.

[2106] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for inputting basic information about the subject, a means for determining the cognitive characteristics of the subject, a means for proposing an optimal learning method based on the determination results, a means for providing learning content, a means for tracking learning progress and conducting comprehension tests, a means for providing individual feedback to the subject, a means for resolving questions during learning in real time, and a means for recognizing and responding to the subject's emotional state using an emotion engine. This makes it possible to provide an optimal learning experience tailored to the subject's individual needs and maximize learning effectiveness. Furthermore, by encouraging the exchange of opinions between subjects as needed, the quality of learning can be expected to improve.

[2107] "Target audience" refers to learners who use the education system.

[2108] "Basic information" refers to basic data such as the subject's name, age, grade, and areas of interest.

[2109] "Cognitive characteristics" refers to the subject's cognitive style, such as visual, linguistic, and auditory.

[2110] A "judgment test" refers to a series of questions or tasks designed to assess a subject's cognitive characteristics.

[2111] "Feedback" refers to individual evaluations and advice provided based on the subject's learning results.

[2112] "Learning method" refers to the learning process and techniques proposed based on the cognitive characteristics of the subject.

[2113] "Learning content" includes learning materials and resources used for learning, such as videos, texts, and audio materials.

[2114] An "emotion engine" refers to a system that has the ability to recognize a subject's emotional state and process that data.

[2115] "Real-time support" refers to the function of providing immediate responses to questions or concerns that students may have while studying.

[2116] "Discussion Topics" refers to topics that are periodically provided by the server for the purpose of exchanging opinions among participants.

[2117] "Opinion exchange" refers to the activity of sharing opinions and thoughts among participants.

[2118] "Server" refers to a central computer that runs the entire system and provides each function.

[2119] "Device" means the computer or mobile device used by a Subject to access the System.

[2120] This invention is an AI system for educational support that maximizes learning effectiveness by determining the cognitive characteristics of each individual and proposing individually appropriate learning methods. Furthermore, by combining it with an emotion engine, it provides an optimal learning experience by taking into account the emotional state of each individual. This system functions among four parties: a server, a terminal, a user, and an emotion engine.

[2121] Overall system...

Claims

1. A means for inputting basic information of the subject; a means for determining cognitive characteristics of a subject; A means for proposing an optimal learning method based on the judgment results; a means of delivering learning content; A means to track learning progress and administer comprehension tests; a means of providing individualized feedback to subjects; A way to resolve questions during learning in real time, A system including:

2. The system according to claim 1, further comprising means for suggesting a discussion topic to the subjects and promoting an exchange of opinions among the subjects.

3. 10. The system of claim 1, further comprising means for providing questions or tasks to assess the subject's cognitive characteristics and for collecting and analyzing the subject's responses.

Images