System

Abstract

A system is provided.SOLUTION: A system comprising: means for collecting specific user information and generating an individual learning curriculum based on the user information; means for recording and analyzing answer data of questions answered by the user; means for updating a learning plan in real time based on the analysis result; and terminal means including a smart speaker for providing an interactive class.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 current educational environment, there is an extreme lack of educational resources and facilities, particularly in areas with low literacy rates and rural areas. In such environments, the necessary number of textbooks and teachers are not available, making it difficult for students to receive an appropriate education. It is also difficult to provide customized learning instruction tailored to each student's characteristics, cultural background, and learning style. Therefore, a new education system is needed to eliminate disparities in educational opportunities and maximize the potential of each learner. [Means for solving the problem]

[0005] The present invention provides a system that includes a means for collecting specific user information and generating an individualized learning curriculum based on the user information, a means for recording and analyzing answer data from questions answered by the user, a means for updating a learning plan in real time based on the analysis results, and a terminal means including a smart speaker for providing interactive, dialogue-based lessons. This allows for an effective learning experience tailored to each individual student, even in areas with limited educational resources. Furthermore, the quality of education can be improved by monitoring learning progress and misunderstanding trends through a dedicated screen for teachers and providing appropriate feedback.

[0006] "User Information" refers to specific information about an individual learner, such as name, age, grade level, ethnic and cultural background, learning style, and existing learning level.

[0007] "Learning curriculum" refers to learning materials and learning plans that are optimal for individual learners and are generated based on user information.

[0008] "Answer data" refers to information that indicates the results and trends of questions answered by learners.

[0009] "Analysis" refers to the process of analyzing trends such as learners' correct answer rates and incorrect answer patterns based on answer data.

[0010] "Study plan" refers to an individual learning curriculum or study plan that is updated based on the analysis results.

[0011] "Real-time updates" means that new information is reflected in the learning plan as soon as it is generated.

[0012] "Interactive lessons" refers to an educational method that involves learners engaging in interactive interactions via smart speakers.

[0013] A "smart speaker" refers to a device that can input and output voice and has the functionality to conduct interactive lessons.

[0014] "Device means" refers to digital devices or equipment used by learners, including but not limited to smart speakers.

[0015] The "teacher-only screen" refers to an interface that allows teachers to check learners' progress and trends in misunderstandings and provide feedback. [Brief explanation of the drawings]

[0016] [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

[0017] 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.

[0018] First, the terms used in the following description will be explained.

[0019] 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).

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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."

[0037] A specific embodiment of the system according to the present invention and its processing flow will be described below.

[0038] The system has the functions of collecting specific user information and generating an individual learning curriculum based on that information, recording and analyzing the answers given by the user, updating the learning plan in real time based on the analysis results, and providing terminal functions including a smart speaker for providing interactive, dialogue-based lessons.

[0039] (Collection of user information and profile registration)

[0040] server

[0041] The server receives information entered by the user from the device and stores it in a database, such as the user's name, age, grade level, ethnic and cultural background, learning style, and existing learning level.

[0042] Specific examples

[0043] A 12-year-old user enters their name, age, ethnic background (e.g., from Sub-Saharan Africa), visual learning style, etc., and the server stores this information in a database.

[0044] (Generating personalized learning curriculum)

[0045] server

[0046] The server analyzes the stored user information and generates an optimal learning curriculum for each individual learner. This curriculum is created as digital learning materials based on the content of compulsory education and the user's cultural background.

[0047] Specific examples

[0048] The server generates mathematics and science learning materials incorporating local language and culture for 12-year-old users from sub-Saharan Africa and sends the materials to the users' devices.

[0049] (Learning progress and feedback)

[0050] Terminal

[0051] As the user works through the questions and answers, the terminal records the answers and sends them to the server.

[0052] server

[0053] The server analyzes the received answer data to determine the user's accuracy rate and answer trends. Based on the analysis results, it updates the study plan in real time and generates additional learning materials to fill in the user's weak points.

[0054] Specific examples

[0055] If a 12-year-old user solves math problems and finds that he gets 90% of the answers right but makes mistakes on some geometry-related questions, the server will generate supplementary geometry-related learning materials and incorporate them into his next learning plan.

[0056] teacher

[0057] Teachers can check the user's learning progress and misunderstandings on a dedicated screen and enter feedback as needed. The server sends this feedback to the user's device and notifies the user in real time.

[0058] (Interactive dialogue-based lessons)

[0059] Terminal

[0060] When a user speaks a question to a smart speaker, the device analyzes the voice and sends the question to the server.

[0061] server

[0062] The server analyzes the user's question, generates the necessary information and answers, and sends them to the device, which then relays the information to the user via voice.

[0063] Specific examples

[0064] When a user asks a question about the Pythagorean theorem, the device sends the question to the server, which responds with an appropriate explanation and example. The smart speaker then explains it to the user and offers additional questions to further deepen their understanding.

[0065] (Teaching material updates)

[0066] server

[0067] If the content of the textbook or the course changes, the new information is automatically uploaded to the server and immediately reflected in each user's learning plan.

[0068] Specific examples

[0069] When new historical facts are discovered and added to the educational curriculum, the server updates each user's learning plan based on this new information and sends new learning materials to the device.

[0070] In this way, this system enables smooth information exchange between the server, terminals, and users, providing an effective learning experience even in areas with inadequate educational environments.

[0071] The processing flow will be explained below.

[0072] Step 1:

[0073] User: The user installs and launches the app. On first launch, the user enters profile information such as name, age, grade level, ethnic and cultural background, learning style, and existing learning level.

[0074] Step 2:

[0075] Terminal: Collects profile information entered by the user and sends it to the server.

[0076] Step 3:

[0077] Server: The server stores the received user information in a database.

[0078] Step 4:

[0079] Server: The server analyzes the stored user information and generates an individualized learning curriculum based on the user's characteristics and learning style. The generated curriculum includes compulsory education content and supplementary materials tailored to the user's cultural background.

[0080] Step 5:

[0081] Server: Prepares the generated learning curriculum as digital learning materials and sends them to the user's device.

[0082] Step 6:

[0083] Terminal: Notifies the user of the received learning curriculum and displays it.

[0084] Step 7:

[0085] User: The user studies according to the provided learning curriculum. When solving a problem, the user inputs the answer.

[0086] Step 8:

[0087] Terminal: Records the user's answers and sends the data to the server.

[0088] Step 9:

[0089] Server: Analyzes the received answer data and determines the user's correct answer rate and answer trends.

[0090] Step 10:

[0091] Server: Updates the user's study plan in real time based on the analysis results, automatically generating additional learning materials and supplementary questions as needed.

[0092] Step 11:

[0093] Server: Sends the updated learning plan to the user's device and notifies them.

[0094] Step 12:

[0095] Device: Display the updated learning plan to the user.

[0096] Step 13:

[0097] Teachers: Teachers can check the user's learning progress and misunderstandings from a dedicated screen. If necessary, they can enter feedback.

[0098] Step 14:

[0099] Server: Receives teacher feedback and sends it to the user's device.

[0100] Step 15:

[0101] Device: Displays received teacher feedback to the user.

[0102] Step 16:

[0103] User: If the user has any questions while studying, they can ask them by voice via a smart speaker.

[0104] Step 17:

[0105] Terminal: Analyzes the user's voice question and sends the question to the server.

[0106] Step 18:

[0107] Server: Analyzes the question, generates the necessary information and answers, and sends them to the device.

[0108] Step 19:

[0109] Terminal: Provides users with answers to questions via a smart speaker.

[0110] Step 20:

[0111] Server: When the content of the educational curriculum or textbooks changes, the new information is uploaded to the database and each user's learning plan is automatically updated.

[0112] Step 21:

[0113] Server: Sends the updated learning plan to the user's device and notifies them.

[0114] Step 22:

[0115] Device: Display new learning materials and updated curriculum to users.

[0116] Example 1

[0117] 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."

[0118] Conventional educational systems have had the problem of being unable to respond to individual user needs, resulting in the provision of uniform teaching materials. Furthermore, it is difficult to provide effective learning support because it is not possible to grasp users' learning progress and level of understanding in real time and provide appropriate feedback. Furthermore, there is a lack of means to provide interactive, dialogue-based lessons, making it difficult to promote deep learning through two-way communication.

[0119] 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.

[0120] In this invention, the server includes means for collecting specific user information and generating an individual education plan based on the user information, means for recording and analyzing answer data to questions answered by the user, and means for updating the education plan in real time based on the analysis results, thereby providing a learning experience tailored to the needs of each individual user and promoting deep understanding through interactive lessons.

[0121] "Specific User Information" means individual information provided by a User, such as name, age, grade level, ethnic and cultural background, learning style, and existing learning level.

[0122] An "individualized education plan" is a curriculum and learning materials tailored to a user's individual needs and learning style, created based on the user's specific user information.

[0123] "Answer data" refers to a record of the answers given by users to questions or problems.

[0124] "Real-time updates" refers to instantly changing and adapting educational plans and teaching material content based on the results of analyzing answer data.

[0125] A "voice recognition device" is a device that recognizes a user's voice, analyzes it, and processes it as information.

[0126] "Analysis" refers to the process of identifying patterns and trends based on collected data and evaluating learning progress and level of understanding.

[0127] The "instructor-only screen" is an interface that allows instructors to check the user's learning progress and answer trends, and to input and provide feedback.

[0128] The present invention relates to a system that collects specific user information and generates an individualized educational plan based on that user information. This system provides a learning experience tailored to the individual needs of each user by smoothly exchanging information between a server, terminals, and users.

[0129] Collection of user information and profile registration

[0130] server

[0131] The server receives user information entered from the device and stores it in a database. This information includes the user's name, age, grade, ethnic and cultural background, learning method, existing learning level, etc. For example, if a 12-year-old user enters their name, age, ethnic background, visual learning style, etc., the server stores this information in a database.

[0132] Generate an Individualized Education Plan

[0133] server

[0134] The server analyzes the stored user information and uses a generative AI model to generate an individualized educational plan. This plan is created as digital learning materials based on the content of the compulsory education curriculum and the user's cultural background. For example, for a 12-year-old user from Sub-Saharan Africa, math and science learning materials incorporating the local language and culture are generated and sent to the user's device.

[0135] Learning progress and feedback

[0136] Terminal

[0137] When a user works on a problem and answers it, the device records the answer and sends it to the server.

[0138] server

[0139] The server analyzes the received answer data and determines the user's accuracy rate and answer trends. Based on the analysis results, the server updates the study plan in real time and generates additional learning materials to address the user's weaknesses. For example, if a user solves arithmetic problems and finds that they answered 90% of the questions correctly but made mistakes on some geometry-related questions, the server will generate supplementary geometry-related learning materials and incorporate them into the next study plan.

[0140] teacher

[0141] Teachers can check the user's learning progress and misunderstandings on a dedicated screen and enter feedback as needed. The server sends this feedback to the user's device and notifies the user in real time.

[0142] Interactive and conversational lessons

[0143] Terminal

[0144] When a user asks a question using a voice recognition device, the terminal analyzes the voice and sends the question to the server.

[0145] server

[0146] The server analyzes the user's question, generates the necessary information and answers, and sends them to the device. The speech recognizer then verbally conveys this information to the user. For example, if a user asks about the Pythagorean theorem, the device sends the question to the server, which returns an appropriate explanation and example problem. The speech recognizer then explains the problem to the user and provides additional problems to further deepen their understanding.

[0147] Updates to teaching materials

[0148] server

[0149] If the content of textbooks or courses changes, the new information is automatically uploaded to the server and immediately reflected in each user's educational plan. For example, if a new historical fact is discovered and added to the educational curriculum, the server updates each user's educational plan based on this new information and sends new learning materials to their device.

[0150] Prompt Sentence Examples

[0151] Curriculum generation: "Create digital learning materials that are appropriate for a 12-year-old from Sub-Saharan Africa. Please consider the user's visual learning style and incorporate local language and culture."

[0152] Interactive Lessons: "Explain the Pythagorean Theorem in detail and provide additional questions to help students understand."

[0153] As described above, this system has the ability to generate individual educational plans based on specific user information and update them in real time, while also providing interactive, dialogue-based education to ensure an effective learning experience.

[0154] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0155] Step 1:

[0156] The user enters information from the device

[0157] The user accesses a terminal and enters information into a form, such as name, age, grade, ethnic and cultural background, learning method, and existing learning level.

[0158] (Input) Data about the user's personal information and learning style.

[0159] (Output) The input data is temporarily saved on the device.

[0160] Step 2:

[0161] The device sends the information to the server

[0162] The terminal converts the information entered by the user into packets and transmits them to the server.

[0163] (Input) User information entered into the terminal.

[0164] (Output) Information is sent to the server.

[0165] Step 3:

[0166] The server receives the information and stores it in a database

[0167] The server analyzes the user information received from the terminal and stores it in a database.

[0168] (Input) User information sent from the terminal.

[0169] (Output) The parsed user information is saved in the database.

[0170] Step 4:

[0171] The server analyzes user information and generates an individualized education plan

[0172] The server analyzes the stored user information using a generative AI model to generate an individualized educational plan.

[0173] (Input) User information stored in the database.

[0174] (Output) The generated individualized education plan.

[0175] Step 5:

[0176] The server sends the educational plan to the device.

[0177] The server transmits the generated individual education plan to the terminal.

[0178] (Input) Generated individualized education plan.

[0179] (Output) The teaching plan is transferred to the terminal.

[0180] Step 6:

[0181] The user works through the questions and enters the answers

[0182] Users work on the digital learning materials provided on their terminals and input answers to the questions.

[0183] (Input) The question and the user's answer displayed on the terminal.

[0184] (Output) Answer data is temporarily saved on the device.

[0185] Step 7:

[0186] The device sends the answer to the server

[0187] The terminal transmits the saved answer data to the server.

[0188] (Input) User's answer data.

[0189] (Output) The answer data is sent to the server.

[0190] Step 8:

[0191] The server analyzes the answer data

[0192] The server analyzes the received answer data, determines the user's accuracy rate and answer trends, and processes the data using a generative AI model.

[0193] (Input) User's answer data.

[0194] (Output) Analysis results.

[0195] Step 9:

[0196] The server updates the educational plan in real time

[0197] Based on the analysis results, the server updates the study plan in real time and generates additional learning materials to fill in the user's weaknesses.

[0198] (Input) Analysis results.

[0199] (Output) Updated lesson plans and generated additional teaching materials.

[0200] Step 10:

[0201] The server sends the updated lesson plan and additional materials to the device.

[0202] The server sends updated lesson plans and additional teaching materials to the terminal.

[0203] (Input) Updated teaching plans and additional materials.

[0204] (Output) The lesson plan and additional materials are sent to the terminal.

[0205] Step 11:

[0206] User asks a question to the smart speaker

[0207] The user speaks a question using a voice recognition device.

[0208] (Input) The user's spoken question.

[0209] (Output) The device recognizes the voice data.

[0210] Step 12:

[0211] The device analyzes the voice and sends it to the server

[0212] The terminal analyzes the user's voice data as text data and sends it to the server.

[0213] (Input) Audio data.

[0214] (Output) The parsed text data is sent to the server.

[0215] Step 13:

[0216] The server analyzes the question and generates the answer

[0217] The server analyzes the received question and generates an appropriate answer using a generative AI model.

[0218] (Input) Parsed text data.

[0219] (Output) The generated answer.

[0220] Step 14:

[0221] The server sends the answer to the device

[0222] The server sends the generated answer to the terminal.

[0223] (Input) The generated answer.

[0224] (Output) The answer is sent to the device.

[0225] Step 15:

[0226] The device provides answers by voice

[0227] The terminal provides the received answer to the user through a voice recognition device.

[0228] (Input) The answer sent from the server.

[0229] (Output) The answer provided aloud.

[0230] (Application example 1)

[0231] 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."

[0232] Conventional skills training systems for factory operators have had difficulty quickly and effectively providing appropriate learning curricula tailored to individual skill levels and experience. Furthermore, they lacked the functionality to analyze learning progress in real time and provide feedback, making it extremely difficult to improve operators' skills. Furthermore, they lacked the functionality to provide interactive, dialogue-based lessons, making it difficult to immediately respond to operators' questions or problems.

[0233] 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.

[0234] In this invention, the server includes means for collecting specific user information and generating an individual learning curriculum based on the user information, means for recording and analyzing answer data for questions answered by the user, means for updating the learning plan in real time based on the analysis results, terminal means including a smart speaker for providing interactive dialogue-based lessons, means for generating a learning curriculum based on the skill level and past training data of the factory operator, means for analyzing the operator's learning progress in real time and providing feedback, means for generating additional learning materials based on the feedback, and means for responding to the learner's questions through the smart speaker. This makes it possible to provide effective training tailored to the individual skill level of the factory operator and enable rapid skill improvement through real-time progress analysis and feedback.

[0235] "Specific user information" is information necessary to identify a user and is data used to generate an individualized learning curriculum.

[0236] An "individualized learning curriculum" is a plan created based on specific user information and including learning content that is optimal for that user.

[0237] "Answer data" is data that records the results and trends of questions answered by users.

[0238] The "analysis results" are the results of analyzing the answer data, and are the basic information for updating the user's study plan.

[0239] A "smart speaker" is a device that interacts with users through a voice interface, providing information and instructions via voice.

[0240] "Terminal means" refers to the device that a user uses to interact with the system, including smart speakers, computers, tablets, etc.

[0241] "Factory operator" refers to an employee who operates and manages machinery and equipment at a manufacturing site.

[0242] "Skill level" is an indicator of an operator's technical proficiency in a particular task.

[0243] "Training data" refers to data that records the content and results of past training.

[0244] "Feedback" is information that provides evaluation and advice on the results of learning or work.

[0245] "Additional learning materials" are learning materials provided to supplement the learning based on the user's learning progress and analysis results.

[0246] A specific embodiment of a learning system for factory operators based on the present invention and its processing flow are described below. This system has the function of collecting specific user information and generating an individual learning curriculum based on that information. It also has the function of recording and analyzing answer data from questions answered by the user and updating the learning plan in real time based on the analysis results. Furthermore, the system features terminal means including a smart speaker for providing interactive, dialogue-based lessons.

[0247] Collection of user information and profile registration

[0248] server

[0249] The server receives information entered by the user from the terminal and stores it in a database. For example, the operator enters their name, age, skill level, past training data, etc.

[0250] Specific examples

[0251] A 30-year-old factory operator enters his or her name, age, entry-level skills, and past training data, and the server stores that information in a database.

[0252] Creating personalized learning curriculum

[0253] server

[0254] The server analyzes the stored user information and generates an optimal learning curriculum for each operator. The generated curriculum is created as digital learning materials based on past training data and skill level.

[0255] Specific examples

[0256] The server generates teaching materials for beginners, such as welding techniques and machine operation, for a 30-year-old beginner operator, and sends the materials to the user's terminal.

[0257] Learning progress and feedback

[0258] Terminal

[0259] As the user works through the questions and answers, the answers are recorded and sent to the server.

[0260] server

[0261] The server analyzes the answer data to determine the user's accuracy rate and answer trends. Based on the analysis results, the server updates the learning plan in real time and generates additional learning materials to fill in the operator's weaknesses.

[0262] Specific examples

[0263] If a 30-year-old operator solves machine operation problems and gets 90% correct, but makes mistakes on some questions related to changing settings, the server will generate supplementary learning materials related to changing settings and incorporate them into the next learning plan.

[0264] Interactive and conversational lessons

[0265] Terminal

[0266] When a user speaks a question to a smart speaker, the voice is analyzed and the question is sent to the server.

[0267] server

[0268] The server analyzes the user's question, generates the necessary information and answers, and sends them to the device, which then relays the information to the user via voice.

[0269] Specific examples

[0270] When a factory operator asks, "Please teach me basic welding techniques," the device sends the question to the server, which then returns appropriate explanations and training materials. The smart speaker then explains the information to the operator aloud and provides further training methods.

[0271] Hardware and Software

[0272] Server: Cloud server (e.g., AWS (registered trademark), Google (registered trademark) Cloud)

[0273] Database: MySQL(registered trademark), PostgreSQL

[0274] AI analysis engine: GPT-4 (registered trademark)

[0275] Devices: Smart speakers (e.g., Amazon Echo, GOOGLE HOME (registered trademark)), factory robots, operator devices (PCs and tablets)

[0276] Examples and prompts

[0277] Specific examples

[0278] A 30-year-old novice operator needs to be trained in a new welding technique.

[0279] The operator asks the smart speaker, "Please tell me about the basic techniques of welding."

[0280] Prompt statement

[0281] User information: 'Name: Ichiro Tanaka, Age: 30, Skill level: Beginner, Past training data: []'. Please generate a learning curriculum appropriate for this user.

[0282] Question: 'Please tell me about the basic techniques of welding'. Please provide a suitable answer.

[0283] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0284] Step 1: Enter and submit user information

[0285] The user inputs information such as their name, age, skill level, and past training data from the terminal, and this input data is sent from the terminal to the server.

[0286] concrete action

[0287] Input: Name, age, skill level, past training data

[0288] Data processing: Convert each item into JSON format

[0289] Output: User information sent to the server

[0290] Example: Name: Yamada Taro, Age: 35, Skill Level: Intermediate, Training Data: []

[0291] Step 2: Save user information

[0292] The server stores the received user information in a database, which is then used to generate a personalized learning curriculum.

[0293] concrete action

[0294] Input: User information sent from the device (JSON format)

[0295] Data processing: Converting data into SQL statements for saving to the database

[0296] Output: User information stored in the database

[0297] Destination: Database (MySQL, PostgreSQL)

[0298] Step 3: Create a personalized learning curriculum

[0299] The server analyzes the stored user information and generates an individual learning curriculum using a generative AI model (GPT-4). The generated curriculum is then sent to the user's device as digital learning materials.

[0300] concrete action

[0301] Input: User information retrieved from the database

[0302] Data processing: Prompt generation and input to GPT-4

[0303] Output: Personalized learning curriculum

[0304] Example prompt: "User information: {'Name': 'Yamada Taro', 'Age': 35, 'Skill level': 'Intermediate', 'Training data': []}. Please generate a learning curriculum appropriate for this user."

[0305] AI used: GPT-4

[0306] Send the generated curriculum to your device

[0307] Step 4: Record your learning progress

[0308] When a user works on a problem and answers it on the terminal, the answer data is recorded by the terminal and transmitted to the server.

[0309] concrete action

[0310] Input: User's answer data

[0311] Data processing: Recording correct and incorrect answers for each answer and generating data for trend analysis

[0312] Output: Answer data sent to the server

[0313] Example: Question ID: 123, Answer: "A", Correct Answer: true

[0314] Step 5: Analyze the answer data and provide feedback

[0315] The server analyzes the received answer data to determine the accuracy rate and answer trends. Based on the analysis results, it updates the learning plan in real time and generates additional learning materials to fill in the operator's weaknesses.

[0316] concrete action

[0317] Input: Answer data sent from the device

[0318] Data processing: Correct answer rate calculation and trend analysis

[0319] Output: Updated learning plan and feedback

[0320] AI used: GPT-4

[0321] Example prompt for generating additional learning materials: "Answer data: [{'Question ID': 123, 'Answer': 'A', 'Correct Answer': true}]. Analyze learning progress and provide feedback.

[0322] Step 6: Interactive and interactive lessons

[0323] When a user speaks a question to a smart speaker, the voice data is analyzed and the question is sent to the server. The server analyzes the question, generates the necessary information and answer, and sends it to the device. The smart speaker then conveys that information by voice.

[0324] concrete action

[0325] Input: A spoken question from the user

[0326] Data processing: speech recognition and text conversion, answer generation using GPT-4

[0327] Output: A spoken response to the user

[0328] AI used: GPT-4

[0329] Example prompt: "Question: 'Tell me about basic welding techniques.' Please provide an appropriate answer."

[0330] Example speech output: "The basic technique of welding is..."

[0331] Step 7: Distribute generated materials and update learning plans

[0332] The server sends the generated additional learning materials and updated study plans to the user's device, and the user continues studying based on the new study plans.

[0333] concrete action

[0334] Input: Updated study plans and additional materials

[0335] Data processing: Converting data to send to the user's device

[0336] Output: Push notifications and delivery of educational materials to users' devices

[0337] Communication method: Data transmission via the Internet

[0338] Example delivery: "New learning plans are available. Check them out in the next session."

[0339] As described above, the system provides factory operators with individual learning curricula, performs real-time progress analysis and feedback, and supports efficient skill development through interactive, dialogue-based lessons.

[0340] 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.

[0341] A specific embodiment of the system according to the present invention and its processing flow will be described below.

[0342] The system has the functions of collecting specific user information and generating an individual learning curriculum based on that information, recording and analyzing the answers given by the user to questions, updating the learning plan in real time based on the analysis results, and providing device functions including a smart speaker that provides interactive lessons.It also has an emotion engine that recognizes the user's emotions.

[0343] (Collection of user information and profile registration)

[0344] server

[0345] The server receives information entered by the user from the device and stores it in a database, such as the user's name, age, grade level, ethnic and cultural background, learning style, and existing learning level.

[0346] Specific examples

[0347] A 12-year-old user enters their name, age, ethnic background (e.g., from Sub-Saharan Africa), visual learning style, etc., and the server stores this information in a database.

[0348] (Generating personalized learning curriculum)

[0349] server

[0350] The server analyzes the stored user information and generates an optimal learning curriculum for each individual learner. This curriculum is created as digital learning materials based on the content of compulsory education and the user's cultural background.

[0351] Specific examples

[0352] The server generates mathematics and science learning materials incorporating local language and culture for 12-year-old users from sub-Saharan Africa and sends the materials to the users' devices.

[0353] (Learning progress and feedback)

[0354] Terminal

[0355] As the user works through the questions and answers, the terminal records the answers and sends them to the server.

[0356] server

[0357] The server analyzes the received answer data to determine the user's accuracy rate and answer trends. Based on the analysis results, it updates the study plan in real time and generates additional learning materials to fill in the user's weak points.

[0358] Specific examples

[0359] If a 12-year-old user solves math problems and finds that he gets 90% of the answers right but makes mistakes on some geometry-related questions, the server will generate supplementary geometry-related learning materials and incorporate them into his next learning plan.

[0360] teacher

[0361] Teachers can check the user's learning progress and misunderstandings on a dedicated screen and enter feedback as needed. The server sends this feedback to the user's device and notifies the user in real time.

[0362] (Interactive dialogue-based lessons)

[0363] Terminal

[0364] When a user speaks a question to a smart speaker, the device analyzes the voice and sends the question to the server.

[0365] server

[0366] The server analyzes the user's question, generates the necessary information and answers, and sends them to the device, which then relays the information to the user via voice.

[0367] Specific examples

[0368] When a user asks a question about the Pythagorean theorem, the device sends the question to the server, which responds with an appropriate explanation and example. The smart speaker then explains it to the user and offers additional questions to further deepen their understanding.

[0369] (Utilizing emotion engines)

[0370] Terminal

[0371] The device detects the emotions expressed by the user through facial expressions and tone of voice while learning, and sends this data to the emotion engine.

[0372] Server (emotion engine)

[0373] The emotion engine analyzes the data sent from the terminal and determines the user's emotional state (e.g., interest, fatigue, frustration, etc.).

[0374] Specific examples

[0375] If the user shows signs of fatigue while studying, the emotion engine will analyze this information and suggest that the user take a break, a suggestion that will be delivered audibly through the smart speaker.

[0376] (Teaching material updates)

[0377] server

[0378] If the content of the textbook or the course changes, the new information is automatically uploaded to the server and immediately reflected in each user's learning plan.

[0379] Specific examples

[0380] When new historical facts are discovered and added to the educational curriculum, the server updates each user's learning plan based on this new information and sends new learning materials to the device.

[0381] (Feedback optimization using emotion engine)

[0382] Server (emotion engine)

[0383] The emotion engine automatically generates feedback and support messages based on the user's emotional state, which are delivered via a smart speaker with the goal of improving the user's learning efficiency.

[0384] Specific examples

[0385] If the user is interested, the emotion engine will provide additional challenges or relevant information to keep them engaged, or if they are frustrated, it will suggest hints or quick solutions to their problems.

[0386] In this way, this system achieves smooth information exchange between the server, terminals, and users, providing an effective learning experience even in areas with inadequate educational environments. The addition of an emotion engine provides optimal support according to the user's emotional state, improving learning efficiency and motivation.

[0387] The processing flow will be explained below.

[0388] Step 1:

[0389] User: The user installs and launches the app. On first launch, the user enters profile information such as name, age, grade level, ethnic and cultural background, learning style, and existing learning level.

[0390] Step 2:

[0391] Terminal: Collects profile information entered by the user and sends it to the server.

[0392] Step 3:

[0393] Server: The server stores the received user information in a database.

[0394] Step 4:

[0395] Server: The server analyzes the stored user information and generates an individualized learning curriculum based on the user's characteristics and learning style. The generated curriculum includes the content of the compulsory education curriculum and supplementary materials tailored to the user's cultural background.

[0396] Step 5:

[0397] Server: Prepares the generated learning curriculum as digital learning materials and sends them to the user's device.

[0398] Step 6:

[0399] Terminal: Notifies the user of the received learning curriculum and displays it.

[0400] Step 7:

[0401] User: The user studies according to the provided learning curriculum. When solving a problem, the user inputs the answer.

[0402] Step 8:

[0403] Terminal: Records the user's answers and sends the data to the server.

[0404] Step 9:

[0405] Server: Analyzes the received answer data and determines the user's correct answer rate and answer trends.

[0406] Step 10:

[0407] Server: Updates the user's study plan in real time based on the analysis results, automatically generating additional learning materials and supplementary questions as needed.

[0408] Step 11:

[0409] Server: Sends the updated learning plan to the user's device and notifies them.

[0410] Step 12:

[0411] Device: Display the updated learning plan to the user.

[0412] Step 13:

[0413] Teacher: The teacher can check the user's learning progress and misunderstandings from a dedicated screen. If necessary, the teacher can enter feedback.

[0414] Step 14:

[0415] Server: Receives teacher feedback and sends it to the user's device.

[0416] Step 15:

[0417] Device: Displays received teacher feedback to the user.

[0418] Step 16:

[0419] User: If the user has any questions while studying, they can ask them by voice via a smart speaker.

[0420] Step 17:

[0421] Terminal: Analyzes the user's voice question and sends the question to the server.

[0422] Step 18:

[0423] Server: Analyzes the question, generates the necessary information and answers, and sends them to the device.

[0424] Step 19:

[0425] Terminal: Provides users with answers to questions via a smart speaker.

[0426] Step 20:

[0427] Terminal: Collects emotional information from the user's voice and facial expressions and sends that data to the server.

[0428] Step 21:

[0429] Server (emotion engine): Analyzes the emotion information sent from the device and determines the user's emotional state (e.g., interest, fatigue, frustration, etc.).

[0430] Step 22:

[0431] Server (Emotion Engine): Adjusts learning curriculum and feedback based on the user's emotional state. For example, it suggests a break if the user is tired, or provides additional relevant information if the user shows interest.

[0432] Step 23:

[0433] Server (emotion engine): Sends automatically generated feedback and support messages to the device.

[0434] Step 24:

[0435] Terminal: Provides users with feedback and support messages from the emotion engine via a smart speaker.

[0436] Step 25:

[0437] Server: When the content of the educational curriculum or textbooks changes, the new information is uploaded to the database and each user's learning plan is automatically updated.

[0438] Step 26:

[0439] Server: Sends the updated learning plan to the user's device and notifies them.

[0440] Step 27:

[0441] Device: Display new learning materials and updated curriculum to users.

[0442] Example 2

[0443] 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."

[0444] Previous educational systems lacked detailed learning support tailored to individual users' cultural backgrounds and learning styles, and the lack of real-time feedback limited the effectiveness of learning. Furthermore, the lack of a mechanism for reflecting users' emotions in the learning process made it difficult to improve learning efficiency and motivation.

[0445] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for collecting specific user information and generating an individual learning curriculum based on the user information; means for recording and analyzing answer data of questions answered by the user; means for updating the learning plan in real time based on the analysis results; voice communication terminal means for providing interactive dialogue-based lessons; and means including an emotion engine for recognizing user emotions and analyzing emotion data to provide learning support. This makes it possible to provide a learning curriculum optimized for each user, real-time feedback according to learning progress, and appropriate support based on the user's emotional state.

[0446] "Specific User Information" is information provided by a user regarding their name, age, grade level, ethnic and cultural background, learning style, and existing learning level.

[0447] An "individual learning curriculum" is a collection of educational content and learning materials optimized for each user based on collected user information.

[0448] "Answer data" is a record of the answers to questions that the user answered while studying.

[0449] "Updating in real time" means immediately reviewing the learning plan based on the progress of learning and analysis results, and providing instruction based on the latest information.

[0450] An "interactive dialogue-based lesson" is a two-way lesson format in which users ask and answer questions via voice communication terminals, and the system provides appropriate feedback and explanations.

[0451] "Voice communication terminal" refers to a device that enables voice communication, specifically a smart speaker.

[0452] The "emotion engine" is part of a system that analyzes the user's emotional state and provides learning support and feedback based on the results of that analysis.

[0453] The "Educator-only screen" is an interface that allows educators to view and manage learning status and analysis results.

[0454] The present invention is a system that collects specific user information and generates an individual learning curriculum based on that user information. This system is realized through the exchange of information between a server, a terminal, and a user.

[0455] 1. Collection of User Information and Profile Registration

[0456] server

[0457] The server receives information entered by the user from their device and stores it in a database. The information entered by the user includes name, age, grade, ethnic and cultural background, learning style, and existing learning level. This information serves as the basis for generating a learning curriculum optimized for each user.

[0458] Examples:

[0459] Users enter information such as "from Sub-Saharan Africa, 12 years old, visual learning style," and the server stores this in a database.

[0460] 2. Creating an individualized learning curriculum

[0461] server

[0462] The server analyzes the stored user information and generates an optimal learning curriculum for each user. This curriculum is in line with the educational curriculum and is adapted to the user's cultural background and learning style. The generated digital learning materials are sent to the user's device.

[0463] Examples:

[0464] The server generates "math and science learning materials appropriate to the background of 12-year-old users from sub-Saharan Africa" ​​and sends them to the device.

[0465] 3. Learning progress and feedback

[0466] Terminal

[0467] The user works on the problems and inputs the answers into the terminal, which records the answer data and transmits it to the server in real time.

[0468] Examples:

[0469] When the user "solves an arithmetic problem and enters the answer," the device records the data sequentially and sends it to the server.

[0470] server

[0471] The server analyzes the answer data to determine the user's accuracy rate and answer trends. Based on the analysis results, it generates a new study plan and creates supplementary materials to strengthen weak points.

[0472] Examples:

[0473] The server "generates supplementary geometry learning materials for users who make many mistakes on geometry problems" and incorporates them into the next learning plan.

[0474] teacher

[0475] Teachers can check the user's learning progress on a dedicated screen and enter feedback as needed, which is then sent to the user's device via the server.

[0476] Examples:

[0477] The teacher "enters additional explanations for specific problems," which are then sent to the user's device in real time.

[0478] 4. Interactive and conversational lessons

[0479] Terminal

[0480] When a user asks a question by voice through a smart speaker, the device analyzes the voice and sends the question to the server.

[0481] server

[0482] The server analyzes the question, generates the necessary information and answers, and sends them to the device, which then relays the information to the user via voice.

[0483] Examples:

[0484] When a user "asks a question about the Pythagorean theorem, the server generates a detailed explanation and examples," which the smart speaker then relays to the user.

[0485] 5. Emotion recognition and support with emotion engine

[0486] Terminal

[0487] The device recognizes the emotions expressed by the user through facial expressions and tone of voice during learning and sends this data to the emotion engine.

[0488] Examples:

[0489] The device captures statements and facial expressions that indicate fatigue while the user is studying and sends them to the emotion engine.

[0490] Server (emotion engine)

[0491] The emotion engine analyzes the received data, determines the user's emotional state, and generates support and suggestions according to that state.

[0492] Examples:

[0493] The emotion engine "generates messages suggesting a break for users who feel tired" and notifies them through a smart speaker.

[0494] 6. Updating teaching materials

[0495] server

[0496] When textbook content or curriculum changes, the new information is automatically uploaded to the server, which instantly updates each user's learning plan.

[0497] Examples:

[0498] When new historical facts are added, the server updates the user's study plan based on that information and sends the new learning materials to the device.

[0499] 7. Optimizing feedback with an emotion engine

[0500] Server (emotion engine)

[0501] The emotion engine automatically generates feedback and support messages based on the user's emotional state, and the feedback is delivered via a smart speaker.

[0502] Examples:

[0503] The emotion engine "provides additional challenges and related information to interested users," which the smart speaker then relays audibly. Conversely, "if users are frustrated, the engine will suggest hints and easy solutions to the problem."

[0504] Example prompts for generative AI models

[0505] Below are some specific examples of prompts for the generative AI model.

[0506] Text format:

[0507] "Generate additional study materials to supplement the user's weak points based on the answer data of the problems the user has solved."

[0508] "How can I generate personalized learning curriculum that takes into account the cultural background of my users?"

[0509] "Use an emotion engine to generate feedback messages to improve user learning efficiency."

[0510] The above is a specific method for implementing the system of the present invention, which enables the provision of a learning curriculum optimized for each user, real-time feedback according to the learning progress, and appropriate support based on the user's emotional state.

[0511] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0512] Step 1: Enter and save user information

[0513] Input: The user enters information such as name, age, grade, ethnic and cultural background, learning style, and existing learning level from the terminal.

[0514] Operation: The terminal transmits the information entered by the user to the server in real time.

[0515] Output: The server stores the received user information in a database. The user information serves as the basis for subsequent curriculum generation and analysis.

[0516] Specific behavior:

[0517] The user enters information such as "from Sub-Saharan Africa, 12 years old, visual learning style," and the device records this and sends it to the server, which stores the information in a database.

[0518] Step 2: Create a personalized learning curriculum

[0519] Input: User information stored on the server (such as name, age, ethnic and cultural background, learning style, existing learning level, etc.).

[0520] How it works: The server analyzes user information and generates an optimal learning curriculum for each user. This analysis can be performed using a generative AI model.

[0521] Output: The generated learning curriculum is sent to the user's device as digital learning materials.

[0522] Specific behavior:

[0523] The server generates "math and science learning materials appropriate to the background of 12-year-old users from sub-Saharan Africa" ​​and sends them to the device.

[0524] Step 3: Record your learning progress and answer data

[0525] Input: The user answers the question and enters the answer into the terminal.

[0526] Operation: The terminal records the answer data entered by the user and transmits it to the server in real time.

[0527] Output: The server stores the received answer data.

[0528] Specific behavior:

[0529] When the user "solves an arithmetic problem and enters the answer," the device records the data sequentially and sends it to the server.

[0530] Step 4: Analyze the answer data and update the study plan

[0531] Input: Answer data stored on the server.

[0532] How it works: The server analyzes the answer data to determine the user's accuracy rate and answer trends. Based on the analysis results, it updates the study plan in real time and generates supplementary learning materials as needed.

[0533] Output: Send the new learning plan and supplementary materials to the user's device.

[0534] Specific behavior:

[0535] The server "generates supplementary geometry learning materials for users who make many mistakes on geometry problems" and incorporates them into the next learning plan.

[0536] Step 5: Teacher review and feedback on learning progress

[0537] Input: User learning progress and analysis results displayed on the educator-only screen.

[0538] How it works: The teacher checks the user's learning progress and trends in misunderstandings on a dedicated screen and provides feedback as needed.

[0539] Output: The feedback is sent to the user's device via the server.

[0540] Specific behavior:

[0541] The teacher "enters additional explanations for specific problems," which are then sent to the user's device in real time.

[0542] Step 6: Conduct interactive and dialogue-based lessons

[0543] Input: The user enters a question by voice through a smart speaker.

[0544] How it works: The device analyzes the voice and sends the question to the server. The server analyzes the question, generates the necessary information and answers, and sends them to the device.

[0545] Output: The smart speaker will verbally communicate the generated information to the user.

[0546] Specific behavior:

[0547] When a user "asks a question about the Pythagorean theorem, the server generates a detailed explanation and examples," which the smart speaker then relays to the user.

[0548] Step 7: Emotion recognition and support with the emotion engine

[0549] Input: Emotion data expressed by the user through facial expressions and vocal tones during training.

[0550] How it works: The device senses emotion data and sends it to the emotion engine, which analyzes the data and determines the user's emotional state.

[0551] Output: Support and suggestions based on the user's emotional state are generated and communicated through a smart speaker.

[0552] Specific behavior:

[0553] The emotion engine "generates messages suggesting a break for users who feel tired" and notifies them through a smart speaker.

[0554] Step 8: Update your materials

[0555] Input: New textbook content and curriculum information.

[0556] How it works: The server automatically uploads new information and updates each user's study plan.

[0557] Output: The updated lesson plan and new learning materials are sent to the user's device.

[0558] Specific behavior:

[0559] When new historical facts are added, the server updates the user's study plan based on that information and sends the new learning materials to the device.

[0560] Step 9: Optimizing feedback with an emotion engine

[0561] Input: The user's emotional state during learning.

[0562] How it works: The emotion engine generates appropriate feedback and support messages based on the user's emotional state.

[0563] Output: Optimized feedback and assistance messages are provided to the user through a smart speaker.

[0564] Specific behavior:

[0565] The emotion engine "provides additional challenges and related information to interested users," which the smart speaker then relays audibly. Conversely, "if users are frustrated, the engine will suggest hints and easy solutions to the problem."

[0566] (Application example 2)

[0567] 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."

[0568] Conventional learning systems have difficulty generating and updating individual curricula based on the characteristics and learning progress of each user, and also have difficulty providing feedback based on the user's emotional state. As a result, there are problems with reduced learning efficiency and motivation.

[0569] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for collecting specific user information and generating an individual curriculum based on the user information; means for recording and analyzing answer data of questions answered by the user; means for updating the plan in real time based on the analysis results; terminal means including a voice recognition device for providing interactive lessons; and means including an emotion engine for analyzing the user's emotional state and providing feedback based on the analysis results. This makes it possible to provide an individually optimized learning curriculum and effective feedback according to the user's emotions.

[0570] "Specific User Information" refers to a user's individual characteristics, such as the user's name, age, grade level, ethnic and cultural background, learning style, and existing learning level.

[0571] "Personalized Curriculum" refers to learning content and progression plans optimized based on specific user information.

[0572] "Answer data" refers to the answer information entered by the user in response to the study question.

[0573] "Analysis results" refers to the results of analyzing the user's learning situation and tendencies based on collected answer data.

[0574] "Real-time plan updating" refers to the process of reviewing and optimizing the learning progress plan at any time based on the analysis results.

[0575] "Interactive lessons" refers to a type of lesson in which users and systems exchange information two-way through audio and visual means to advance learning.

[0576] A "voice recognizer" refers to a device that analyzes a user's speech, recognizes its content, and generates a response.

[0577] "Emotional state" refers to a psychological state, such as interest, fatigue, or frustration, that can be inferred from a user's facial expression, tone of voice, or behavior.

[0578] An "emotion engine" refers to a software component that analyzes a user's emotional state and generates appropriate feedback and support messages based on that state.

[0579] The system of the present invention includes functions for collecting user information, generating an individual curriculum based on that information, recording and analyzing user answer data, and updating the plan in real time based on the analysis results. It also includes terminal means including a voice recognition device that provides interactive lessons, and an emotion engine that analyzes the user's emotional state and provides feedback.

[0580] System program generation

[0581] 1. User Information Collection:

[0582] The server receives information entered by the user through a smartphone or smart glasses, such as name, age, grade, learning style, and current learning level, and stores it in a database, allowing optimization according to the characteristics of each individual user.

[0583] 2. Generating personalized learning curriculum:

[0584] The server analyzes the collected user information and generates an optimal learning curriculum for the user, which is customized to meet the user's individual learning needs.

[0585] 3. Learning progress and feedback:

[0586] When a user answers a question, the device records the answer data and sends it to the server, which then analyzes the received answer data, evaluates the user's progress and learning trends, and updates the learning plan in real time, while providing appropriate feedback to the user.

[0587] 4. Providing interactive lessons:

[0588] The system allows two-way dialogue with users via a voice recognition device, and when a user asks a specific question, the system analyzes the question and provides appropriate answers and additional learning materials. This interactive lesson is conducted via a smart speaker or head-mounted display.

[0589] 5. Leveraging the Emotion Engine:

[0590] The device's camera and microphone detect the user's emotional state and send the data to the emotion engine, which then generates appropriate feedback and support messages based on the analysis results. For example, if the user feels fatigued while studying, the engine suggests taking a break.

[0591] Hardware and software used

[0592] Hardware

[0593] Smartphone

[0594] Smart Glasses

[0595] head-mounted display

[0596] smart speaker

[0597] software

[0598] Database Management Systems

[0599] Voice Recognition Software

[0600] Emotion Engine

[0601] Curriculum Generation Engine (CurriculumGenerator)

[0602] Specific examples

[0603] As a concrete example of collecting user data, consider a 12-year-old user who inputs information into the system, such as their name, age, ethnic background (e.g., from Sub-Saharan Africa), and visual learning style. The system uses this information to provide learning materials that are appropriate for the user's cultural background. For example, if the user uses a smart speaker to ask about "Pythagoras' Theorem," the system can provide an appropriate explanation and offer additional learning tasks.

[0604] Prompt Sentence Examples

[0605] "What support message should be generated if the user shows fatigue during learning?"

[0606] "If a 12-year-old user asks about the Pythagorean theorem, provide a concise explanation and generate additional tasks to further increase interest."

[0607] This will enable us to provide an effective learning experience even in areas where the educational environment is inadequate.

[0608] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0609] Step 1:

[0610] The server collects user information. The user inputs information such as name, age, grade, ethnic and cultural background, learning style, and current learning level through a smartphone or smart glasses. This information is sent by the device to the server and stored in a database. The input is user information, and the output is the saved user profile.

[0611] Step 2:

[0612] The server generates an individual learning curriculum based on the collected user information. This involves retrieving user information from a database and generating appropriate learning materials and curriculum based on that information. The input is a user profile, and the output is an individually optimized learning curriculum.

[0613] Step 3:

[0614] The device records the answer data of the questions answered by the user and sends it to the server. When the user answers a study question through the device, the question and answer data are temporarily saved on the device and periodically sent to the server. The input is the answer data, and the output is the study record sent to the server.

[0615] Step 4:

[0616] The server analyzes the received answer data. It uses a specific algorithm to analyze the user's accuracy rate and answer trends, and derives each user's strengths and weaknesses. The input is the answer data, and the output is the analysis results.

[0617] Step 5:

[0618] The server updates the study plan in real time based on the analysis results. It generates a new study plan that reflects the analysis results and sends it to the user's device. This new plan includes content that strengthens the user's weaknesses. The input is the analysis results, and the output is the updated study plan.

[0619] Step 6:

[0620] To provide interactive lessons, the terminal uses a voice recognition device to accept questions from users. When a user inputs a question by voice, the voice data is analyzed, converted into text data, and sent to the server. The input is voice data, and the output is text data.

[0621] Step 7:

[0622] The server generates answers to users' text-based questions. Using an AI model, it generates optimal answers and additional learning tasks for the user's questions and sends them to the device. The input is text data (user's question), and the output is the answer text and additional tasks.

[0623] Step 8:

[0624] The terminal communicates the answers and additional tasks received from the server to the user by voice. It uses speech synthesis software to convert text data into speech and provides it to the user. The input is the answer text and additional tasks, and the output is speech data.

[0625] Step 9:

[0626] The device senses the user's emotional state using a camera and microphone, collects data on the user's facial expressions and tone of voice, and sends it to the emotion engine. The input is facial expression data and tone of voice data, and the output is emotion data.

[0627] Step 10:

[0628] The server (emotion engine) analyzes the emotion data to determine the user's emotional state. Based on the analysis results, it generates appropriate feedback and support messages and sends them to the device. The input is emotion data, and the output is feedback and support messages.

[0629] Step 11:

[0630] The device notifies the user of feedback and support messages received from the server. Notifications are given by voice, screen display, vibration, etc. The input is the feedback and support messages, and the output is the user notification.

[0631] Through these steps, the system of the present invention is able to provide a learning curriculum tailored to the user's individual needs, manage learning progress in real time, and provide feedback tailored to the user's emotional state.

[0632] 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.

[0633] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by 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.

[0634] 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.

[0635] [Second embodiment]

[0636] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0637] 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.

[0638] 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).

[0639] 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.

[0640] 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.

[0641] 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).

[0642] 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.

[0643] 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.

[0644] 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.

[0645] 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.

[0646] 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.

[0647] 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."

[0648] A specific embodiment of the system according to the present invention and its processing flow will be described below.

[0649] The system has the functions of collecting specific user information and generating an individual learning curriculum based on that information, recording and analyzing the answers given by the user, updating the learning plan in real time based on the analysis results, and providing terminal functions including a smart speaker for providing interactive, dialogue-based lessons.

[0650] (Collection of user information and profile registration)

[0651] server

[0652] The server receives information entered by the user from the device and stores it in a database, such as the user's name, age, grade level, ethnic and cultural background, learning style, and existing learning level.

[0653] Specific examples

[0654] A 12-year-old user enters their name, age, ethnic background (e.g., from Sub-Saharan Africa), visual learning style, etc., and the server stores this information in a database.

[0655] (Generating personalized learning curriculum)

[0656] server

[0657] The server analyzes the stored user information and generates an optimal learning curriculum for each individual learner. This curriculum is created as digital learning materials based on the content of compulsory education and the user's cultural background.

[0658] Specific examples

[0659] The server generates mathematics and science learning materials incorporating local language and culture for 12-year-old users from sub-Saharan Africa and sends the materials to the users' devices.

[0660] (Learning progress and feedback)

[0661] Terminal

[0662] As the user works through the questions and answers, the terminal records the answers and sends them to the server.

[0663] server

[0664] The server analyzes the received answer data to determine the user's accuracy rate and answer trends. Based on the analysis results, it updates the study plan in real time and generates additional learning materials to fill in the user's weak points.

[0665] Specific examples

[0666] If a 12-year-old user solves math problems and finds that he gets 90% of the answers right but makes mistakes on some geometry-related questions, the server will generate supplementary geometry-related learning materials and incorporate them into his next learning plan.

[0667] teacher

[0668] Teachers can check the user's learning progress and misunderstandings on a dedicated screen and enter feedback as needed. The server sends this feedback to the user's device and notifies the user in real time.

[0669] (Interactive dialogue-based lessons)

[0670] Terminal

[0671] When a user speaks a question to a smart speaker, the device analyzes the voice and sends the question to the server.

[0672] server

[0673] The server analyzes the user's question, generates the necessary information and answers, and sends them to the device, which then relays the information to the user via voice.

[0674] Specific examples

[0675] When a user asks a question about the Pythagorean theorem, the device sends the question to the server, which responds with an appropriate explanation and example. The smart speaker then explains it to the user and offers additional questions to further deepen their understanding.

[0676] (Teaching material updates)

[0677] server

[0678] If the content of the textbook or the course changes, the new information is automatically uploaded to the server and immediately reflected in each user's learning plan.

[0679] Specific examples

[0680] When new historical facts are discovered and added to the educational curriculum, the server updates each user's learning plan based on this new information and sends new learning materials to the device.

[0681] In this way, this system enables smooth information exchange between the server, terminals, and users, providing an effective learning experience even in areas with inadequate educational environments.

[0682] The processing flow will be explained below.

[0683] Step 1:

[0684] User: The user installs and launches the app. On first launch, the user enters profile information such as name, age, grade level, ethnic and cultural background, learning style, and existing learning level.

[0685] Step 2:

[0686] Terminal: Collects profile information entered by the user and sends it to the server.

[0687] Step 3:

[0688] Server: The server stores the received user information in a database.

[0689] Step 4:

[0690] Server: The server analyzes the stored user information and generates an individualized learning curriculum based on the user's characteristics and learning style. The generated curriculum includes compulsory education content and supplementary materials tailored to the user's cultural background.

[0691] Step 5:

[0692] Server: Prepares the generated learning curriculum as digital learning materials and sends them to the user's device.

[0693] Step 6:

[0694] Terminal: Notifies the user of the received learning curriculum and displays it.

[0695] Step 7:

[0696] User: The user studies according to the provided learning curriculum. When solving a problem, the user inputs the answer.

[0697] Step 8:

[0698] Terminal: Records the user's answers and sends the data to the server.

[0699] Step 9:

[0700] Server: Analyzes the received answer data and determines the user's correct answer rate and answer trends.

[0701] Step 10:

[0702] Server: Updates the user's study plan in real time based on the analysis results, automatically generating additional learning materials and supplementary questions as needed.

[0703] Step 11:

[0704] Server: Sends the updated learning plan to the user's device and notifies them.

[0705] Step 12:

[0706] Device: Display the updated learning plan to the user.

[0707] Step 13:

[0708] Teachers: Teachers can check the user's learning progress and misunderstandings from a dedicated screen. If necessary, they can enter feedback.

[0709] Step 14:

[0710] Server: Receives teacher feedback and sends it to the user's device.

[0711] Step 15:

[0712] Device: Displays received teacher feedback to the user.

[0713] Step 16:

[0714] User: If the user has any questions while studying, they can ask them by voice via a smart speaker.

[0715] Step 17:

[0716] Terminal: Analyzes the user's voice question and sends the question to the server.

[0717] Step 18:

[0718] Server: Analyzes the question, generates the necessary information and answers, and sends them to the device.

[0719] Step 19:

[0720] Terminal: Provides users with answers to questions via a smart speaker.

[0721] Step 20:

[0722] Server: When the content of the educational curriculum or textbooks changes, the new information is uploaded to the database and each user's learning plan is automatically updated.

[0723] Step 21:

[0724] Server: Sends the updated learning plan to the user's device and notifies them.

[0725] Step 22:

[0726] Device: Display new learning materials and updated curriculum to users.

[0727] Example 1

[0728] 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."

[0729] Conventional educational systems have had the problem of being unable to respond to individual user needs, resulting in the provision of uniform teaching materials. Furthermore, it is difficult to provide effective learning support because it is not possible to grasp users' learning progress and level of understanding in real time and provide appropriate feedback. Furthermore, there is a lack of means to provide interactive, dialogue-based lessons, making it difficult to promote deep learning through two-way communication.

[0730] 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.

[0731] In this invention, the server includes means for collecting specific user information and generating an individual education plan based on the user information, means for recording and analyzing answer data to questions answered by the user, and means for updating the education plan in real time based on the analysis results, thereby providing a learning experience tailored to the needs of each individual user and promoting deep understanding through interactive lessons.

[0732] "Specific User Information" means individual information provided by a User, such as name, age, grade level, ethnic and cultural background, learning style, and existing learning level.

[0733] An "individualized education plan" is a curriculum and learning materials tailored to a user's individual needs and learning style, created based on the user's specific user information.

[0734] "Answer data" refers to a record of the answers given by users to questions or problems.

[0735] "Real-time updates" refers to instantly changing and adapting educational plans and teaching material content based on the results of analyzing answer data.

[0736] A "voice recognition device" is a device that recognizes a user's voice, analyzes it, and processes it as information.

[0737] "Analysis" refers to the process of identifying patterns and trends based on collected data and evaluating learning progress and level of understanding.

[0738] The "instructor-only screen" is an interface that allows instructors to check the user's learning progress and answer trends, and to input and provide feedback.

[0739] The present invention relates to a system that collects specific user information and generates an individualized educational plan based on that user information. This system provides a learning experience tailored to the individual needs of each user by smoothly exchanging information between a server, terminals, and users.

[0740] Collection of user information and profile registration

[0741] server

[0742] The server receives user information entered from the device and stores it in a database. This information includes the user's name, age, grade, ethnic and cultural background, learning method, existing learning level, etc. For example, if a 12-year-old user enters their name, age, ethnic background, visual learning style, etc., the server stores this information in a database.

[0743] Generate an Individualized Education Plan

[0744] server

[0745] The server analyzes the stored user information and uses a generative AI model to generate an individualized educational plan. This plan is created as digital learning materials based on the content of the compulsory education curriculum and the user's cultural background. For example, for a 12-year-old user from Sub-Saharan Africa, math and science learning materials incorporating the local language and culture are generated and sent to the user's device.

[0746] Learning progress and feedback

[0747] Terminal

[0748] When a user works on a problem and answers it, the device records the answer and sends it to the server.

[0749] server

[0750] The server analyzes the received answer data and determines the user's accuracy rate and answer trends. Based on the analysis results, the server updates the study plan in real time and generates additional learning materials to address the user's weaknesses. For example, if a user solves arithmetic problems and finds that they answered 90% of the questions correctly but made mistakes on some geometry-related questions, the server will generate supplementary geometry-related learning materials and incorporate them into the next study plan.

[0751] teacher

[0752] Teachers can check the user's learning progress and misunderstandings on a dedicated screen and enter feedback as needed. The server sends this feedback to the user's device and notifies the user in real time.

[0753] Interactive and conversational lessons

[0754] Terminal

[0755] When a user asks a question using a voice recognition device, the terminal analyzes the voice and sends the question to the server.

[0756] server

[0757] The server analyzes the user's question, generates the necessary information and answers, and sends them to the device. The speech recognizer then verbally conveys this information to the user. For example, if a user asks about the Pythagorean theorem, the device sends the question to the server, which returns an appropriate explanation and example problem. The speech recognizer then explains the problem to the user and provides additional problems to further deepen their understanding.

[0758] Updates to teaching materials

[0759] server

[0760] If the content of textbooks or courses changes, the new information is automatically uploaded to the server and immediately reflected in each user's educational plan. For example, if a new historical fact is discovered and added to the educational curriculum, the server updates each user's educational plan based on this new information and sends new learning materials to their device.

[0761] Prompt Sentence Examples

[0762] Curriculum generation: "Create digital learning materials that are appropriate for a 12-year-old from Sub-Saharan Africa. Please consider the user's visual learning style and incorporate local language and culture."

[0763] Interactive Lessons: "Explain the Pythagorean Theorem in detail and provide additional questions to help students understand."

[0764] As described above, this system has the ability to generate individual educational plans based on specific user information and update them in real time, while also providing interactive, dialogue-based education to ensure an effective learning experience.

[0765] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0766] Step 1:

[0767] The user enters information from the device

[0768] The user accesses a terminal and enters information into a form, such as name, age, grade, ethnic and cultural background, learning method, and existing learning level.

[0769] (Input) Data about the user's personal information and learning style.

[0770] (Output) The input data is temporarily saved on the device.

[0771] Step 2:

[0772] The device sends the information to the server

[0773] The terminal converts the information entered by the user into packets and transmits them to the server.

[0774] (Input) User information entered into the terminal.

[0775] (Output) Information is sent to the server.

[0776] Step 3:

[0777] The server receives the information and stores it in a database

[0778] The server analyzes the user information received from the terminal and stores it in a database.

[0779] (Input) User information sent from the terminal.

[0780] (Output) The parsed user information is saved in the database.

[0781] Step 4:

[0782] The server analyzes user information and generates an individualized education plan

[0783] The server analyzes the stored user information using a generative AI model to generate an individualized educational plan.

[0784] (Input) User information stored in the database.

[0785] (Output) The generated individualized education plan.

[0786] Step 5:

[0787] The server sends the educational plan to the device.

[0788] The server transmits the generated individual education plan to the terminal.

[0789] (Input) Generated individualized education plan.

[0790] (Output) The teaching plan is transferred to the terminal.

[0791] Step 6:

[0792] The user works through the questions and enters the answers

[0793] Users work on the digital learning materials provided on their terminals and input answers to the questions.

[0794] (Input) The question and the user's answer displayed on the terminal.

[0795] (Output) Answer data is temporarily saved on the device.

[0796] Step 7:

[0797] The device sends the answer to the server

[0798] The terminal transmits the saved answer data to the server.

[0799] (Input) User's answer data.

[0800] (Output) The answer data is sent to the server.

[0801] Step 8:

[0802] The server analyzes the answer data

[0803] The server analyzes the received answer data, determines the user's accuracy rate and answer trends, and processes the data using a generative AI model.

[0804] (Input) User's answer data.

[0805] (Output) Analysis results.

[0806] Step 9:

[0807] The server updates the educational plan in real time

[0808] Based on the analysis results, the server updates the study plan in real time and generates additional learning materials to fill in the user's weaknesses.

[0809] (Input) Analysis results.

[0810] (Output) Updated lesson plans and generated additional teaching materials.

[0811] Step 10:

[0812] The server sends the updated lesson plan and additional materials to the device.

[0813] The server sends updated lesson plans and additional teaching materials to the terminal.

[0814] (Input) Updated teaching plans and additional materials.

[0815] (Output) The lesson plan and additional materials are sent to the terminal.

[0816] Step 11:

[0817] User asks a question to the smart speaker

[0818] The user speaks a question using a voice recognition device.

[0819] (Input) The user's spoken question.

[0820] (Output) The device recognizes the voice data.

[0821] Step 12:

[0822] The device analyzes the voice and sends it to the server

[0823] The terminal analyzes the user's voice data as text data and sends it to the server.

[0824] (Input) Audio data.

[0825] (Output) The parsed text data is sent to the server.

[0826] Step 13:

[0827] The server analyzes the question and generates the answer

[0828] The server analyzes the received question and generates an appropriate answer using a generative AI model.

[0829] (Input) Parsed text data.

[0830] (Output) The generated answer.

[0831] Step 14:

[0832] The server sends the answer to the device

[0833] The server sends the generated answer to the terminal.

[0834] (Input) The generated answer.

[0835] (Output) The answer is sent to the device.

[0836] Step 15:

[0837] The device provides answers by voice

[0838] The terminal provides the received answer to the user through a voice recognition device.

[0839] (Input) The answer sent from the server.

[0840] (Output) The answer provided aloud.

[0841] (Application example 1)

[0842] 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."

[0843] Conventional skills training systems for factory operators have had difficulty quickly and effectively providing appropriate learning curricula tailored to individual skill levels and experience. Furthermore, they lacked the functionality to analyze learning progress in real time and provide feedback, making it extremely difficult to improve operators' skills. Furthermore, they lacked the functionality to provide interactive, dialogue-based lessons, making it difficult to immediately respond to operators' questions or problems.

[0844] 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.

[0845] In this invention, the server includes means for collecting specific user information and generating an individual learning curriculum based on the user information, means for recording and analyzing answer data for questions answered by the user, means for updating the learning plan in real time based on the analysis results, terminal means including a smart speaker for providing interactive dialogue-based lessons, means for generating a learning curriculum based on the skill level and past training data of the factory operator, means for analyzing the operator's learning progress in real time and providing feedback, means for generating additional learning materials based on the feedback, and means for responding to the learner's questions through the smart speaker. This makes it possible to provide effective training tailored to the individual skill level of the factory operator and enable rapid skill improvement through real-time progress analysis and feedback.

[0846] "Specific user information" is information necessary to identify a user and is data used to generate an individualized learning curriculum.

[0847] An "individualized learning curriculum" is a plan created based on specific user information and including learning content that is optimal for that user.

[0848] "Answer data" is data that records the results and trends of questions answered by users.

[0849] The "analysis results" are the results of analyzing the answer data, and are the basic information for updating the user's study plan.

[0850] A "smart speaker" is a device that interacts with users through a voice interface, providing information and instructions via voice.

[0851] "Terminal means" refers to the device that a user uses to interact with the system, including smart speakers, computers, tablets, etc.

[0852] "Factory operator" refers to an employee who operates and manages machinery and equipment at a manufacturing site.

[0853] "Skill level" is an indicator of an operator's technical proficiency in a particular task.

[0854] "Training data" refers to data that records the content and results of past training.

[0855] "Feedback" is information that provides evaluation and advice on the results of learning or work.

[0856] "Additional learning materials" are learning materials provided to supplement the learning based on the user's learning progress and analysis results.

[0857] A specific embodiment of a learning system for factory operators based on the present invention and its processing flow are described below. This system has the function of collecting specific user information and generating an individual learning curriculum based on that information. It also has the function of recording and analyzing answer data from questions answered by the user and updating the learning plan in real time based on the analysis results. Furthermore, the system features terminal means including a smart speaker for providing interactive, dialogue-based lessons.

[0858] Collection of user information and profile registration

[0859] server

[0860] The server receives information entered by the user from the terminal and stores it in a database. For example, the operator enters their name, age, skill level, past training data, etc.

[0861] Specific examples

[0862] A 30-year-old factory operator enters his or her name, age, entry-level skills, and past training data, and the server stores that information in a database.

[0863] Creating personalized learning curriculum

[0864] server

[0865] The server analyzes the stored user information and generates an optimal learning curriculum for each operator. The generated curriculum is created as digital learning materials based on past training data and skill level.

[0866] Specific examples

[0867] The server generates teaching materials for beginners, such as welding techniques and machine operation, for a 30-year-old beginner operator, and sends the materials to the user's terminal.

[0868] Learning progress and feedback

[0869] Terminal

[0870] As the user works through the questions and answers, the answers are recorded and sent to the server.

[0871] server

[0872] The server analyzes the answer data to determine the user's accuracy rate and answer trends. Based on the analysis results, the server updates the learning plan in real time and generates additional learning materials to fill in the operator's weaknesses.

[0873] Specific examples

[0874] If a 30-year-old operator solves machine operation problems and gets 90% correct, but makes mistakes on some questions related to changing settings, the server will generate supplementary learning materials related to changing settings and incorporate them into the next learning plan.

[0875] Interactive and conversational lessons

[0876] Terminal

[0877] When a user speaks a question to a smart speaker, the voice is analyzed and the question is sent to the server.

[0878] server

[0879] The server analyzes the user's question, generates the necessary information and answers, and sends them to the device, which then relays the information to the user via voice.

[0880] Specific examples

[0881] When a factory operator asks, "Please teach me basic welding techniques," the device sends the question to the server, which then returns appropriate explanations and training materials. The smart speaker then explains the information to the operator aloud and provides further training methods.

[0882] Hardware and Software

[0883] Server: Cloud server (e.g. AWS, Google Cloud)

[0884] Database: MySQL, PostgreSQL

[0885] AI analysis engine: GPT-4

[0886] Devices: Smart speakers (e.g., Amazon Echo, Google Home), factory robots, operator devices (PCs and tablets)

[0887] Examples and prompts

[0888] Specific examples

[0889] A 30-year-old novice operator needs to be trained in a new welding technique.

[0890] The operator asks the smart speaker, "Please tell me about the basic techniques of welding."

[0891] Prompt statement

[0892] User information: 'Name: Ichiro Tanaka, Age: 30, Skill level: Beginner, Past training data: []'. Please generate a learning curriculum appropriate for this user.

[0893] Question: 'Please tell me about the basic techniques of welding'. Please provide a suitable answer.

[0894] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0895] Step 1: Enter and submit user information

[0896] The user inputs information such as their name, age, skill level, and past training data from the terminal, and this input data is sent from the terminal to the server.

[0897] concrete action

[0898] Input: Name, age, skill level, past training data

[0899] Data processing: Convert each item into JSON format

[0900] Output: User information sent to the server

[0901] Example: Name: Yamada Taro, Age: 35, Skill Level: Intermediate, Training Data: []

[0902] Step 2: Save user information

[0903] The server stores the received user information in a database, which is then used to generate a personalized learning curriculum.

[0904] concrete action

[0905] Input: User information sent from the device (JSON format)

[0906] Data processing: Converting data into SQL statements for saving to the database

[0907] Output: User information stored in the database

[0908] Destination: Database (MySQL, PostgreSQL)

[0909] Step 3: Create a personalized learning curriculum

[0910] The server analyzes the stored user information and generates an individual learning curriculum using a generative AI model (GPT-4). The generated curriculum is then sent to the user's device as digital learning materials.

[0911] concrete action

[0912] Input: User information retrieved from the database

[0913] Data processing: Prompt generation and input to GPT-4

[0914] Output: Personalized learning curriculum

[0915] Example prompt: "User information: {'Name': 'Yamada Taro', 'Age': 35, 'Skill level': 'Intermediate', 'Training data': []}. Please generate a learning curriculum appropriate for this user."

[0916] AI used: GPT-4

[0917] Send the generated curriculum to your device

[0918] Step 4: Record your learning progress

[0919] When a user works on a problem and answers it on the terminal, the answer data is recorded by the terminal and transmitted to the server.

[0920] concrete action

[0921] Input: User's answer data

[0922] Data processing: Recording correct and incorrect answers for each answer and generating data for trend analysis

[0923] Output: Answer data sent to the server

[0924] Example: Question ID: 123, Answer: "A", Correct Answer: true

[0925] Step 5: Analyze the answer data and provide feedback

[0926] The server analyzes the received answer data to determine the accuracy rate and answer trends. Based on the analysis results, it updates the learning plan in real time and generates additional learning materials to fill in the operator's weaknesses.

[0927] concrete action

[0928] Input: Answer data sent from the device

[0929] Data processing: Correct answer rate calculation and trend analysis

[0930] Output: Updated learning plan and feedback

[0931] AI used: GPT-4

[0932] Example prompt for generating additional learning materials: "Answer data: [{'Question ID': 123, 'Answer': 'A', 'Correct Answer': true}]. Analyze learning progress and provide feedback.

[0933] Step 6: Interactive and interactive lessons

[0934] When a user speaks a question to a smart speaker, the voice data is analyzed and the question is sent to the server. The server analyzes the question, generates the necessary information and answer, and sends it to the device. The smart speaker then conveys that information by voice.

[0935] concrete action

[0936] Input: A spoken question from the user

[0937] Data processing: speech recognition and text conversion, answer generation using GPT-4

[0938] Output: A spoken response to the user

[0939] AI used: GPT-4

[0940] Example prompt: "Question: 'Tell me about basic welding techniques.' Please provide an appropriate answer."

[0941] Example speech output: "The basic technique of welding is..."

[0942] Step 7: Distribute generated materials and update learning plans

[0943] The server sends the generated additional learning materials and updated study plans to the user's device, and the user continues studying based on the new study plans.

[0944] concrete action

[0945] Input: Updated study plans and additional materials

[0946] Data processing: Converting data to send to the user's device

[0947] Output: Push notifications and delivery of educational materials to users' devices

[0948] Communication method: Data transmission via the Internet

[0949] Example delivery: "New learning plans are available. Check them out in the next session."

[0950] As described above, the system provides factory operators with individual learning curricula, performs real-time progress analysis and feedback, and supports efficient skill development through interactive, dialogue-based lessons.

[0951] 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.

[0952] A specific embodiment of the system according to the present invention and its processing flow will be described below.

[0953] The system has the functions of collecting specific user information and generating an individual learning curriculum based on that information, recording and analyzing the answers given by the user to questions, updating the learning plan in real time based on the analysis results, and providing device functions including a smart speaker that provides interactive lessons.It also has an emotion engine that recognizes the user's emotions.

[0954] (Collection of user information and profile registration)

[0955] server

[0956] The server receives information entered by the user from the device and stores it in a database, such as the user's name, age, grade level, ethnic and cultural background, learning style, and existing learning level.

[0957] Specific examples

[0958] A 12-year-old user enters their name, age, ethnic background (e.g., from Sub-Saharan Africa), visual learning style, etc., and the server stores this information in a database.

[0959] (Generating personalized learning curriculum)

[0960] server

[0961] The server analyzes the stored user information and generates an optimal learning curriculum for each individual learner. This curriculum is created as digital learning materials based on the content of compulsory education and the user's cultural background.

[0962] Specific examples

[0963] The server generates mathematics and science learning materials incorporating local language and culture for 12-year-old users from sub-Saharan Africa and sends the materials to the users' devices.

[0964] (Learning progress and feedback)

[0965] Terminal

[0966] As the user works through the questions and answers, the terminal records the answers and sends them to the server.

[0967] server

[0968] The server analyzes the received answer data to determine the user's accuracy rate and answer trends. Based on the analysis results, it updates the study plan in real time and generates additional learning materials to fill in the user's weak points.

[0969] Specific examples

[0970] If a 12-year-old user solves math problems and finds that he gets 90% of the answers right but makes mistakes on some geometry-related questions, the server will generate supplementary geometry-related learning materials and incorporate them into his next learning plan.

[0971] teacher

[0972] Teachers can check the user's learning progress and misunderstandings on a dedicated screen and enter feedback as needed. The server sends this feedback to the user's device and notifies the user in real time.

[0973] (Interactive dialogue-based lessons)

[0974] Terminal

[0975] When a user speaks a question to a smart speaker, the device analyzes the voice and sends the question to the server.

[0976] server

[0977] The server analyzes the user's question, generates the necessary information and answers, and sends them to the device, which then relays the information to the user via voice.

[0978] Specific examples

[0979] When a user asks a question about the Pythagorean theorem, the device sends the question to the server, which responds with an appropriate explanation and example. The smart speaker then explains it to the user and offers additional questions to further deepen their understanding.

[0980] (Utilizing emotion engines)

[0981] Terminal

[0982] The device detects the emotions expressed by the user through facial expressions and tone of voice while learning, and sends this data to the emotion engine.

[0983] Server (emotion engine)

[0984] The emotion engine analyzes the data sent from the terminal and determines the user's emotional state (e.g., interest, fatigue, frustration, etc.).

[0985] Specific examples

[0986] If the user shows signs of fatigue while studying, the emotion engine will analyze this information and suggest that the user take a break, a suggestion that will be delivered audibly through the smart speaker.

[0987] (Teaching material updates)

[0988] server

[0989] If the content of the textbook or the course changes, the new information is automatically uploaded to the server and immediately reflected in each user's learning plan.

[0990] Specific examples

[0991] When new historical facts are discovered and added to the educational curriculum, the server updates each user's learning plan based on this new information and sends new learning materials to the device.

[0992] (Feedback optimization using emotion engine)

[0993] Server (emotion engine)

[0994] The emotion engine automatically generates feedback and support messages based on the user's emotional state, which are delivered via a smart speaker with the goal of improving the user's learning efficiency.

[0995] Specific examples

[0996] If the user is interested, the emotion engine will provide additional challenges or relevant information to keep them engaged, or if they are frustrated, it will suggest hints or quick solutions to their problems.

[0997] In this way, this system achieves smooth information exchange between the server, terminals, and users, providing an effective learning experience even in areas with inadequate educational environments. The addition of an emotion engine provides optimal support according to the user's emotional state, improving learning efficiency and motivation.

[0998] The processing flow will be explained below.

[0999] Step 1:

[1000] User: The user installs and launches the app. On first launch, the user enters profile information such as name, age, grade level, ethnic and cultural background, learning style, and existing learning level.

[1001] Step 2:

[1002] Terminal: Collects profile information entered by the user and sends it to the server.

[1003] Step 3:

[1004] Server: The server stores the received user information in a database.

[1005] Step 4:

[1006] Server: The server analyzes the stored user information and generates an individualized learning curriculum based on the user's characteristics and learning style. The generated curriculum includes the content of the compulsory education curriculum and supplementary materials tailored to the user's cultural background.

[1007] Step 5:

[1008] Server: Prepares the generated learning curriculum as digital learning materials and sends them to the user's device.

[1009] Step 6:

[1010] Terminal: Notifies the user of the received learning curriculum and displays it.

[1011] Step 7:

[1012] User: The user studies according to the provided learning curriculum. When solving a problem, the user inputs the answer.

[1013] Step 8:

[1014] Terminal: Records the user's answers and sends the data to the server.

[1015] Step 9:

[1016] Server: Analyzes the received answer data and determines the user's correct answer rate and answer trends.

[1017] Step 10:

[1018] Server: Updates the user's study plan in real time based on the analysis results, automatically generating additional learning materials and supplementary questions as needed.

[1019] Step 11:

[1020] Server: Sends the updated learning plan to the user's device and notifies them.

[1021] Step 12:

[1022] Device: Display the updated learning plan to the user.

[1023] Step 13:

[1024] Teacher: The teacher can check the user's learning progress and misunderstandings from a dedicated screen. If necessary, the teacher can enter feedback.

[1025] Step 14:

[1026] Server: Receives teacher feedback and sends it to the user's device.

[1027] Step 15:

[1028] Device: Displays received teacher feedback to the user.

[1029] Step 16:

[1030] User: If the user has any questions while studying, they can ask them by voice via a smart speaker.

[1031] Step 17:

[1032] Terminal: Analyzes the user's voice question and sends the question to the server.

[1033] Step 18:

[1034] Server: Analyzes the question, generates the necessary information and answers, and sends them to the device.

[1035] Step 19:

[1036] Terminal: Provides users with answers to questions via a smart speaker.

[1037] Step 20:

[1038] Terminal: Collects emotional information from the user's voice and facial expressions and sends that data to the server.

[1039] Step 21:

[1040] Server (emotion engine): Analyzes the emotion information sent from the device and determines the user's emotional state (e.g., interest, fatigue, frustration, etc.).

[1041] Step 22:

[1042] Server (Emotion Engine): Adjusts learning curriculum and feedback based on the user's emotional state. For example, it suggests a break if the user is tired, or provides additional relevant information if the user shows interest.

[1043] Step 23:

[1044] Server (emotion engine): Sends automatically generated feedback and support messages to the device.

[1045] Step 24:

[1046] Terminal: Provides users with feedback and support messages from the emotion engine via a smart speaker.

[1047] Step 25:

[1048] Server: When the content of the educational curriculum or textbooks changes, the new information is uploaded to the database and each user's learning plan is automatically updated.

[1049] Step 26:

[1050] Server: Sends the updated learning plan to the user's device and notifies them.

[1051] Step 27:

[1052] Device: Display new learning materials and updated curriculum to users.

[1053] Example 2

[1054] 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."

[1055] Previous educational systems lacked detailed learning support tailored to individual users' cultural backgrounds and learning styles, and the lack of real-time feedback limited the effectiveness of learning. Furthermore, the lack of a mechanism for reflecting users' emotions in the learning process made it difficult to improve learning efficiency and motivation.

[1056] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for collecting specific user information and generating an individual learning curriculum based on the user information; means for recording and analyzing answer data of questions answered by the user; means for updating the learning plan in real time based on the analysis results; voice communication terminal means for providing interactive dialogue-based lessons; and means including an emotion engine for recognizing user emotions and analyzing emotion data to provide learning support. This makes it possible to provide a learning curriculum optimized for each user, real-time feedback according to learning progress, and appropriate support based on the user's emotional state.

[1057] "Specific User Information" is information provided by a user regarding their name, age, grade level, ethnic and cultural background, learning style, and existing learning level.

[1058] An "individual learning curriculum" is a collection of educational content and learning materials optimized for each user based on collected user information.

[1059] "Answer data" is a record of the answers to questions that the user answered while studying.

[1060] "Updating in real time" means immediately reviewing the learning plan based on the progress of learning and analysis results, and providing instruction based on the latest information.

[1061] An "interactive dialogue-based lesson" is a two-way lesson format in which users ask and answer questions via voice communication terminals, and the system provides appropriate feedback and explanations.

[1062] "Voice communication terminal" refers to a device that enables voice communication, specifically a smart speaker.

[1063] The "emotion engine" is part of a system that analyzes the user's emotional state and provides learning support and feedback based on the results of that analysis.

[1064] The "Educator-only screen" is an interface that allows educators to view and manage learning status and analysis results.

[1065] The present invention is a system that collects specific user information and generates an individual learning curriculum based on that user information. This system is realized through the exchange of information between a server, a terminal, and a user.

[1066] 1. Collection of User Information and Profile Registration

[1067] server

[1068] The server receives information entered by the user from their device and stores it in a database. The information entered by the user includes name, age, grade, ethnic and cultural background, learning style, and existing learning level. This information serves as the basis for generating a learning curriculum optimized for each user.

[1069] Examples:

[1070] Users enter information such as "from Sub-Saharan Africa, 12 years old, visual learning style," and the server stores this in a database.

[1071] 2. Creating an individualized learning curriculum

[1072] server

[1073] The server analyzes the stored user information and generates an optimal learning curriculum for each user. This curriculum is in line with the educational curriculum and is adapted to the user's cultural background and learning style. The generated digital learning materials are sent to the user's device.

[1074] Examples:

[1075] The server generates "math and science learning materials appropriate to the background of 12-year-old users from sub-Saharan Africa" ​​and sends them to the device.

[1076] 3. Learning progress and feedback

[1077] Terminal

[1078] The user works on the problems and inputs the answers into the terminal, which records the answer data and transmits it to the server in real time.

[1079] Examples:

[1080] When the user "solves an arithmetic problem and enters the answer," the device records the data sequentially and sends it to the server.

[1081] server

[1082] The server analyzes the answer data to determine the user's accuracy rate and answer trends. Based on the analysis results, it generates a new study plan and creates supplementary materials to strengthen weak points.

[1083] Examples:

[1084] The server "generates supplementary geometry learning materials for users who make many mistakes on geometry problems" and incorporates them into the next learning plan.

[1085] teacher

[1086] Teachers can check the user's learning progress on a dedicated screen and enter feedback as needed, which is then sent to the user's device via the server.

[1087] Examples:

[1088] The teacher "enters additional explanations for specific problems," which are then sent to the user's device in real time.

[1089] 4. Interactive and conversational lessons

[1090] Terminal

[1091] When a user asks a question by voice through a smart speaker, the device analyzes the voice and sends the question to the server.

[1092] server

[1093] The server analyzes the question, generates the necessary information and answers, and sends them to the device, which then relays the information to the user via voice.

[1094] Examples:

[1095] When a user "asks a question about the Pythagorean theorem, the server generates a detailed explanation and examples," which the smart speaker then relays to the user.

[1096] 5. Emotion recognition and support with emotion engine

[1097] Terminal

[1098] The device recognizes the emotions expressed by the user through facial expressions and tone of voice during learning and sends this data to the emotion engine.

[1099] Examples:

[1100] The device captures statements and facial expressions that indicate fatigue while the user is studying and sends them to the emotion engine.

[1101] Server (emotion engine)

[1102] The emotion engine analyzes the received data, determines the user's emotional state, and generates support and suggestions according to that state.

[1103] Examples:

[1104] The emotion engine "generates messages suggesting a break for users who feel tired" and notifies them through a smart speaker.

[1105] 6. Updating teaching materials

[1106] server

[1107] When textbook content or curriculum changes, the new information is automatically uploaded to the server, which instantly updates each user's learning plan.

[1108] Examples:

[1109] When new historical facts are added, the server updates the user's study plan based on that information and sends the new learning materials to the device.

[1110] 7. Optimizing feedback with an emotion engine

[1111] Server (emotion engine)

[1112] The emotion engine automatically generates feedback and support messages based on the user's emotional state, and the feedback is delivered via a smart speaker.

[1113] Examples:

[1114] The emotion engine "provides additional challenges and related information to interested users," which the smart speaker then relays audibly. Conversely, "if users are frustrated, the engine will suggest hints and easy solutions to the problem."

[1115] Example prompts for generative AI models

[1116] Below are some specific examples of prompts for the generative AI model.

[1117] Text format:

[1118] "Generate additional study materials to supplement the user's weak points based on the answer data of the problems the user has solved."

[1119] "How can I generate personalized learning curriculum that takes into account the cultural background of my users?"

[1120] "Use an emotion engine to generate feedback messages to improve user learning efficiency."

[1121] The above is a specific method for implementing the system of the present invention, which enables the provision of a learning curriculum optimized for each user, real-time feedback according to the learning progress, and appropriate support based on the user's emotional state.

[1122] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1123] Step 1: Enter and save user information

[1124] Input: The user enters information such as name, age, grade, ethnic and cultural background, learning style, and existing learning level from the terminal.

[1125] Operation: The terminal transmits the information entered by the user to the server in real time.

[1126] Output: The server stores the received user information in a database. The user information serves as the basis for subsequent curriculum generation and analysis.

[1127] Specific behavior:

[1128] The user enters information such as "from Sub-Saharan Africa, 12 years old, visual learning style," and the device records this and sends it to the server, which stores the information in a database.

[1129] Step 2: Create a personalized learning curriculum

[1130] Input: User information stored on the server (such as name, age, ethnic and cultural background, learning style, existing learning level, etc.).

[1131] How it works: The server analyzes user information and generates an optimal learning curriculum for each user. This analysis can be performed using a generative AI model.

[1132] Output: The generated learning curriculum is sent to the user's device as digital learning materials.

[1133] Specific behavior:

[1134] The server generates "math and science learning materials appropriate to the background of 12-year-old users from sub-Saharan Africa" ​​and sends them to the device.

[1135] Step 3: Record your learning progress and answer data

[1136] Input: The user answers the question and enters the answer into the terminal.

[1137] Operation: The terminal records the answer data entered by the user and transmits it to the server in real time.

[1138] Output: The server stores the received answer data.

[1139] Specific behavior:

[1140] When the user "solves an arithmetic problem and enters the answer," the device records the data sequentially and sends it to the server.

[1141] Step 4: Analyze the answer data and update the study plan

[1142] Input: Answer data stored on the server.

[1143] How it works: The server analyzes the answer data to determine the user's accuracy rate and answer trends. Based on the analysis results, it updates the study plan in real time and generates supplementary learning materials as needed.

[1144] Output: Send the new learning plan and supplementary materials to the user's device.

[1145] Specific behavior:

[1146] The server "generates supplementary geometry learning materials for users who make many mistakes on geometry problems" and incorporates them into the next learning plan.

[1147] Step 5: Teacher review and feedback on learning progress

[1148] Input: User learning progress and analysis results displayed on the educator-only screen.

[1149] How it works: The teacher checks the user's learning progress and trends in misunderstandings on a dedicated screen and provides feedback as needed.

[1150] Output: The feedback is sent to the user's device via the server.

[1151] Specific behavior:

[1152] The teacher "enters additional explanations for specific problems," which are then sent to the user's device in real time.

[1153] Step 6: Conduct interactive and dialogue-based lessons

[1154] Input: The user enters a question by voice through a smart speaker.

[1155] How it works: The device analyzes the voice and sends the question to the server. The server analyzes the question, generates the necessary information and answers, and sends them to the device.

[1156] Output: The smart speaker will verbally communicate the generated information to the user.

[1157] Specific behavior:

[1158] When a user "asks a question about the Pythagorean theorem, the server generates a detailed explanation and examples," which the smart speaker then relays to the user.

[1159] Step 7: Emotion recognition and support with the emotion engine

[1160] Input: Emotion data expressed by the user through facial expressions and vocal tones during training.

[1161] How it works: The device senses emotion data and sends it to the emotion engine, which analyzes the data and determines the user's emotional state.

[1162] Output: Support and suggestions based on the user's emotional state are generated and communicated through a smart speaker.

[1163] Specific behavior:

[1164] The emotion engine "generates messages suggesting a break for users who feel tired" and notifies them through a smart speaker.

[1165] Step 8: Update your materials

[1166] Input: New textbook content and curriculum information.

[1167] How it works: The server automatically uploads new information and updates each user's study plan.

[1168] Output: The updated lesson plan and new learning materials are sent to the user's device.

[1169] Specific behavior:

[1170] When new historical facts are added, the server updates the user's study plan based on that information and sends the new learning materials to the device.

[1171] Step 9: Optimizing feedback with an emotion engine

[1172] Input: The user's emotional state during learning.

[1173] How it works: The emotion engine generates appropriate feedback and support messages based on the user's emotional state.

[1174] Output: Optimized feedback and assistance messages are provided to the user through a smart speaker.

[1175] Specific behavior:

[1176] The emotion engine "provides additional challenges and related information to interested users," which the smart speaker then relays audibly. Conversely, "if users are frustrated, the engine will suggest hints and easy solutions to the problem."

[1177] (Application example 2)

[1178] 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."

[1179] Conventional learning systems have difficulty generating and updating individual curricula based on the characteristics and learning progress of each user, and also have difficulty providing feedback based on the user's emotional state. As a result, there are problems with reduced learning efficiency and motivation.

[1180] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for collecting specific user information and generating an individual curriculum based on the user information; means for recording and analyzing answer data of questions answered by the user; means for updating the plan in real time based on the analysis results; terminal means including a voice recognition device for providing interactive lessons; and means including an emotion engine for analyzing the user's emotional state and providing feedback based on the analysis results. This makes it possible to provide an individually optimized learning curriculum and effective feedback according to the user's emotions.

[1181] "Specific User Information" refers to a user's individual characteristics, such as the user's name, age, grade level, ethnic and cultural background, learning style, and existing learning level.

[1182] "Personalized Curriculum" refers to learning content and progression plans optimized based on specific user information.

[1183] "Answer data" refers to the answer information entered by the user in response to the study question.

[1184] "Analysis results" refers to the results of analyzing the user's learning situation and tendencies based on collected answer data.

[1185] "Real-time plan updating" refers to the process of reviewing and optimizing the learning progress plan at any time based on the analysis results.

[1186] "Interactive lessons" refers to a type of lesson in which users and systems exchange information two-way through audio and visual means to advance learning.

[1187] A "voice recognizer" refers to a device that analyzes a user's speech, recognizes its content, and generates a response.

[1188] "Emotional state" refers to a psychological state, such as interest, fatigue, or frustration, that can be inferred from a user's facial expression, tone of voice, or behavior.

[1189] An "emotion engine" refers to a software component that analyzes a user's emotional state and generates appropriate feedback and support messages based on that state.

[1190] The system of the present invention includes functions for collecting user information, generating an individual curriculum based on that information, recording and analyzing user answer data, and updating the plan in real time based on the analysis results. It also includes terminal means including a voice recognition device that provides interactive lessons, and an emotion engine that analyzes the user's emotional state and provides feedback.

[1191] System program generation

[1192] 1. User Information Collection:

[1193] The server receives information entered by the user through a smartphone or smart glasses, such as name, age, grade, learning style, and current learning level, and stores it in a database, allowing optimization according to the characteristics of each individual user.

[1194] 2. Generating personalized learning curriculum:

[1195] The server analyzes the collected user information and generates an optimal learning curriculum for the user, which is customized to meet the user's individual learning needs.

[1196] 3. Learning progress and feedback:

[1197] When a user answers a question, the device records the answer data and sends it to the server, which then analyzes the received answer data, evaluates the user's progress and learning trends, and updates the learning plan in real time, while providing appropriate feedback to the user.

[1198] 4. Providing interactive lessons:

[1199] The system allows two-way dialogue with users via a voice recognition device, and when a user asks a specific question, the system analyzes the question and provides appropriate answers and additional learning materials. This interactive lesson is conducted via a smart speaker or head-mounted display.

[1200] 5. Leveraging the Emotion Engine:

[1201] The device's camera and microphone detect the user's emotional state and send the data to the emotion engine, which then generates appropriate feedback and support messages based on the analysis results. For example, if the user feels fatigued while studying, the engine suggests taking a break.

[1202] Hardware and software used

[1203] Hardware

[1204] Smartphone

[1205] Smart Glasses

[1206] head-mounted display

[1207] smart speaker

[1208] software

[1209] Database Management Systems

[1210] Voice Recognition Software

[1211] Emotion Engine

[1212] Curriculum Generation Engine (CurriculumGenerator)

[1213] Specific examples

[1214] As a concrete example of collecting user data, consider a 12-year-old user who inputs information into the system, such as their name, age, ethnic background (e.g., from Sub-Saharan Africa), and visual learning style. The system uses this information to provide learning materials that are appropriate for the user's cultural background. For example, if the user uses a smart speaker to ask about "Pythagoras' Theorem," the system can provide an appropriate explanation and offer additional learning tasks.

[1215] Prompt Sentence Examples

[1216] "What support message should be generated if the user shows fatigue during learning?"

[1217] "If a 12-year-old user asks about the Pythagorean theorem, provide a concise explanation and generate additional tasks to further increase interest."

[1218] This will enable us to provide an effective learning experience even in areas where the educational environment is inadequate.

[1219] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1220] Step 1:

[1221] The server collects user information. The user inputs information such as name, age, grade, ethnic and cultural background, learning style, and current learning level through a smartphone or smart glasses. This information is sent by the device to the server and stored in a database. The input is user information, and the output is the saved user profile.

[1222] Step 2:

[1223] The server generates an individual learning curriculum based on the collected user information. This involves retrieving user information from a database and generating appropriate learning materials and curriculum based on that information. The input is a user profile, and the output is an individually optimized learning curriculum.

[1224] Step 3:

[1225] The device records the answer data of the questions answered by the user and sends it to the server. When the user answers a study question through the device, the question and answer data are temporarily saved on the device and periodically sent to the server. The input is the answer data, and the output is the study record sent to the server.

[1226] Step 4:

[1227] The server analyzes the received answer data. It uses a specific algorithm to analyze the user's accuracy rate and answer trends, and derives each user's strengths and weaknesses. The input is the answer data, and the output is the analysis results.

[1228] Step 5:

[1229] The server updates the study plan in real time based on the analysis results. It generates a new study plan that reflects the analysis results and sends it to the user's device. This new plan includes content that strengthens the user's weaknesses. The input is the analysis results, and the output is the updated study plan.

[1230] Step 6:

[1231] To provide interactive lessons, the terminal uses a voice recognition device to accept questions from users. When a user inputs a question by voice, the voice data is analyzed, converted into text data, and sent to the server. The input is voice data, and the output is text data.

[1232] Step 7:

[1233] The server generates answers to users' text-based questions. Using an AI model, it generates optimal answers and additional learning tasks for the user's questions and sends them to the device. The input is text data (user's question), and the output is the answer text and additional tasks.

[1234] Step 8:

[1235] The terminal communicates the answers and additional tasks received from the server to the user by voice. It uses speech synthesis software to convert text data into speech and provides it to the user. The input is the answer text and additional tasks, and the output is speech data.

[1236] Step 9:

[1237] The device senses the user's emotional state using a camera and microphone, collects data on the user's facial expressions and tone of voice, and sends it to the emotion engine. The input is facial expression data and tone of voice data, and the output is emotion data.

[1238] Step 10:

[1239] The server (emotion engine) analyzes the emotion data to determine the user's emotional state. Based on the analysis results, it generates appropriate feedback and support messages and sends them to the device. The input is emotion data, and the output is feedback and support messages.

[1240] Step 11:

[1241] The device notifies the user of feedback and support messages received from the server. Notifications are given by voice, screen display, vibration, etc. The input is the feedback and support messages, and the output is the user notification.

[1242] Through these steps, the system of the present invention is able to provide a learning curriculum tailored to the user's individual needs, manage learning progress in real time, and provide feedback tailored to the user's emotional state.

[1243] 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.

[1244] 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.

[1245] 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.

[1246] [Third embodiment]

[1247] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1248] 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.

[1249] 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).

[1250] 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.

[1251] 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.

[1252] 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).

[1253] 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.

[1254] 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.

[1255] 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.

[1256] 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.

[1257] 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.

[1258] 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."

[1259] A specific embodiment of the system according to the present invention and its processing flow will be described below.

[1260] The system has the functions of collecting specific user information and generating an individual learning curriculum based on that information, recording and analyzing the answers given by the user, updating the learning plan in real time based on the analysis results, and providing terminal functions including a smart speaker for providing interactive, dialogue-based lessons.

[1261] (Collection of user information and profile registration)

[1262] server

[1263] The server receives information entered by the user from the device and stores it in a database, such as the user's name, age, grade level, ethnic and cultural background, learning style, and existing learning level.

[1264] Specific examples

[1265] A 12-year-old user enters their name, age, ethnic background (e.g., from Sub-Saharan Africa), visual learning style, etc., and the server stores this information in a database.

[1266] (Generating personalized learning curriculum)

[1267] server

[1268] The server analyzes the stored user information and generates an optimal learning curriculum for each individual learner. This curriculum is created as digital learning materials based on the content of compulsory education and the user's cultural background.

[1269] Specific examples

[1270] The server generates mathematics and science learning materials incorporating local language and culture for 12-year-old users from sub-Saharan Africa and sends the materials to the users' devices.

[1271] (Learning progress and feedback)

[1272] Terminal

[1273] As the user works through the questions and answers, the terminal records the answers and sends them to the server.

[1274] server

[1275] The server analyzes the received answer data to determine the user's accuracy rate and answer trends. Based on the analysis results, it updates the study plan in real time and generates additional learning materials to fill in the user's weak points.

[1276] Specific examples

[1277] If a 12-year-old user solves math problems and finds that he gets 90% of the answers right but makes mistakes on some geometry-related questions, the server will generate supplementary geometry-related learning materials and incorporate them into his next learning plan.

[1278] teacher

[1279] Teachers can check the user's learning progress and misunderstandings on a dedicated screen and enter feedback as needed. The server sends this feedback to the user's device and notifies the user in real time.

[1280] (Interactive dialogue-based lessons)

[1281] Terminal

[1282] When a user speaks a question to a smart speaker, the device analyzes the voice and sends the question to the server.

[1283] server

[1284] The server analyzes the user's question, generates the necessary information and answers, and sends them to the device, which then relays the information to the user via voice.

[1285] Specific examples

[1286] When a user asks a question about the Pythagorean theorem, the device sends the question to the server, which responds with an appropriate explanation and example. The smart speaker then explains it to the user and offers additional questions to further deepen their understanding.

[1287] (Teaching material updates)

[1288] server

[1289] If the content of the textbook or the course changes, the new information is automatically uploaded to the server and immediately reflected in each user's learning plan.

[1290] Specific examples

[1291] When new historical facts are discovered and added to the educational curriculum, the server updates each user's learning plan based on this new information and sends new learning materials to the device.

[1292] In this way, this system enables smooth information exchange between the server, terminals, and users, providing an effective learning experience even in areas with inadequate educational environments.

[1293] The processing flow will be explained below.

[1294] Step 1:

[1295] User: The user installs and launches the app. On first launch, the user enters profile information such as name, age, grade level, ethnic and cultural background, learning style, and existing learning level.

[1296] Step 2:

[1297] Terminal: Collects profile information entered by the user and sends it to the server.

[1298] Step 3:

[1299] Server: The server stores the received user information in a database.

[1300] Step 4:

[1301] Server: The server analyzes the stored user information and generates an individualized learning curriculum based on the user's characteristics and learning style. The generated curriculum includes compulsory education content and supplementary materials tailored to the user's cultural background.

[1302] Step 5:

[1303] Server: Prepares the generated learning curriculum as digital learning materials and sends them to the user's device.

[1304] Step 6:

[1305] Terminal: Notifies the user of the received learning curriculum and displays it.

[1306] Step 7:

[1307] User: The user studies according to the provided learning curriculum. When solving a problem, the user inputs the answer.

[1308] Step 8:

[1309] Terminal: Records the user's answers and sends the data to the server.

[1310] Step 9:

[1311] Server: Analyzes the received answer data and determines the user's correct answer rate and answer trends.

[1312] Step 10:

[1313] Server: Updates the user's study plan in real time based on the analysis results, automatically generating additional learning materials and supplementary questions as needed.

[1314] Step 11:

[1315] Server: Sends the updated learning plan to the user's device and notifies them.

[1316] Step 12:

[1317] Device: Display the updated learning plan to the user.

[1318] Step 13:

[1319] Teachers: Teachers can check the user's learning progress and misunderstandings from a dedicated screen. If necessary, they can enter feedback.

[1320] Step 14:

[1321] Server: Receives teacher feedback and sends it to the user's device.

[1322] Step 15:

[1323] Device: Displays received teacher feedback to the user.

[1324] Step 16:

[1325] User: If the user has any questions while studying, they can ask them by voice via a smart speaker.

[1326] Step 17:

[1327] Terminal: Analyzes the user's voice question and sends the question to the server.

[1328] Step 18:

[1329] Server: Analyzes the question, generates the necessary information and answers, and sends them to the device.

[1330] Step 19:

[1331] Terminal: Provides users with answers to questions via a smart speaker.

[1332] Step 20:

[1333] Server: When the content of the educational curriculum or textbooks changes, the new information is uploaded to the database and each user's learning plan is automatically updated.

[1334] Step 21:

[1335] Server: Sends the updated learning plan to the user's device and notifies them.

[1336] Step 22:

[1337] Device: Display new learning materials and updated curriculum to users.

[1338] Example 1

[1339] 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."

[1340] Conventional educational systems have had the problem of being unable to respond to individual user needs, resulting in the provision of uniform teaching materials. Furthermore, it is difficult to provide effective learning support because it is not possible to grasp users' learning progress and level of understanding in real time and provide appropriate feedback. Furthermore, there is a lack of means to provide interactive, dialogue-based lessons, making it difficult to promote deep learning through two-way communication.

[1341] 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.

[1342] In this invention, the server includes means for collecting specific user information and generating an individual education plan based on the user information, means for recording and analyzing answer data to questions answered by the user, and means for updating the education plan in real time based on the analysis results, thereby providing a learning experience tailored to the needs of each individual user and promoting deep understanding through interactive lessons.

[1343] "Specific User Information" means individual information provided by a User, such as name, age, grade level, ethnic and cultural background, learning style, and existing learning level.

[1344] An "individualized education plan" is a curriculum and learning materials tailored to a user's individual needs and learning style, created based on the user's specific user information.

[1345] "Answer data" refers to a record of the answers given by users to questions or problems.

[1346] "Real-time updates" refers to instantly changing and adapting educational plans and teaching material content based on the results of analyzing answer data.

[1347] A "voice recognition device" is a device that recognizes a user's voice, analyzes it, and processes it as information.

[1348] "Analysis" refers to the process of identifying patterns and trends based on collected data and evaluating learning progress and level of understanding.

[1349] The "instructor-only screen" is an interface that allows instructors to check the user's learning progress and answer trends, and to input and provide feedback.

[1350] The present invention relates to a system that collects specific user information and generates an individualized educational plan based on that user information. This system provides a learning experience tailored to the individual needs of each user by smoothly exchanging information between a server, terminals, and users.

[1351] Collection of user information and profile registration

[1352] server

[1353] The server receives user information entered from the device and stores it in a database. This information includes the user's name, age, grade, ethnic and cultural background, learning method, existing learning level, etc. For example, if a 12-year-old user enters their name, age, ethnic background, visual learning style, etc., the server stores this information in a database.

[1354] Generate an Individualized Education Plan

[1355] server

[1356] The server analyzes the stored user information and uses a generative AI model to generate an individualized educational plan. This plan is created as digital learning materials based on the content of the compulsory education curriculum and the user's cultural background. For example, for a 12-year-old user from Sub-Saharan Africa, math and science learning materials incorporating the local language and culture are generated and sent to the user's device.

[1357] Learning progress and feedback

[1358] Terminal

[1359] When a user works on a problem and answers it, the device records the answer and sends it to the server.

[1360] server

[1361] The server analyzes the received answer data and determines the user's accuracy rate and answer trends. Based on the analysis results, the server updates the study plan in real time and generates additional learning materials to address the user's weaknesses. For example, if a user solves arithmetic problems and finds that they answered 90% of the questions correctly but made mistakes on some geometry-related questions, the server will generate supplementary geometry-related learning materials and incorporate them into the next study plan.

[1362] teacher

[1363] Teachers can check the user's learning progress and misunderstandings on a dedicated screen and enter feedback as needed. The server sends this feedback to the user's device and notifies the user in real time.

[1364] Interactive and conversational lessons

[1365] Terminal

[1366] When a user asks a question using a voice recognition device, the terminal analyzes the voice and sends the question to the server.

[1367] server

[1368] The server analyzes the user's question, generates the necessary information and answers, and sends them to the device. The speech recognizer then verbally conveys this information to the user. For example, if a user asks about the Pythagorean theorem, the device sends the question to the server, which returns an appropriate explanation and example problem. The speech recognizer then explains the problem to the user and provides additional problems to further deepen their understanding.

[1369] Updates to teaching materials

[1370] server

[1371] If the content of textbooks or courses changes, the new information is automatically uploaded to the server and immediately reflected in each user's educational plan. For example, if a new historical fact is discovered and added to the educational curriculum, the server updates each user's educational plan based on this new information and sends new learning materials to their device.

[1372] Prompt Sentence Examples

[1373] Curriculum generation: "Create digital learning materials that are appropriate for a 12-year-old from Sub-Saharan Africa. Please consider the user's visual learning style and incorporate local language and culture."

[1374] Interactive Lessons: "Explain the Pythagorean Theorem in detail and provide additional questions to help students understand."

[1375] As described above, this system has the ability to generate individual educational plans based on specific user information and update them in real time, while also providing interactive, dialogue-based education to ensure an effective learning experience.

[1376] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1377] Step 1:

[1378] The user enters information from the device

[1379] The user accesses a terminal and enters information into a form, such as name, age, grade, ethnic and cultural background, learning method, and existing learning level.

[1380] (Input) Data about the user's personal information and learning style.

[1381] (Output) The input data is temporarily saved on the device.

[1382] Step 2:

[1383] The device sends the information to the server

[1384] The terminal converts the information entered by the user into packets and transmits them to the server.

[1385] (Input) User information entered into the terminal.

[1386] (Output) Information is sent to the server.

[1387] Step 3:

[1388] The server receives the information and stores it in a database

[1389] The server analyzes the user information received from the terminal and stores it in a database.

[1390] (Input) User information sent from the terminal.

[1391] (Output) The parsed user information is saved in the database.

[1392] Step 4:

[1393] The server analyzes user information and generates an individualized education plan

[1394] The server analyzes the stored user information using a generative AI model to generate an individualized educational plan.

[1395] (Input) User information stored in the database.

[1396] (Output) The generated individualized education plan.

[1397] Step 5:

[1398] The server sends the educational plan to the device.

[1399] The server transmits the generated individual education plan to the terminal.

[1400] (Input) Generated individualized education plan.

[1401] (Output) The teaching plan is transferred to the terminal.

[1402] Step 6:

[1403] The user works through the questions and enters the answers

[1404] Users work on the digital learning materials provided on their terminals and input answers to the questions.

[1405] (Input) The question and the user's answer displayed on the terminal.

[1406] (Output) Answer data is temporarily saved on the device.

[1407] Step 7:

[1408] The device sends the answer to the server

[1409] The terminal transmits the saved answer data to the server.

[1410] (Input) User's answer data.

[1411] (Output) The answer data is sent to the server.

[1412] Step 8:

[1413] The server analyzes the answer data

[1414] The server analyzes the received answer data, determines the user's accuracy rate and answer trends, and processes the data using a generative AI model.

[1415] (Input) User's answer data.

[1416] (Output) Analysis results.

[1417] Step 9:

[1418] The server updates the educational plan in real time

[1419] Based on the analysis results, the server updates the study plan in real time and generates additional learning materials to fill in the user's weaknesses.

[1420] (Input) Analysis results.

[1421] (Output) Updated lesson plans and generated additional teaching materials.

[1422] Step 10:

[1423] The server sends the updated lesson plan and additional materials to the device.

[1424] The server sends updated lesson plans and additional teaching materials to the terminal.

[1425] (Input) Updated teaching plans and additional materials.

[1426] (Output) The lesson plan and additional materials are sent to the terminal.

[1427] Step 11:

[1428] User asks a question to the smart speaker

[1429] The user speaks a question using a voice recognition device.

[1430] (Input) The user's spoken question.

[1431] (Output) The device recognizes the voice data.

[1432] Step 12:

[1433] The device analyzes the voice and sends it to the server

[1434] The terminal analyzes the user's voice data as text data and sends it to the server.

[1435] (Input) Audio data.

[1436] (Output) The parsed text data is sent to the server.

[1437] Step 13:

[1438] The server analyzes the question and generates the answer

[1439] The server analyzes the received question and generates an appropriate answer using a generative AI model.

[1440] (Input) Parsed text data.

[1441] (Output) The generated answer.

[1442] Step 14:

[1443] The server sends the answer to the device

[1444] The server sends the generated answer to the terminal.

[1445] (Input) The generated answer.

[1446] (Output) The answer is sent to the device.

[1447] Step 15:

[1448] The device provides answers by voice

[1449] The terminal provides the received answer to the user through a voice recognition device.

[1450] (Input) The answer sent from the server.

[1451] (Output) The answer provided aloud.

[1452] (Application example 1)

[1453] 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."

[1454] Conventional skills training systems for factory operators have had difficulty quickly and effectively providing appropriate learning curricula tailored to individual skill levels and experience. Furthermore, they lacked the functionality to analyze learning progress in real time and provide feedback, making it extremely difficult to improve operators' skills. Furthermore, they lacked the functionality to provide interactive, dialogue-based lessons, making it difficult to immediately respond to operators' questions or problems.

[1455] 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.

[1456] In this invention, the server includes means for collecting specific user information and generating an individual learning curriculum based on the user information, means for recording and analyzing answer data for questions answered by the user, means for updating the learning plan in real time based on the analysis results, terminal means including a smart speaker for providing interactive dialogue-based lessons, means for generating a learning curriculum based on the skill level and past training data of the factory operator, means for analyzing the operator's learning progress in real time and providing feedback, means for generating additional learning materials based on the feedback, and means for responding to the learner's questions through the smart speaker. This makes it possible to provide effective training tailored to the individual skill level of the factory operator and enable rapid skill improvement through real-time progress analysis and feedback.

[1457] "Specific user information" is information necessary to identify a user and is data used to generate an individualized learning curriculum.

[1458] An "individualized learning curriculum" is a plan created based on specific user information and including learning content that is optimal for that user.

[1459] "Answer data" is data that records the results and trends of questions answered by users.

[1460] The "analysis results" are the results of analyzing the answer data, and are the basic information for updating the user's study plan.

[1461] A "smart speaker" is a device that interacts with users through a voice interface, providing information and instructions via voice.

[1462] "Terminal means" refers to the device that a user uses to interact with the system, including smart speakers, computers, tablets, etc.

[1463] "Factory operator" refers to an employee who operates and manages machinery and equipment at a manufacturing site.

[1464] "Skill level" is an indicator of an operator's technical proficiency in a particular task.

[1465] "Training data" refers to data that records the content and results of past training.

[1466] "Feedback" is information that provides evaluation and advice on the results of learning or work.

[1467] "Additional learning materials" are learning materials provided to supplement the learning based on the user's learning progress and analysis results.

[1468] A specific embodiment of a learning system for factory operators based on the present invention and its processing flow are described below. This system has the function of collecting specific user information and generating an individual learning curriculum based on that information. It also has the function of recording and analyzing answer data from questions answered by the user and updating the learning plan in real time based on the analysis results. Furthermore, the system features terminal means including a smart speaker for providing interactive, dialogue-based lessons.

[1469] Collection of user information and profile registration

[1470] server

[1471] The server receives information entered by the user from the terminal and stores it in a database. For example, the operator enters their name, age, skill level, past training data, etc.

[1472] Specific examples

[1473] A 30-year-old factory operator enters his or her name, age, entry-level skills, and past training data, and the server stores that information in a database.

[1474] Creating personalized learning curriculum

[1475] server

[1476] The server analyzes the stored user information and generates an optimal learning curriculum for each operator. The generated curriculum is created as digital learning materials based on past training data and skill level.

[1477] Specific examples

[1478] The server generates teaching materials for beginners, such as welding techniques and machine operation, for a 30-year-old beginner operator, and sends the materials to the user's terminal.

[1479] Learning progress and feedback

[1480] Terminal

[1481] As the user works through the questions and answers, the answers are recorded and sent to the server.

[1482] server

[1483] The server analyzes the answer data to determine the user's accuracy rate and answer trends. Based on the analysis results, the server updates the learning plan in real time and generates additional learning materials to fill in the operator's weaknesses.

[1484] Specific examples

[1485] If a 30-year-old operator solves machine operation problems and gets 90% correct, but makes mistakes on some questions related to changing settings, the server will generate supplementary learning materials related to changing settings and incorporate them into the next learning plan.

[1486] Interactive and conversational lessons

[1487] Terminal

[1488] When a user speaks a question to a smart speaker, the voice is analyzed and the question is sent to the server.

[1489] server

[1490] The server analyzes the user's question, generates the necessary information and answers, and sends them to the device, which then relays the information to the user via voice.

[1491] Specific examples

[1492] When a factory operator asks, "Please teach me basic welding techniques," the device sends the question to the server, which then returns appropriate explanations and training materials. The smart speaker then explains the information to the operator aloud and provides further training methods.

[1493] Hardware and Software

[1494] Server: Cloud server (e.g. AWS, Google Cloud)

[1495] Database: MySQL, PostgreSQL

[1496] AI analysis engine: GPT-4

[1497] Devices: Smart speakers (e.g., Amazon Echo, Google Home), factory robots, operator devices (PCs and tablets)

[1498] Examples and prompts

[1499] Specific examples

[1500] A 30-year-old novice operator needs to be trained in a new welding technique.

[1501] The operator asks the smart speaker, "Please tell me about the basic techniques of welding."

[1502] Prompt statement

[1503] User information: 'Name: Ichiro Tanaka, Age: 30, Skill level: Beginner, Past training data: []'. Please generate a learning curriculum appropriate for this user.

[1504] Question: 'Please tell me about the basic techniques of welding'. Please provide a suitable answer.

[1505] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1506] Step 1: Enter and submit user information

[1507] The user inputs information such as their name, age, skill level, and past training data from the terminal, and this input data is sent from the terminal to the server.

[1508] concrete action

[1509] Input: Name, age, skill level, past training data

[1510] Data processing: Convert each item into JSON format

[1511] Output: User information sent to the server

[1512] Example: Name: Yamada Taro, Age: 35, Skill Level: Intermediate, Training Data: []

[1513] Step 2: Save user information

[1514] The server stores the received user information in a database, which is then used to generate a personalized learning curriculum.

[1515] concrete action

[1516] Input: User information sent from the device (JSON format)

[1517] Data processing: Converting data into SQL statements for saving to the database

[1518] Output: User information stored in the database

[1519] Destination: Database (MySQL, PostgreSQL)

[1520] Step 3: Create a personalized learning curriculum

[1521] The server analyzes the stored user information and generates an individual learning curriculum using a generative AI model (GPT-4). The generated curriculum is then sent to the user's device as digital learning materials.

[1522] concrete action

[1523] Input: User information retrieved from the database

[1524] Data processing: Prompt generation and input to GPT-4

[1525] Output: Personalized learning curriculum

[1526] Example prompt: "User information: {'Name': 'Yamada Taro', 'Age': 35, 'Skill level': 'Intermediate', 'Training data': []}. Please generate a learning curriculum appropriate for this user."

[1527] AI used: GPT-4

[1528] Send the generated curriculum to your device

[1529] Step 4: Record your learning progress

[1530] When a user works on a problem and answers it on the terminal, the answer data is recorded by the terminal and transmitted to the server.

[1531] concrete action

[1532] Input: User's answer data

[1533] Data processing: Recording correct and incorrect answers for each answer and generating data for trend analysis

[1534] Output: Answer data sent to the server

[1535] Example: Question ID: 123, Answer: "A", Correct Answer: true

[1536] Step 5: Analyze the answer data and provide feedback

[1537] The server analyzes the received answer data to determine the accuracy rate and answer trends. Based on the analysis results, it updates the learning plan in real time and generates additional learning materials to fill in the operator's weaknesses.

[1538] concrete action

[1539] Input: Answer data sent from the device

[1540] Data processing: Correct answer rate calculation and trend analysis

[1541] Output: Updated learning plan and feedback

[1542] AI used: GPT-4

[1543] Example prompt for generating additional learning materials: "Answer data: [{'Question ID': 123, 'Answer': 'A', 'Correct Answer': true}]. Analyze learning progress and provide feedback.

[1544] Step 6: Interactive and interactive lessons

[1545] When a user speaks a question to a smart speaker, the voice data is analyzed and the question is sent to the server. The server analyzes the question, generates the necessary information and answer, and sends it to the device. The smart speaker then conveys that information by voice.

[1546] concrete action

[1547] Input: A spoken question from the user

[1548] Data processing: speech recognition and text conversion, answer generation using GPT-4

[1549] Output: A spoken response to the user

[1550] AI used: GPT-4

[1551] Example prompt: "Question: 'Tell me about basic welding techniques.' Please provide an appropriate answer."

[1552] Example speech output: "The basic technique of welding is..."

[1553] Step 7: Distribute generated materials and update learning plans

[1554] The server sends the generated additional learning materials and updated study plans to the user's device, and the user continues studying based on the new study plans.

[1555] concrete action

[1556] Input: Updated study plans and additional materials

[1557] Data processing: Converting data to send to the user's device

[1558] Output: Push notifications and delivery of educational materials to users' devices

[1559] Communication method: Data transmission via the Internet

[1560] Example delivery: "New learning plans are available. Check them out in the next session."

[1561] As described above, the system provides factory operators with individual learning curricula, performs real-time progress analysis and feedback, and supports efficient skill development through interactive, dialogue-based lessons.

[1562] 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.

[1563] A specific embodiment of the system according to the present invention and its processing flow will be described below.

[1564] The system has the functions of collecting specific user information and generating an individual learning curriculum based on that information, recording and analyzing the answers given by the user to questions, updating the learning plan in real time based on the analysis results, and providing device functions including a smart speaker that provides interactive lessons.It also has an emotion engine that recognizes the user's emotions.

[1565] (Collection of user information and profile registration)

[1566] server

[1567] The server receives information entered by the user from the device and stores it in a database, such as the user's name, age, grade level, ethnic and cultural background, learning style, and existing learning level.

[1568] Specific examples

[1569] A 12-year-old user enters their name, age, ethnic background (e.g., from Sub-Saharan Africa), visual learning style, etc., and the server stores this information in a database.

[1570] (Generating personalized learning curriculum)

[1571] server

[1572] The server analyzes the stored user information and generates an optimal learning curriculum for each individual learner. This curriculum is created as digital learning materials based on the content of compulsory education and the user's cultural background.

[1573] Specific examples

[1574] The server generates mathematics and science learning materials incorporating local language and culture for 12-year-old users from sub-Saharan Africa and sends the materials to the users' devices.

[1575] (Learning progress and feedback)

[1576] Terminal

[1577] As the user works through the questions and answers, the terminal records the answers and sends them to the server.

[1578] server

[1579] The server analyzes the received answer data to determine the user's accuracy rate and answer trends. Based on the analysis results, it updates the study plan in real time and generates additional learning materials to fill in the user's weak points.

[1580] Specific examples

[1581] If a 12-year-old user solves math problems and finds that he gets 90% of the answers right but makes mistakes on some geometry-related questions, the server will generate supplementary geometry-related learning materials and incorporate them into his next learning plan.

[1582] teacher

[1583] Teachers can check the user's learning progress and misunderstandings on a dedicated screen and enter feedback as needed. The server sends this feedback to the user's device and notifies the user in real time.

[1584] (Interactive dialogue-based lessons)

[1585] Terminal

[1586] When a user speaks a question to a smart speaker, the device analyzes the voice and sends the question to the server.

[1587] server

[1588] The server analyzes the user's question, generates the necessary information and answers, and sends them to the device, which then relays the information to the user via voice.

[1589] Specific examples

[1590] When a user asks a question about the Pythagorean theorem, the device sends the question to the server, which responds with an appropriate explanation and example. The smart speaker then explains it to the user and offers additional questions to further deepen their understanding.

[1591] (Utilizing emotion engines)

[1592] Terminal

[1593] The device detects the emotions expressed by the user through facial expressions and tone of voice while learning, and sends this data to the emotion engine.

[1594] Server (emotion engine)

[1595] The emotion engine analyzes the data sent from the terminal and determines the user's emotional state (e.g., interest, fatigue, frustration, etc.).

[1596] Specific examples

[1597] If the user shows signs of fatigue while studying, the emotion engine will analyze this information and suggest that the user take a break, a suggestion that will be delivered audibly through the smart speaker.

[1598] (Teaching material updates)

[1599] server

[1600] If the content of the textbook or the course changes, the new information is automatically uploaded to the server and immediately reflected in each user's learning plan.

[1601] Specific examples

[1602] When new historical facts are discovered and added to the educational curriculum, the server updates each user's learning plan based on this new information and sends new learning materials to the device.

[1603] (Feedback optimization using emotion engine)

[1604] Server (emotion engine)

[1605] The emotion engine automatically generates feedback and support messages based on the user's emotional state, which are delivered via a smart speaker with the goal of improving the user's learning efficiency.

[1606] Specific examples

[1607] If the user is interested, the emotion engine will provide additional challenges or relevant information to keep them engaged, or if they are frustrated, it will suggest hints or quick solutions to their problems.

[1608] In this way, this system achieves smooth information exchange between the server, terminals, and users, providing an effective learning experience even in areas with inadequate educational environments. The addition of an emotion engine provides optimal support according to the user's emotional state, improving learning efficiency and motivation.

[1609] The processing flow will be explained below.

[1610] Step 1:

[1611] User: The user installs and launches the app. On first launch, the user enters profile information such as name, age, grade level, ethnic and cultural background, learning style, and existing learning level.

[1612] Step 2:

[1613] Terminal: Collects profile information entered by the user and sends it to the server.

[1614] Step 3:

[1615] Server: The server stores the received user information in a database.

[1616] Step 4:

[1617] Server: The server analyzes the stored user information and generates an individualized learning curriculum based on the user's characteristics and learning style. The generated curriculum includes the content of the compulsory education curriculum and supplementary materials tailored to the user's cultural background.

[1618] Step 5:

[1619] Server: Prepares the generated learning curriculum as digital learning materials and sends them to the user's device.

[1620] Step 6:

[1621] Terminal: Notifies the user of the received learning curriculum and displays it.

[1622] Step 7:

[1623] User: The user studies according to the provided learning curriculum. When solving a problem, the user inputs the answer.

[1624] Step 8:

[1625] Terminal: Records the user's answers and sends the data to the server.

[1626] Step 9:

[1627] Server: Analyzes the received answer data and determines the user's correct answer rate and answer trends.

[1628] Step 10:

[1629] Server: Updates the user's study plan in real time based on the analysis results, automatically generating additional learning materials and supplementary questions as needed.

[1630] Step 11:

[1631] Server: Sends the updated learning plan to the user's device and notifies them.

[1632] Step 12:

[1633] Device: Display the updated learning plan to the user.

[1634] Step 13:

[1635] Teacher: The teacher can check the user's learning progress and misunderstandings from a dedicated screen. If necessary, the teacher can enter feedback.

[1636] Step 14:

[1637] Server: Receives teacher feedback and sends it to the user's device.

[1638] Step 15:

[1639] Device: Displays received teacher feedback to the user.

[1640] Step 16:

[1641] User: If the user has any questions while studying, they can ask them by voice via a smart speaker.

[1642] Step 17:

[1643] Terminal: Analyzes the user's voice question and sends the question to the server.

[1644] Step 18:

[1645] Server: Analyzes the question, generates the necessary information and answers, and sends them to the device.

[1646] Step 19:

[1647] Terminal: Provides users with answers to questions via a smart speaker.

[1648] Step 20:

[1649] Terminal: Collects emotional information from the user's voice and facial expressions and sends that data to the server.

[1650] Step 21:

[1651] Server (emotion engine): Analyzes the emotion information sent from the device and determines the user's emotional state (e.g., interest, fatigue, frustration, etc.).

[1652] Step 22:

[1653] Server (Emotion Engine): Adjusts learning curriculum and feedback based on the user's emotional state. For example, it suggests a break if the user is tired, or provides additional relevant information if the user shows interest.

[1654] Step 23:

[1655] Server (emotion engine): Sends automatically generated feedback and support messages to the device.

[1656] Step 24:

[1657] Terminal: Provides users with feedback and support messages from the emotion engine via a smart speaker.

[1658] Step 25:

[1659] Server: When the content of the educational curriculum or textbooks changes, the new information is uploaded to the database and each user's learning plan is automatically updated.

[1660] Step 26:

[1661] Server: Sends the updated learning plan to the user's device and notifies them.

[1662] Step 27:

[1663] Device: Display new learning materials and updated curriculum to users.

[1664] Example 2

[1665] 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."

[1666] Previous educational systems lacked detailed learning support tailored to individual users' cultural backgrounds and learning styles, and the lack of real-time feedback limited the effectiveness of learning. Furthermore, the lack of a mechanism for reflecting users' emotions in the learning process made it difficult to improve learning efficiency and motivation.

[1667] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for collecting specific user information and generating an individual learning curriculum based on the user information; means for recording and analyzing answer data of questions answered by the user; means for updating the learning plan in real time based on the analysis results; voice communication terminal means for providing interactive dialogue-based lessons; and means including an emotion engine for recognizing user emotions and analyzing emotion data to provide learning support. This makes it possible to provide a learning curriculum optimized for each user, real-time feedback according to learning progress, and appropriate support based on the user's emotional state.

[1668] "Specific User Information" is information provided by a user regarding their name, age, grade level, ethnic and cultural background, learning style, and existing learning level.

[1669] An "individual learning curriculum" is a collection of educational content and learning materials optimized for each user based on collected user information.

[1670] "Answer data" is a record of the answers to questions that the user answered while studying.

[1671] "Updating in real time" means immediately reviewing the learning plan based on the progress of learning and analysis results, and providing instruction based on the latest information.

[1672] An "interactive dialogue-based lesson" is a two-way lesson format in which users ask and answer questions via voice communication terminals, and the system provides appropriate feedback and explanations.

[1673] "Voice communication terminal" refers to a device that enables voice communication, specifically a smart speaker.

[1674] The "emotion engine" is part of a system that analyzes the user's emotional state and provides learning support and feedback based on the results of that analysis.

[1675] The "Educator-only screen" is an interface that allows educators to view and manage learning status and analysis results.

[1676] The present invention is a system that collects specific user information and generates an individual learning curriculum based on that user information. This system is realized through the exchange of information between a server, a terminal, and a user.

[1677] 1. Collection of User Information and Profile Registration

[1678] server

[1679] The server receives information entered by the user from their device and stores it in a database. The information entered by the user includes name, age, grade, ethnic and cultural background, learning style, and existing learning level. This information serves as the basis for generating a learning curriculum optimized for each user.

[1680] Examples:

[1681] Users enter information such as "from Sub-Saharan Africa, 12 years old, visual learning style," and the server stores this in a database.

[1682] 2. Creating an individualized learning curriculum

[1683] server

[1684] The server analyzes the stored user information and generates an optimal learning curriculum for each user. This curriculum is in line with the educational curriculum and is adapted to the user's cultural background and learning style. The generated digital learning materials are sent to the user's device.

[1685] Examples:

[1686] The server generates "math and science learning materials appropriate to the background of 12-year-old users from sub-Saharan Africa" ​​and sends them to the device.

[1687] 3. Learning progress and feedback

[1688] Terminal

[1689] The user works on the problems and inputs the answers into the terminal, which records the answer data and transmits it to the server in real time.

[1690] Examples:

[1691] When the user "solves an arithmetic problem and enters the answer," the device records the data sequentially and sends it to the server.

[1692] server

[1693] The server analyzes the answer data to determine the user's accuracy rate and answer trends. Based on the analysis results, it generates a new study plan and creates supplementary materials to strengthen weak points.

[1694] Examples:

[1695] The server "generates supplementary geometry learning materials for users who make many mistakes on geometry problems" and incorporates them into the next learning plan.

[1696] teacher

[1697] Teachers can check the user's learning progress on a dedicated screen and enter feedback as needed, which is then sent to the user's device via the server.

[1698] Examples:

[1699] The teacher "enters additional explanations for specific problems," which are then sent to the user's device in real time.

[1700] 4. Interactive and conversational lessons

[1701] Terminal

[1702] When a user asks a question by voice through a smart speaker, the device analyzes the voice and sends the question to the server.

[1703] server

[1704] The server analyzes the question, generates the necessary information and answers, and sends them to the device, which then relays the information to the user via voice.

[1705] Examples:

[1706] When a user "asks a question about the Pythagorean theorem, the server generates a detailed explanation and examples," which the smart speaker then relays to the user.

[1707] 5. Emotion recognition and support with emotion engine

[1708] Terminal

[1709] The device recognizes the emotions expressed by the user through facial expressions and tone of voice during learning and sends this data to the emotion engine.

[1710] Examples:

[1711] The device captures statements and facial expressions that indicate fatigue while the user is studying and sends them to the emotion engine.

[1712] Server (emotion engine)

[1713] The emotion engine analyzes the received data, determines the user's emotional state, and generates support and suggestions according to that state.

[1714] Examples:

[1715] The emotion engine "generates messages suggesting a break for users who feel tired" and notifies them through a smart speaker.

[1716] 6. Updating teaching materials

[1717] server

[1718] When textbook content or curriculum changes, the new information is automatically uploaded to the server, which instantly updates each user's learning plan.

[1719] Examples:

[1720] When new historical facts are added, the server updates the user's study plan based on that information and sends the new learning materials to the device.

[1721] 7. Optimizing feedback with an emotion engine

[1722] Server (emotion engine)

[1723] The emotion engine automatically generates feedback and support messages based on the user's emotional state, and the feedback is delivered via a smart speaker.

[1724] Examples:

[1725] The emotion engine "provides additional challenges and related information to interested users," which the smart speaker then relays audibly. Conversely, "if users are frustrated, the engine will suggest hints and easy solutions to the problem."

[1726] Example prompts for generative AI models

[1727] Below are some specific examples of prompts for the generative AI model.

[1728] Text format:

[1729] "Generate additional study materials to supplement the user's weak points based on the answer data of the problems the user has solved."

[1730] "How can I generate personalized learning curriculum that takes into account the cultural background of my users?"

[1731] "Use an emotion engine to generate feedback messages to improve user learning efficiency."

[1732] The above is a specific method for implementing the system of the present invention, which enables the provision of a learning curriculum optimized for each user, real-time feedback according to the learning progress, and appropriate support based on the user's emotional state.

[1733] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1734] Step 1: Enter and save user information

[1735] Input: The user enters information such as name, age, grade, ethnic and cultural background, learning style, and existing learning level from the terminal.

[1736] Operation: The terminal transmits the information entered by the user to the server in real time.

[1737] Output: The server stores the received user information in a database. The user information serves as the basis for subsequent curriculum generation and analysis.

[1738] Specific behavior:

[1739] The user enters information such as "from Sub-Saharan Africa, 12 years old, visual learning style," and the device records this and sends it to the server, which stores the information in a database.

[1740] Step 2: Create a personalized learning curriculum

[1741] Input: User information stored on the server (such as name, age, ethnic and cultural background, learning style, existing learning level, etc.).

[1742] How it works: The server analyzes user information and generates an optimal learning curriculum for each user. This analysis can be performed using a generative AI model.

[1743] Output: The generated learning curriculum is sent to the user's device as digital learning materials.

[1744] Specific behavior:

[1745] The server generates "math and science learning materials appropriate to the background of 12-year-old users from sub-Saharan Africa" ​​and sends them to the device.

[1746] Step 3: Record your learning progress and answer data

[1747] Input: The user answers the question and enters the answer into the terminal.

[1748] Operation: The terminal records the answer data entered by the user and transmits it to the server in real time.

[1749] Output: The server stores the received answer data.

[1750] Specific behavior:

[1751] When the user "solves an arithmetic problem and enters the answer," the device records the data sequentially and sends it to the server.

[1752] Step 4: Analyze the answer data and update the study plan

[1753] Input: Answer data stored on the server.

[1754] How it works: The server analyzes the answer data to determine the user's accuracy rate and answer trends. Based on the analysis results, it updates the study plan in real time and generates supplementary learning materials as needed.

[1755] Output: Send the new learning plan and supplementary materials to the user's device.

[1756] Specific behavior:

[1757] The server "generates supplementary geometry learning materials for users who make many mistakes on geometry problems" and incorporates them into the next learning plan.

[1758] Step 5: Teacher review and feedback on learning progress

[1759] Input: User learning progress and analysis results displayed on the educator-only screen.

[1760] How it works: The teacher checks the user's learning progress and trends in misunderstandings on a dedicated screen and provides feedback as needed.

[1761] Output: The feedback is sent to the user's device via the server.

[1762] Specific behavior:

[1763] The teacher "enters additional explanations for specific problems," which are then sent to the user's device in real time.

[1764] Step 6: Conduct interactive and dialogue-based lessons

[1765] Input: The user enters a question by voice through a smart speaker.

[1766] How it works: The device analyzes the voice and sends the question to the server. The server analyzes the question, generates the necessary information and answers, and sends them to the device.

[1767] Output: The smart speaker will verbally communicate the generated information to the user.

[1768] Specific behavior:

[1769] When a user "asks a question about the Pythagorean theorem, the server generates a detailed explanation and examples," which the smart speaker then relays to the user.

[1770] Step 7: Emotion recognition and support with the emotion engine

[1771] Input: Emotion data expressed by the user through facial expressions and vocal tones during training.

[1772] How it works: The device senses emotion data and sends it to the emotion engine, which analyzes the data and determines the user's emotional state.

[1773] Output: Support and suggestions based on the user's emotional state are generated and communicated through a smart speaker.

[1774] Specific behavior:

[1775] The emotion engine "generates messages suggesting a break for users who feel tired" and notifies them through a smart speaker.

[1776] Step 8: Update your materials

[1777] Input: New textbook content and curriculum information.

[1778] How it works: The server automatically uploads new information and updates each user's study plan.

[1779] Output: The updated lesson plan and new learning materials are sent to the user's device.

[1780] Specific behavior:

[1781] When new historical facts are added, the server updates the user's study plan based on that information and sends the new learning materials to the device.

[1782] Step 9: Optimizing feedback with an emotion engine

[1783] Input: The user's emotional state during learning.

[1784] How it works: The emotion engine generates appropriate feedback and support messages based on the user's emotional state.

[1785] Output: Optimized feedback and assistance messages are provided to the user through a smart speaker.

[1786] Specific behavior:

[1787] The emotion engine "provides additional challenges and related information to interested users," which the smart speaker then relays audibly. Conversely, "if users are frustrated, the engine will suggest hints and easy solutions to the problem."

[1788] (Application example 2)

[1789] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1790] Conventional learning systems have difficulty generating and updating individual curricula based on the characteristics and learning progress of each user, and also have difficulty providing feedback based on the user's emotional state. As a result, there are problems with reduced learning efficiency and motivation.

[1791] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for collecting specific user information and generating an individual curriculum based on the user information; means for recording and analyzing answer data of questions answered by the user; means for updating the plan in real time based on the analysis results; terminal means including a voice recognition device for providing interactive lessons; and means including an emotion engine for analyzing the user's emotional state and providing feedback based on the analysis results. This makes it possible to provide an individually optimized learning curriculum and effective feedback according to the user's emotions.

[1792] "Specific User Information" refers to a user's individual characteristics, such as the user's name, age, grade level, ethnic and cultural background, learning style, and existing learning level.

[1793] "Personalized Curriculum" refers to learning content and progression plans optimized based on specific user information.

[1794] "Answer data" refers to the answer information entered by the user in response to the study question.

[1795] "Analysis results" refers to the results of analyzing the user's learning situation and tendencies based on collected answer data.

[1796] "Real-time plan updating" refers to the process of reviewing and optimizing the learning progress plan at any time based on the analysis results.

[1797] "Interactive lessons" refers to a type of lesson in which users and systems exchange information two-way through audio and visual means to advance learning.

[1798] A "voice recognizer" refers to a device that analyzes a user's speech, recognizes its content, and generates a response.

[1799] "Emotional state" refers to a psychological state, such as interest, fatigue, or frustration, that can be inferred from a user's facial expression, tone of voice, or behavior.

[1800] An "emotion engine" refers to a software component that analyzes a user's emotional state and generates appropriate feedback and support messages based on that state.

[1801] The system of the present invention includes functions for collecting user information, generating an individual curriculum based on that information, recording and analyzing user answer data, and updating the plan in real time based on the analysis results. It also includes terminal means including a voice recognition device that provides interactive lessons, and an emotion engine that analyzes the user's emotional state and provides feedback.

[1802] System program generation

[1803] 1. User Information Collection:

[1804] The server receives information entered by the user through a smartphone or smart glasses, such as name, age, grade, learning style, and current learning level, and stores it in a database, allowing optimization according to the characteristics of each individual user.

[1805] 2. Generating personalized learning curriculum:

[1806] The server analyzes the collected user information and generates an optimal learning curriculum for the user, which is customized to meet the user's individual learning needs.

[1807] 3. Learning progress and feedback:

[1808] When a user answers a question, the device records the answer data and sends it to the server, which then analyzes the received answer data, evaluates the user's progress and learning trends, and updates the learning plan in real time, while providing appropriate feedback to the user.

[1809] 4. Providing interactive lessons:

[1810] The system allows two-way dialogue with users via a voice recognition device, and when a user asks a specific question, the system analyzes the question and provides appropriate answers and additional learning materials. This interactive lesson is conducted via a smart speaker or head-mounted display.

[1811] 5. Leveraging the Emotion Engine:

[1812] The device's camera and microphone detect the user's emotional state and send the data to the emotion engine, which then generates appropriate feedback and support messages based on the analysis results. For example, if the user feels fatigued while studying, the engine suggests taking a break.

[1813] Hardware and software used

[1814] Hardware

[1815] Smartphone

[1816] Smart Glasses

[1817] head-mounted display

[1818] smart speaker

[1819] software

[1820] Database Management Systems

[1821] Voice Recognition Software

[1822] Emotion Engine

[1823] Curriculum Generation Engine (CurriculumGenerator)

[1824] Specific examples

[1825] As a concrete example of collecting user data, consider a 12-year-old user who inputs information into the system, such as their name, age, ethnic background (e.g., from Sub-Saharan Africa), and visual learning style. The system uses this information to provide learning materials that are appropriate for the user's cultural background. For example, if the user uses a smart speaker to ask about "Pythagoras' Theorem," the system can provide an appropriate explanation and offer additional learning tasks.

[1826] Prompt Sentence Examples

[1827] "What support message should be generated if the user shows fatigue during learning?"

[1828] "If a 12-year-old user asks about the Pythagorean theorem, provide a concise explanation and generate additional tasks to further increase interest."

[1829] This will enable us to provide an effective learning experience even in areas where the educational environment is inadequate.

[1830] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1831] Step 1:

[1832] The server collects user information. The user inputs information such as name, age, grade, ethnic and cultural background, learning style, and current learning level through a smartphone or smart glasses. This information is sent by the device to the server and stored in a database. The input is user information, and the output is the saved user profile.

[1833] Step 2:

[1834] The server generates an individual learning curriculum based on the collected user information. This involves retrieving user information from a database and generating appropriate learning materials and curriculum based on that information. The input is a user profile, and the output is an individually optimized learning curriculum.

[1835] Step 3:

[1836] The device records the answer data of the questions answered by the user and sends it to the server. When the user answers a study question through the device, the question and answer data are temporarily saved on the device and periodically sent to the server. The input is the answer data, and the output is the study record sent to the server.

[1837] Step 4:

[1838] The server analyzes the received answer data. It uses a specific algorithm to analyze the user's accuracy rate and answer trends, and derives each user's strengths and weaknesses. The input is the answer data, and the output is the analysis results.

[1839] Step 5:

[1840] The server updates the study plan in real time based on the analysis results. It generates a new study plan that reflects the analysis results and sends it to the user's device. This new plan includes content that strengthens the user's weaknesses. The input is the analysis results, and the output is the updated study plan.

[1841] Step 6:

[1842] To provide interactive lessons, the terminal uses a voice recognition device to accept questions from users. When a user inputs a question by voice, the voice data is analyzed, converted into text data, and sent to the server. The input is voice data, and the output is text data.

[1843] Step 7:

[1844] The server generates answers to users' text-based questions. Using an AI model, it generates optimal answers and additional learning tasks for the user's questions and sends them to the device. The input is text data (user's question), and the output is the answer text and additional tasks.

[1845] Step 8:

[1846] The terminal communicates the answers and additional tasks received from the server to the user by voice. It uses speech synthesis software to convert text data into speech and provides it to the user. The input is the answer text and additional tasks, and the output is speech data.

[1847] Step 9:

[1848] The device senses the user's emotional state using a camera and microphone, collects data on the user's facial expressions and tone of voice, and sends it to the emotion engine. The input is facial expression data and tone of voice data, and the output is emotion data.

[1849] Step 10:

[1850] The server (emotion engine) analyzes the emotion data to determine the user's emotional state. Based on the analysis results, it generates appropriate feedback and support messages and sends them to the device. The input is emotion data, and the output is feedback and support messages.

[1851] Step 11:

[1852] The device notifies the user of feedback and support messages received from the server. Notifications are given by voice, screen display, vibration, etc. The input is the feedback and support messages, and the output is the user notification.

[1853] Through these steps, the system of the present invention is able to provide a learning curriculum tailored to the user's individual needs, manage learning progress in real time, and provide feedback tailored to the user's emotional state.

[1854] 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.

[1855] 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.

[1856] 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.

[1857] [Fourth embodiment]

[1858] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1859] 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.

[1860] 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).

[1861] 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.

[1862] 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.

[1863] 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).

[1864] 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.

[1865] 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.

[1866] 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.

[1867] 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.

[1868] 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.

[1869] 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.

[1870] 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."

[1871] A specific embodiment of the system according to the present invention and its processing flow will be described below.

[1872] The system has the functions of collecting specific user information and generating an individual learning curriculum based on that information, recording and analyzing the answers given by the user, updating the learning plan in real time based on the analysis results, and providing terminal functions including a smart speaker for providing interactive, dialogue-based lessons.

[1873] (Collection of user information and profile registration)

[1874] server

[1875] The server receives information entered by the user from the device and stores it in a database, such as the user's name, age, grade level, ethnic and cultural background, learning style, and existing learning level.

[1876] Specific examples

[1877] A 12-year-old user enters their name, age, ethnic background (e.g., from Sub-Saharan Africa), visual learning style, etc., and the server stores this information in a database.

[1878] (Generating personalized learning curriculum)

[1879] server

[1880] The server analyzes the stored user information and generates an optimal learning curriculum for each individual learner. This curriculum is created as digital learning materials based on the content of compulsory education and the user's cultural background.

[1881] Specific examples

[1882] The server generates mathematics and science learning materials incorporating local language and culture for 12-year-old users from sub-Saharan Africa and sends the materials to the users' devices.

[1883] (Learning progress and feedback)

[1884] Terminal

[1885] As the user works through the questions and answers, the terminal records the answers and sends them to the server.

[1886] server

[1887] The server analyzes the received answer data to determine the user's accuracy rate and answer trends. Based on the analysis results, it updates the study plan in real time and generates additional learning materials to fill in the user's weak points.

[1888] Specific examples

[1889] If a 12-year-old user solves math problems and finds that he gets 90% of the answers right but makes mistakes on some geometry-related questions, the server will generate supplementary geometry-related learning materials and incorporate them into his next learning plan.

[1890] teacher

[1891] Teachers can check the user's learning progress and misunderstandings on a dedicated screen and enter feedback as needed. The server sends this feedback to the user's device and notifies the user in real time.

[1892] (Interactive dialogue-based lessons)

[1893] Terminal

[1894] When a user speaks a question to a smart speaker, the device analyzes the voice and sends the question to the server.

[1895] server

[1896] The server analyzes the user's question, generates the necessary information and answers, and sends them to the device, which then relays the information to the user via voice.

[1897] Specific examples

[1898] When a user asks a question about the Pythagorean theorem, the device sends the question to the server, which responds with an appropriate explanation and example. The smart speaker then explains it to the user and offers additional questions to further deepen their understanding.

[1899] (Teaching material updates)

[1900] server

[1901] If the content of the textbook or the course changes, the new information is automatically uploaded to the server and immediately reflected in each user's learning plan.

[1902] Specific examples

[1903] When new historical facts are discovered and added to the educational curriculum, the server updates each user's learning plan based on this new information and sends new learning materials to the device.

[1904] In this way, this system enables smooth information exchange between the server, terminals, and users, providing an effective learning experience even in areas with inadequate educational environments.

[1905] The processing flow will be explained below.

[1906] Step 1:

[1907] User: The user installs and launches the app. On first launch, the user enters profile information such as name, age, grade level, ethnic and cultural background, learning style, and existing learning level.

[1908] Step 2:

[1909] Terminal: Collects profile information entered by the user and sends it to the server.

[1910] Step 3:

[1911] Server: The server stores the received user information in a database.

[1912] Step 4:

[1913] Server: The server analyzes the stored user information and generates an individualized learning curriculum based on the user's characteristics and learning style. The generated curriculum includes compulsory education content and supplementary materials tailored to the user's cultural background.

[1914] Step 5:

[1915] Server: Prepares the generated learning curriculum as digital learning materials and sends them to the user's device.

[1916] Step 6:

[1917] Terminal: Notifies the user of the received learning curriculum and displays it.

[1918] Step 7:

[1919] User: The user studies according to the provided learning curriculum. When solving a problem, the user inputs the answer.

[1920] Step 8:

[1921] Terminal: Records the user's answers and sends the data to the server.

[1922] Step 9:

[1923] Server: Analyzes the received answer data and determines the user's correct answer rate and answer trends.

[1924] Step 10:

[1925] Server: Updates the user's study plan in real time based on the analysis results, automatically generating additional learning materials and supplementary questions as needed.

[1926] Step 11:

[1927] Server: Sends the updated learning plan to the user's device and notifies them.

[1928] Step 12:

[1929] Device: Display the updated learning plan to the user.

[1930] Step 13:

[1931] Teachers: Teachers can check the user's learning progress and misunderstandings from a dedicated screen. If necessary, they can enter feedback.

[1932] Step 14:

[1933] Server: Receives teacher feedback and sends it to the user's device.

[1934] Step 15:

[1935] Device: Displays received teacher feedback to the user.

[1936] Step 16:

[1937] User: If the user has any questions while studying, they can ask them by voice via a smart speaker.

[1938] Step 17:

[1939] Terminal: Analyzes the user's voice question and sends the question to the server.

[1940] Step 18:

[1941] Server: Analyzes the question, generates the necessary information and answers, and sends them to the device.

[1942] Step 19:

[1943] Terminal: Provides users with answers to questions via a smart speaker.

[1944] Step 20:

[1945] Server: When the content of the educational curriculum or textbooks changes, the new information is uploaded to the database and each user's learning plan is automatically updated.

[1946] Step 21:

[1947] Server: Sends the updated learning plan to the user's device and notifies them.

[1948] Step 22:

[1949] Device: Display new learning materials and updated curriculum to users.

[1950] Example 1

[1951] 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."

[1952] Conventional educational systems have had the problem of being unable to respond to individual user needs, resulting in the provision of uniform teaching materials. Furthermore, it is difficult to provide effective learning support because it is not possible to grasp users' learning progress and level of understanding in real time and provide appropriate feedback. Furthermore, there is a lack of means to provide interactive, dialogue-based lessons, making it difficult to promote deep learning through two-way communication.

[1953] 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.

[1954] In this invention, the server includes means for collecting specific user information and generating an individual education plan based on the user information, means for recording and analyzing answer data to questions answered by the user, and means for updating the education plan in real time based on the analysis results, thereby providing a learning experience tailored to the needs of each individual user and promoting deep understanding through interactive lessons.

[1955] "Specific User Information" means individual information provided by a User, such as name, age, grade level, ethnic and cultural background, learning style, and existing learning level.

[1956] An "individualized education plan" is a curriculum and learning materials tailored to a user's individual needs and learning style, created based on the user's specific user information.

[1957] "Answer data" refers to a record of the answers given by users to questions or problems.

[1958] "Real-time updates" refers to instantly changing and adapting educational plans and teaching material content based on the results of analyzing answer data.

[1959] A "voice recognition device" is a device that recognizes a user's voice, analyzes it, and processes it as information.

[1960] "Analysis" refers to the process of identifying patterns and trends based on collected data and evaluating learning progress and level of understanding.

[1961] The "instructor-only screen" is an interface that allows instructors to check the user's learning progress and answer trends, and to input and provide feedback.

[1962] The present invention relates to a system that collects specific user information and generates an individualized educational plan based on that user information. This system provides a learning experience tailored to the individual needs of each user by smoothly exchanging information between a server, terminals, and users.

[1963] Collection of user information and profile registration

[1964] server

[1965] The server receives user information entered from the device and stores it in a database. This information includes the user's name, age, grade, ethnic and cultural background, learning method, existing learning level, etc. For example, if a 12-year-old user enters their name, age, ethnic background, visual learning style, etc., the server stores this information in a database.

[1966] Generate an Individualized Education Plan

[1967] server

[1968] The server analyzes the stored user information and uses a generative AI model to generate an individualized educational plan. This plan is created as digital learning materials based on the content of the compulsory education curriculum and the user's cultural background. For example, for a 12-year-old user from Sub-Saharan Africa, math and science learning materials incorporating the local language and culture are generated and sent to the user's device.

[1969] Learning progress and feedback

[1970] Terminal

[1971] When a user works on a problem and answers it, the device records the answer and sends it to the server.

[1972] server

[1973] The server analyzes the received answer data and determines the user's accuracy rate and answer trends. Based on the analysis results, the server updates the study plan in real time and generates additional learning materials to address the user's weaknesses. For example, if a user solves arithmetic problems and finds that they answered 90% of the questions correctly but made mistakes on some geometry-related questions, the server will generate supplementary geometry-related learning materials and incorporate them into the next study plan.

[1974] teacher

[1975] Teachers can check the user's learning progress and misunderstandings on a dedicated screen and enter feedback as needed. The server sends this feedback to the user's device and notifies the user in real time.

[1976] Interactive and conversational lessons

[1977] Terminal

[1978] When a user asks a question using a voice recognition device, the terminal analyzes the voice and sends the question to the server.

[1979] server

[1980] The server analyzes the user's question, generates the necessary information and answers, and sends them to the device. The speech recognizer then verbally conveys this information to the user. For example, if a user asks about the Pythagorean theorem, the device sends the question to the server, which returns an appropriate explanation and example problem. The speech recognizer then explains the problem to the user and provides additional problems to further deepen their understanding.

[1981] Updates to teaching materials

[1982] server

[1983] If the content of textbooks or courses changes, the new information is automatically uploaded to the server and immediately reflected in each user's educational plan. For example, if a new historical fact is discovered and added to the educational curriculum, the server updates each user's educational plan based on this new information and sends new learning materials to their device.

[1984] Prompt Sentence Examples

[1985] Curriculum generation: "Create digital learning materials that are appropriate for a 12-year-old from Sub-Saharan Africa. Please consider the user's visual learning style and incorporate local language and culture."

[1986] Interactive Lessons: "Explain the Pythagorean Theorem in detail and provide additional questions to help students understand."

[1987] As described above, this system has the ability to generate individual educational plans based on specific user information and update them in real time, while also providing interactive, dialogue-based education to ensure an effective learning experience.

[1988] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1989] Step 1:

[1990] The user enters information from the device

[1991] The user accesses a terminal and enters information into a form, such as name, age, grade, ethnic and cultural background, learning method, and existing learning level.

[1992] (Input) Data about the user's personal information and learning style.

[1993] (Output) The input data is temporarily saved on the device.

[1994] Step 2:

[1995] The device sends the information to the server

[1996] The terminal converts the information entered by the user into packets and transmits them to the server.

[1997] (Input) User information entered into the terminal.

[1998] (Output) Information is sent to the server.

[1999] Step 3:

[2000] The server receives the information and stores it in a database

[2001] The server analyzes the user information received from the terminal and stores it in a database.

[2002] (Input) User information sent from the terminal.

[2003] (Output) The parsed user information is saved in the database.

[2004] Step 4:

[2005] The server analyzes user information and generates an individualized education plan

[2006] The server analyzes the stored user information using a generative AI model to generate an individualized educational plan.

[2007] (Input) User information stored in the database.

[2008] (Output) The generated individualized education plan.

[2009] Step 5:

[2010] The server sends the educational plan to the device.

[2011] The server transmits the generated individual education plan to the terminal.

[2012] (Input) Generated individualized education plan.

[2013] (Output) The teaching plan is transferred to the terminal.

[2014] Step 6:

[2015] The user works through the questions and enters the answers

[2016] Users work on the digital learning materials provided on their terminals and input answers to the questions.

[2017] (Input) The question and the user's answer displayed on the terminal.

[2018] (Output) Answer data is temporarily saved on the device.

[2019] Step 7:

[2020] The device sends the answer to the server

[2021] The terminal transmits the saved answer data to the server.

[2022] (Input) User's answer data.

[2023] (Output) The answer data is sent to the server.

[2024] Step 8:

[2025] The server analyzes the answer data

[2026] The server analyzes the received answer data, determines the user's accuracy rate and answer trends, and processes the data using a generative AI model.

[2027] (Input) User's answer data.

[2028] (Output) Analysis results.

[2029] Step 9:

[2030] The server updates the educational plan in real time

[2031] Based on the analysis results, the server updates the study plan in real time and generates additional learning materials to fill in the user's weaknesses.

[2032] (Input) Analysis results.

[2033] (Output) Updated lesson plans and generated additional teaching materials.

[2034] Step 10:

[2035] The server sends the updated lesson plan and additional materials to the device.

[2036] The server sends updated lesson plans and additional teaching materials to the terminal.

[2037] (Input) Updated teaching plans and additional materials.

[2038] (Output) The lesson plan and additional materials are sent to the terminal.

[2039] Step 11:

[2040] User asks a question to the smart speaker

[2041] The user speaks a question using a voice recognition device.

[2042] (Input) The user's spoken question.

[2043] (Output) The device recognizes the voice data.

[2044] Step 12:

[2045] The device analyzes the voice and sends it to the server

[2046] The terminal analyzes the user's voice data as text data and sends it to the server.

[2047] (Input) Audio data.

[2048] (Output) The parsed text data is sent to the server.

[2049] Step 13:

[2050] The server analyzes the question and generates the answer

[2051] The server analyzes the received question and generates an appropriate answer using a generative AI model.

[2052] (Input) Parsed text data.

[2053] (Output) The generated answer.

[2054] Step 14:

[2055] The server sends the answer to the device

[2056] The server sends the generated answer to the terminal.

[2057] (Input) The generated answer.

[2058] (Output) The answer is sent to the device.

[2059] Step 15:

[2060] The device provides answers by voice

[2061] The terminal provides the received answer to the user through a voice recognition device.

[2062] (Input) The answer sent from the server.

[2063] (Output) The answer provided aloud.

[2064] (Application example 1)

[2065] 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."

[2066] Conventional skills training systems for factory operators have had difficulty quickly and effectively providing appropriate learning curricula tailored to individual skill levels and experience. Furthermore, they lacked the functionality to analyze learning progress in real time and provide feedback, making it extremely difficult to improve operators' skills. Furthermore, they lacked the functionality to provide interactive, dialogue-based lessons, making it difficult to immediately respond to operators' questions or problems.

[2067] 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.

[2068] In this invention, the server includes means for collecting specific user information and generating an individual learning curriculum based on the user information, means for recording and analyzing answer data for questions answered by the user, means for updating the learning plan in real time based on the analysis results, terminal means including a smart speaker for providing interactive dialogue-based lessons, means for generating a learning curriculum based on the skill level and past training data of the factory operator, means for analyzing the operator's learning progress in real time and providing feedback, means for generating additional learning materials based on the feedback, and means for responding to the learner's questions through the smart speaker. This makes it possible to provide effective training tailored to the individual skill level of the factory operator and enable rapid skill improvement through real-time progress analysis and feedback.

[2069] "Specific user information" is information necessary to identify a user and is data used to generate an individualized learning curriculum.

[2070] An "individualized learning curriculum" is a plan created based on specific user information and including learning content that is optimal for that user.

[2071] "Answer data" is data that records the results and trends of questions answered by users.

[2072] The "analysis results" are the results of analyzing the answer data, and are the basic information for updating the user's study plan.

[2073] A "smart speaker" is a device that interacts with users through a voice interface, providing information and instructions via voice.

[2074] "Terminal means" refers to the device that a user uses to interact with the system, including smart speakers, computers, tablets, etc.

[2075] "Factory operator" refers to an employee who operates and manages machinery and equipment at a manufacturing site.

[2076] "Skill level" is an indicator of an operator's technical proficiency in a particular task.

[2077] "Training data" refers to data that records the content and results of past training.

[2078] "Feedback" is information that provides evaluation and advice on the results of learning or work.

[2079] "Additional learning materials" are learning materials provided to supplement the learning based on the user's learning progress and analysis results.

[2080] A specific embodiment of a learning system for factory operators based on the present invention and its processing flow are described below. This system has the function of collecting specific user information and generating an individual learning curriculum based on that information. It also has the function of recording and analyzing answer data from questions answered by the user and updating the learning plan in real time based on the analysis results. Furthermore, the system features terminal means including a smart speaker for providing interactive, dialogue-based lessons.

[2081] Collection of user information and profile registration

[2082] server

[2083] The server receives information entered by the user from the terminal and stores it in a database. For example, the operator enters their name, age, skill level, past training data, etc.

[2084] Specific examples

[2085] A 30-year-old factory operator enters his or her name, age, entry-level skills, and past training data, and the server stores that information in a database.

[2086] Creating personalized learning curriculum

[2087] server

[2088] The server analyzes the stored user information and generates an optimal learning curriculum for each operator. The generated curriculum is created as digital learning materials based on past training data and skill level.

[2089] Specific examples

[2090] The server generates teaching materials for beginners, such as welding techniques and machine operation, for a 30-year-old beginner operator, and sends the materials to the user's terminal.

[2091] Learning progress and feedback

[2092] Terminal

[2093] As the user works through the questions and answers, the answers are recorded and sent to the server.

[2094] server

[2095] The server analyzes the answer data to determine the user's accuracy rate and answer trends. Based on the analysis results, the server updates the learning plan in real time and generates additional learning materials to fill in the operator's weaknesses.

[2096] Specific examples

[2097] If a 30-year-old operator solves machine operation problems and gets 90% correct, but makes mistakes on some questions related to changing settings, the server will generate supplementary learning materials related to changing settings and incorporate them into the next learning plan.

[2098] Interactive and conversational lessons

[2099] Terminal

[2100] When a user speaks a question to a smart speaker, the voice is analyzed and the question is sent to the server.

[2101] server

[2102] The server analyzes the user's question, generates the necessary information and answers, and sends them to the device, which then relays the information to the user via voice.

[2103] Specific examples

[2104] When a factory operator asks, "Please teach me basic welding techniques," the device sends the question to the server, which then returns appropriate explanations and training materials. The smart speaker then explains the information to the operator aloud and provides further training methods.

[2105] Hardware and Software

[2106] Server: Cloud server (e.g. AWS, Google Cloud)

[2107] Database: MySQL, PostgreSQL

[2108] AI analysis engine: GPT-4

[2109] Devices: Smart speakers (e.g., Amazon Echo, Google Home), factory robots, operator devices (PCs and tablets)

[2110] Examples and prompts

[2111] Specific examples

[2112] A 30-year-old novice operator needs to be trained in a new welding technique.

[2113] The operator asks the smart speaker, "Please tell me about the basic techniques of welding."

[2114] Prompt statement

[2115] User information: 'Name: Ichiro Tanaka, Age: 30, Skill level: Beginner, Past training data: []'. Please generate a learning curriculum appropriate for this user.

[2116] Question: 'Please tell me about the basic techniques of welding'. Please provide a suitable answer.

[2117] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2118] Step 1: Enter and submit user information

[2119] The user inputs information such as their name, age, skill level, and past training data from the terminal, and this input data is sent from the terminal to the server.

[2120] concrete action

[2121] Input: Name, age, skill level, past training data

[2122] Data processing: Convert each item into JSON format

[2123] Output: User information sent to the server

[2124] Example: Name: Yamada Taro, Age: 35, Skill Level: Intermediate, Training Data: []

[2125] Step 2: Save user information

[2126] The server stores the received user information in a database, which is then used to generate a personalized learning curriculum.

[2127] concrete action

[2128] Input: User information sent from the device (JSON format)

[2129] Data processing: Converting data into SQL statements for saving to the database

[2130] Output: User information stored in the database

[2131] Destination: Database (MySQL, PostgreSQL)

[2132] Step 3: Create a personalized learning curriculum

[2133] The server analyzes the stored user information and generates an individual learning curriculum using a generative AI model (GPT-4). The generated curriculum is then sent to the user's device as digital learning materials.

[2134] concrete action

[2135] Input: User information retrieved from the database

[2136] Data processing: Prompt generation and input to GPT-4

[2137] Output: Personalized learning curriculum

[2138] Example prompt: "User information: {'Name': 'Yamada Taro', 'Age': 35, 'Skill level': 'Intermediate', 'Training data': []}. Please generate a learning curriculum appropriate for this user."

[2139] AI used: GPT-4

[2140] Send the generated curriculum to your device

[2141] Step 4: Record your learning progress

[2142] When a user works on a problem and answers it on the terminal, the answer data is recorded by the terminal and transmitted to the server.

[2143] concrete action

[2144] Input: User's answer data

[2145] Data processing: Recording correct and incorrect answers for each answer and generating data for trend analysis

[2146] Output: Answer data sent to the server

[2147] Example: Question ID: 123, Answer: "A", Correct Answer: true

[2148] Step 5: Analyze the answer data and provide feedback

[2149] The server analyzes the received answer data to determine the accuracy rate and answer trends. Based on the analysis results, it updates the learning plan in real time and generates additional learning materials to fill in the operator's weaknesses.

[2150] concrete action

[2151] Input: Answer data sent from the device

[2152] Data processing: Correct answer rate calculation and trend analysis

[2153] Output: Updated learning plan and feedback

[2154] AI used: GPT-4

[2155] Example prompt for generating additional learning materials: "Answer data: [{'Question ID': 123, 'Answer': 'A', 'Correct Answer': true}]. Analyze learning progress and provide feedback.

[2156] Step 6: Interactive and interactive lessons

[2157] When a user speaks a question to a smart speaker, the voice data is analyzed and the question is sent to the server. The server analyzes the question, generates the necessary information and answer, and sends it to the device. The smart speaker then conveys that information by voice.

[2158] concrete action

[2159] Input: A spoken question from the user

[2160] Data processing: speech recognition and text conversion, answer generation using GPT-4

[2161] Output: A spoken response to the user

[2162] AI used: GPT-4

[2163] Example prompt: "Question: 'Tell me about basic welding techniques.' Please provide an appropriate answer."

[2164] Example speech output: "The basic technique of welding is..."

[2165] Step 7: Distribute generated materials and update learning plans

[2166] The server sends the generated additional learning materials and updated study plans to the user's device, and the user continues studying based on the new study plans.

[2167] concrete action

[2168] Input: Updated study plans and additional materials

[2169] Data processing: Converting data to send to the user's device

[2170] Output: Push notifications and delivery of educational materials to users' devices

[2171] Communication method: Data transmission via the Internet

[2172] Example delivery: "New learning plans are available. Check them out in the next session."

[2173] As described above, the system provides factory operators with individual learning curricula, performs real-time progress analysis and feedback, and supports efficient skill development through interactive, dialogue-based lessons.

[2174] 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.

[2175] A specific embodiment of the system according to the present invention and its processing flow will be described below.

[2176] The system has the functions of collecting specific user information and generating an individual learning curriculum based on that information, recording and analyzing the answers given by the user to questions, updating the learning plan in real time based on the analysis results, and providing device functions including a smart speaker that provides interactive lessons.It also has an emotion engine that recognizes the user's emotions.

[2177] (Collection of user information and profile registration)

[2178] server

[2179] The server receives information entered by the user from the device and stores it in a database, such as the user's name, age, grade level, ethnic and cultural background, learning style, and existing learning level.

[2180] Specific examples

[2181] A 12-year-old user enters their name, age, ethnic background (e.g., from Sub-Saharan Africa), visual learning style, etc., and the server stores this information in a database.

[2182] (Generating personalized learning curriculum)

[2183] server

[2184] The server analyzes the stored user information and generates an optimal learning curriculum for each individual learner. This curriculum is created as digital learning materials based on the content of compulsory education and the user's cultural background.

[2185] Specific examples

[2186] The server generates mathematics and science learning materials incorporating local language and culture for 12-year-old users from sub-Saharan Africa and sends the materials to the users' devices.

[2187] (Learning progress and feedback)

[2188] Terminal

[2189] As the user works through the questions and answers, the terminal records the answers and sends them to the server.

[2190] server

[2191] The server analyzes the received answer data to determine the user's accuracy rate and answer trends. Based on the analysis results, it updates the study plan in real time and generates additional learning materials to fill in the user's weak points.

[2192] Specific examples

[2193] If a 12-year-old user solves math problems and finds that he gets 90% of the answers right but makes mistakes on some geometry-related questions, the server will generate supplementary geometry-related learning materials and incorporate them into his next learning plan.

[2194] teacher

[2195] Teachers can check the user's learning progress and misunderstandings on a dedicated screen and enter feedback as needed. The server sends this feedback to the user's device and notifies the user in real time.

[2196] (Interactive dialogue-based lessons)

[2197] Terminal

[2198] When a user speaks a question to a smart speaker, the device analyzes the voice and sends the question to the server.

[2199] server

[2200] The server analyzes the user's question, generates the necessary information and answers, and sends them to the device, which then relays the information to the user via voice.

[2201] Specific examples

[2202] When a user asks a question about the Pythagorean theorem, the device sends the question to the server, which responds with an appropriate explanation and example. The smart speaker then explains it to the user and offers additional questions to further deepen their understanding.

[2203] (Utilizing emotion engines)

[2204] Terminal

[2205] The device detects the emotions expressed by the user through facial expressions and tone of voice while learning, and sends this data to the emotion engine.

[2206] Server (emotion engine)

[2207] The emotion engine analyzes the data sent from the terminal and determines the user's emotional state (e.g., interest, fatigue, frustration, etc.).

[2208] Specific examples

[2209] If the user shows signs of fatigue while studying, the emotion engine will analyze this information and suggest that the user take a break, a suggestion that will be delivered audibly through the smart speaker.

[2210] (Teaching material updates)

[2211] server

[2212] If the content of the textbook or the course changes, the new information is automatically uploaded to the server and immediately reflected in each user's learning plan.

[2213] Specific examples

[2214] When new historical facts are discovered and added to the educational curriculum, the server updates each user's learning plan based on this new information and sends new learning materials to the device.

[2215] (Feedback optimization using emotion engine)

[2216] Server (emotion engine)

[2217] The emotion engine automatically generates feedback and support messages based on the user's emotional state, which are delivered via a smart speaker with the goal of improving the user's learning efficiency.

[2218] Specific examples

[2219] If the user is interested, the emotion engine will provide additional challenges or relevant information to keep them engaged, or if they are frustrated, it will suggest hints or quick solutions to their problems.

[2220] In this way, this system achieves smooth information exchange between the server, terminals, and users, providing an effective learning experience even in areas with inadequate educational environments. The addition of an emotion engine provides optimal support according to the user's emotional state, improving learning efficiency and motivation.

[2221] The processing flow will be explained below.

[2222] Step 1:

[2223] User: The user installs and launches the app. On first launch, the user enters profile information such as name, age, grade level, ethnic and cultural background, learning style, and existing learning level.

[2224] Step 2:

[2225] Terminal: Collects profile information entered by the user and sends it to the server.

[2226] Step 3:

[2227] Server: The server stores the received user information in a database.

[2228] Step 4:

[2229] Server: The server analyzes the stored user information and generates an individualized learning curriculum based on the user's characteristics and learning style. The generated curriculum includes the content of the compulsory education curriculum and supplementary materials tailored to the user's cultural background.

[2230] Step 5:

[2231] Server: Prepares the generated learning curriculum as digital learning materials and sends them to the user's device.

[2232] Step 6:

[2233] Terminal: Notifies the user of the received learning curriculum and displays it.

[2234] Step 7:

[2235] User: The user studies according to the provided learning curriculum. When solving a problem, the user inputs the answer.

[2236] Step 8:

[2237] Terminal: Records the user's answers and sends the data to the server.

[2238] Step 9:

[2239] Server: Analyzes the received answer data and determines the user's correct answer rate and answer trends.

[2240] Step 10:

[2241] Server: Updates the user's study plan in real time based on the analysis results, automatically generating additional learning materials and supplementary questions as needed.

[2242] Step 11:

[2243] Server: Sends the updated learning plan to the user's device and notifies them.

[2244] Step 12:

[2245] Device: Display the updated learning plan to the user.

[2246] Step 13:

[2247] Teacher: The teacher can check the user's learning progress and misunderstandings from a dedicated screen. If necessary, the teacher can enter feedback.

[2248] Step 14:

[2249] Server: Receives teacher feedback and sends it to the user's device.

[2250] Step 15:

[2251] Device: Displays received teacher feedback to the user.

[2252] Step 16:

[2253] User: If the user has any questions while studying, they can ask them by voice via a smart speaker.

[2254] Step 17:

[2255] Terminal: Analyzes the user's voice question and sends the question to the server.

[2256] Step 18:

[2257] Server: Analyzes the question, generates the necessary information and answers, and sends them to the device.

[2258] Step 19:

[2259] Terminal: Provides users with answers to questions via a smart speaker.

[2260] Step 20:

[2261] Terminal: Collects emotional information from the user's voice and facial expressions and sends that data to the server.

[2262] Step 21:

[2263] Server (emotion engine): Analyzes the emotion information sent from the device and determines the user's emotional state (e.g., interest, fatigue, frustration, etc.).

[2264] Step 22:

[2265] Server (Emotion Engine): Adjusts learning curriculum and feedback based on the user's emotional state. For example, it suggests a break if the user is tired, or provides additional relevant information if the user shows interest.

[2266] Step 23:

[2267] Server (emotion engine): Sends automatically generated feedback and support messages to the device.

[2268] Step 24:

[2269] Terminal: Provides users with feedback and support messages from the emotion engine via a smart speaker.

[2270] Step 25:

[2271] Server: When the content of the educational curriculum or textbooks changes, the new information is uploaded to the database and each user's learning plan is automatically updated.

[2272] Step 26:

[2273] Server: Sends the updated learning plan to the user's device and notifies them.

[2274] Step 27:

[2275] Device: Display new learning materials and updated curriculum to users.

[2276] Example 2

[2277] 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."

[2278] Previous educational systems lacked detailed learning support tailored to individual users' cultural backgrounds and learning styles, and the lack of real-time feedback limited the effectiveness of learning. Furthermore, the lack of a mechanism for reflecting users' emotions in the learning process made it difficult to improve learning efficiency and motivation.

[2279] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for collecting specific user information and generating an individual learning curriculum based on the user information; means for recording and analyzing answer data of questions answered by the user; means for updating the learning plan in real time based on the analysis results; voice communication terminal means for providing interactive dialogue-based lessons; and means including an emotion engine for recognizing user emotions and analyzing emotion data to provide learning support. This makes it possible to provide a learning curriculum optimized for each user, real-time feedback according to learning progress, and appropriate support based on the user's emotional state.

[2280] "Specific User Information" is information provided by a user regarding their name, age, grade level, ethnic and cultural background, learning style, and existing learning level.

[2281] An "individual learning curriculum" is a collection of educational content and learning materials optimized for each user based on collected user information.

[2282] "Answer data" is a record of the answers to questions that the user answered while studying.

[2283] "Updating in real time" means immediately reviewing the learning plan based on the progress of learning and analysis results, and providing instruction based on the latest information.

[2284] An "interactive dialogue-based lesson" is a two-way lesson format in which users ask and answer questions via voice communication terminals, and the system provides appropriate feedback and explanations.

[2285] "Voice communication terminal" refers to a device that enables voice communication, specifically a smart speaker.

[2286] The "emotion engine" is part of a system that analyzes the user's emotional state and provides learning support and feedback based on the results of that analysis.

[2287] The "Educator-only screen" is an interface that allows educators to view and manage learning status and analysis results.

[2288] The present invention is a system that collects specific user information and generates an individual learning curriculum based on that user information. This system is realized through the exchange of information between a server, a terminal, and a user.

[2289] 1. Collection of User Information and Profile Registration

[2290] server

[2291] The server receives information entered by the user from their device and stores it in a database. The information entered by the user includes name, age, grade, ethnic and cultural background, learning style, and existing learning level. This information serves as the basis for generating a learning curriculum optimized for each user.

[2292] Examples:

[2293] Users enter information such as "from Sub-Saharan Africa, 12 years old, visual learning style," and the server stores this in a database.

[2294] 2. Creating an individualized learning curriculum

[2295] server

[2296] The server analyzes the stored user information and generates an optimal learning curriculum for each user. This curriculum is in line with the educational curriculum and is adapted to the user's cultural background and learning style. The generated digital learning materials are sent to the user's device.

[2297] Examples:

[2298] The server generates "math and science learning materials appropriate to the background of 12-year-old users from sub-Saharan Africa" ​​and sends them to the device.

[2299] 3. Learning progress and feedback

[2300] Terminal

[2301] The user works on the problems and inputs the answers into the terminal, which records the answer data and transmits it to the server in real time.

[2302] Examples:

[2303] When the user "solves an arithmetic problem and enters the answer," the device records the data sequentially and sends it to the server.

[2304] server

[2305] The server analyzes the answer data to determine the user's accuracy rate and answer trends. Based on the analysis results, it generates a new study plan and creates supplementary materials to strengthen weak points.

[2306] Examples:

[2307] The server "generates supplementary geometry learning materials for users who make many mistakes on geometry problems" and incorporates them into the next learning plan.

[2308] teacher

[2309] Teachers can check the user's learning progress on a dedicated screen and enter feedback as needed, which is then sent to the user's device via the server.

[2310] Examples:

[2311] The teacher "enters additional explanations for specific problems," which are then sent to the user's device in real time.

[2312] 4. Interactive and conversational lessons

[2313] Terminal

[2314] When a user asks a question by voice through a smart speaker, the device analyzes the voice and sends the question to the server.

[2315] server

[2316] The server analyzes the question, generates the necessary information and answers, and sends them to the device, which then relays the information to the user via voice.

[2317] Examples:

[2318] When a user "asks a question about the Pythagorean theorem, the server generates a detailed explanation and examples," which the smart speaker then relays to the user.

[2319] 5. Emotion recognition and support with emotion engine

[2320] Terminal

[2321] The device recognizes the emotions expressed by the user through facial expressions and tone of voice during learning and sends this data to the emotion engine.

[2322] Examples:

[2323] The device captures statements and facial expressions that indicate fatigue while the user is studying and sends them to the emotion engine.

[2324] Server (emotion engine)

[2325] The emotion engine analyzes the received data, determines the user's emotional state, and generates support and suggestions according to that state.

[2326] Examples:

[2327] The emotion engine "generates messages suggesting a break for users who feel tired" and notifies them through a smart speaker.

[2328] 6. Updating teaching materials

[2329] server

[2330] When textbook content or curriculum changes, the new information is automatically uploaded to the server, which instantly updates each user's learning plan.

[2331] Examples:

[2332] When new historical facts are added, the server updates the user's study plan based on that information and sends the new learning materials to the device.

[2333] 7. Optimizing feedback with an emotion engine

[2334] Server (emotion engine)

[2335] The emotion engine automatically generates feedback and support messages based on the user's emotional state, and the feedback is delivered via a smart speaker.

[2336] Examples:

[2337] The emotion engine "provides additional challenges and related information to interested users," which the smart speaker then relays audibly. Conversely, "if users are frustrated, the engine will suggest hints and easy solutions to the problem."

[2338] Example prompts for generative AI models

[2339] Below are some specific examples of prompts for the generative AI model.

[2340] Text format:

[2341] "Generate additional study materials to supplement the user's weak points based on the answer data of the problems the user has solved."

[2342] "How can I generate personalized learning curriculum that takes into account the cultural background of my users?"

[2343] "Use an emotion engine to generate feedback messages to improve user learning efficiency."

[2344] The above is a specific method for implementing the system of the present invention, which enables the provision of a learning curriculum optimized for each user, real-time feedback according to the learning progress, and appropriate support based on the user's emotional state.

[2345] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2346] Step 1: Enter and save user information

[2347] Input: The user enters information such as name, age, grade, ethnic and cultural background, learning style, and existing learning level from the terminal.

[2348] Operation: The terminal transmits the information entered by the user to the server in real time.

[2349] Output: The server stores the received user information in a database. The user information serves as the basis for subsequent curriculum generation and analysis.

[2350] Specific behavior:

[2351] The user enters information such as "from Sub-Saharan Africa, 12 years old, visual learning style," and the device records this and sends it to the server, which stores the information in a database.

[2352] Step 2: Create a personalized learning curriculum

[2353] Input: User information stored on the server (such as name, age, ethnic and cultural background, learning style, existing learning level, etc.).

[2354] How it works: The server analyzes user information and generates an optimal learning curriculum for each user. This analysis can be performed using a generative AI model.

[2355] Output: The generated learning curriculum is sent to the user's device as digital learning materials.

[2356] Specific behavior:

[2357] The server generates "math and science learning materials appropriate to the background of 12-year-old users from sub-Saharan Africa" ​​and sends them to the device.

[2358] Step 3: Record your learning progress and answer data

[2359] Input: The user answers the question and enters the answer into the terminal.

[2360] Operation: The terminal records the answer data entered by the user and transmits it to the server in real time.

[2361] Output: The server stores the received answer data.

[2362] Specific behavior:

[2363] When the user "solves an arithmetic problem and enters the answer," the device records the data sequentially and sends it to the server.

[2364] Step 4: Analyze the answer data and update the study plan

[2365] Input: Answer data stored on the server.

[2366] How it works: The server analyzes the answer data to determine the user's accuracy rate and answer trends. Based on the analysis results, it updates the study plan in real time and generates supplementary learning materials as needed.

[2367] Output: Send the new learning plan and supplementary materials to the user's device.

[2368] Specific behavior:

[2369] The server "generates supplementary geometry learning materials for users who make many mistakes on geometry problems" and incorporates them into the next learning plan.

[2370] Step 5: Teacher review and feedback on learning progress

[2371] Input: User learning progress and analysis results displayed on the educator-only screen.

[2372] How it works: The teacher checks the user's learning progress and trends in misunderstandings on a dedicated screen and provides feedback as needed.

[2373] Output: The feedback is sent to the user's device via the server.

[2374] Specific behavior:

[2375] The teacher "enters additional explanations for specific problems," which are then sent to the user's device in real time.

[2376] Step 6: Conduct interactive and dialogue-based lessons

[2377] Input: The user enters a question by voice through a smart speaker.

[2378] How it works: The device analyzes the voice and sends the question to the server. The server analyzes the question, generates the necessary information and answers, and sends them to the device.

[2379] Output: The smart speaker will verbally communicate the generated information to the user.

[2380] Specific behavior:

[2381] When a user "asks a question about the Pythagorean theorem, the server generates a detailed explanation and examples," which the smart speaker then relays to the user.

[2382] Step 7: Emotion recognition and support with the emotion engine

[2383] Input: Emotion data expressed by the user through facial expressions and vocal tones during training.

[2384] How it works: The device senses emotion data and sends it to the emotion engine, which analyzes the data and determines the user's emotional state.

[2385] Output: Support and suggestions based on the user's emotional state are generated and communicated through a smart speaker.

[2386] Specific behavior:

[2387] The emotion engine "generates messages suggesting a break for users who feel tired" and notifies them through a smart speaker.

[2388] Step 8: Update your materials

[2389] Input: New textbook content and curriculum information.

[2390] How it works: The server automatically uploads new information and updates each user's study plan.

[2391] Output: The updated lesson plan and new learning materials are sent to the user's device.

[2392] Specific behavior:

[2393] When new historical facts are added, the server updates the user's study plan based on that information and sends the new learning materials to the device.

[2394] Step 9: Optimizing feedback with an emotion engine

[2395] Input: The user's emotional state during learning.

[2396] How it works: The emotion engine generates appropriate feedback and support messages based on the user's emotional state.

[2397] Output: Optimized feedback and assistance messages are provided to the user through a smart speaker.

[2398] Specific behavior:

[2399] The emotion engine "provides additional challenges and related information to interested users," which the smart speaker then relays audibly. Conversely, "if users are frustrated, the engine will suggest hints and easy solutions to the problem."

[2400] (Application example 2)

[2401] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2402] Conventional learning systems have difficulty generating and updating individual curricula based on the characteristics and learning progress of each user, and also have difficulty providing feedback based on the user's emotional state. As a result, there are problems with reduced learning efficiency and motivation.

[2403] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for collecting specific user information and generating an individual curriculum based on the user information; means for recording and analyzing answer data of questions answered by the user; means for updating the plan in real time based on the analysis results; terminal means including a voice recognition device for providing interactive lessons; and means including an emotion engine for analyzing the user's emotional state and providing feedback based on the analysis results. This makes it possible to provide an individually optimized learning curriculum and effective feedback according to the user's emotions.

[2404] "Specific User Information" refers to a user's individual characteristics, such as the user's name, age, grade level, ethnic and cultural background, learning style, and existing learning level.

[2405] "Personalized Curriculum" refers to learning content and progression plans optimized based on specific user information.

[2406] "Answer data" refers to the answer information entered by the user in response to the study question.

[2407] "Analysis results" refers to the results of analyzing the user's learning situation and tendencies based on collected answer data.

[2408] "Real-time plan updating" refers to the process of reviewing and optimizing the learning progress plan at any time based on the analysis results.

[2409] "Interactive lessons" refers to a type of lesson in which users and systems exchange information two-way through audio and visual means to advance learning.

[2410] A "voice recognizer" refers to a device that analyzes a user's speech, recognizes its content, and generates a response.

[2411] "Emotional state" refers to a psychological state, such as interest, fatigue, or frustration, that can be inferred from a user's facial expression, tone of voice, or behavior.

[2412] An "emotion engine" refers to a software component that analyzes a user's emotional state and generates appropriate feedback and support messages based on that state.

[2413] The system of the present invention includes functions for collecting user information, generating an individual curriculum based on that information, recording and analyzing user answer data, and updating the plan in real time based on the analysis results. It also includes terminal means including a voice recognition device that provides interactive lessons, and an emotion engine that analyzes the user's emotional state and provides feedback.

[2414] System program generation

[2415] 1. User Information Collection:

[2416] The server receives information entered by the user through a smartphone or smart glasses, such as name, age, grade, learning style, and current learning level, and stores it in a database, allowing optimization according to the characteristics of each individual user.

[2417] 2. Generating personalized learning curriculum:

[2418] The server analyzes the collected user information and generates an optimal learning curriculum for the user, which is customized to meet the user's individual learning needs.

[2419] 3. Learning progress and feedback:

[2420] When a user answers a question, the device records the answer data and sends it to the server, which then analyzes the received answer data, evaluates the user's progress and learning trends, and updates the learning plan in real time, while providing appropriate feedback to the user.

[2421] 4. Providing interactive lessons:

[2422] The system allows two-way dialogue with users via a voice recognition device, and when a user asks a specific question, the system analyzes the question and provides appropriate answers and additional learning materials. This interactive lesson is conducted via a smart speaker or head-mounted display.

[2423] 5. Leveraging the Emotion Engine:

[2424] The device's camera and microphone detect the user's emotional state and send the data to the emotion engine, which then generates appropriate feedback and support messages based on the analysis results. For example, if the user feels fatigued while studying, the engine suggests taking a break.

[2425] Hardware and software used

[2426] Hardware

[2427] Smartphone

[2428] Smart Glasses

[2429] head-mounted display

[2430] smart speaker

[2431] software

[2432] Database Management Systems

[2433] Voice Recognition Software

[2434] Emotion Engine

[2435] Curriculum Generation Engine (CurriculumGenerator)

[2436] Specific examples

[2437] As a concrete example of collecting user data, consider a 12-year-old user who inputs information into the system, such as their name, age, ethnic background (e.g., from Sub-Saharan Africa), and visual learning style. The system uses this information to provide learning materials that are appropriate for the user's cultural background. For example, if the user uses a smart speaker to ask about "Pythagoras' Theorem," the system can provide an appropriate explanation and offer additional learning tasks.

[2438] Prompt Sentence Examples

[2439] "What support message should be generated if the user shows fatigue during learning?"

[2440] "If a 12-year-old user asks about the Pythagorean theorem, provide a concise explanation and generate additional tasks to further increase interest."

[2441] This will enable us to provide an effective learning experience even in areas where the educational environment is inadequate.

[2442] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2443] Step 1:

[2444] The server collects user information. The user inputs information such as name, age, grade, ethnic and cultural background, learning style, and current learning level through a smartphone or smart glasses. This information is sent by the device to the server and stored in a database. The input is user information, and the output is the saved user profile.

[2445] Step 2:

[2446] The server generates an individual learning curriculum based on the collected user information. This involves retrieving user information from a database and generating appropriate learning materials and curriculum based on that information. The input is a user profile, and the output is an individually optimized learning curriculum.

[2447] Step 3:

[2448] The device records the answer data of the questions answered by the user and sends it to the server. When the user answers a study question through the device, the question and answer data are temporarily saved on the device and periodically sent to the server. The input is the answer data, and the output is the study record sent to the server.

[2449] Step 4:

[2450] The server analyzes the received answer data. It uses a specific algorithm to analyze the user's accuracy rate and answer trends, and derives each user's strengths and weaknesses. The input is the answer data, and the output is the analysis results.

[2451] Step 5:

[2452] The server updates the study plan in real time based on the analysis results. It generates a new study plan that reflects the analysis results and sends it to the user's device. This new plan includes content that strengthens the user's weaknesses. The input is the analysis results, and the output is the updated study plan.

[2453] Step 6:

[2454] To provide interactive lessons, the terminal uses a voice recognition device to accept questions from users. When a user inputs a question by voice, the voice data is analyzed, converted into text data, and sent to the server. The input is voice data, and the output is text data.

[2455] Step...

Claims

1. means for collecting specific user information and generating an individual learning curriculum based on the user information; A means for recording and analyzing answer data of questions answered by the user; means for updating the learning plan in real time based on the analysis results; a terminal means including a smart speaker for providing interactive dialogue lessons; A system including:

2. 10. The system of claim 1, wherein the user information includes ethnic and cultural background, learning style, and existing learning level.

3. 2. The system according to claim 1, wherein the server includes means for providing a teacher-only screen and displaying the user's learning progress and tendency of misunderstandings.

Images