System

Abstract

To provide a system which solves the problem of labor shortage and realizes rational and effective learning guidance.SOLUTION: A learning support system includes a means for inputting information such as a target of a student, a current academic ability, and a strong or weak field, a means for transmitting the information to a server, a means for storing the information in a database by the server, a means for generating an optimum curriculum based on the stored information by an AI engine, a means for storing the generated curriculum in the database, a means for receiving a question from the student by using a tablet terminal and transmitting the question to the AI engine, a means for generating a response to the question by the AI engine and returning the response to the student, a means for analyzing a response of the student in real time and transmitting the information to the server, a means for adjusting a learning content of the student in real time by the AI engine, and a means for sharing progress data of the student with a guardian or a private tutor.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] Due to the declining birthrate, cram schools are facing a serious shortage of part-time university student instructors. This has led to a decline in the quality of instruction, resulting in a lack of detailed instruction for each student. Furthermore, with education costs increasing year by year, there is a demand for streamlined learning methods that allow for individualized instruction, but this is difficult to achieve with existing staff. Therefore, it is necessary to introduce a new system that provides efficient and effective instruction and alleviates the labor shortage. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a private tutoring system that utilizes AI technology. Specifically, information such as a student's goals, current academic ability, and areas of strength and weakness is input, sent to a server, and stored in a database. An AI engine then generates an optimal curriculum based on this information and stores it in the database. Students use tablet devices to take lessons based on the curriculum, and the AI ​​engine generates answers if they ask questions during class. Furthermore, by analyzing students' responses in real time and adjusting the lesson content, flexible instruction can be provided based on the student's level of understanding. Furthermore, by sharing student progress data with parents and cram school staff, it becomes easier to understand the student's learning situation. These measures solve the problem of labor shortages and realize rational and effective learning instruction.

[0006] "Students" refers to children and students who are the recipients of education at cram schools.

[0007] "Objectives" refer to the learning goals and objectives that students are trying to achieve.

[0008] "Current academic ability" refers to a student's current level of knowledge and understanding.

[0009] "Strengths" refer to areas of learning or subjects in which a student excels.

[0010] "Weak areas" refer to areas of learning or subjects in which students have particular difficulty.

[0011] "Information" refers to data such as students' goals, current academic ability, strengths and weaknesses, etc.

[0012] "Server" refers to a computer system used for the purpose of processing and storing information.

[0013] "Database" refers to a system that accumulates and manages information built on a server.

[0014] An "AI engine" refers to software that analyzes data and performs specific tasks based on artificial intelligence technology.

[0015] "Curriculum" refers to an educational plan that defines what students should learn and the order in which they should learn it.

[0016] A "tablet device" refers to a portable computing device that can be operated using a touch screen.

[0017] "Generate" refers to creating new data or results based on certain inputs.

[0018] Taking a "class" means that a student is participating in an educational activity to learn the content.

[0019] "Questions" refer to doubts or clarifications that students raise in order to deepen their understanding.

[0020] "Answer" refers to the answer or explanation provided to a question.

[0021] "Reaction" refers to reactions shown during class, such as students' facial expressions and tone of voice.

[0022] "Analyzing" means examining data in detail to find meaning and patterns.

[0023] "Adjust" refers to changing or modifying the content or methods of lessons according to the situation.

[0024] "Progress data" refers to information about a student's learning progress and achievements.

[0025] "Guardian" means a student's parent or other person with supervisory responsibility.

[0026] "Cram school personnel" refers to staff and instructors involved in the operation and education of cram schools.

[0027] A "system" refers to a collection of multiple elements that function in conjunction with one another. [Brief explanation of the drawings]

[0028] [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

[0029] 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.

[0030] First, the terms used in the following description will be explained.

[0031] 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).

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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."

[0036] [First embodiment]

[0037] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0038] 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.

[0039] 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).

[0040] 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.

[0041] 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.

[0042] 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.

[0043] 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.

[0044] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0045] 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.

[0046] 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.

[0047] 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.

[0048] 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."

[0049] The present invention is a private tutoring system that utilizes artificial intelligence (AI), and the method for realizing this system is explained below. Here, each component, its function, and specific operating procedures are shown.

[0050] First, the cram school staff (users) register a new student in the system. Using a dedicated interface, users input information such as the student's goals, current academic ability, and areas of strength and weakness. The terminal receives this information and sends it to the server. The server stores the received information in a database.

[0051] Next, the server retrieves student information from the database and passes it to the AI ​​engine. The AI ​​engine uses this information to generate an optimal curriculum. The generated curriculum is then saved in the database via the server again.

[0052] Students come to the cram school and take classes using a tablet device. The device retrieves curriculum information from the server and provides the students with lesson materials based on that information. If a student has a question during the actual class, the user (student) inputs the question through the tablet device. The device sends the question to the server, which passes it on to the AI ​​engine. The AI ​​engine generates the optimal answer to the question and sends it to the device via the server. The device returns the generated answer to the student.

[0053] The device also features a system for analyzing students' facial expressions and tone of voice in real time during class. The device analyzes students' reactions and sends the data to a server. The server passes this data to an AI engine, which then adjusts the lesson content based on the analysis results. For example, if a student shows signs of confusion, the AI ​​engine will instruct the teacher to lower the difficulty of the lesson or provide additional explanations.

[0054] Furthermore, all questions and answers during the lesson are stored in a database and taken into consideration when creating the next curriculum, thus providing a set of curriculum that is optimized for each individual student.

[0055] Finally, students' learning progress data is analyzed periodically, and the results are compiled into a report. This report is shared via a server with parents and cram school staff via email, etc. This allows students' progress to be tracked as needed and necessary measures to be taken.

[0056] In this way, the present invention solves the problem of labor shortages while realizing efficient and effective learning instruction that meets individual learning needs.

[0057] The processing flow will be explained below.

[0058] Step 1:

[0059] The user (a cram school staff member) enters information about a new student (goals, current academic ability, areas of strength and weakness, etc.) into a dedicated interface. The device then sends this information to the server.

[0060] Step 2:

[0061] The server stores the received student information in a database, which is used in subsequent processes.

[0062] Step 3:

[0063] The server retrieves student information from the database and passes it to the AI ​​engine, which then generates the optimal curriculum based on this information.

[0064] Step 4:

[0065] The generated curriculum is stored in a database via a server, which allows the curriculum information to be used later.

[0066] Step 5:

[0067] Students attend classes at the cram school using a tablet device. The device retrieves current curriculum information from the server and provides students with the materials they need for class.

[0068] Step 6:

[0069] If a student has a question during class, the user (student) can input the question through a tablet device, which then sends the question to the server.

[0070] Step 7:

[0071] The server passes the question to the AI ​​engine, which generates the optimal answer to the question, and the generated answer is sent to the device via the server.

[0072] Step 8:

[0073] The device displays the generated answer to the user (student), allowing the student to immediately resolve their doubts.

[0074] Step 9:

[0075] During class, the device captures students' reactions in real time for analysis of their facial expressions and tone of voice, and this data is sent to a server.

[0076] Step 10:

[0077] The server passes the student's reaction data to an AI engine, which then adjusts the lesson content based on the analysis results. For example, if a student is confused, it will instruct the AI ​​engine to lower the difficulty of the lesson.

[0078] Step 11:

[0079] All questions and answers are stored in a database, which will be used to create the next curriculum.

[0080] Step 12:

[0081] The AI ​​engine periodically analyzes students' learning progress data and generates progress reports, which are shared with parents and cram school staff via a server.

[0082] Example 1

[0083] 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."

[0084] Conventional individualized learning systems struggled to provide an effective curriculum tailored to each learner's learning progress and level of understanding, making it difficult to maximize learning efficiency. Furthermore, they lacked the means to respond to learners' reactions and questions in real time, making it impossible to provide optimal instruction to each learner. Furthermore, reporting progress to parents and educational facility officials was time-consuming, making it difficult to share information in a timely manner.

[0085] 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.

[0086] In this invention, the server includes: a means for inputting information such as a learner's goals, current academic ability, and areas of strength and weakness; a means for transmitting the information to the server; a means for the server to store the information in a database; a means for an AI engine to generate an optimal curriculum based on the stored information; a means for storing the generated curriculum in a database; a means for a learner to take lessons based on the curriculum using a mobile device; a means for accepting questions from the learner during lessons and transmitting the questions to the AI ​​engine; a means for the AI ​​engine to generate answers to the questions and return the answers to the learner; a means for analyzing the learner's responses (e.g., facial expressions, tone of voice) in real time and transmitting the information to the server; a means for the AI ​​engine to analyze the learner's responses and adjust the lesson content in real time; a means for sharing the learner's progress data with parents and educational facility personnel; and a means for storing the learner's question data and answer data for a certain period of time and utilizing them when creating the next curriculum. This enables the provision of teaching methods optimized for each learner and high learning effectiveness. The ability to quickly and accurately share information with parents and educational facility personnel also enables appropriate management of the learner's learning progress.

[0087] "Learner" refers to an individual who uses the system to receive an education.

[0088] A "server" refers to a computer device that provides specific services or information over a network.

[0089] A "database" refers to a system that stores and manages large amounts of data in an organized manner.

[0090] An "AI engine" refers to a system that uses artificial intelligence technology to analyze data and generate optimal results.

[0091] "Curriculum" refers to a learning plan that is structured based on the learner's educational goals.

[0092] "Mobile devices" refer to electronic devices that are portable and used by learners. Examples include tablets and smartphones.

[0093] "Analyzing in real time" refers to the process of analyzing input information immediately and obtaining results.

[0094] "Progress data" refers to data that indicates the progress and results of a learner's learning activities.

[0095] "Guardian" means the parent or guardian's representative.

[0096] "Educational facility personnel" refers to staff and administrators of the educational institution to which the learner belongs.

[0097] "Question data" refers to information about questions entered by learners.

[0098] "Answer data" refers to information about an answer generated based on question data.

[0099] MODE FOR CARRYING OUT THE INVENTION

[0100] This invention is a personalized tutoring system that utilizes artificial intelligence (AI). This section explains in detail each component and the role they play. This system enables efficient learning instruction tailored to the needs of each learner.

[0101] First, the user registers a new learner using a dedicated web interface. The user enters information into the interface, such as the learner's goals, current academic ability, and areas of strength and weakness, and presses the submit button. At this time, the device receives the entered information and sends it to the server. For example, the user enters "Taro Tanaka, second-year junior high school student, aims to raise his math score by 10 points, his strengths are set theory, and his weaknesses are simultaneous equations." This information is sent to the server, which stores it in a database.

[0102] Next, the server retrieves the learner's information from the database and passes it to the AI ​​engine. The AI ​​engine analyzes the learner's information and generates an optimal curriculum. The generated curriculum is then saved in the database via the server again. For example, based on the information of "Taro Tanaka," the AI ​​engine generates a curriculum of "review of basic mathematics, review of set theory, basics and applications of simultaneous equations, and practice with past exam questions."

[0103] At a cram school, learners attend classes using mobile devices (e.g., tablet devices). The devices connect to a server and obtain curriculum information. Lesson materials are displayed on the device based on the obtained curriculum, and the learner follows along as they study. If a question arises during class, the learner enters it through the device. The device sends the question to the server, which passes it on to an AI engine. The AI ​​engine generates the best answer to the question, and that answer is sent to the device via the server. The device displays the generated answer to the learner.

[0104] The device also has a function for analyzing learners' facial expressions and tone of voice in real time during lessons. The device analyzes the learners' reactions and sends the data to a server. The server passes the data to an AI engine, which then adjusts the lesson content based on the analysis results. For example, if a learner shows a confused expression, the AI ​​engine will issue instructions to lower the difficulty of the lesson, and these instructions will be sent to the device via the server.

[0105] Furthermore, all question and answer data is stored in a database and reflected in the next curriculum creation, providing a set of curriculum optimized for each individual learner.

[0106] Finally, the learner's learning progress data is periodically retrieved from the database by the server and passed to the AI ​​engine. The AI ​​engine analyzes the progress data and generates a report. This report is then emailed to parents and educational institution officials via the server. For example, a progress report summarizing the learner's achievements and challenges can be emailed to parents.

[0107] Example prompt sentence:

[0108] We have a student named "Taro Tanaka" who is in the second year of junior high school. His goal is to raise his math score by 10 points. His current strengths are "set theory" and his weaknesses are "simultaneous equations." Please generate the optimal learning curriculum for him.

[0109] In this way, the present invention is a system that provides efficient and effective learning guidance that meets individual learning needs and achieves high learning results.

[0110] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0111] Program processing flow

[0112] Step 1: Register student information

[0113] Specific behavior:

[0114] The user opens a dedicated web interface.

[0115] The user enters the learner's basic information (name, grade, goal, areas of strength and weakness) and presses the send button.

[0116] The terminal receives this input data. Input: Basic information of the learner. Output: Learner information data sent to the terminal.

[0117] Data processing and calculation:

[0118] The terminal formats the input information and sends it to the server.

[0119] Examples:

[0120] The user enters "Taro Tanaka, second-year junior high school student, increase math score by 10, strong point is set theory, weak point is simultaneous equations" and presses the send button.

[0121] Step 2: Saving to the database

[0122] Specific behavior:

[0123] The server receives the learner information sent from the terminal.

[0124] The server stores the received information in a database. Input: Learner information data. Output: Information stored in the database.

[0125] Data processing and calculation:

[0126] The server stores the received data in a database in an appropriate format.

[0127] Examples:

[0128] The server stores the information in a database: "Taro Tanaka, second-year junior high school student, aims to raise his mathematics score by 10 points, his forte is set theory, his weakness is simultaneous equations."

[0129] Step 3: Generate the curriculum

[0130] Specific behavior:

[0131] The server retrieves the learner's information from the database.

[0132] The server passes the acquired information to the AI ​​engine. Input: Learner information. Output: Information passed to the AI ​​engine.

[0133] Data processing and calculation:

[0134] The AI ​​engine analyzes learner information and generates the optimal curriculum.

[0135] Examples:

[0136] Based on the information "Taro Tanaka, second-year junior high school student, aims to raise his mathematics score by 10 points, his strengths are set theory, and his weaknesses are simultaneous equations," the AI ​​engine generates a curriculum of "reviewing basic mathematics, reviewing set theory, learning from the basics to applications of simultaneous equations, and practicing past exam questions."

[0137] Step 4: Save the curriculum

[0138] Specific behavior:

[0139] The server stores the generated curriculum in a database. Input: Generated curriculum. Output: Curriculum stored in the database.

[0140] Data processing and calculation:

[0141] The server formats the generated curriculum data and stores it in a database.

[0142] Examples:

[0143] The generated curriculum, "Review of basic mathematics, review of set theory, basics to applications of simultaneous equations, and practice of past exam questions," is saved in a database.

[0144] Step 5: Conducting lessons

[0145] Specific behavior:

[0146] The device (tablet) connects to the server and retrieves curriculum information.

[0147] The terminal displays the lesson material based on the acquired curriculum information. Input: Curriculum information. Output: Lesson material displayed on the terminal.

[0148] Data processing and calculation:

[0149] The device selects and displays appropriate lesson materials based on the acquired curriculum.

[0150] Examples:

[0151] Taro Tanaka will use a tablet to take classes based on the curriculum: "Review of basic mathematics, review of set theory, basics and applications of simultaneous equations, and practice with past exam questions."

[0152] Step 6: Accepting and answering questions

[0153] Specific behavior:

[0154] Learners enter their questions during class.

[0155] The terminal sends the question to the server. Input: The learner's question. Output: The question data sent to the server.

[0156] The server passes the question to the AI ​​engine.

[0157] The AI ​​engine generates answers to questions.

[0158] The server sends the generated response to the terminal.

[0159] The device displays the answer to the learner. Input: Answer from the AI ​​engine. Output: Answer displayed on the device.

[0160] Data processing and calculation:

[0161] The AI ​​engine analyzes the question data and generates the optimal answer.

[0162] Examples:

[0163] Taro Tanaka types in a question about simultaneous equations, saying, "I don't know how to solve simultaneous equations." The AI ​​engine generates a "basic solution to simultaneous equations" and displays it on the tablet.

[0164] Step 7: Analyze responses and adjust lesson content

[0165] Specific behavior:

[0166] The device analyzes the learner's facial expressions and tone of voice in real time.

[0167] The device sends the analysis results to the server. Input: Facial expression and tone of voice data. Output: Analysis data sent to the server.

[0168] The server passes the analysis results to the AI ​​engine.

[0169] The AI ​​engine adjusts the lesson content based on the analysis results.

[0170] The server transmits the adjusted content to the terminal.

[0171] The device displays the adjusted lesson content to the learner. Input: Instructions from the AI ​​engine. Output: Adjusted lesson content.

[0172] Data processing and calculation:

[0173] The AI ​​engine analyzes facial expressions and tone of voice data to adjust the lesson content optimally.

[0174] Examples:

[0175] If Taro Tanaka looks confused, the AI ​​engine will instruct him to "slow down the pace of the lesson," and the change will be reflected on the tablet.

[0176] Step 8: Generate and share progress reports

[0177] Specific behavior:

[0178] The server periodically retrieves learner progress data from the database.

[0179] The server passes the acquired data to the AI ​​engine. Input: Progress data. Output: Data passed to the AI ​​engine.

[0180] An AI engine analyzes progress data and generates reports.

[0181] The server sends the generated report to parents and educational institution officials. Input: Generated report. Output: Sent report.

[0182] Data processing and calculation:

[0183] The AI ​​engine analyzes the progress data and creates a detailed report.

[0184] Examples:

[0185] The server retrieves Taro Tanaka's monthly progress data, and the AI ​​engine analyzes the data to generate a report that is then emailed to his parents.

[0186] (Application example 1)

[0187] 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."

[0188] Current individualized cram school systems have difficulty analyzing students' reactions (facial expressions and tone of voice) in real time while lessons are in progress and instantly adjusting lesson content. Furthermore, in on-site work in factories and other places, systems that provide appropriate instructions and support in real time according to the worker's skills and situation are inadequate. This leads to a lack of efficient instruction and support at cram schools and on-site factories, resulting in problems such as reduced learning effectiveness and work efficiency.

[0189] 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.

[0190] In this invention, the server includes: means for inputting information such as a student's goals, current academic ability, and areas of strength and weakness; means for transmitting that information to the server; means for the server to store that information in a database; means for an AI engine to generate an optimal curriculum based on the stored information; means for storing the generated curriculum in a database; means for a student to take lessons based on the curriculum using a tablet device; means for accepting questions from students during lessons and transmitting those questions to the AI ​​engine; means for the AI ​​engine to generate answers to the questions and return those answers to the students; means for analyzing students' reactions (facial expressions, tone of voice, etc.) in real time and transmitting that information to the server; means for the AI ​​engine to analyze students' reactions and adjust lesson content in real time; means for sharing students' progress data with parents and cram school personnel; means for a worker to register individual skills, goals, and tasks that the worker is good at and bad at; means for analyzing the worker's facial expressions and tone of voice in real time and transmitting that information to the server; and means for the AI ​​engine to analyze the worker's reactions and adjust task content in real time. This allows for optimal guidance and work support for each individual.

[0191] A "student" is an individual receiving education at a cram school or educational facility.

[0192] "Goals" refer to specific results or objectives that you want to achieve in individual learning or work.

[0193] "Academic ability" is the ability that represents a student's current knowledge and understanding of learning.

[0194] "Strengths and weaknesses" indicate areas of learning or work in which a student is particularly strong or weak.

[0195] A "server" is a device that manages and stores data and provides data and functions over a computer network.

[0196] A "database" is a place where data is systematically organized and stored in digital form.

[0197] An "AI engine" is the core part of software that uses artificial intelligence to analyze data and generate optimal results and answers.

[0198] A "curriculum" refers to a systematically planned learning program that covers the subjects and content that students should learn.

[0199] A "tablet device" is a small, portable computing device that can be operated primarily via a touch screen.

[0200] "Reactions" refers to real-time feedback such as facial expressions, tone of voice, and behavior shown by students or workers during lessons or work.

[0201] "Worker" refers to a person who performs a specific task in a factory or on a work site.

[0202] "Skills" refers to the knowledge and abilities that a worker has to perform a specific task or technique.

[0203] "Instruction" refers to the act of teaching and guiding students or workers on how to study or work in an appropriate manner.

[0204] "Work support" refers to providing appropriate instructions and assistance to workers so that they can perform their work efficiently.

[0205] System program description

[0206] This invention proposes a system that utilizes an AI engine to provide real-time support for work and learning in private tutoring schools and factory sites.

[0207] Hardware used

[0208] server:

[0209] It is the central device that manages and stores data and exchanges it through communications. The server stores information in a database and runs the AI ​​engine.

[0210] Tablet or smart glasses:

[0211] It will be used as a user interface for cram school students to take lessons and for factory workers to receive work instructions.

[0212] Camera and Microphone:

[0213] This device captures the facial expressions and tone of voice of students and workers in real time.

[0214] Software used

[0215] OpenCV:

[0216] Used to analyze video data from cameras in real time.

[0217] TensorFlow:

[0218] It is used to implement AI models that analyze the facial expressions and tone of voice of students and workers.

[0219] Database Management Systems:

[0220] Stored data is managed using MySQL, PostgreSQL, etc.

[0221] How to carry out the invention

[0222] 1. Registration of information:

[0223] The user (a cram school staff member or a factory manager) uses a dedicated interface to input information such as the student's or worker's goals, current academic ability and skills, and areas of strength and weakness. This information is sent to the server and stored in a database.

[0224] 2. Generate curriculum or work instructions:

[0225] The server passes the stored information to an AI engine to generate optimal curriculum and work instructions, which are then stored back in the database.

[0226] 3. Real-time analysis and feedback:

[0227] The tablet devices and smart glasses use cameras and microphones to capture the facial expressions and tone of voice of students and workers in real time. This data is sent to a server and analyzed by an AI engine. The lesson content and work instructions are adjusted in real time based on the analysis results.

[0228] 4. Question and Answer Management:

[0229] Students and workers can input any questions they may have along the way, and these questions are passed to the AI ​​engine via the server. The AI ​​engine then generates the optimal answer and responds automatically.

[0230] 5. Sharing progress data:

[0231] Data on the progress of lessons and work is stored on a server and periodically analyzed. The results of the analysis are generated as a report and shared with parents and administrators.

[0232] Examples of specific examples and prompts

[0233] Examples:

[0234] Cram school:

[0235] As students take math lessons on tablets, cameras capture their facial expressions, and if AI detects confusion, it simplifies the material or provides additional explanations.

[0236] Factory floor:

[0237] When a worker wears smart glasses to assemble a machine, the glasses analyze hand movements and facial expressions in real time and provide instructions such as "tighten the screws a little more" as needed.

[0238] Example prompt sentence:

[0239] Let AI generate the optimal curriculum based on information such as students' goals, strengths and weaknesses. Then, use the generated curriculum as input to analyze students' facial expressions and tone of voice in real time during class and generate appropriate feedback.

[0240] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0241] Step 1:

[0242] The user inputs information about the student or worker. The user inputs information such as the student's or worker's goals, current academic ability and skills, and areas of strength and weakness through a dedicated interface. The input information is sent to the server, which stores the received information in a database.

[0243] Step 2:

[0244] The server retrieves information from the database and passes it to the AI ​​engine. The server then passes various information about students and workers to the AI ​​engine as input data. Based on this input data, the AI ​​engine generates optimal curriculum and work instructions. The generated curriculum and work instructions are saved in the database.

[0245] Step 3:

[0246] Students and workers use devices to start activities based on the curriculum and work instructions. Students use tablet devices to attend classes, and workers wear smart glasses to perform their work. The devices obtain the curriculum and work instructions from the server and use them.

[0247] Step 4:

[0248] To prepare for real-time analysis, the device captures the students' and workers' behavior through a camera and microphone, and the video and audio data is sent to the server.

[0249] Step 5:

[0250] The server passes the video and audio data to the AI ​​engine for real-time analysis. The AI ​​engine uses OpenCV to analyze the video data and TensorFlow to analyze the audio data. This allows the facial expressions and tone of voice of students and workers to be analyzed. The results of this analysis are sent to the server.

[0251] Step 6:

[0252] The server receives the analysis results and adjusts the curriculum and work instructions in real time based on them.The server generates feedback on lesson content and work instructions based on the analysis results of the AI ​​engine and sends that feedback to the device.

[0253] Step 7:

[0254] Students and workers receive real-time feedback through their devices. Specifically, instructions and points of caution are displayed on tablets or smart glasses. For example, during a lesson, a message such as "You don't fully understand this part, so we'll show you additional explanations," or while working, instructions such as "Tighten the screws a little more" are displayed.

[0255] Step 8:

[0256] The user inputs a question from a student or worker. The question is sent from the device to the server, and then passed from the server to the AI ​​engine. The AI ​​engine generates the optimal answer to the question and returns that answer to the server.

[0257] Step 9:

[0258] The server sends the generated answers to the terminal, where students or workers can check the answers. The answers are displayed and the problems are resolved.

[0259] Step 10:

[0260] The server periodically accumulates progress data of students and workers and passes it to the AI ​​engine for analysis. Based on the progress data, the AI ​​engine analyzes the performance of students and workers and generates a report of the results.

[0261] Step 11:

[0262] The server generates reports that are shared with parents and administrators. The reports include information on the progress of students and workers, as well as issues and areas for improvement, and are shared via email or other means.

[0263] 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.

[0264] The present invention is a private tutoring system that combines artificial intelligence (AI) technology and emotion analysis technology, and a specific implementation method thereof will be described below.

[0265] First, the cram school staff (users) register a new student in the system. Using a dedicated interface, users input information such as the student's goals, current academic ability, and areas of strength and weakness. The terminal receives this information and sends it to the server. The server stores the received information in a database.

[0266] Next, the server retrieves student information from the database and passes it to the AI ​​engine. The AI ​​engine uses this information to generate an optimal curriculum. The generated curriculum is then saved in the database via the server again.

[0267] Students come to a cram school and take classes using a tablet device. The device retrieves curriculum information from the server and provides the student with lesson materials based on that information. If a student has a question during class, the user (student) enters the question through the tablet device. The device sends the question to the server, which passes it on to the AI ​​engine. The AI ​​engine generates the optimal answer to the question and sends it to the device via the server. The device displays the generated answer to the student.

[0268] The system also features an emotion engine that analyzes students' facial expressions and tone of voice in real time during class. The device captures students' reactions and analyzes this data using the emotion engine. The emotion engine then performs a detailed analysis of students' emotional states, such as stress levels and excitement, and sends the analysis results to a server. The server then passes the emotion data to the AI ​​engine, which then adjusts the lesson content based on the analysis results. For example, if the AI ​​engine detects signs of student confusion, it will adjust the difficulty of the lesson or provide additional explanations.

[0269] Furthermore, all question and answer data and emotional data from lessons are stored in a database and taken into consideration when creating the next curriculum, providing a set of curriculum optimized for each individual student.

[0270] The emotion engine periodically accumulates and analyzes students' emotional data and generates reports based on progress data. These reports are shared via email and other means with parents and cram school staff via the server. This allows for a comprehensive understanding of students' learning status and emotional state, enabling appropriate countermeasures to be taken.

[0271] In this way, the present invention solves the problem of labor shortages, improves learning efficiency, meets individual needs, and provides learning support that takes into account the emotional state of students.

[0272] The processing flow will be explained below.

[0273] Step 1:

[0274] The user (a cram school staff member) enters information about a new student (goals, current academic ability, areas of strength and weakness, etc.) into a dedicated interface. The device acquires this information and sends it to the server.

[0275] Step 2:

[0276] The server receives the student information and stores it in a database, which is used for the next process.

[0277] Step 3:

[0278] The server retrieves student information from the database and provides it to the AI ​​engine, which then generates the optimal curriculum based on this information.

[0279] Step 4:

[0280] The curriculum generated by the AI ​​engine is stored in a database via the server, and this curriculum information is used in later steps.

[0281] Step 5:

[0282] Students arrive at the cram school and take classes using a tablet device. The device retrieves current curriculum information from the server and presents the student with the materials they need for class.

[0283] Step 6:

[0284] If a student has a question during class, the user (student) enters the question into the tablet device, which then sends the question to the server.

[0285] Step 7:

[0286] The server sends the question to the AI ​​engine, which generates the optimal answer to the question, and the generated answer is sent to the device via the server.

[0287] Step 8:

[0288] The device displays the generated answer to the user (student), allowing the student to immediately resolve their doubts.

[0289] Step 9:

[0290] During class, the device captures students' facial expressions and tone of voice in real time and sends them to the emotion engine, which then analyzes the data.

[0291] Step 10:

[0292] The emotion engine sends the results of its analysis to a server, which then provides them to an AI engine. The AI ​​engine then adjusts the lesson content based on the analysis results. For example, if a student's stress level is high, it will adjust the difficulty of the lesson to be lower.

[0293] Step 11:

[0294] All questions, answers, and emotional data are stored in a database, which will be used to create the next curriculum and plan lessons.

[0295] Step 12:

[0296] The AI ​​engine periodically generates progress reports for students based on the accumulated data. These reports are shared via email with parents and cram school staff via the server, allowing for a comprehensive understanding of the student's learning progress.

[0297] Through the above steps, the present invention provides a learning experience optimized to the needs of each individual student, solving the problem of labor shortages while also realizing advanced learning support that takes into account the emotional state of students.

[0298] Example 2

[0299] 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."

[0300] Conventional individualized tutoring systems struggled to adjust lesson content in real time based on students' academic ability, level of understanding, and emotional state. As a result, they were unable to provide a learning experience optimized for each student's needs, making it difficult to achieve efficient learning outcomes. It was also difficult to provide immediate and appropriate answers to students' questions, which could lead to inconsistent learning. Furthermore, there was a lack of appropriate means for sharing students' progress and emotional state with parents and tutoring staff.

[0301] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0302] In this invention, the server includes: means for inputting information such as a student's goals, current academic ability, and areas of strength and weakness; means for transmitting the information to the server; means for the server to store the information in a database; means for an AI engine to generate an optimal curriculum based on the stored information; means for storing the generated curriculum in a database; means for a student to take lessons based on the curriculum using a tablet device; means for accepting questions from students during lessons and transmitting the questions to the AI ​​engine; means for the AI ​​engine to generate answers to the questions and return the answers to the students; means for analyzing students' reactions (facial expressions, tone of voice, etc.) in real time and transmitting the information to the server; means for an emotion analysis engine to periodically accumulate and analyze students' emotional data and transmit the analysis results to the server; means for the AI ​​engine to analyze students' reactions and adjust lesson content in real time; means for sharing student progress data with parents and cram school staff; and means for automatically adjusting lesson content based on the student's emotional state. This makes it possible to adjust lesson content in real time according to the student's academic ability, level of understanding, and emotional state, thereby providing an optimized learning experience for each student.

[0303] "Student goals" refer to the specific outcomes or goals that students want to achieve through their studies.

[0304] "Current academic ability" is an assessment of the level of knowledge and skills that a student currently possesses.

[0305] "Strong and weak areas" refers to subjects or areas in which a student is particularly strong and weak.

[0306] A "server" refers to the central device of a computer system that stores and processes data.

[0307] A "database" is a system for organizing and storing information and data.

[0308] An "AI engine" refers to a program that uses machine learning and data analysis to generate optimal curriculum and answers.

[0309] "Curriculum" refers to an educational plan organized according to specific goals or learning objectives.

[0310] "Tablet device" refers to a portable computing device with a touchscreen.

[0311] "Questions" refer to matters that students are unsure about or want to confirm while studying.

[0312] "Answer" refers to the answer or explanation provided to a question.

[0313] "Responses" refer to non-verbal feedback such as facial expressions and tone of voice shown by students during class.

[0314] An "emotion analysis engine" refers to a system that analyzes students' facial expressions, voices, etc. to evaluate their emotional state.

[0315] "Progress Data" refers to data that shows a student's learning process and academic progress.

[0316] "Guardians" refers to the parents or guardians of students attending cram schools.

[0317] "Cram school personnel" refers to staff, teachers, and other personnel who work at cram schools.

[0318] "Class content" refers to the teaching materials, content taught, learning activities, etc. used in class.

[0319] "Storage" refers to the collection and storage of information or data.

[0320] "Analysis" refers to the detailed examination and analysis of information or data.

[0321] The present invention is a private tutoring system that combines artificial intelligence (AI) technology and emotion analysis technology. This system provides an optimal curriculum based on a student's learning status and can personalize the learning experience by analyzing their reactions and emotional state in real time. A specific method for implementing this invention is described below.

[0322] First, to register a new student in the system, the user (cram school staff) enters information such as the student's goals, current academic ability, and areas of strength and weakness through a dedicated interface. The device (PC or tablet) sends this information to the server. The server stores the received information in a database. Specifically, the information is managed using a relational database such as MySQL or PostgreSQL.

[0323] The server then retrieves student information from the database and passes it to the AI ​​engine, which uses machine learning frameworks such as TensorFlow and PyTorch to analyze student characteristics and generate an optimal curriculum. This generated curriculum is then stored in the database via the server.

[0324] When a student comes to a cram school and takes a class using a tablet device, the device retrieves curriculum information from the server and provides the student with lesson materials based on that information. If a student has a question during class, the user (student) inputs the question through the tablet device. The device sends the question to the server, which then passes it on to the AI ​​engine. The AI ​​engine generates the optimal answer to the question and sends it to the device via the server. The device then displays the generated answer to the student.

[0325] For emotion analysis, the device captures students' facial expressions and tone of voice in real time and sends them to the emotion engine. The emotion engine uses technologies such as OpenCV and Dlib to analyze the student's stress level and excitement. The analysis results are sent to a server, which passes them on to an AI engine. The AI ​​engine then adjusts the lesson content based on this data. For example, if a student is confused, the AI ​​engine may instruct the teacher to lower the difficulty of the lesson or provide additional explanations.

[0326] Every time a student takes a class, all their questions, answers, and emotional data are stored in a database. This information is taken into account when generating the next curriculum, providing a more personalized learning experience.

[0327] Furthermore, the emotion engine periodically accumulates and analyzes students' emotional data and generates reports based on progress data. The server then shares these reports with parents and cram school staff via email, etc. This allows for a comprehensive understanding of students' learning status and emotional state, enabling appropriate countermeasures to be taken.

[0328] Examples of examples and prompts:

[0329] For example, if a new student wants to learn the basics of mathematics, the user (a cram school staff member) fills in a special input form with the following information: "Goal: Understand the basics of mathematics, Current academic level: Intermediate, Strong areas: Arithmetic, Weak areas: Algebra." Based on this information, the AI ​​engine generates a curriculum that starts with basic arithmetic and gradually progresses to Algebra.

[0330] Example prompt:

[0331] Prompt for user (cram school staff): "Please enter registration information for a new student. Please include their goals, current academic ability, and areas of strength and weakness."

[0332] Prompt for students: "If you have any questions during class, please use the tablet to type your question and we will provide you with an immediate answer."

[0333] This invention will solve the problem of labor shortages, improve learning efficiency, and meet individual needs, and will also provide learning support that takes into account the emotional state of students.

[0334] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0335] Step 1:

[0336] The user (cram school staff) enters information such as the student's goals, current academic ability, and areas of strength and weakness using a dedicated interface (e.g., web form or app). After entering the information, the device sends it to the server, which then stores the received information in a database.

[0337] Input: Information such as student goals, current academic ability, strengths and weaknesses

[0338] Output: Save student information to database

[0339] Specific operation: The user enters the required information into a dedicated web form and clicks the "Submit" button. The device sends this information to the server, which then stores it in a database.

[0340] Step 2:

[0341] The server retrieves student information from the database and passes it to the AI ​​engine. The AI ​​engine uses machine learning frameworks such as TensorFlow and PyTorch to analyze the student's characteristics. Based on this, it generates an optimal curriculum. The generated curriculum is then saved in the database via the server.

[0342] Input: Student information stored in the database

[0343] Output: Save the generated curriculum to a database

[0344] Specific operation: The server periodically checks for newly added student information and forwards this information to the AI ​​engine. The AI ​​engine generates an optimal curriculum and sends it back to the server. The server stores the curriculum in a database.

[0345] Step 3:

[0346] When students come to the cram school and take classes using a tablet device, the device retrieves curriculum information from the server and provides the students with lesson materials based on that information.

[0347] Input: Curriculum information stored in the database

[0348] Output: Lesson materials provided to students

[0349] Specific operation: When a student logs in to a tablet device, the system automatically downloads the student's curriculum from the server and then displays the first lesson slide to the student.

[0350] Step 4:

[0351] If a student has a question during class, the user (student) inputs the question through a tablet device. The device sends the question to the server, which passes it to the AI ​​engine. The AI ​​engine generates the optimal answer to the question and sends it to the device via the server. The device then displays the generated answer to the student.

[0352] Input: Student question

[0353] Output: Answer from the AI ​​engine

[0354] Specific operation: The student taps the "Ask a question" button and enters the question text. The question is sent to the server, where the AI ​​engine analyzes it and generates an answer. The device receives this and displays it to the student.

[0355] Step 5:

[0356] The device captures the student's facial expressions and tone of voice in real time and sends them to the emotion engine, which analyzes the student's stress level and excitement level and sends the results to the server.

[0357] Input: Facial expressions and tone of voice captured in real time

[0358] Output: Emotion analysis results

[0359] How it works: The tablet's camera and microphone capture the student's face and voice, and send them to the emotion engine every few seconds. The analyzed data is then sent to the server.

[0360] Step 6:

[0361] The server passes the emotional data to an AI engine, which then adjusts the lesson content based on the data. For example, if a student is confused, the AI ​​engine can lower the difficulty of the lesson or provide additional explanations.

[0362] Input: Sentiment analysis results

[0363] Output: Adjusted lesson content

[0364] Specific operation: The server receives the analysis results from the emotion engine and forwards them to the AI ​​engine. The AI ​​engine gradually adjusts the lesson content and sends it to the device via the server. The device then displays the new instructions to the student.

[0365] Step 7:

[0366] All questions, answers, and emotional data from lessons are stored in a database, and this data is taken into account when generating the next curriculum.

[0367] Input: Questions and answers, emotion data

[0368] Output: Individual data to be reflected in the next curriculum

[0369] Specific operation: After the lesson ends, the device automatically sends all learning data to the server, which stores this data in a database and references it when the AI ​​engine generates the next curriculum.

[0370] Step 8:

[0371] The emotion engine periodically analyzes students' emotion data and generates reports based on their progress. The server then shares these reports with parents and school staff via email or other means.

[0372] Input: Accumulated emotion data

[0373] Output: Progress report

[0374] How it works: The emotion engine analyzes students' emotion data monthly and generates a report. The server converts this report into PDF format and sends it to the email addresses of parents and other relevant parties.

[0375] (Application example 2)

[0376] 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."

[0377] Conventional learning support systems and customer service support systems in brick-and-mortar stores have had difficulty accurately grasping the emotional state of individual customers or students in real time and providing appropriate instruction or customer service based on that information. Furthermore, there was a lack of efficient means for suggesting optimal products based on customers' emotions and purchasing history.

[0378] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means. In this invention, the server includes: means for inputting information such as a student's goals, current academic ability, and areas of strength and weakness; means for transmitting the information to the server; means for the server to store the information in a database; means for an AI engine to generate an optimal curriculum based on the stored information; means for storing the generated curriculum in a database; means for a student to take lessons based on the curriculum using a tablet device; means for accepting questions from students during lessons and transmitting the questions to the AI ​​engine; means for the AI ​​engine to generate answers to the questions and return the answers to the students; means for analyzing students' reactions (facial expressions, tone of voice, etc.) in real time and transmitting the information to the server; means for the AI ​​engine to analyze students' reactions and adjust lesson content in real time; means for sharing student progress data with parents and cram school personnel; means for analyzing customers' facial expressions and tone of voice in a store to grasp their emotional state; means for the AI ​​engine to generate optimal customer service methods and product suggestions based on the customer's emotional state and purchase history; and means for notifying store staff of the customer service methods and product suggestions. This will enable individually optimized learning support and personalized customer service in physical stores.

[0379] "Student goals" are the specific learning outcomes or objectives that students want to achieve during the learning process.

[0380] "Current academic ability" refers to the level of knowledge and skills that a student currently possesses.

[0381] "Strong and weak areas" refer to subjects or areas that are relatively easy for students to understand and master, and subjects or areas that are difficult for students to understand and master.

[0382] "Means for inputting information" refers to the interface or device through which a user provides information about a student or customer to the system.

[0383] "Means for sending to the server" refers to the communication protocol or technology used to transfer data from the terminal to the server.

[0384] "Means for storing data in a database" refers to a mechanism for efficiently recording received data and making it possible to search and update it as needed.

[0385] An "AI engine" is software that uses artificial intelligence to analyze data and generate solutions or suggestions for specific problems.

[0386] "Curriculum generation means" refers to algorithms or processes for constructing appropriate lesson plans and materials based on student information.

[0387] A "tablet device" is a portable computer that allows input and operation via a touch screen.

[0388] "Means for accepting questions and sending them to the AI ​​engine" refers to a mechanism that allows students or customers to input doubts or queries into the system and forward them to the AI ​​engine.

[0389] "Means for generating and returning an answer" refers to the mechanism by which the AI ​​engine creates the optimal answer to a question and provides that answer to the questioner.

[0390] "Means for analyzing reactions in real time" refers to technology that instantly evaluates the reactions of students or customers, such as facial expressions and tone of voice, and analyzes their emotional state.

[0391] "Means for sharing progress data" refers to a system for notifying relevant parties of progress data on students' learning status and customer purchasing behavior.

[0392] "Means of analyzing facial expressions and tone of voice to grasp emotional state" refers to technology that analyzes data acquired using a camera or microphone to identify the subject's emotions.

[0393] "Means for generating optimal customer service methods and product suggestions based on purchasing history" refers to a system in which AI uses customers' past purchasing data to generate optimal customer service methods and suggested products for purchase.

[0394] "Means of notifying store staff of customer service methods and product suggestions" refers to a system that provides information generated by AI to store staff in real time or at any time.

[0395] This invention is a personalized learning and customer service support system that combines AI technology and emotion analysis technology. First, we will explain the overall flow of the system.

[0396] 1. Enter student and customer information

[0397] The user enters information such as the student's goals, current academic ability, areas of strength and weakness, as well as the customer's purchasing history and preferred categories through a dedicated interface. This information is sent from the terminal to the server.

[0398] 2. Storing data and sending it to the AI ​​engine

[0399] The server stores the received information in a database. The server then sends the stored information to the AI ​​engine. The AI ​​engine generates the optimal curriculum and customer service methods based on the received information, and stores them in the database again via the server.

[0400] 3. Teaching and customer service using tablet devices

[0401] Students come to the cram school and take lessons using a tablet device. The device provides lessons based on curriculum information obtained from the server. In physical stores, store staff use smart glasses or smartphones to capture customers' facial expressions and tone of voice. This real-time data is sent to the server for analysis.

[0402] 4. Questions and Answers

[0403] If a student has a question during class, they can input it into their tablet device. The device sends the question to the server, which passes it on to the AI ​​engine. The AI ​​engine generates the optimal answer and sends it back to the device via the server. Similarly, when dealing with customers in-store, the AI ​​engine will suggest the best product and customer service methods.

[0404] 5. Sentiment analysis and adjustment of lesson content and customer service content

[0405] During lessons, the devices capture students' facial expressions and tone of voice in real time and send them to a server. An emotion analysis engine analyzes this data to determine students' stress levels and excitement levels. The AI ​​engine adjusts lesson content in real time based on the emotional data. In-store, customer service methods and product recommendations are adjusted based on customer emotional data.

[0406] 6. Sharing progress data

[0407] All questions and answers during lessons, as well as student emotional data, are stored in a database. This data is taken into consideration when creating the next curriculum and proposing customer service methods. Progress reports are generated by an AI engine and shared with parents, cram school staff, and store personnel. This allows for a comprehensive understanding of the status of students and customers and allows for appropriate countermeasures to be taken.

[0408] Hardware and software used

[0409] Hardware: Tablets, smart glasses, smartphones

[0410] Software: Python-based AI engine, OpenCV (image processing library), Emotion Analysis API, database management system

[0411] Examples of specific examples and prompts

[0412] As a specific example, when dealing with customers in a physical store, if the AI ​​engine detects signs of confusion in the customer, it will suggest to the store staff that they "speak in a calm tone and explain about new products in the store."

[0413] Example prompt sentence:

[0414] "If a customer is confused, please suggest the best way to serve them."

[0415] In this way, the system provides both individually optimized learning support and customer service in a physical store, solving conventional problems.

[0416] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0417] Step 1:

[0418] The user enters information such as the student's goals, current academic ability, areas of strength and weakness, as well as the customer's purchasing history and preferred categories into a dedicated interface. The entered information is sent from the terminal to the server.

[0419] Input: Student and Customer Information

[0420] Output: Information data sent to the server

[0421] How it works: The user uses a dedicated interface to input information via a keyboard or touchscreen. The device collects this data and sends it to the server via an HTTP request.

[0422] Step 2:

[0423] The server stores the received information in a database.

[0424] Input: Information data sent from the terminal

[0425] Output: Information stored in the database

[0426] Specific operations: The server stores the received data in a structured format using a database management system, and inserts it into the database using an SQL query.

[0427] Step 3:

[0428] The server sends the stored information to the AI ​​engine, which then generates the optimal curriculum and customer service methods based on the received information, and stores them in the database again via the server.

[0429] Input: Information stored in a database

[0430] Output: Generated curriculum and customer service methods

[0431] Specific operation: The server sends data to the AI ​​engine using an API request. The AI ​​engine analyzes the data using a machine learning model and generates the optimal curriculum and customer service method. The generated data is sent to the server as an API response, and the server stores it in the database again.

[0432] Step 4:

[0433] Students come to the cram school and use tablets to take lessons based on the curriculum, while store staff use smart glasses or smartphones to capture customers' facial expressions and tone of voice.

[0434] Input: Curriculum information obtained from the server, customer facial expressions and tone of voice

[0435] Output: Lesson content delivered, real-time data captured

[0436] How it works: The tablet device retrieves curriculum information from the server and displays lesson content accordingly. The smart glasses or smartphone uses a camera and microphone to capture the customer's facial expressions and tone of voice in real time, formatting the data and sending it to the server.

[0437] Step 5:

[0438] If a student has a question during class, they can enter it into their tablet device, which then sends it to the server, which then passes it on to the AI ​​engine.

[0439] Input: Student question

[0440] Output: Question data sent to the server

[0441] How it works: Students enter questions into their tablet devices, which then capture and send them to the server. The server then passes the received question data to the AI ​​engine via an API request.

[0442] Step 6:

[0443] The AI ​​engine generates the optimal answer and sends it to the device via the server.

[0444] Input: Question data sent from the server

[0445] Output: Answer data returned to the student

[0446] How it works: The AI ​​engine analyzes the question data and uses machine learning models to generate the best answer. The generated answer is returned to the server via an API response, and the server then sends it to the student's device.

[0447] Step 7:

[0448] During class, the device captures students' facial expressions and tone of voice in real time and sends them to a server. An AI engine analyzes this data to determine students' stress levels and excitement levels.

[0449] Input: Real-time facial expression data and tone of voice data of students

[0450] Output: Parsed emotion data

[0451] How it works: The tablet uses a camera and microphone to capture students' facial expressions and tone of voice, and sends the data to a server. An AI engine analyzes this data and identifies their emotional state.

[0452] Step 8:

[0453] The AI ​​engine adjusts lesson content in real time based on emotional data, and in-store customer service methods and product recommendations are adjusted based on customer emotional data.

[0454] Input: Parsed emotion data

[0455] Output: Adjusted lesson content and customer service methods

[0456] Specific actions: Based on the analysis results, the AI ​​engine adjusts the lesson content to lower the difficulty level or provide additional explanations as needed. In physical stores, it changes and adjusts customer service methods and product recommendations based on the customer's emotional state.

[0457] Step 9:

[0458] All questions and answers during lessons, as well as student emotional data, are stored in a database and are taken into consideration when creating the next curriculum and proposing customer service methods.

[0459] Input: Question and answer data during class, emotion data

[0460] Output: Progress data stored in a database

[0461] Specific operation: The server saves questions, answers, and emotion data from lessons in a database. This data is used to generate the next curriculum and improve customer service methods.

[0462] Step 10:

[0463] Progress reports are generated by an AI engine and shared with parents, cram school staff, and store personnel.

[0464] Input: Progress data stored in the database

[0465] Output: Generated progress report

[0466] How it works: The AI ​​engine analyzes the progress data and creates a report. The report is then shared via email with parents, cram school staff, and store staff via a server.

[0467] 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.

[0468] 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.

[0469] 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.

[0470] [Second embodiment]

[0471] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0472] 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.

[0473] 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).

[0474] 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.

[0475] 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.

[0476] 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).

[0477] 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.

[0478] 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.

[0479] 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.

[0480] 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.

[0481] 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.

[0482] 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."

[0483] The present invention is a private tutoring system that utilizes artificial intelligence (AI), and the method for realizing this system is explained below. Here, each component, its function, and specific operating procedures are shown.

[0484] First, the cram school staff (users) register a new student in the system. Using a dedicated interface, users input information such as the student's goals, current academic ability, and areas of strength and weakness. The terminal receives this information and sends it to the server. The server stores the received information in a database.

[0485] Next, the server retrieves student information from the database and passes it to the AI ​​engine. The AI ​​engine uses this information to generate an optimal curriculum. The generated curriculum is then saved in the database via the server again.

[0486] Students come to the cram school and take classes using a tablet device. The device retrieves curriculum information from the server and provides the students with lesson materials based on that information. If a student has a question during the actual class, the user (student) inputs the question through the tablet device. The device sends the question to the server, which passes it on to the AI ​​engine. The AI ​​engine generates the optimal answer to the question and sends it to the device via the server. The device returns the generated answer to the student.

[0487] The device also features a system for analyzing students' facial expressions and tone of voice in real time during class. The device analyzes students' reactions and sends the data to a server. The server passes this data to an AI engine, which then adjusts the lesson content based on the analysis results. For example, if a student shows signs of confusion, the AI ​​engine will instruct the teacher to lower the difficulty of the lesson or provide additional explanations.

[0488] Furthermore, all questions and answers during the lesson are stored in a database and taken into consideration when creating the next curriculum, thus providing a set of curriculum that is optimized for each individual student.

[0489] Finally, students' learning progress data is analyzed periodically, and the results are compiled into a report. This report is shared via a server with parents and cram school staff via email, etc. This allows students' progress to be tracked as needed and necessary measures to be taken.

[0490] In this way, the present invention solves the problem of labor shortages while realizing efficient and effective learning instruction that meets individual learning needs.

[0491] The processing flow will be explained below.

[0492] Step 1:

[0493] The user (a cram school staff member) enters information about a new student (goals, current academic ability, areas of strength and weakness, etc.) into a dedicated interface. The device then sends this information to the server.

[0494] Step 2:

[0495] The server stores the received student information in a database, which is used in subsequent processes.

[0496] Step 3:

[0497] The server retrieves student information from the database and passes it to the AI ​​engine, which then generates the optimal curriculum based on this information.

[0498] Step 4:

[0499] The generated curriculum is stored in a database via a server, which allows the curriculum information to be used later.

[0500] Step 5:

[0501] Students attend classes at the cram school using a tablet device. The device retrieves current curriculum information from the server and provides students with the materials they need for class.

[0502] Step 6:

[0503] If a student has a question during class, the user (student) can input the question through a tablet device, which then sends the question to the server.

[0504] Step 7:

[0505] The server passes the question to the AI ​​engine, which generates the optimal answer to the question, and the generated answer is sent to the device via the server.

[0506] Step 8:

[0507] The device displays the generated answer to the user (student), allowing the student to immediately resolve their doubts.

[0508] Step 9:

[0509] During class, the device captures students' reactions in real time for analysis of their facial expressions and tone of voice, and this data is sent to a server.

[0510] Step 10:

[0511] The server passes the student's reaction data to an AI engine, which then adjusts the lesson content based on the analysis results. For example, if a student is confused, it will instruct the AI ​​engine to lower the difficulty of the lesson.

[0512] Step 11:

[0513] All questions and answers are stored in a database, which will be used to create the next curriculum.

[0514] Step 12:

[0515] The AI ​​engine periodically analyzes students' learning progress data and generates progress reports, which are shared with parents and cram school staff via a server.

[0516] Example 1

[0517] 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."

[0518] Conventional individualized learning systems struggled to provide an effective curriculum tailored to each learner's learning progress and level of understanding, making it difficult to maximize learning efficiency. Furthermore, they lacked the means to respond to learners' reactions and questions in real time, making it impossible to provide optimal instruction to each learner. Furthermore, reporting progress to parents and educational facility officials was time-consuming, making it difficult to share information in a timely manner.

[0519] 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.

[0520] In this invention, the server includes: a means for inputting information such as a learner's goals, current academic ability, and areas of strength and weakness; a means for transmitting the information to the server; a means for the server to store the information in a database; a means for an AI engine to generate an optimal curriculum based on the stored information; a means for storing the generated curriculum in a database; a means for a learner to take lessons based on the curriculum using a mobile device; a means for accepting questions from the learner during lessons and transmitting the questions to the AI ​​engine; a means for the AI ​​engine to generate answers to the questions and return the answers to the learner; a means for analyzing the learner's responses (e.g., facial expressions, tone of voice) in real time and transmitting the information to the server; a means for the AI ​​engine to analyze the learner's responses and adjust the lesson content in real time; a means for sharing the learner's progress data with parents and educational facility personnel; and a means for storing the learner's question data and answer data for a certain period of time and utilizing them when creating the next curriculum. This enables the provision of teaching methods optimized for each learner and high learning effectiveness. The ability to quickly and accurately share information with parents and educational facility personnel also enables appropriate management of the learner's learning progress.

[0521] "Learner" refers to an individual who uses the system to receive an education.

[0522] A "server" refers to a computer device that provides specific services or information over a network.

[0523] A "database" refers to a system that stores and manages large amounts of data in an organized manner.

[0524] An "AI engine" refers to a system that uses artificial intelligence technology to analyze data and generate optimal results.

[0525] "Curriculum" refers to a learning plan that is structured based on the learner's educational goals.

[0526] "Mobile devices" refer to electronic devices that are portable and used by learners. Examples include tablets and smartphones.

[0527] "Analyzing in real time" refers to the process of analyzing input information immediately and obtaining results.

[0528] "Progress data" refers to data that indicates the progress and results of a learner's learning activities.

[0529] "Guardian" means the parent or guardian's representative.

[0530] "Educational facility personnel" refers to staff and administrators of the educational institution to which the learner belongs.

[0531] "Question data" refers to information about questions entered by learners.

[0532] "Answer data" refers to information about an answer generated based on question data.

[0533] MODE FOR CARRYING OUT THE INVENTION

[0534] This invention is a personalized tutoring system that utilizes artificial intelligence (AI). This section explains in detail each component and the role they play. This system enables efficient learning instruction tailored to the needs of each learner.

[0535] First, the user registers a new learner using a dedicated web interface. The user enters information into the interface, such as the learner's goals, current academic ability, and areas of strength and weakness, and presses the submit button. At this time, the device receives the entered information and sends it to the server. For example, the user enters "Taro Tanaka, second-year junior high school student, aims to raise his math score by 10 points, his strengths are set theory, and his weaknesses are simultaneous equations." This information is sent to the server, which stores it in a database.

[0536] Next, the server retrieves the learner's information from the database and passes it to the AI ​​engine. The AI ​​engine analyzes the learner's information and generates an optimal curriculum. The generated curriculum is then saved in the database via the server again. For example, based on the information of "Taro Tanaka," the AI ​​engine generates a curriculum of "review of basic mathematics, review of set theory, basics and applications of simultaneous equations, and practice with past exam questions."

[0537] At a cram school, learners attend classes using mobile devices (e.g., tablet devices). The devices connect to a server and obtain curriculum information. Lesson materials are displayed on the device based on the obtained curriculum, and the learner follows along as they study. If a question arises during class, the learner enters it through the device. The device sends the question to the server, which passes it on to an AI engine. The AI ​​engine generates the best answer to the question, and that answer is sent to the device via the server. The device displays the generated answer to the learner.

[0538] The device also has a function for analyzing learners' facial expressions and tone of voice in real time during lessons. The device analyzes the learners' reactions and sends the data to a server. The server passes the data to an AI engine, which then adjusts the lesson content based on the analysis results. For example, if a learner shows a confused expression, the AI ​​engine will issue instructions to lower the difficulty of the lesson, and these instructions will be sent to the device via the server.

[0539] Furthermore, all question and answer data is stored in a database and reflected in the next curriculum creation, providing a set of curriculum optimized for each individual learner.

[0540] Finally, the learner's learning progress data is periodically retrieved from the database by the server and passed to the AI ​​engine. The AI ​​engine analyzes the progress data and generates a report. This report is then emailed to parents and educational institution officials via the server. For example, a progress report summarizing the learner's achievements and challenges can be emailed to parents.

[0541] Example prompt sentence:

[0542] We have a student named "Taro Tanaka" who is in the second year of junior high school. His goal is to raise his math score by 10 points. His current strengths are "set theory" and his weaknesses are "simultaneous equations." Please generate the optimal learning curriculum for him.

[0543] In this way, the present invention is a system that provides efficient and effective learning guidance that meets individual learning needs and achieves high learning results.

[0544] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0545] Program processing flow

[0546] Step 1: Register student information

[0547] Specific behavior:

[0548] The user opens a dedicated web interface.

[0549] The user enters the learner's basic information (name, grade, goal, areas of strength and weakness) and presses the send button.

[0550] The terminal receives this input data. Input: Basic information of the learner. Output: Learner information data sent to the terminal.

[0551] Data processing and calculation:

[0552] The terminal formats the input information and sends it to the server.

[0553] Examples:

[0554] The user enters "Taro Tanaka, second-year junior high school student, increase math score by 10, strong point is set theory, weak point is simultaneous equations" and presses the send button.

[0555] Step 2: Saving to the database

[0556] Specific behavior:

[0557] The server receives the learner information sent from the terminal.

[0558] The server stores the received information in a database. Input: Learner information data. Output: Information stored in the database.

[0559] Data processing and calculation:

[0560] The server stores the received data in a database in an appropriate format.

[0561] Examples:

[0562] The server stores the information in a database: "Taro Tanaka, second-year junior high school student, aims to raise his mathematics score by 10 points, his forte is set theory, his weakness is simultaneous equations."

[0563] Step 3: Generate the curriculum

[0564] Specific behavior:

[0565] The server retrieves the learner's information from the database.

[0566] The server passes the acquired information to the AI ​​engine. Input: Learner information. Output: Information passed to the AI ​​engine.

[0567] Data processing and calculation:

[0568] The AI ​​engine analyzes learner information and generates the optimal curriculum.

[0569] Examples:

[0570] Based on the information "Taro Tanaka, second-year junior high school student, aims to raise his mathematics score by 10 points, his strengths are set theory, and his weaknesses are simultaneous equations," the AI ​​engine generates a curriculum of "reviewing basic mathematics, reviewing set theory, learning from the basics to applications of simultaneous equations, and practicing past exam questions."

[0571] Step 4: Save the curriculum

[0572] Specific behavior:

[0573] The server stores the generated curriculum in a database. Input: Generated curriculum. Output: Curriculum stored in the database.

[0574] Data processing and calculation:

[0575] The server formats the generated curriculum data and stores it in a database.

[0576] Examples:

[0577] The generated curriculum, "Review of basic mathematics, review of set theory, basics to applications of simultaneous equations, and practice of past exam questions," is saved in a database.

[0578] Step 5: Conducting lessons

[0579] Specific behavior:

[0580] The device (tablet) connects to the server and retrieves curriculum information.

[0581] The terminal displays the lesson material based on the acquired curriculum information. Input: Curriculum information. Output: Lesson material displayed on the terminal.

[0582] Data processing and calculation:

[0583] The device selects and displays appropriate lesson materials based on the acquired curriculum.

[0584] Examples:

[0585] Taro Tanaka will use a tablet to take classes based on the curriculum: "Review of basic mathematics, review of set theory, basics and applications of simultaneous equations, and practice with past exam questions."

[0586] Step 6: Accepting and answering questions

[0587] Specific behavior:

[0588] Learners enter their questions during class.

[0589] The terminal sends the question to the server. Input: The learner's question. Output: The question data sent to the server.

[0590] The server passes the question to the AI ​​engine.

[0591] The AI ​​engine generates answers to questions.

[0592] The server sends the generated response to the terminal.

[0593] The device displays the answer to the learner. Input: Answer from the AI ​​engine. Output: Answer displayed on the device.

[0594] Data processing and calculation:

[0595] The AI ​​engine analyzes the question data and generates the optimal answer.

[0596] Examples:

[0597] Taro Tanaka types in a question about simultaneous equations, saying, "I don't know how to solve simultaneous equations." The AI ​​engine generates a "basic solution to simultaneous equations" and displays it on the tablet.

[0598] Step 7: Analyze responses and adjust lesson content

[0599] Specific behavior:

[0600] The device analyzes the learner's facial expressions and tone of voice in real time.

[0601] The device sends the analysis results to the server. Input: Facial expression and tone of voice data. Output: Analysis data sent to the server.

[0602] The server passes the analysis results to the AI ​​engine.

[0603] The AI ​​engine adjusts the lesson content based on the analysis results.

[0604] The server transmits the adjusted content to the terminal.

[0605] The device displays the adjusted lesson content to the learner. Input: Instructions from the AI ​​engine. Output: Adjusted lesson content.

[0606] Data processing and calculation:

[0607] The AI ​​engine analyzes facial expressions and tone of voice data to adjust the lesson content optimally.

[0608] Examples:

[0609] If Taro Tanaka looks confused, the AI ​​engine will instruct him to "slow down the pace of the lesson," and the change will be reflected on the tablet.

[0610] Step 8: Generate and share progress reports

[0611] Specific behavior:

[0612] The server periodically retrieves learner progress data from the database.

[0613] The server passes the acquired data to the AI ​​engine. Input: Progress data. Output: Data passed to the AI ​​engine.

[0614] An AI engine analyzes progress data and generates reports.

[0615] The server sends the generated report to parents and educational institution officials. Input: Generated report. Output: Sent report.

[0616] Data processing and calculation:

[0617] The AI ​​engine analyzes the progress data and creates a detailed report.

[0618] Examples:

[0619] The server retrieves Taro Tanaka's monthly progress data, and the AI ​​engine analyzes the data to generate a report that is then emailed to his parents.

[0620] (Application example 1)

[0621] 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."

[0622] Current individualized cram school systems have difficulty analyzing students' reactions (facial expressions and tone of voice) in real time while lessons are in progress and instantly adjusting lesson content. Furthermore, in on-site work in factories and other places, systems that provide appropriate instructions and support in real time according to the worker's skills and situation are inadequate. This leads to a lack of efficient instruction and support at cram schools and on-site factories, resulting in problems such as reduced learning effectiveness and work efficiency.

[0623] 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.

[0624] In this invention, the server includes: means for inputting information such as a student's goals, current academic ability, and areas of strength and weakness; means for transmitting that information to the server; means for the server to store that information in a database; means for an AI engine to generate an optimal curriculum based on the stored information; means for storing the generated curriculum in a database; means for a student to take lessons based on the curriculum using a tablet device; means for accepting questions from students during lessons and transmitting those questions to the AI ​​engine; means for the AI ​​engine to generate answers to the questions and return those answers to the students; means for analyzing students' reactions (facial expressions, tone of voice, etc.) in real time and transmitting that information to the server; means for the AI ​​engine to analyze students' reactions and adjust lesson content in real time; means for sharing students' progress data with parents and cram school personnel; means for a worker to register individual skills, goals, and tasks that the worker is good at and bad at; means for analyzing the worker's facial expressions and tone of voice in real time and transmitting that information to the server; and means for the AI ​​engine to analyze the worker's reactions and adjust task content in real time. This allows for optimal guidance and work support for each individual.

[0625] A "student" is an individual receiving education at a cram school or educational facility.

[0626] "Goals" refer to specific results or objectives that you want to achieve in individual learning or work.

[0627] "Academic ability" is the ability that represents a student's current knowledge and understanding of learning.

[0628] "Strengths and weaknesses" indicate areas of learning or work in which a student is particularly strong or weak.

[0629] A "server" is a device that manages and stores data and provides data and functions over a computer network.

[0630] A "database" is a place where data is systematically organized and stored in digital form.

[0631] An "AI engine" is the core part of software that uses artificial intelligence to analyze data and generate optimal results and answers.

[0632] A "curriculum" refers to a systematically planned learning program that covers the subjects and content that students should learn.

[0633] A "tablet device" is a small, portable computing device that can be operated primarily via a touch screen.

[0634] "Reactions" refers to real-time feedback such as facial expressions, tone of voice, and behavior shown by students or workers during lessons or work.

[0635] "Worker" refers to a person who performs a specific task in a factory or on a work site.

[0636] "Skills" refers to the knowledge and abilities that a worker has to perform a specific task or technique.

[0637] "Instruction" refers to the act of teaching and guiding students or workers on how to study or work in an appropriate manner.

[0638] "Work support" refers to providing appropriate instructions and assistance to workers so that they can perform their work efficiently.

[0639] System program description

[0640] This invention proposes a system that utilizes an AI engine to provide real-time support for work and learning in private tutoring schools and factory sites.

[0641] Hardware used

[0642] server:

[0643] It is the central device that manages and stores data and exchanges it through communications. The server stores information in a database and runs the AI ​​engine.

[0644] Tablet or smart glasses:

[0645] It will be used as a user interface for cram school students to take lessons and for factory workers to receive work instructions.

[0646] Camera and Microphone:

[0647] This device captures the facial expressions and tone of voice of students and workers in real time.

[0648] Software used

[0649] OpenCV:

[0650] Used to analyze video data from cameras in real time.

[0651] TensorFlow:

[0652] It is used to implement AI models that analyze the facial expressions and tone of voice of students and workers.

[0653] Database Management Systems:

[0654] Stored data is managed using MySQL, PostgreSQL, etc.

[0655] How to carry out the invention

[0656] 1. Registration of information:

[0657] The user (a cram school staff member or a factory manager) uses a dedicated interface to input information such as the student's or worker's goals, current academic ability and skills, and areas of strength and weakness. This information is sent to the server and stored in a database.

[0658] 2. Generate curriculum or work instructions:

[0659] The server passes the stored information to an AI engine to generate optimal curriculum and work instructions, which are then stored back in the database.

[0660] 3. Real-time analysis and feedback:

[0661] The tablet devices and smart glasses use cameras and microphones to capture the facial expressions and tone of voice of students and workers in real time. This data is sent to a server and analyzed by an AI engine. The lesson content and work instructions are adjusted in real time based on the analysis results.

[0662] 4. Question and Answer Management:

[0663] Students and workers can input any questions they may have along the way, and these questions are passed to the AI ​​engine via the server. The AI ​​engine then generates the optimal answer and responds automatically.

[0664] 5. Sharing progress data:

[0665] Data on the progress of lessons and work is stored on a server and periodically analyzed. The results of the analysis are generated as a report and shared with parents and administrators.

[0666] Examples of specific examples and prompts

[0667] Examples:

[0668] Cram school:

[0669] As students take math lessons on tablets, cameras capture their facial expressions, and if AI detects confusion, it simplifies the material or provides additional explanations.

[0670] Factory floor:

[0671] When a worker wears smart glasses to assemble a machine, the glasses analyze hand movements and facial expressions in real time and provide instructions such as "tighten the screws a little more" as needed.

[0672] Example prompt sentence:

[0673] Let AI generate the optimal curriculum based on information such as students' goals, strengths and weaknesses. Then, use the generated curriculum as input to analyze students' facial expressions and tone of voice in real time during class and generate appropriate feedback.

[0674] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0675] Step 1:

[0676] The user inputs information about the student or worker. The user inputs information such as the student's or worker's goals, current academic ability and skills, and areas of strength and weakness through a dedicated interface. The input information is sent to the server, which stores the received information in a database.

[0677] Step 2:

[0678] The server retrieves information from the database and passes it to the AI ​​engine. The server then passes various information about students and workers to the AI ​​engine as input data. Based on this input data, the AI ​​engine generates optimal curriculum and work instructions. The generated curriculum and work instructions are saved in the database.

[0679] Step 3:

[0680] Students and workers use devices to start activities based on the curriculum and work instructions. Students use tablet devices to attend classes, and workers wear smart glasses to perform their work. The devices obtain the curriculum and work instructions from the server and use them.

[0681] Step 4:

[0682] To prepare for real-time analysis, the device captures the students' and workers' behavior through a camera and microphone, and the video and audio data is sent to the server.

[0683] Step 5:

[0684] The server passes the video and audio data to the AI ​​engine for real-time analysis. The AI ​​engine uses OpenCV to analyze the video data and TensorFlow to analyze the audio data. This allows the facial expressions and tone of voice of students and workers to be analyzed. The results of this analysis are sent to the server.

[0685] Step 6:

[0686] The server receives the analysis results and adjusts the curriculum and work instructions in real time based on them.The server generates feedback on lesson content and work instructions based on the analysis results of the AI ​​engine and sends that feedback to the device.

[0687] Step 7:

[0688] Students and workers receive real-time feedback through their devices. Specifically, instructions and points of caution are displayed on tablets or smart glasses. For example, during a lesson, a message such as "You don't fully understand this part, so we'll show you additional explanations," or while working, instructions such as "Tighten the screws a little more" are displayed.

[0689] Step 8:

[0690] The user inputs a question from a student or worker. The question is sent from the device to the server, and then passed from the server to the AI ​​engine. The AI ​​engine generates the optimal answer to the question and returns that answer to the server.

[0691] Step 9:

[0692] The server sends the generated answers to the terminal, where students or workers can check the answers. The answers are displayed and the problems are resolved.

[0693] Step 10:

[0694] The server periodically accumulates progress data of students and workers and passes it to the AI ​​engine for analysis. Based on the progress data, the AI ​​engine analyzes the performance of students and workers and generates a report of the results.

[0695] Step 11:

[0696] The server generates reports that are shared with parents and administrators. The reports include information on the progress of students and workers, as well as issues and areas for improvement, and are shared via email or other means.

[0697] 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.

[0698] The present invention is a private tutoring system that combines artificial intelligence (AI) technology and emotion analysis technology, and a specific implementation method thereof will be described below.

[0699] First, the cram school staff (users) register a new student in the system. Using a dedicated interface, users input information such as the student's goals, current academic ability, and areas of strength and weakness. The terminal receives this information and sends it to the server. The server stores the received information in a database.

[0700] Next, the server retrieves student information from the database and passes it to the AI ​​engine. The AI ​​engine uses this information to generate an optimal curriculum. The generated curriculum is then saved in the database via the server again.

[0701] Students come to a cram school and take classes using a tablet device. The device retrieves curriculum information from the server and provides the student with lesson materials based on that information. If a student has a question during class, the user (student) enters the question through the tablet device. The device sends the question to the server, which passes it on to the AI ​​engine. The AI ​​engine generates the optimal answer to the question and sends it to the device via the server. The device displays the generated answer to the student.

[0702] The system also features an emotion engine that analyzes students' facial expressions and tone of voice in real time during class. The device captures students' reactions and analyzes this data using the emotion engine. The emotion engine then performs a detailed analysis of students' emotional states, such as stress levels and excitement, and sends the analysis results to a server. The server then passes the emotion data to the AI ​​engine, which then adjusts the lesson content based on the analysis results. For example, if the AI ​​engine detects signs of student confusion, it will adjust the difficulty of the lesson or provide additional explanations.

[0703] Furthermore, all question and answer data and emotional data from lessons are stored in a database and taken into consideration when creating the next curriculum, providing a set of curriculum optimized for each individual student.

[0704] The emotion engine periodically accumulates and analyzes students' emotional data and generates reports based on progress data. These reports are shared via email and other means with parents and cram school staff via the server. This allows for a comprehensive understanding of students' learning status and emotional state, enabling appropriate countermeasures to be taken.

[0705] In this way, the present invention solves the problem of labor shortages, improves learning efficiency, meets individual needs, and provides learning support that takes into account the emotional state of students.

[0706] The processing flow will be explained below.

[0707] Step 1:

[0708] The user (a cram school staff member) enters information about a new student (goals, current academic ability, areas of strength and weakness, etc.) into a dedicated interface. The device acquires this information and sends it to the server.

[0709] Step 2:

[0710] The server receives the student information and stores it in a database, which is used for the next process.

[0711] Step 3:

[0712] The server retrieves student information from the database and provides it to the AI ​​engine, which then generates the optimal curriculum based on this information.

[0713] Step 4:

[0714] The curriculum generated by the AI ​​engine is stored in a database via the server, and this curriculum information is used in later steps.

[0715] Step 5:

[0716] Students arrive at the cram school and take classes using a tablet device. The device retrieves current curriculum information from the server and presents the student with the materials they need for class.

[0717] Step 6:

[0718] If a student has a question during class, the user (student) enters the question into the tablet device, which then sends the question to the server.

[0719] Step 7:

[0720] The server sends the question to the AI ​​engine, which generates the optimal answer to the question, and the generated answer is sent to the device via the server.

[0721] Step 8:

[0722] The device displays the generated answer to the user (student), allowing the student to immediately resolve their doubts.

[0723] Step 9:

[0724] During class, the device captures students' facial expressions and tone of voice in real time and sends them to the emotion engine, which then analyzes the data.

[0725] Step 10:

[0726] The emotion engine sends the results of its analysis to a server, which then provides them to an AI engine. The AI ​​engine then adjusts the lesson content based on the analysis results. For example, if a student's stress level is high, it will adjust the difficulty of the lesson to be lower.

[0727] Step 11:

[0728] All questions, answers, and emotional data are stored in a database, which will be used to create the next curriculum and plan lessons.

[0729] Step 12:

[0730] The AI ​​engine periodically generates progress reports for students based on the accumulated data. These reports are shared via email with parents and cram school staff via the server, allowing for a comprehensive understanding of the student's learning progress.

[0731] Through the above steps, the present invention provides a learning experience optimized to the needs of each individual student, solving the problem of labor shortages while also realizing advanced learning support that takes into account the emotional state of students.

[0732] Example 2

[0733] 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."

[0734] Conventional individualized tutoring systems struggled to adjust lesson content in real time based on students' academic ability, level of understanding, and emotional state. As a result, they were unable to provide a learning experience optimized for each student's needs, making it difficult to achieve efficient learning outcomes. It was also difficult to provide immediate and appropriate answers to students' questions, which could lead to inconsistent learning. Furthermore, there was a lack of appropriate means for sharing students' progress and emotional state with parents and tutoring staff.

[0735] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0736] In this invention, the server includes: means for inputting information such as a student's goals, current academic ability, and areas of strength and weakness; means for transmitting the information to the server; means for the server to store the information in a database; means for an AI engine to generate an optimal curriculum based on the stored information; means for storing the generated curriculum in a database; means for a student to take lessons based on the curriculum using a tablet device; means for accepting questions from students during lessons and transmitting the questions to the AI ​​engine; means for the AI ​​engine to generate answers to the questions and return the answers to the students; means for analyzing students' reactions (facial expressions, tone of voice, etc.) in real time and transmitting the information to the server; means for an emotion analysis engine to periodically accumulate and analyze students' emotional data and transmit the analysis results to the server; means for the AI ​​engine to analyze students' reactions and adjust lesson content in real time; means for sharing student progress data with parents and cram school staff; and means for automatically adjusting lesson content based on the student's emotional state. This makes it possible to adjust lesson content in real time according to the student's academic ability, level of understanding, and emotional state, thereby providing an optimized learning experience for each student.

[0737] "Student goals" refer to the specific outcomes or goals that students want to achieve through their studies.

[0738] "Current academic ability" is an assessment of the level of knowledge and skills that a student currently possesses.

[0739] "Strong and weak areas" refers to subjects or areas in which a student is particularly strong and weak.

[0740] A "server" refers to the central device of a computer system that stores and processes data.

[0741] A "database" is a system for organizing and storing information and data.

[0742] An "AI engine" refers to a program that uses machine learning and data analysis to generate optimal curriculum and answers.

[0743] "Curriculum" refers to an educational plan organized according to specific goals or learning objectives.

[0744] "Tablet device" refers to a portable computing device with a touchscreen.

[0745] "Questions" refer to matters that students are unsure about or want to confirm while studying.

[0746] "Answer" refers to the answer or explanation provided to a question.

[0747] "Responses" refer to non-verbal feedback such as facial expressions and tone of voice shown by students during class.

[0748] An "emotion analysis engine" refers to a system that analyzes students' facial expressions, voices, etc. to evaluate their emotional state.

[0749] "Progress Data" refers to data that shows a student's learning process and academic progress.

[0750] "Guardians" refers to the parents or guardians of students attending cram schools.

[0751] "Cram school personnel" refers to staff, teachers, and other personnel who work at cram schools.

[0752] "Class content" refers to the teaching materials, content taught, learning activities, etc. used in class.

[0753] "Storage" refers to the collection and storage of information or data.

[0754] "Analysis" refers to the detailed examination and analysis of information or data.

[0755] The present invention is a private tutoring system that combines artificial intelligence (AI) technology and emotion analysis technology. This system provides an optimal curriculum based on a student's learning status and can personalize the learning experience by analyzing their reactions and emotional state in real time. A specific method for implementing this invention is described below.

[0756] First, to register a new student in the system, the user (cram school staff) enters information such as the student's goals, current academic ability, and areas of strength and weakness through a dedicated interface. The device (PC or tablet) sends this information to the server. The server stores the received information in a database. Specifically, the information is managed using a relational database such as MySQL or PostgreSQL.

[0757] The server then retrieves student information from the database and passes it to the AI ​​engine, which uses machine learning frameworks such as TensorFlow and PyTorch to analyze student characteristics and generate an optimal curriculum. This generated curriculum is then stored in the database via the server.

[0758] When a student comes to a cram school and takes a class using a tablet device, the device retrieves curriculum information from the server and provides the student with lesson materials based on that information. If a student has a question during class, the user (student) inputs the question through the tablet device. The device sends the question to the server, which then passes it on to the AI ​​engine. The AI ​​engine generates the optimal answer to the question and sends it to the device via the server. The device then displays the generated answer to the student.

[0759] For emotion analysis, the device captures students' facial expressions and tone of voice in real time and sends them to the emotion engine. The emotion engine uses technologies such as OpenCV and Dlib to analyze the student's stress level and excitement. The analysis results are sent to a server, which passes them on to an AI engine. The AI ​​engine then adjusts the lesson content based on this data. For example, if a student is confused, the AI ​​engine may instruct the teacher to lower the difficulty of the lesson or provide additional explanations.

[0760] Every time a student takes a class, all their questions, answers, and emotional data are stored in a database. This information is taken into account when generating the next curriculum, providing a more personalized learning experience.

[0761] Furthermore, the emotion engine periodically accumulates and analyzes students' emotional data and generates reports based on progress data. The server then shares these reports with parents and cram school staff via email, etc. This allows for a comprehensive understanding of students' learning status and emotional state, enabling appropriate countermeasures to be taken.

[0762] Examples of examples and prompts:

[0763] For example, if a new student wants to learn the basics of mathematics, the user (a cram school staff member) fills in a special input form with the following information: "Goal: Understand the basics of mathematics, Current academic level: Intermediate, Strong areas: Arithmetic, Weak areas: Algebra." Based on this information, the AI ​​engine generates a curriculum that starts with basic arithmetic and gradually progresses to Algebra.

[0764] Example prompt:

[0765] Prompt for user (cram school staff): "Please enter registration information for a new student. Please include their goals, current academic ability, and areas of strength and weakness."

[0766] Prompt for students: "If you have any questions during class, please use the tablet to type your question and we will provide you with an immediate answer."

[0767] This invention will solve the problem of labor shortages, improve learning efficiency, and meet individual needs, and will also provide learning support that takes into account the emotional state of students.

[0768] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0769] Step 1:

[0770] The user (cram school staff) enters information such as the student's goals, current academic ability, and areas of strength and weakness using a dedicated interface (e.g., web form or app). After entering the information, the device sends it to the server, which then stores the received information in a database.

[0771] Input: Information such as student goals, current academic ability, strengths and weaknesses

[0772] Output: Save student information to database

[0773] Specific operation: The user enters the required information into a dedicated web form and clicks the "Submit" button. The device sends this information to the server, which then stores it in a database.

[0774] Step 2:

[0775] The server retrieves student information from the database and passes it to the AI ​​engine. The AI ​​engine uses machine learning frameworks such as TensorFlow and PyTorch to analyze the student's characteristics. Based on this, it generates an optimal curriculum. The generated curriculum is then saved in the database via the server.

[0776] Input: Student information stored in the database

[0777] Output: Save the generated curriculum to a database

[0778] Specific operation: The server periodically checks for newly added student information and forwards this information to the AI ​​engine. The AI ​​engine generates an optimal curriculum and sends it back to the server. The server stores the curriculum in a database.

[0779] Step 3:

[0780] When students come to the cram school and take classes using a tablet device, the device retrieves curriculum information from the server and provides the students with lesson materials based on that information.

[0781] Input: Curriculum information stored in the database

[0782] Output: Lesson materials provided to students

[0783] Specific operation: When a student logs in to a tablet device, the system automatically downloads the student's curriculum from the server and then displays the first lesson slide to the student.

[0784] Step 4:

[0785] If a student has a question during class, the user (student) inputs the question through a tablet device. The device sends the question to the server, which passes it to the AI ​​engine. The AI ​​engine generates the optimal answer to the question and sends it to the device via the server. The device then displays the generated answer to the student.

[0786] Input: Student question

[0787] Output: Answer from the AI ​​engine

[0788] Specific operation: The student taps the "Ask a question" button and enters the question text. The question is sent to the server, where the AI ​​engine analyzes it and generates an answer. The device receives this and displays it to the student.

[0789] Step 5:

[0790] The device captures the student's facial expressions and tone of voice in real time and sends them to the emotion engine, which analyzes the student's stress level and excitement level and sends the results to the server.

[0791] Input: Facial expressions and tone of voice captured in real time

[0792] Output: Emotion analysis results

[0793] How it works: The tablet's camera and microphone capture the student's face and voice, and send them to the emotion engine every few seconds. The analyzed data is then sent to the server.

[0794] Step 6:

[0795] The server passes the emotional data to an AI engine, which then adjusts the lesson content based on the data. For example, if a student is confused, the AI ​​engine can lower the difficulty of the lesson or provide additional explanations.

[0796] Input: Sentiment analysis results

[0797] Output: Adjusted lesson content

[0798] Specific operation: The server receives the analysis results from the emotion engine and forwards them to the AI ​​engine. The AI ​​engine gradually adjusts the lesson content and sends it to the device via the server. The device then displays the new instructions to the student.

[0799] Step 7:

[0800] All questions, answers, and emotional data from lessons are stored in a database, and this data is taken into account when generating the next curriculum.

[0801] Input: Questions and answers, emotion data

[0802] Output: Individual data to be reflected in the next curriculum

[0803] Specific operation: After the lesson ends, the device automatically sends all learning data to the server, which stores this data in a database and uses it as a reference when the AI ​​engine generates the next curriculum.

[0804] Step 8:

[0805] The emotion engine periodically analyzes students' emotion data and generates reports based on their progress. The server then shares these reports with parents and school staff via email or other means.

[0806] Input: Accumulated emotion data

[0807] Output: Progress report

[0808] How it works: The emotion engine analyzes students' emotion data monthly and generates a report. The server converts this report into PDF format and sends it to the email addresses of parents and other relevant parties.

[0809] (Application example 2)

[0810] 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."

[0811] Conventional learning support systems and customer service support systems in brick-and-mortar stores have had difficulty accurately grasping the emotional state of individual customers or students in real time and providing appropriate instruction or customer service based on that information. Furthermore, there was a lack of efficient means for suggesting optimal products based on customers' emotions and purchasing history.

[0812] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means. In this invention, the server includes: means for inputting information such as a student's goals, current academic ability, and areas of strength and weakness; means for transmitting the information to the server; means for the server to store the information in a database; means for an AI engine to generate an optimal curriculum based on the stored information; means for storing the generated curriculum in a database; means for a student to take lessons based on the curriculum using a tablet device; means for accepting questions from students during lessons and transmitting the questions to the AI ​​engine; means for the AI ​​engine to generate answers to the questions and return the answers to the students; means for analyzing students' reactions (facial expressions, tone of voice, etc.) in real time and transmitting the information to the server; means for the AI ​​engine to analyze students' reactions and adjust lesson content in real time; means for sharing student progress data with parents and cram school personnel; means for analyzing customers' facial expressions and tone of voice in a store to grasp their emotional state; means for the AI ​​engine to generate optimal customer service methods and product suggestions based on the customer's emotional state and purchase history; and means for notifying store staff of the customer service methods and product suggestions. This will enable individually optimized learning support and personalized customer service in physical stores.

[0813] "Student goals" are the specific learning outcomes or objectives that students want to achieve during the learning process.

[0814] "Current academic ability" refers to the level of knowledge and skills that a student currently possesses.

[0815] "Strong and weak areas" refer to subjects or areas that are relatively easy for students to understand and master, and subjects or areas that are difficult for students to understand and master.

[0816] "Means for inputting information" refers to the interface or device through which a user provides information about a student or customer to the system.

[0817] "Means for sending to the server" refers to the communication protocol or technology used to transfer data from the terminal to the server.

[0818] "Means for storing data in a database" refers to a mechanism for efficiently recording received data and making it possible to search and update it as needed.

[0819] An "AI engine" is software that uses artificial intelligence to analyze data and generate solutions or suggestions for specific problems.

[0820] "Curriculum generation means" refers to algorithms or processes for constructing appropriate lesson plans and materials based on student information.

[0821] A "tablet device" is a portable computer that allows input and operation via a touch screen.

[0822] "Means for accepting questions and sending them to the AI ​​engine" refers to a mechanism that allows students or customers to input doubts or queries into the system and forward them to the AI ​​engine.

[0823] "Means for generating and returning an answer" refers to the mechanism by which the AI ​​engine creates the optimal answer to a question and provides that answer to the questioner.

[0824] "Means for analyzing reactions in real time" refers to technology that instantly evaluates the reactions of students or customers, such as facial expressions and tone of voice, and analyzes their emotional state.

[0825] "Means for sharing progress data" refers to a system for notifying relevant parties of progress data on students' learning status and customer purchasing behavior.

[0826] "Means of analyzing facial expressions and tone of voice to grasp emotional state" refers to technology that analyzes data acquired using a camera or microphone to identify the subject's emotions.

[0827] "Means for generating optimal customer service methods and product suggestions based on purchasing history" refers to a system in which AI uses customers' past purchasing data to generate optimal customer service methods and suggested products for purchase.

[0828] "Means of notifying store staff of customer service methods and product suggestions" refers to a system that provides information generated by AI to store staff in real time or at any time.

[0829] This invention is a personalized learning and customer service support system that combines AI technology and emotion analysis technology. First, we will explain the overall flow of the system.

[0830] 1. Enter student and customer information

[0831] The user enters information such as the student's goals, current academic ability, areas of strength and weakness, as well as the customer's purchasing history and preferred categories through a dedicated interface. This information is sent from the terminal to the server.

[0832] 2. Storing data and sending it to the AI ​​engine

[0833] The server stores the received information in a database. The server then sends the stored information to the AI ​​engine. The AI ​​engine generates the optimal curriculum and customer service methods based on the received information, and stores them in the database again via the server.

[0834] 3. Teaching and customer service using tablet devices

[0835] Students come to the cram school and take lessons using a tablet device. The device provides lessons based on curriculum information obtained from the server. In physical stores, store staff use smart glasses or smartphones to capture customers' facial expressions and tone of voice. This real-time data is sent to the server for analysis.

[0836] 4. Questions and Answers

[0837] If a student has a question during class, they can input it into their tablet device. The device sends the question to the server, which passes it on to the AI ​​engine. The AI ​​engine generates the optimal answer and sends it back to the device via the server. Similarly, when dealing with customers in-store, the AI ​​engine will suggest the best product and customer service methods.

[0838] 5. Sentiment analysis and adjustment of lesson content and customer service content

[0839] During lessons, the devices capture students' facial expressions and tone of voice in real time and send them to a server. An emotion analysis engine analyzes this data to determine students' stress levels and excitement levels. The AI ​​engine adjusts lesson content in real time based on the emotional data. In-store, customer service methods and product recommendations are adjusted based on customer emotional data.

[0840] 6. Sharing progress data

[0841] All questions and answers during lessons, as well as student emotional data, are stored in a database. This data is taken into consideration when creating the next curriculum and proposing customer service methods. Progress reports are generated by an AI engine and shared with parents, cram school staff, and store personnel. This allows for a comprehensive understanding of the status of students and customers and allows for appropriate countermeasures to be taken.

[0842] Hardware and software used

[0843] Hardware: Tablets, smart glasses, smartphones

[0844] Software: Python-based AI engine, OpenCV (image processing library), Emotion Analysis API, database management system

[0845] Examples of specific examples and prompts

[0846] As a specific example, when dealing with customers in a physical store, if the AI ​​engine detects signs of confusion in the customer, it will suggest to the store staff that they "speak in a calm tone and explain about new products in the store."

[0847] Example prompt sentence:

[0848] "If a customer is confused, please suggest the best way to serve them."

[0849] In this way, the system provides both individually optimized learning support and customer service in a physical store, solving conventional problems.

[0850] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0851] Step 1:

[0852] The user enters information such as the student's goals, current academic ability, areas of strength and weakness, as well as the customer's purchasing history and preferred categories into a dedicated interface. The entered information is sent from the terminal to the server.

[0853] Input: Student and Customer Information

[0854] Output: Information data sent to the server

[0855] How it works: The user uses a dedicated interface to input information via a keyboard or touchscreen. The device collects this data and sends it to the server via an HTTP request.

[0856] Step 2:

[0857] The server stores the received information in a database.

[0858] Input: Information data sent from the terminal

[0859] Output: Information stored in the database

[0860] Specific operations: The server stores the received data in a structured format using a database management system, and inserts it into the database using an SQL query.

[0861] Step 3:

[0862] The server sends the stored information to the AI ​​engine, which then generates the optimal curriculum and customer service methods based on the received information, and stores them in the database again via the server.

[0863] Input: Information stored in a database

[0864] Output: Generated curriculum and customer service methods

[0865] Specific operation: The server sends data to the AI ​​engine using an API request. The AI ​​engine analyzes the data using a machine learning model and generates the optimal curriculum and customer service method. The generated data is sent to the server as an API response, and the server stores it in the database again.

[0866] Step 4:

[0867] Students come to the cram school and use tablets to take lessons based on the curriculum, while store staff use smart glasses or smartphones to capture customers' facial expressions and tone of voice.

[0868] Input: Curriculum information obtained from the server, customer facial expressions and tone of voice

[0869] Output: Lesson content delivered, real-time data captured

[0870] How it works: The tablet device retrieves curriculum information from the server and displays lesson content accordingly. The smart glasses or smartphone uses a camera and microphone to capture the customer's facial expressions and tone of voice in real time, formatting the data and sending it to the server.

[0871] Step 5:

[0872] If a student has a question during class, they can enter it into their tablet device, which then sends it to the server, which then passes it on to the AI ​​engine.

[0873] Input: Student question

[0874] Output: Question data sent to the server

[0875] How it works: Students enter questions into their tablet devices, which then capture and send them to the server. The server then passes the received question data to the AI ​​engine via an API request.

[0876] Step 6:

[0877] The AI ​​engine generates the optimal answer and sends it to the device via the server.

[0878] Input: Question data sent from the server

[0879] Output: Answer data returned to the student

[0880] How it works: The AI ​​engine analyzes the question data and uses machine learning models to generate the best answer. The generated answer is returned to the server via an API response, and the server then sends it to the student's device.

[0881] Step 7:

[0882] During class, the device captures students' facial expressions and tone of voice in real time and sends them to a server. An AI engine analyzes this data to determine students' stress levels and excitement levels.

[0883] Input: Real-time facial expression data and tone of voice data of students

[0884] Output: Parsed emotion data

[0885] How it works: The tablet uses a camera and microphone to capture students' facial expressions and tone of voice, and sends the data to a server. An AI engine analyzes this data and identifies their emotional state.

[0886] Step 8:

[0887] The AI ​​engine adjusts lesson content in real time based on emotional data, and in-store customer service methods and product recommendations are adjusted based on customer emotional data.

[0888] Input: Parsed emotion data

[0889] Output: Adjusted lesson content and customer service methods

[0890] Specific actions: Based on the analysis results, the AI ​​engine adjusts the lesson content to lower the difficulty level or provide additional explanations as needed. In physical stores, it changes and adjusts customer service methods and product recommendations based on the customer's emotional state.

[0891] Step 9:

[0892] All questions and answers during lessons, as well as student emotional data, are stored in a database and are taken into consideration when creating the next curriculum and proposing customer service methods.

[0893] Input: Question and answer data during class, emotion data

[0894] Output: Progress data stored in a database

[0895] Specific operation: The server saves questions, answers, and emotion data from lessons in a database. This data is used to generate the next curriculum and improve customer service methods.

[0896] Step 10:

[0897] Progress reports are generated by an AI engine and shared with parents, cram school staff, and store personnel.

[0898] Input: Progress data stored in the database

[0899] Output: Generated progress report

[0900] How it works: The AI ​​engine analyzes the progress data and creates a report. The report is then shared via email with parents, cram school staff, and store staff via a server.

[0901] 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.

[0902] 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.

[0903] 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.

[0904] [Third embodiment]

[0905] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0906] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0907] 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).

[0908] 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.

[0909] 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.

[0910] 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).

[0911] 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.

[0912] 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.

[0913] 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.

[0914] 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.

[0915] 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.

[0916] 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."

[0917] The present invention is a private tutoring system that utilizes artificial intelligence (AI), and the method for realizing this system is explained below. Here, each component, its function, and specific operating procedures are shown.

[0918] First, the cram school staff (users) register a new student in the system. Using a dedicated interface, users input information such as the student's goals, current academic ability, and areas of strength and weakness. The terminal receives this information and sends it to the server. The server stores the received information in a database.

[0919] Next, the server retrieves student information from the database and passes it to the AI ​​engine. The AI ​​engine uses this information to generate an optimal curriculum. The generated curriculum is then saved in the database via the server again.

[0920] Students come to the cram school and take classes using a tablet device. The device retrieves curriculum information from the server and provides the students with lesson materials based on that information. If a student has a question during the actual class, the user (student) inputs the question through the tablet device. The device sends the question to the server, which passes it on to the AI ​​engine. The AI ​​engine generates the optimal answer to the question and sends it to the device via the server. The device returns the generated answer to the student.

[0921] The device also features a system for analyzing students' facial expressions and tone of voice in real time during class. The device analyzes students' reactions and sends the data to a server. The server passes this data to an AI engine, which then adjusts the lesson content based on the analysis results. For example, if a student shows signs of confusion, the AI ​​engine will instruct the teacher to lower the difficulty of the lesson or provide additional explanations.

[0922] Furthermore, all questions and answers during the lesson are stored in a database and taken into consideration when creating the next curriculum, thus providing a set of curriculum that is optimized for each individual student.

[0923] Finally, students' learning progress data is analyzed periodically, and the results are compiled into a report. This report is shared via a server with parents and cram school staff via email, etc. This allows students' progress to be tracked as needed and necessary measures to be taken.

[0924] In this way, the present invention solves the problem of labor shortages while realizing efficient and effective learning instruction that meets individual learning needs.

[0925] The processing flow will be explained below.

[0926] Step 1:

[0927] The user (a cram school staff member) enters information about a new student (goals, current academic ability, areas of strength and weakness, etc.) into a dedicated interface. The device then sends this information to the server.

[0928] Step 2:

[0929] The server stores the received student information in a database, which is used in subsequent processes.

[0930] Step 3:

[0931] The server retrieves student information from the database and passes it to the AI ​​engine, which then generates the optimal curriculum based on this information.

[0932] Step 4:

[0933] The generated curriculum is stored in a database via a server, which allows the curriculum information to be used later.

[0934] Step 5:

[0935] Students attend classes at the cram school using a tablet device. The device retrieves current curriculum information from the server and provides students with the materials they need for class.

[0936] Step 6:

[0937] If a student has a question during class, the user (student) can input the question through a tablet device, which then sends the question to the server.

[0938] Step 7:

[0939] The server passes the question to the AI ​​engine, which generates the optimal answer to the question, and the generated answer is sent to the device via the server.

[0940] Step 8:

[0941] The device displays the generated answer to the user (student), allowing the student to immediately resolve their doubts.

[0942] Step 9:

[0943] During class, the device captures students' reactions in real time for analysis of their facial expressions and tone of voice, and this data is sent to a server.

[0944] Step 10:

[0945] The server passes the student's reaction data to an AI engine, which then adjusts the lesson content based on the analysis results. For example, if a student is confused, it will instruct the AI ​​engine to lower the difficulty of the lesson.

[0946] Step 11:

[0947] All questions and answers are stored in a database, which will be used to create the next curriculum.

[0948] Step 12:

[0949] The AI ​​engine periodically analyzes students' learning progress data and generates progress reports, which are shared with parents and cram school staff via a server.

[0950] Example 1

[0951] 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."

[0952] Conventional individualized learning systems struggled to provide an effective curriculum tailored to each learner's learning progress and level of understanding, making it difficult to maximize learning efficiency. Furthermore, they lacked the means to respond to learners' reactions and questions in real time, making it impossible to provide optimal instruction to each learner. Furthermore, reporting progress to parents and educational facility officials was time-consuming, making it difficult to share information in a timely manner.

[0953] 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.

[0954] In this invention, the server includes: a means for inputting information such as a learner's goals, current academic ability, and areas of strength and weakness; a means for transmitting the information to the server; a means for the server to store the information in a database; a means for an AI engine to generate an optimal curriculum based on the stored information; a means for storing the generated curriculum in a database; a means for a learner to take lessons based on the curriculum using a mobile device; a means for accepting questions from the learner during lessons and transmitting the questions to the AI ​​engine; a means for the AI ​​engine to generate answers to the questions and return the answers to the learner; a means for analyzing the learner's responses (e.g., facial expressions, tone of voice) in real time and transmitting the information to the server; a means for the AI ​​engine to analyze the learner's responses and adjust the lesson content in real time; a means for sharing the learner's progress data with parents and educational facility personnel; and a means for storing the learner's question data and answer data for a certain period of time and utilizing them when creating the next curriculum. This enables the provision of teaching methods optimized for each learner and high learning effectiveness. The ability to quickly and accurately share information with parents and educational facility personnel also enables appropriate management of the learner's learning progress.

[0955] "Learner" refers to an individual who uses the system to receive an education.

[0956] A "server" refers to a computer device that provides specific services or information over a network.

[0957] A "database" refers to a system that stores and manages large amounts of data in an organized manner.

[0958] An "AI engine" refers to a system that uses artificial intelligence technology to analyze data and generate optimal results.

[0959] "Curriculum" refers to a learning plan that is structured based on the learner's educational goals.

[0960] "Mobile devices" refer to electronic devices that are portable and used by learners. Examples include tablets and smartphones.

[0961] "Analyzing in real time" refers to the process of analyzing input information immediately and obtaining results.

[0962] "Progress data" refers to data that indicates the progress and results of a learner's learning activities.

[0963] "Guardian" means the parent or guardian's representative.

[0964] "Educational facility personnel" refers to staff and administrators of the educational institution to which the learner belongs.

[0965] "Question data" refers to information about questions entered by learners.

[0966] "Answer data" refers to information about an answer generated based on question data.

[0967] MODE FOR CARRYING OUT THE INVENTION

[0968] This invention is a personalized tutoring system that utilizes artificial intelligence (AI). This section explains in detail each component and the role they play. This system enables efficient learning instruction tailored to the needs of each learner.

[0969] First, the user registers a new learner using a dedicated web interface. The user enters information into the interface, such as the learner's goals, current academic ability, and areas of strength and weakness, and presses the submit button. At this time, the device receives the entered information and sends it to the server. For example, the user enters "Taro Tanaka, second-year junior high school student, aims to raise his math score by 10 points, his strengths are set theory, and his weaknesses are simultaneous equations." This information is sent to the server, which stores it in a database.

[0970] Next, the server retrieves the learner's information from the database and passes it to the AI ​​engine. The AI ​​engine analyzes the learner's information and generates an optimal curriculum. The generated curriculum is then saved in the database via the server again. For example, based on the information of "Taro Tanaka," the AI ​​engine generates a curriculum of "review of basic mathematics, review of set theory, basics and applications of simultaneous equations, and practice with past exam questions."

[0971] At a cram school, learners attend classes using mobile devices (e.g., tablet devices). The devices connect to a server and obtain curriculum information. Lesson materials are displayed on the device based on the obtained curriculum, and the learner follows along as they study. If a question arises during class, the learner enters it through the device. The device sends the question to the server, which passes it on to an AI engine. The AI ​​engine generates the best answer to the question, and that answer is sent to the device via the server. The device displays the generated answer to the learner.

[0972] The device also has a function for analyzing learners' facial expressions and tone of voice in real time during lessons. The device analyzes the learners' reactions and sends the data to a server. The server passes the data to an AI engine, which then adjusts the lesson content based on the analysis results. For example, if a learner shows a confused expression, the AI ​​engine will issue instructions to lower the difficulty of the lesson, and these instructions will be sent to the device via the server.

[0973] Furthermore, all question and answer data is stored in a database and reflected in the next curriculum creation, providing a set of curriculum optimized for each individual learner.

[0974] Finally, the learner's learning progress data is periodically retrieved from the database by the server and passed to the AI ​​engine. The AI ​​engine analyzes the progress data and generates a report. This report is then emailed to parents and educational institution officials via the server. For example, a progress report summarizing the learner's achievements and challenges can be emailed to parents.

[0975] Example prompt sentence:

[0976] We have a student named "Taro Tanaka" who is in the second year of junior high school. His goal is to raise his math score by 10 points. His current strengths are "set theory" and his weaknesses are "simultaneous equations." Please generate the optimal learning curriculum for him.

[0977] In this way, the present invention is a system that provides efficient and effective learning guidance that meets individual learning needs and achieves high learning results.

[0978] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0979] Program processing flow

[0980] Step 1: Register student information

[0981] Specific behavior:

[0982] The user opens a dedicated web interface.

[0983] The user enters the learner's basic information (name, grade, goal, areas of strength and weakness) and presses the send button.

[0984] The terminal receives this input data. Input: Basic information of the learner. Output: Learner information data sent to the terminal.

[0985] Data processing and calculation:

[0986] The terminal formats the input information and sends it to the server.

[0987] Examples:

[0988] The user enters "Taro Tanaka, second-year junior high school student, increase math score by 10, strong point is set theory, weak point is simultaneous equations" and presses the send button.

[0989] Step 2: Saving to the database

[0990] Specific behavior:

[0991] The server receives the learner information sent from the terminal.

[0992] The server stores the received information in a database. Input: Learner information data. Output: Information stored in the database.

[0993] Data processing and calculation:

[0994] The server stores the received data in a database in an appropriate format.

[0995] Examples:

[0996] The server stores the information in a database: "Taro Tanaka, second-year junior high school student, aims to raise his mathematics score by 10 points, his forte is set theory, his weakness is simultaneous equations."

[0997] Step 3: Generate the curriculum

[0998] Specific behavior:

[0999] The server retrieves the learner's information from the database.

[1000] The server passes the acquired information to the AI ​​engine. Input: Learner information. Output: Information passed to the AI ​​engine.

[1001] Data processing and calculation:

[1002] The AI ​​engine analyzes learner information and generates the optimal curriculum.

[1003] Examples:

[1004] Based on the information "Taro Tanaka, second-year junior high school student, aims to raise his mathematics score by 10 points, his strengths are set theory, and his weaknesses are simultaneous equations," the AI ​​engine generates a curriculum of "reviewing basic mathematics, reviewing set theory, learning from the basics to applications of simultaneous equations, and practicing past exam questions."

[1005] Step 4: Save the curriculum

[1006] Specific behavior:

[1007] The server stores the generated curriculum in a database. Input: Generated curriculum. Output: Curriculum stored in the database.

[1008] Data processing and calculation:

[1009] The server formats the generated curriculum data and stores it in a database.

[1010] Examples:

[1011] The generated curriculum, "Review of basic mathematics, review of set theory, basics to applications of simultaneous equations, and practice of past exam questions," is saved in a database.

[1012] Step 5: Conducting lessons

[1013] Specific behavior:

[1014] The device (tablet) connects to the server and retrieves curriculum information.

[1015] The terminal displays the lesson material based on the acquired curriculum information. Input: Curriculum information. Output: Lesson material displayed on the terminal.

[1016] Data processing and calculation:

[1017] The device selects and displays appropriate lesson materials based on the acquired curriculum.

[1018] Examples:

[1019] Taro Tanaka will use a tablet to take classes based on the curriculum: "Review of basic mathematics, review of set theory, basics and applications of simultaneous equations, and practice with past exam questions."

[1020] Step 6: Accepting and answering questions

[1021] Specific behavior:

[1022] Learners enter their questions during class.

[1023] The terminal sends the question to the server. Input: The learner's question. Output: The question data sent to the server.

[1024] The server passes the question to the AI ​​engine.

[1025] The AI ​​engine generates answers to questions.

[1026] The server sends the generated response to the terminal.

[1027] The device displays the answer to the learner. Input: Answer from the AI ​​engine. Output: Answer displayed on the device.

[1028] Data processing and calculation:

[1029] The AI ​​engine analyzes the question data and generates the optimal answer.

[1030] Examples:

[1031] Taro Tanaka types in a question about simultaneous equations, saying, "I don't know how to solve simultaneous equations." The AI ​​engine generates a "basic solution to simultaneous equations" and displays it on the tablet.

[1032] Step 7: Analyze responses and adjust lesson content

[1033] Specific behavior:

[1034] The device analyzes the learner's facial expressions and tone of voice in real time.

[1035] The device sends the analysis results to the server. Input: Facial expression and tone of voice data. Output: Analysis data sent to the server.

[1036] The server passes the analysis results to the AI ​​engine.

[1037] The AI ​​engine adjusts the lesson content based on the analysis results.

[1038] The server transmits the adjusted content to the terminal.

[1039] The device displays the adjusted lesson content to the learner. Input: Instructions from the AI ​​engine. Output: Adjusted lesson content.

[1040] Data processing and calculation:

[1041] The AI ​​engine analyzes facial expressions and tone of voice data to adjust the lesson content optimally.

[1042] Examples:

[1043] If Taro Tanaka looks confused, the AI ​​engine will instruct him to "slow down the pace of the lesson," and the change will be reflected on the tablet.

[1044] Step 8: Generate and share progress reports

[1045] Specific behavior:

[1046] The server periodically retrieves learner progress data from the database.

[1047] The server passes the acquired data to the AI ​​engine. Input: Progress data. Output: Data passed to the AI ​​engine.

[1048] An AI engine analyzes progress data and generates reports.

[1049] The server sends the generated report to parents and educational institution officials. Input: Generated report. Output: Sent report.

[1050] Data processing and calculation:

[1051] The AI ​​engine analyzes the progress data and creates a detailed report.

[1052] Examples:

[1053] The server retrieves Taro Tanaka's monthly progress data, and the AI ​​engine analyzes the data to generate a report that is then emailed to his parents.

[1054] (Application example 1)

[1055] 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."

[1056] Current individualized cram school systems have difficulty analyzing students' reactions (facial expressions and tone of voice) in real time while lessons are in progress and instantly adjusting lesson content. Furthermore, in on-site work in factories and other places, systems that provide appropriate instructions and support in real time according to the worker's skills and situation are inadequate. This leads to a lack of efficient instruction and support at cram schools and on-site factories, resulting in problems such as reduced learning effectiveness and work efficiency.

[1057] 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.

[1058] In this invention, the server includes: means for inputting information such as a student's goals, current academic ability, and areas of strength and weakness; means for transmitting that information to the server; means for the server to store that information in a database; means for an AI engine to generate an optimal curriculum based on the stored information; means for storing the generated curriculum in a database; means for a student to take lessons based on the curriculum using a tablet device; means for accepting questions from students during lessons and transmitting those questions to the AI ​​engine; means for the AI ​​engine to generate answers to the questions and return those answers to the students; means for analyzing students' reactions (facial expressions, tone of voice, etc.) in real time and transmitting that information to the server; means for the AI ​​engine to analyze students' reactions and adjust lesson content in real time; means for sharing students' progress data with parents and cram school personnel; means for a worker to register individual skills, goals, and tasks that the worker is good at and bad at; means for analyzing the worker's facial expressions and tone of voice in real time and transmitting that information to the server; and means for the AI ​​engine to analyze the worker's reactions and adjust task content in real time. This allows for optimal guidance and work support for each individual.

[1059] A "student" is an individual receiving education at a cram school or educational facility.

[1060] "Goals" refer to specific results or objectives that you want to achieve in individual learning or work.

[1061] "Academic ability" is the ability that represents a student's current knowledge and understanding of learning.

[1062] "Strengths and weaknesses" indicate areas of learning or work in which a student is particularly strong or weak.

[1063] A "server" is a device that manages and stores data and provides data and functions over a computer network.

[1064] A "database" is a place where data is systematically organized and stored in digital form.

[1065] An "AI engine" is the core part of software that uses artificial intelligence to analyze data and generate optimal results and answers.

[1066] A "curriculum" refers to a systematically planned learning program that covers the subjects and content that students should learn.

[1067] A "tablet device" is a small, portable computing device that can be operated primarily via a touch screen.

[1068] "Reactions" refers to real-time feedback such as facial expressions, tone of voice, and behavior shown by students or workers during lessons or work.

[1069] "Worker" refers to a person who performs a specific task in a factory or on a work site.

[1070] "Skills" refers to the knowledge and abilities that a worker has to perform a specific task or technique.

[1071] "Instruction" refers to the act of teaching and guiding students or workers on how to study or work in an appropriate manner.

[1072] "Work support" refers to providing appropriate instructions and assistance to workers so that they can perform their work efficiently.

[1073] System program description

[1074] This invention proposes a system that utilizes an AI engine to provide real-time support for work and learning in private tutoring schools and factory sites.

[1075] Hardware used

[1076] server:

[1077] It is the central device that manages and stores data and exchanges it through communications. The server stores information in a database and runs the AI ​​engine.

[1078] Tablet or smart glasses:

[1079] It will be used as a user interface for cram school students to take lessons and for factory workers to receive work instructions.

[1080] Camera and Microphone:

[1081] This device captures the facial expressions and tone of voice of students and workers in real time.

[1082] Software used

[1083] OpenCV:

[1084] Used to analyze video data from cameras in real time.

[1085] TensorFlow:

[1086] It is used to implement AI models that analyze the facial expressions and tone of voice of students and workers.

[1087] Database Management Systems:

[1088] Stored data is managed using MySQL, PostgreSQL, etc.

[1089] How to carry out the invention

[1090] 1. Registration of information:

[1091] The user (a cram school staff member or a factory manager) uses a dedicated interface to input information such as the student's or worker's goals, current academic ability and skills, and areas of strength and weakness. This information is sent to the server and stored in a database.

[1092] 2. Generate curriculum or work instructions:

[1093] The server passes the stored information to an AI engine to generate optimal curriculum and work instructions, which are then stored back in the database.

[1094] 3. Real-time analysis and feedback:

[1095] The tablet devices and smart glasses use cameras and microphones to capture the facial expressions and tone of voice of students and workers in real time. This data is sent to a server and analyzed by an AI engine. The lesson content and work instructions are adjusted in real time based on the analysis results.

[1096] 4. Question and Answer Management:

[1097] Students and workers can input any questions they may have along the way, and these questions are passed to the AI ​​engine via the server. The AI ​​engine then generates the optimal answer and responds automatically.

[1098] 5. Sharing progress data:

[1099] Data on the progress of lessons and work is stored on a server and periodically analyzed. The results of the analysis are generated as a report and shared with parents and administrators.

[1100] Examples of specific examples and prompts

[1101] Examples:

[1102] Cram school:

[1103] As students take math lessons on tablets, cameras capture their facial expressions, and if AI detects confusion, it simplifies the material or provides additional explanations.

[1104] Factory floor:

[1105] When a worker wears smart glasses to assemble a machine, the glasses analyze hand movements and facial expressions in real time and provide instructions such as "tighten the screws a little more" as needed.

[1106] Example prompt sentence:

[1107] Let AI generate the optimal curriculum based on information such as students' goals, strengths and weaknesses. Then, use the generated curriculum as input to analyze students' facial expressions and tone of voice in real time during class and generate appropriate feedback.

[1108] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1109] Step 1:

[1110] The user inputs information about the student or worker. The user inputs information such as the student's or worker's goals, current academic ability and skills, and areas of strength and weakness through a dedicated interface. The input information is sent to the server, which stores the received information in a database.

[1111] Step 2:

[1112] The server retrieves information from the database and passes it to the AI ​​engine. The server then passes various information about students and workers to the AI ​​engine as input data. Based on this input data, the AI ​​engine generates optimal curriculum and work instructions. The generated curriculum and work instructions are saved in the database.

[1113] Step 3:

[1114] Students and workers use devices to start activities based on the curriculum and work instructions. Students use tablet devices to attend classes, and workers wear smart glasses to perform their work. The devices obtain the curriculum and work instructions from the server and use them.

[1115] Step 4:

[1116] To prepare for real-time analysis, the device captures the students' and workers' behavior through a camera and microphone, and the video and audio data is sent to the server.

[1117] Step 5:

[1118] The server passes the video and audio data to the AI ​​engine for real-time analysis. The AI ​​engine uses OpenCV to analyze the video data and TensorFlow to analyze the audio data. This allows the facial expressions and tone of voice of students and workers to be analyzed. The results of this analysis are sent to the server.

[1119] Step 6:

[1120] The server receives the analysis results and adjusts the curriculum and work instructions in real time based on them.The server generates feedback on lesson content and work instructions based on the analysis results of the AI ​​engine and sends that feedback to the device.

[1121] Step 7:

[1122] Students and workers receive real-time feedback through their devices. Specifically, instructions and points of caution are displayed on tablets or smart glasses. For example, during a lesson, a message such as "You don't fully understand this part, so we'll show you additional explanations," or while working, instructions such as "Tighten the screws a little more" are displayed.

[1123] Step 8:

[1124] The user inputs a question from a student or worker. The question is sent from the device to the server, and then passed from the server to the AI ​​engine. The AI ​​engine generates the optimal answer to the question and returns that answer to the server.

[1125] Step 9:

[1126] The server sends the generated answers to the terminal, where students or workers can check the answers. The answers are displayed and the problems are resolved.

[1127] Step 10:

[1128] The server periodically accumulates progress data of students and workers and passes it to the AI ​​engine for analysis. Based on the progress data, the AI ​​engine analyzes the performance of students and workers and generates a report of the results.

[1129] Step 11:

[1130] The server generates reports that are shared with parents and administrators. The reports include information on the progress of students and workers, as well as issues and areas for improvement, and are shared via email or other means.

[1131] 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.

[1132] The present invention is a private tutoring system that combines artificial intelligence (AI) technology and emotion analysis technology, and a specific implementation method thereof will be described below.

[1133] First, the cram school staff (users) register a new student in the system. Using a dedicated interface, users input information such as the student's goals, current academic ability, and areas of strength and weakness. The terminal receives this information and sends it to the server. The server stores the received information in a database.

[1134] Next, the server retrieves student information from the database and passes it to the AI ​​engine. The AI ​​engine uses this information to generate an optimal curriculum. The generated curriculum is then saved in the database via the server again.

[1135] Students come to a cram school and take classes using a tablet device. The device retrieves curriculum information from the server and provides the student with lesson materials based on that information. If a student has a question during class, the user (student) enters the question through the tablet device. The device sends the question to the server, which passes it on to the AI ​​engine. The AI ​​engine generates the optimal answer to the question and sends it to the device via the server. The device displays the generated answer to the student.

[1136] The system also features an emotion engine that analyzes students' facial expressions and tone of voice in real time during class. The device captures students' reactions and analyzes this data using the emotion engine. The emotion engine then performs a detailed analysis of students' emotional states, such as stress levels and excitement, and sends the analysis results to a server. The server then passes the emotion data to the AI ​​engine, which then adjusts the lesson content based on the analysis results. For example, if the AI ​​engine detects signs of student confusion, it will adjust the difficulty of the lesson or provide additional explanations.

[1137] Furthermore, all question and answer data and emotional data from lessons are stored in a database and taken into consideration when creating the next curriculum, providing a set of curriculum optimized for each individual student.

[1138] The emotion engine periodically accumulates and analyzes students' emotional data and generates reports based on progress data. These reports are shared via email and other means with parents and cram school staff via the server. This allows for a comprehensive understanding of students' learning status and emotional state, enabling appropriate countermeasures to be taken.

[1139] In this way, the present invention solves the problem of labor shortages, improves learning efficiency, meets individual needs, and provides learning support that takes into account the emotional state of students.

[1140] The processing flow will be explained below.

[1141] Step 1:

[1142] The user (a cram school staff member) enters information about a new student (goals, current academic ability, areas of strength and weakness, etc.) into a dedicated interface. The device acquires this information and sends it to the server.

[1143] Step 2:

[1144] The server receives the student information and stores it in a database, which is used for the next process.

[1145] Step 3:

[1146] The server retrieves student information from the database and provides it to the AI ​​engine, which then generates the optimal curriculum based on this information.

[1147] Step 4:

[1148] The curriculum generated by the AI ​​engine is stored in a database via the server, and this curriculum information is used in later steps.

[1149] Step 5:

[1150] Students arrive at the cram school and take classes using a tablet device. The device retrieves current curriculum information from the server and presents the student with the materials they need for class.

[1151] Step 6:

[1152] If a student has a question during class, the user (student) enters the question into the tablet device, which then sends the question to the server.

[1153] Step 7:

[1154] The server sends the question to the AI ​​engine, which generates the optimal answer to the question, and the generated answer is sent to the device via the server.

[1155] Step 8:

[1156] The device displays the generated answer to the user (student), allowing the student to immediately resolve their doubts.

[1157] Step 9:

[1158] During class, the device captures students' facial expressions and tone of voice in real time and sends them to the emotion engine, which then analyzes the data.

[1159] Step 10:

[1160] The emotion engine sends the results of its analysis to a server, which then provides them to an AI engine. The AI ​​engine then adjusts the lesson content based on the analysis results. For example, if a student's stress level is high, it will adjust the difficulty of the lesson to be lower.

[1161] Step 11:

[1162] All questions, answers, and emotional data are stored in a database, which will be used to create the next curriculum and plan lessons.

[1163] Step 12:

[1164] The AI ​​engine periodically generates progress reports for students based on the accumulated data. These reports are shared via email with parents and cram school staff via the server, allowing for a comprehensive understanding of the student's learning progress.

[1165] Through the above steps, the present invention provides a learning experience optimized to the needs of each individual student, solving the problem of labor shortages while also realizing advanced learning support that takes into account the emotional state of students.

[1166] Example 2

[1167] 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."

[1168] Conventional individualized tutoring systems struggled to adjust lesson content in real time based on students' academic ability, level of understanding, and emotional state. As a result, they were unable to provide a learning experience optimized for each student's needs, making it difficult to achieve efficient learning outcomes. It was also difficult to provide immediate and appropriate answers to students' questions, which could lead to inconsistent learning. Furthermore, there was a lack of appropriate means for sharing students' progress and emotional state with parents and tutoring staff.

[1169] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1170] In this invention, the server includes: means for inputting information such as a student's goals, current academic ability, and areas of strength and weakness; means for transmitting the information to the server; means for the server to store the information in a database; means for an AI engine to generate an optimal curriculum based on the stored information; means for storing the generated curriculum in a database; means for a student to take lessons based on the curriculum using a tablet device; means for accepting questions from students during lessons and transmitting the questions to the AI ​​engine; means for the AI ​​engine to generate answers to the questions and return the answers to the students; means for analyzing students' reactions (facial expressions, tone of voice, etc.) in real time and transmitting the information to the server; means for an emotion analysis engine to periodically accumulate and analyze students' emotional data and transmit the analysis results to the server; means for the AI ​​engine to analyze students' reactions and adjust lesson content in real time; means for sharing student progress data with parents and cram school staff; and means for automatically adjusting lesson content based on the student's emotional state. This makes it possible to adjust lesson content in real time according to the student's academic ability, level of understanding, and emotional state, thereby providing an optimized learning experience for each student.

[1171] "Student goals" refer to the specific outcomes or goals that students want to achieve through their studies.

[1172] "Current academic ability" is an assessment of the level of knowledge and skills that a student currently possesses.

[1173] "Strong and weak areas" refers to subjects or areas in which a student is particularly strong and weak.

[1174] A "server" refers to the central device of a computer system that stores and processes data.

[1175] A "database" is a system for organizing and storing information and data.

[1176] An "AI engine" refers to a program that uses machine learning and data analysis to generate optimal curriculum and answers.

[1177] "Curriculum" refers to an educational plan organized according to specific goals or learning objectives.

[1178] "Tablet device" refers to a portable computing device with a touchscreen.

[1179] "Questions" refer to matters that students are unsure about or want to confirm while studying.

[1180] "Answer" refers to the answer or explanation provided to a question.

[1181] "Responses" refer to non-verbal feedback such as facial expressions and tone of voice shown by students during class.

[1182] An "emotion analysis engine" refers to a system that analyzes students' facial expressions, voices, etc. to evaluate their emotional state.

[1183] "Progress Data" refers to data that shows a student's learning process and academic progress.

[1184] "Guardians" refers to the parents or guardians of students attending cram schools.

[1185] "Cram school personnel" refers to staff, teachers, and other personnel who work at cram schools.

[1186] "Class content" refers to the teaching materials, content taught, learning activities, etc. used in class.

[1187] "Storage" refers to the collection and storage of information or data.

[1188] "Analysis" refers to the detailed examination and analysis of information or data.

[1189] The present invention is a private tutoring system that combines artificial intelligence (AI) technology and emotion analysis technology. This system provides an optimal curriculum based on a student's learning status and can personalize the learning experience by analyzing their reactions and emotional state in real time. A specific method for implementing this invention is described below.

[1190] First, to register a new student in the system, the user (cram school staff) enters information such as the student's goals, current academic ability, and areas of strength and weakness through a dedicated interface. The device (PC or tablet) sends this information to the server. The server stores the received information in a database. Specifically, the information is managed using a relational database such as MySQL or PostgreSQL.

[1191] The server then retrieves student information from the database and passes it to the AI ​​engine, which uses machine learning frameworks such as TensorFlow and PyTorch to analyze student characteristics and generate an optimal curriculum. This generated curriculum is then stored in the database via the server.

[1192] When a student comes to a cram school and takes a class using a tablet device, the device retrieves curriculum information from the server and provides the student with lesson materials based on that information. If a student has a question during class, the user (student) inputs the question through the tablet device. The device sends the question to the server, which then passes it on to the AI ​​engine. The AI ​​engine generates the optimal answer to the question and sends it to the device via the server. The device then displays the generated answer to the student.

[1193] For emotion analysis, the device captures students' facial expressions and tone of voice in real time and sends them to the emotion engine. The emotion engine uses technologies such as OpenCV and Dlib to analyze the student's stress level and excitement. The analysis results are sent to a server, which passes them on to an AI engine. The AI ​​engine then adjusts the lesson content based on this data. For example, if a student is confused, the AI ​​engine may instruct the teacher to lower the difficulty of the lesson or provide additional explanations.

[1194] Every time a student takes a class, all their questions, answers, and emotional data are stored in a database. This information is taken into account when generating the next curriculum, providing a more personalized learning experience.

[1195] Furthermore, the emotion engine periodically accumulates and analyzes students' emotional data and generates reports based on progress data. The server then shares these reports with parents and cram school staff via email, etc. This allows for a comprehensive understanding of students' learning status and emotional state, enabling appropriate countermeasures to be taken.

[1196] Examples of examples and prompts:

[1197] For example, if a new student wants to learn the basics of mathematics, the user (a cram school staff member) fills in a special input form with the following information: "Goal: Understand the basics of mathematics, Current academic level: Intermediate, Strong areas: Arithmetic, Weak areas: Algebra." Based on this information, the AI ​​engine generates a curriculum that starts with basic arithmetic and gradually progresses to Algebra.

[1198] Example prompt:

[1199] Prompt for user (cram school staff): "Please enter registration information for a new student. Please include their goals, current academic ability, and areas of strength and weakness."

[1200] Prompt for students: "If you have any questions during class, please use the tablet to type your question and we will provide you with an immediate answer."

[1201] This invention will solve the problem of labor shortages, improve learning efficiency, and meet individual needs, and will also provide learning support that takes into account the emotional state of students.

[1202] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1203] Step 1:

[1204] The user (cram school staff) enters information such as the student's goals, current academic ability, and areas of strength and weakness using a dedicated interface (e.g., web form or app). After entering the information, the device sends it to the server, which then stores the received information in a database.

[1205] Input: Information such as student goals, current academic ability, strengths and weaknesses

[1206] Output: Save student information to database

[1207] Specific operation: The user enters the required information into a dedicated web form and clicks the "Submit" button. The device sends this information to the server, which then stores it in a database.

[1208] Step 2:

[1209] The server retrieves student information from the database and passes it to the AI ​​engine. The AI ​​engine uses machine learning frameworks such as TensorFlow and PyTorch to analyze the student's characteristics. Based on this, it generates an optimal curriculum. The generated curriculum is then saved in the database via the server.

[1210] Input: Student information stored in the database

[1211] Output: Save the generated curriculum to a database

[1212] Specific operation: The server periodically checks for newly added student information and forwards this information to the AI ​​engine. The AI ​​engine generates an optimal curriculum and sends it back to the server. The server stores the curriculum in a database.

[1213] Step 3:

[1214] When students come to the cram school and take classes using a tablet device, the device retrieves curriculum information from the server and provides the students with lesson materials based on that information.

[1215] Input: Curriculum information stored in the database

[1216] Output: Lesson materials provided to students

[1217] Specific operation: When a student logs in to a tablet device, the system automatically downloads the student's curriculum from the server and then displays the first lesson slide to the student.

[1218] Step 4:

[1219] If a student has a question during class, the user (student) inputs the question through a tablet device. The device sends the question to the server, which passes it to the AI ​​engine. The AI ​​engine generates the optimal answer to the question and sends it to the device via the server. The device then displays the generated answer to the student.

[1220] Input: Student question

[1221] Output: Answer from the AI ​​engine

[1222] Specific operation: The student taps the "Ask a question" button and enters the question text. The question is sent to the server, where the AI ​​engine analyzes it and generates an answer. The device receives this and displays it to the student.

[1223] Step 5:

[1224] The device captures the student's facial expressions and tone of voice in real time and sends them to the emotion engine, which analyzes the student's stress level and excitement level and sends the results to the server.

[1225] Input: Facial expressions and tone of voice captured in real time

[1226] Output: Emotion analysis results

[1227] How it works: The tablet's camera and microphone capture the student's face and voice, and send them to the emotion engine every few seconds. The analyzed data is then sent to the server.

[1228] Step 6:

[1229] The server passes the emotional data to an AI engine, which then adjusts the lesson content based on the data. For example, if a student is confused, the AI ​​engine can lower the difficulty of the lesson or provide additional explanations.

[1230] Input: Sentiment analysis results

[1231] Output: Adjusted lesson content

[1232] Specific operation: The server receives the analysis results from the emotion engine and forwards them to the AI ​​engine. The AI ​​engine gradually adjusts the lesson content and sends it to the device via the server. The device then displays the new instructions to the student.

[1233] Step 7:

[1234] All questions, answers, and emotional data from lessons are stored in a database, and this data is taken into account when generating the next curriculum.

[1235] Input: Questions and answers, emotion data

[1236] Output: Individual data to be reflected in the next curriculum

[1237] Specific operation: After the lesson ends, the device automatically sends all learning data to the server, which stores this data in a database and uses it as a reference when the AI ​​engine generates the next curriculum.

[1238] Step 8:

[1239] The emotion engine periodically analyzes students' emotion data and generates reports based on their progress. The server then shares these reports with parents and school staff via email or other means.

[1240] Input: Accumulated emotion data

[1241] Output: Progress report

[1242] How it works: The emotion engine analyzes students' emotion data monthly and generates a report. The server converts this report into PDF format and sends it to the email addresses of parents and other relevant parties.

[1243] (Application example 2)

[1244] 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."

[1245] Conventional learning support systems and customer service support systems in brick-and-mortar stores have had difficulty accurately grasping the emotional state of individual customers or students in real time and providing appropriate instruction or customer service based on that information. Furthermore, there was a lack of efficient means for suggesting optimal products based on customers' emotions and purchasing history.

[1246] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means. In this invention, the server includes: means for inputting information such as a student's goals, current academic ability, and areas of strength and weakness; means for transmitting the information to the server; means for the server to store the information in a database; means for an AI engine to generate an optimal curriculum based on the stored information; means for storing the generated curriculum in a database; means for a student to take lessons based on the curriculum using a tablet device; means for accepting questions from students during lessons and transmitting the questions to the AI ​​engine; means for the AI ​​engine to generate answers to the questions and return the answers to the students; means for analyzing students' reactions (facial expressions, tone of voice, etc.) in real time and transmitting the information to the server; means for the AI ​​engine to analyze students' reactions and adjust lesson content in real time; means for sharing student progress data with parents and cram school personnel; means for analyzing customers' facial expressions and tone of voice in a store to grasp their emotional state; means for the AI ​​engine to generate optimal customer service methods and product suggestions based on the customer's emotional state and purchase history; and means for notifying store staff of the customer service methods and product suggestions. This will enable individually optimized learning support and personalized customer service in physical stores.

[1247] "Student goals" are the specific learning outcomes or objectives that students want to achieve during the learning process.

[1248] "Current academic ability" refers to the level of knowledge and skills that a student currently possesses.

[1249] "Strong and weak areas" refer to subjects or areas that are relatively easy for students to understand and master, and subjects or areas that are difficult for students to understand and master.

[1250] "Means for inputting information" refers to the interface or device through which a user provides information about a student or customer to the system.

[1251] "Means for sending to the server" refers to the communication protocol or technology used to transfer data from the terminal to the server.

[1252] "Means for storing data in a database" refers to a mechanism for efficiently recording received data and making it possible to search and update it as needed.

[1253] An "AI engine" is software that uses artificial intelligence to analyze data and generate solutions or suggestions for specific problems.

[1254] "Curriculum generation means" refers to algorithms or processes for constructing appropriate lesson plans and materials based on student information.

[1255] A "tablet device" is a portable computer that allows input and operation via a touch screen.

[1256] "Means for accepting questions and sending them to the AI ​​engine" refers to a mechanism that allows students or customers to input doubts or queries into the system and forward them to the AI ​​engine.

[1257] "Means for generating and returning an answer" refers to the mechanism by which the AI ​​engine creates the optimal answer to a question and provides that answer to the questioner.

[1258] "Means for analyzing reactions in real time" refers to technology that instantly evaluates the reactions of students or customers, such as facial expressions and tone of voice, and analyzes their emotional state.

[1259] "Means for sharing progress data" refers to a system for notifying relevant parties of progress data on students' learning status and customer purchasing behavior.

[1260] "Means of analyzing facial expressions and tone of voice to grasp emotional state" refers to technology that analyzes data acquired using a camera or microphone to identify the subject's emotions.

[1261] "Means for generating optimal customer service methods and product suggestions based on purchasing history" refers to a system in which AI uses customers' past purchasing data to generate optimal customer service methods and suggested products for purchase.

[1262] "Means of notifying store staff of customer service methods and product suggestions" refers to a system that provides information generated by AI to store staff in real time or at any time.

[1263] This invention is a personalized learning and customer service support system that combines AI technology and emotion analysis technology. First, we will explain the overall flow of the system.

[1264] 1. Enter student and customer information

[1265] The user enters information such as the student's goals, current academic ability, areas of strength and weakness, as well as the customer's purchasing history and preferred categories through a dedicated interface. This information is sent from the terminal to the server.

[1266] 2. Storing data and sending it to the AI ​​engine

[1267] The server stores the received information in a database. The server then sends the stored information to the AI ​​engine. The AI ​​engine generates the optimal curriculum and customer service methods based on the received information, and stores them in the database again via the server.

[1268] 3. Teaching and customer service using tablet devices

[1269] Students come to the cram school and take lessons using a tablet device. The device provides lessons based on curriculum information obtained from the server. In physical stores, store staff use smart glasses or smartphones to capture customers' facial expressions and tone of voice. This real-time data is sent to the server for analysis.

[1270] 4. Questions and Answers

[1271] If a student has a question during class, they can input it into their tablet device. The device sends the question to the server, which passes it on to the AI ​​engine. The AI ​​engine generates the optimal answer and sends it back to the device via the server. Similarly, when dealing with customers in-store, the AI ​​engine will suggest the best product and customer service methods.

[1272] 5. Sentiment analysis and adjustment of lesson content and customer service content

[1273] During lessons, the devices capture students' facial expressions and tone of voice in real time and send them to a server. An emotion analysis engine analyzes this data to determine students' stress levels and excitement levels. The AI ​​engine adjusts lesson content in real time based on the emotional data. In-store, customer service methods and product recommendations are adjusted based on customer emotional data.

[1274] 6. Sharing progress data

[1275] All questions and answers during lessons, as well as student emotional data, are stored in a database. This data is taken into consideration when creating the next curriculum and proposing customer service methods. Progress reports are generated by an AI engine and shared with parents, cram school staff, and store personnel. This allows for a comprehensive understanding of the status of students and customers and allows for appropriate countermeasures to be taken.

[1276] Hardware and software used

[1277] Hardware: Tablets, smart glasses, smartphones

[1278] Software: Python-based AI engine, OpenCV (image processing library), Emotion Analysis API, database management system

[1279] Examples of specific examples and prompts

[1280] As a specific example, when dealing with customers in a physical store, if the AI ​​engine detects signs of confusion in the customer, it will suggest to the store staff that they "speak in a calm tone and explain about new products in the store."

[1281] Example prompt sentence:

[1282] "If a customer is confused, please suggest the best way to serve them."

[1283] In this way, the system provides both individually optimized learning support and customer service in a physical store, solving conventional problems.

[1284] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1285] Step 1:

[1286] The user enters information such as the student's goals, current academic ability, areas of strength and weakness, as well as the customer's purchasing history and preferred categories into a dedicated interface. The entered information is sent from the terminal to the server.

[1287] Input: Student and Customer Information

[1288] Output: Information data sent to the server

[1289] How it works: The user uses a dedicated interface to input information via a keyboard or touchscreen. The device collects this data and sends it to the server via an HTTP request.

[1290] Step 2:

[1291] The server stores the received information in a database.

[1292] Input: Information data sent from the terminal

[1293] Output: Information stored in the database

[1294] Specific operations: The server stores the received data in a structured format using a database management system, and inserts it into the database using an SQL query.

[1295] Step 3:

[1296] The server sends the stored information to the AI ​​engine, which then generates the optimal curriculum and customer service methods based on the received information, and stores them in the database again via the server.

[1297] Input: Information stored in a database

[1298] Output: Generated curriculum and customer service methods

[1299] Specific operation: The server sends data to the AI ​​engine using an API request. The AI ​​engine analyzes the data using a machine learning model and generates the optimal curriculum and customer service method. The generated data is sent to the server as an API response, and the server stores it in the database again.

[1300] Step 4:

[1301] Students come to the cram school and use tablets to take lessons based on the curriculum, while store staff use smart glasses or smartphones to capture customers' facial expressions and tone of voice.

[1302] Input: Curriculum information obtained from the server, customer facial expressions and tone of voice

[1303] Output: Lesson content delivered, real-time data captured

[1304] How it works: The tablet device retrieves curriculum information from the server and displays lesson content accordingly. The smart glasses or smartphone uses a camera and microphone to capture the customer's facial expressions and tone of voice in real time, formatting the data and sending it to the server.

[1305] Step 5:

[1306] If a student has a question during class, they can enter it into their tablet device, which then sends it to the server, which then passes it on to the AI ​​engine.

[1307] Input: Student question

[1308] Output: Question data sent to the server

[1309] How it works: Students enter questions into their tablet devices, which then capture and send them to the server. The server then passes the received question data to the AI ​​engine via an API request.

[1310] Step 6:

[1311] The AI ​​engine generates the optimal answer and sends it to the device via the server.

[1312] Input: Question data sent from the server

[1313] Output: Answer data returned to the student

[1314] How it works: The AI ​​engine analyzes the question data and uses machine learning models to generate the best answer. The generated answer is returned to the server via an API response, and the server then sends it to the student's device.

[1315] Step 7:

[1316] During class, the device captures students' facial expressions and tone of voice in real time and sends them to a server. An AI engine analyzes this data to determine students' stress levels and excitement levels.

[1317] Input: Real-time facial expression data and tone of voice data of students

[1318] Output: Parsed emotion data

[1319] How it works: The tablet uses a camera and microphone to capture students' facial expressions and tone of voice, and sends the data to a server. An AI engine analyzes this data and identifies their emotional state.

[1320] Step 8:

[1321] The AI ​​engine adjusts lesson content in real time based on emotional data, and in-store customer service methods and product recommendations are adjusted based on customer emotional data.

[1322] Input: Parsed emotion data

[1323] Output: Adjusted lesson content and customer service methods

[1324] Specific actions: Based on the analysis results, the AI ​​engine adjusts the lesson content to lower the difficulty level or provide additional explanations as needed. In physical stores, it changes and adjusts customer service methods and product recommendations based on the customer's emotional state.

[1325] Step 9:

[1326] All questions and answers during lessons, as well as student emotional data, are stored in a database and are taken into consideration when creating the next curriculum and proposing customer service methods.

[1327] Input: Question and answer data during class, emotion data

[1328] Output: Progress data stored in a database

[1329] Specific operation: The server saves questions, answers, and emotion data from lessons in a database. This data is used to generate the next curriculum and improve customer service methods.

[1330] Step 10:

[1331] Progress reports are generated by an AI engine and shared with parents, cram school staff, and store personnel.

[1332] Input: Progress data stored in the database

[1333] Output: Generated progress report

[1334] How it works: The AI ​​engine analyzes the progress data and creates a report. The report is then shared via email with parents, cram school staff, and store staff via a server.

[1335] 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.

[1336] 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.

[1337] 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.

[1338] [Fourth embodiment]

[1339] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1340] 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.

[1341] 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).

[1342] 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.

[1343] 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.

[1344] 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).

[1345] 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.

[1346] 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.

[1347] 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.

[1348] 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.

[1349] 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.

[1350] 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.

[1351] 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."

[1352] The present invention is a private tutoring system that utilizes artificial intelligence (AI), and the method for realizing this system is explained below. Here, each component, its function, and specific operating procedures are shown.

[1353] First, the cram school staff (users) register a new student in the system. Using a dedicated interface, users input information such as the student's goals, current academic ability, and areas of strength and weakness. The terminal receives this information and sends it to the server. The server stores the received information in a database.

[1354] Next, the server retrieves student information from the database and passes it to the AI ​​engine. The AI ​​engine uses this information to generate an optimal curriculum. The generated curriculum is then saved in the database via the server again.

[1355] Students come to the cram school and take classes using a tablet device. The device retrieves curriculum information from the server and provides the students with lesson materials based on that information. If a student has a question during the actual class, the user (student) inputs the question through the tablet device. The device sends the question to the server, which passes it on to the AI ​​engine. The AI ​​engine generates the optimal answer to the question and sends it to the device via the server. The device returns the generated answer to the student.

[1356] The device also features a system for analyzing students' facial expressions and tone of voice in real time during class. The device analyzes students' reactions and sends the data to a server. The server passes this data to an AI engine, which then adjusts the lesson content based on the analysis results. For example, if a student shows signs of confusion, the AI ​​engine will instruct the teacher to lower the difficulty of the lesson or provide additional explanations.

[1357] Furthermore, all questions and answers during the lesson are stored in a database and taken into consideration when creating the next curriculum, thus providing a set of curriculum that is optimized for each individual student.

[1358] Finally, students' learning progress data is analyzed periodically, and the results are compiled into a report. This report is shared via a server with parents and cram school staff via email, etc. This allows students' progress to be tracked as needed and necessary measures to be taken.

[1359] In this way, the present invention solves the problem of labor shortages while realizing efficient and effective learning instruction that meets individual learning needs.

[1360] The processing flow will be explained below.

[1361] Step 1:

[1362] The user (a cram school staff member) enters information about a new student (goals, current academic ability, areas of strength and weakness, etc.) into a dedicated interface. The device then sends this information to the server.

[1363] Step 2:

[1364] The server stores the received student information in a database, which is used in subsequent processes.

[1365] Step 3:

[1366] The server retrieves student information from the database and passes it to the AI ​​engine, which then generates the optimal curriculum based on this information.

[1367] Step 4:

[1368] The generated curriculum is stored in a database via a server, which allows the curriculum information to be used later.

[1369] Step 5:

[1370] Students attend classes at the cram school using a tablet device. The device retrieves current curriculum information from the server and provides students with the materials they need for class.

[1371] Step 6:

[1372] If a student has a question during class, the user (student) can input the question through a tablet device, which then sends the question to the server.

[1373] Step 7:

[1374] The server passes the question to the AI ​​engine, which generates the optimal answer to the question, and the generated answer is sent to the device via the server.

[1375] Step 8:

[1376] The device displays the generated answer to the user (student), allowing the student to immediately resolve their doubts.

[1377] Step 9:

[1378] During class, the device captures students' reactions in real time for analysis of their facial expressions and tone of voice, and this data is sent to a server.

[1379] Step 10:

[1380] The server passes the student's reaction data to an AI engine, which then adjusts the lesson content based on the analysis results. For example, if a student is confused, it will instruct the AI ​​engine to lower the difficulty of the lesson.

[1381] Step 11:

[1382] All questions and answers are stored in a database, which will be used to create the next curriculum.

[1383] Step 12:

[1384] The AI ​​engine periodically analyzes students' learning progress data and generates progress reports, which are shared with parents and cram school staff via a server.

[1385] Example 1

[1386] 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."

[1387] Conventional individualized learning systems struggled to provide an effective curriculum tailored to each learner's learning progress and level of understanding, making it difficult to maximize learning efficiency. Furthermore, they lacked the means to respond to learners' reactions and questions in real time, making it impossible to provide optimal instruction to each learner. Furthermore, reporting progress to parents and educational facility officials was time-consuming, making it difficult to share information in a timely manner.

[1388] 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.

[1389] In this invention, the server includes: a means for inputting information such as a learner's goals, current academic ability, and areas of strength and weakness; a means for transmitting the information to the server; a means for the server to store the information in a database; a means for an AI engine to generate an optimal curriculum based on the stored information; a means for storing the generated curriculum in a database; a means for a learner to take lessons based on the curriculum using a mobile device; a means for accepting questions from the learner during lessons and transmitting the questions to the AI ​​engine; a means for the AI ​​engine to generate answers to the questions and return the answers to the learner; a means for analyzing the learner's responses (e.g., facial expressions, tone of voice) in real time and transmitting the information to the server; a means for the AI ​​engine to analyze the learner's responses and adjust the lesson content in real time; a means for sharing the learner's progress data with parents and educational facility personnel; and a means for storing the learner's question data and answer data for a certain period of time and utilizing them when creating the next curriculum. This enables the provision of teaching methods optimized for each learner and high learning effectiveness. The ability to quickly and accurately share information with parents and educational facility personnel also enables appropriate management of the learner's learning progress.

[1390] "Learner" refers to an individual who uses the system to receive an education.

[1391] A "server" refers to a computer device that provides specific services or information over a network.

[1392] A "database" refers to a system that stores and manages large amounts of data in an organized manner.

[1393] An "AI engine" refers to a system that uses artificial intelligence technology to analyze data and generate optimal results.

[1394] "Curriculum" refers to a learning plan that is structured based on the learner's educational goals.

[1395] "Mobile devices" refer to electronic devices that are portable and used by learners. Examples include tablets and smartphones.

[1396] "Analyzing in real time" refers to the process of analyzing input information immediately and obtaining results.

[1397] "Progress data" refers to data that indicates the progress and results of a learner's learning activities.

[1398] "Guardian" means the parent or guardian's representative.

[1399] "Educational facility personnel" refers to staff and administrators of the educational institution to which the learner belongs.

[1400] "Question data" refers to information about questions entered by learners.

[1401] "Answer data" refers to information about an answer generated based on question data.

[1402] MODE FOR CARRYING OUT THE INVENTION

[1403] This invention is a personalized tutoring system that utilizes artificial intelligence (AI). This section explains in detail each component and the role they play. This system enables efficient learning instruction tailored to the needs of each learner.

[1404] First, the user registers a new learner using a dedicated web interface. The user enters information into the interface, such as the learner's goals, current academic ability, and areas of strength and weakness, and presses the submit button. At this time, the device receives the entered information and sends it to the server. For example, the user enters "Taro Tanaka, second-year junior high school student, aims to raise his math score by 10 points, his strengths are set theory, and his weaknesses are simultaneous equations." This information is sent to the server, which stores it in a database.

[1405] Next, the server retrieves the learner's information from the database and passes it to the AI ​​engine. The AI ​​engine analyzes the learner's information and generates an optimal curriculum. The generated curriculum is then saved in the database via the server again. For example, based on the information of "Taro Tanaka," the AI ​​engine generates a curriculum of "review of basic mathematics, review of set theory, basics and applications of simultaneous equations, and practice with past exam questions."

[1406] At a cram school, learners attend classes using mobile devices (e.g., tablet devices). The devices connect to a server and obtain curriculum information. Lesson materials are displayed on the device based on the obtained curriculum, and the learner follows along as they study. If a question arises during class, the learner enters it through the device. The device sends the question to the server, which passes it on to an AI engine. The AI ​​engine generates the best answer to the question, and that answer is sent to the device via the server. The device displays the generated answer to the learner.

[1407] The device also has a function for analyzing learners' facial expressions and tone of voice in real time during lessons. The device analyzes the learners' reactions and sends the data to a server. The server passes the data to an AI engine, which then adjusts the lesson content based on the analysis results. For example, if a learner shows a confused expression, the AI ​​engine will issue instructions to lower the difficulty of the lesson, and these instructions will be sent to the device via the server.

[1408] Furthermore, all question and answer data is stored in a database and reflected in the next curriculum creation, providing a set of curriculum optimized for each individual learner.

[1409] Finally, the learner's learning progress data is periodically retrieved from the database by the server and passed to the AI ​​engine. The AI ​​engine analyzes the progress data and generates a report. This report is then emailed to parents and educational institution officials via the server. For example, a progress report summarizing the learner's achievements and challenges can be emailed to parents.

[1410] Example prompt sentence:

[1411] We have a student named "Taro Tanaka" who is in the second year of junior high school. His goal is to raise his math score by 10 points. His current strengths are "set theory" and his weaknesses are "simultaneous equations." Please generate the optimal learning curriculum for him.

[1412] In this way, the present invention is a system that provides efficient and effective learning guidance that meets individual learning needs and achieves high learning results.

[1413] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1414] Program processing flow

[1415] Step 1: Register student information

[1416] Specific behavior:

[1417] The user opens a dedicated web interface.

[1418] The user enters the learner's basic information (name, grade, goal, areas of strength and weakness) and presses the send button.

[1419] The terminal receives this input data. Input: Basic information of the learner. Output: Learner information data sent to the terminal.

[1420] Data processing and calculation:

[1421] The terminal formats the input information and sends it to the server.

[1422] Examples:

[1423] The user enters "Taro Tanaka, second-year junior high school student, increase math score by 10, strong point is set theory, weak point is simultaneous equations" and presses the send button.

[1424] Step 2: Saving to the database

[1425] Specific behavior:

[1426] The server receives the learner information sent from the terminal.

[1427] The server stores the received information in a database. Input: Learner information data. Output: Information stored in the database.

[1428] Data processing and calculation:

[1429] The server stores the received data in a database in an appropriate format.

[1430] Examples:

[1431] The server stores the information in a database: "Taro Tanaka, second-year junior high school student, aims to raise his mathematics score by 10 points, his forte is set theory, his weakness is simultaneous equations."

[1432] Step 3: Generate the curriculum

[1433] Specific behavior:

[1434] The server retrieves the learner's information from the database.

[1435] The server passes the acquired information to the AI ​​engine. Input: Learner information. Output: Information passed to the AI ​​engine.

[1436] Data processing and calculation:

[1437] The AI ​​engine analyzes learner information and generates the optimal curriculum.

[1438] Examples:

[1439] Based on the information "Taro Tanaka, second-year junior high school student, aims to raise his mathematics score by 10 points, his strengths are set theory, and his weaknesses are simultaneous equations," the AI ​​engine generates a curriculum of "reviewing basic mathematics, reviewing set theory, learning from the basics to applications of simultaneous equations, and practicing past exam questions."

[1440] Step 4: Save the curriculum

[1441] Specific behavior:

[1442] The server stores the generated curriculum in a database. Input: Generated curriculum. Output: Curriculum stored in the database.

[1443] Data processing and calculation:

[1444] The server formats the generated curriculum data and stores it in a database.

[1445] Examples:

[1446] The generated curriculum, "Review of basic mathematics, review of set theory, basics to applications of simultaneous equations, and practice of past exam questions," is saved in a database.

[1447] Step 5: Conducting lessons

[1448] Specific behavior:

[1449] The device (tablet) connects to the server and retrieves curriculum information.

[1450] The terminal displays the lesson material based on the acquired curriculum information. Input: Curriculum information. Output: Lesson material displayed on the terminal.

[1451] Data processing and calculation:

[1452] The device selects and displays appropriate lesson materials based on the acquired curriculum.

[1453] Examples:

[1454] Taro Tanaka will use a tablet to take classes based on the curriculum: "Review of basic mathematics, review of set theory, basics and applications of simultaneous equations, and practice with past exam questions."

[1455] Step 6: Accepting and answering questions

[1456] Specific behavior:

[1457] Learners enter their questions during class.

[1458] The terminal sends the question to the server. Input: The learner's question. Output: The question data sent to the server.

[1459] The server passes the question to the AI ​​engine.

[1460] The AI ​​engine generates answers to questions.

[1461] The server sends the generated response to the terminal.

[1462] The device displays the answer to the learner. Input: Answer from the AI ​​engine. Output: Answer displayed on the device.

[1463] Data processing and calculation:

[1464] The AI ​​engine analyzes the question data and generates the optimal answer.

[1465] Examples:

[1466] Taro Tanaka types in a question about simultaneous equations, saying, "I don't know how to solve simultaneous equations." The AI ​​engine generates a "basic solution to simultaneous equations" and displays it on the tablet.

[1467] Step 7: Analyze responses and adjust lesson content

[1468] Specific behavior:

[1469] The device analyzes the learner's facial expressions and tone of voice in real time.

[1470] The device sends the analysis results to the server. Input: Facial expression and tone of voice data. Output: Analysis data sent to the server.

[1471] The server passes the analysis results to the AI ​​engine.

[1472] The AI ​​engine adjusts the lesson content based on the analysis results.

[1473] The server transmits the adjusted content to the terminal.

[1474] The device displays the adjusted lesson content to the learner. Input: Instructions from the AI ​​engine. Output: Adjusted lesson content.

[1475] Data processing and calculation:

[1476] The AI ​​engine analyzes facial expressions and tone of voice data to adjust the lesson content optimally.

[1477] Examples:

[1478] If Taro Tanaka looks confused, the AI ​​engine will instruct him to "slow down the pace of the lesson," and the change will be reflected on the tablet.

[1479] Step 8: Generate and share progress reports

[1480] Specific behavior:

[1481] The server periodically retrieves learner progress data from the database.

[1482] The server passes the acquired data to the AI ​​engine. Input: Progress data. Output: Data passed to the AI ​​engine.

[1483] An AI engine analyzes progress data and generates reports.

[1484] The server sends the generated report to parents and educational institution officials. Input: Generated report. Output: Sent report.

[1485] Data processing and calculation:

[1486] The AI ​​engine analyzes the progress data and creates a detailed report.

[1487] Examples:

[1488] The server retrieves Taro Tanaka's monthly progress data, and the AI ​​engine analyzes the data to generate a report that is then emailed to his parents.

[1489] (Application example 1)

[1490] 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."

[1491] Current individualized cram school systems have difficulty analyzing students' reactions (facial expressions and tone of voice) in real time while lessons are in progress and instantly adjusting lesson content. Furthermore, in on-site work in factories and other places, systems that provide appropriate instructions and support in real time according to the worker's skills and situation are inadequate. This leads to a lack of efficient instruction and support at cram schools and on-site factories, resulting in problems such as reduced learning effectiveness and work efficiency.

[1492] 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.

[1493] In this invention, the server includes: means for inputting information such as a student's goals, current academic ability, and areas of strength and weakness; means for transmitting that information to the server; means for the server to store that information in a database; means for an AI engine to generate an optimal curriculum based on the stored information; means for storing the generated curriculum in a database; means for a student to take lessons based on the curriculum using a tablet device; means for accepting questions from students during lessons and transmitting those questions to the AI ​​engine; means for the AI ​​engine to generate answers to the questions and return those answers to the students; means for analyzing students' reactions (facial expressions, tone of voice, etc.) in real time and transmitting that information to the server; means for the AI ​​engine to analyze students' reactions and adjust lesson content in real time; means for sharing students' progress data with parents and cram school personnel; means for a worker to register individual skills, goals, and tasks that the worker is good at and bad at; means for analyzing the worker's facial expressions and tone of voice in real time and transmitting that information to the server; and means for the AI ​​engine to analyze the worker's reactions and adjust task content in real time. This allows for optimal guidance and work support for each individual.

[1494] A "student" is an individual receiving education at a cram school or educational facility.

[1495] "Goals" refer to specific results or objectives that you want to achieve in individual learning or work.

[1496] "Academic ability" is the ability that represents a student's current knowledge and understanding of learning.

[1497] "Strengths and weaknesses" indicate areas of learning or work in which a student is particularly strong or weak.

[1498] A "server" is a device that manages and stores data and provides data and functions over a computer network.

[1499] A "database" is a place where data is systematically organized and stored in digital form.

[1500] An "AI engine" is the core part of software that uses artificial intelligence to analyze data and generate optimal results and answers.

[1501] A "curriculum" refers to a systematically planned learning program that covers the subjects and content that students should learn.

[1502] A "tablet device" is a small, portable computing device that can be operated primarily via a touch screen.

[1503] "Reactions" refers to real-time feedback such as facial expressions, tone of voice, and behavior shown by students or workers during lessons or work.

[1504] "Worker" refers to a person who performs a specific task in a factory or on a work site.

[1505] "Skills" refers to the knowledge and abilities that a worker has to perform a specific task or technique.

[1506] "Instruction" refers to the act of teaching and guiding students or workers on how to study or work in an appropriate manner.

[1507] "Work support" refers to providing appropriate instructions and assistance to workers so that they can perform their work efficiently.

[1508] System program description

[1509] This invention proposes a system that utilizes an AI engine to provide real-time support for work and learning in private tutoring schools and factory sites.

[1510] Hardware used

[1511] server:

[1512] It is the central device that manages and stores data and exchanges it through communications. The server stores information in a database and runs the AI ​​engine.

[1513] Tablet or smart glasses:

[1514] It will be used as a user interface for cram school students to take lessons and for factory workers to receive work instructions.

[1515] Camera and Microphone:

[1516] This device captures the facial expressions and tone of voice of students and workers in real time.

[1517] Software used

[1518] OpenCV:

[1519] Used to analyze video data from cameras in real time.

[1520] TensorFlow:

[1521] It is used to implement AI models that analyze the facial expressions and tone of voice of students and workers.

[1522] Database Management Systems:

[1523] Stored data is managed using MySQL, PostgreSQL, etc.

[1524] How to carry out the invention

[1525] 1. Registration of information:

[1526] The user (a cram school staff member or a factory manager) uses a dedicated interface to input information such as the student's or worker's goals, current academic ability and skills, and areas of strength and weakness. This information is sent to the server and stored in a database.

[1527] 2. Generate curriculum or work instructions:

[1528] The server passes the stored information to an AI engine to generate optimal curriculum and work instructions, which are then stored back in the database.

[1529] 3. Real-time analysis and feedback:

[1530] The tablet devices and smart glasses use cameras and microphones to capture the facial expressions and tone of voice of students and workers in real time. This data is sent to a server and analyzed by an AI engine. The lesson content and work instructions are adjusted in real time based on the analysis results.

[1531] 4. Question and Answer Management:

[1532] Students and workers can input any questions they may have along the way, and these questions are passed to the AI ​​engine via the server. The AI ​​engine then generates the optimal answer and responds automatically.

[1533] 5. Sharing progress data:

[1534] Data on the progress of lessons and work is stored on a server and periodically analyzed. The results of the analysis are generated as a report and shared with parents and administrators.

[1535] Examples of specific examples and prompts

[1536] Examples:

[1537] Cram school:

[1538] As students take math lessons on tablets, cameras capture their facial expressions, and if AI detects confusion, it simplifies the material or provides additional explanations.

[1539] Factory floor:

[1540] When a worker wears smart glasses to assemble a machine, the glasses analyze hand movements and facial expressions in real time and provide instructions such as "tighten the screws a little more" as needed.

[1541] Example prompt sentence:

[1542] Let AI generate the optimal curriculum based on information such as students' goals, strengths and weaknesses. Then, use the generated curriculum as input to analyze students' facial expressions and tone of voice in real time during class and generate appropriate feedback.

[1543] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1544] Step 1:

[1545] The user inputs information about the student or worker. The user inputs information such as the student's or worker's goals, current academic ability and skills, and areas of strength and weakness through a dedicated interface. The input information is sent to the server, which stores the received information in a database.

[1546] Step 2:

[1547] The server retrieves information from the database and passes it to the AI ​​engine. The server then passes various information about students and workers to the AI ​​engine as input data. Based on this input data, the AI ​​engine generates optimal curriculum and work instructions. The generated curriculum and work instructions are saved in the database.

[1548] Step 3:

[1549] Students and workers use devices to start activities based on the curriculum and work instructions. Students use tablet devices to attend classes, and workers wear smart glasses to perform their work. The devices obtain the curriculum and work instructions from the server and use them.

[1550] Step 4:

[1551] To prepare for real-time analysis, the device captures the students' and workers' behavior through a camera and microphone, and the video and audio data is sent to the server.

[1552] Step 5:

[1553] The server passes the video and audio data to the AI ​​engine for real-time analysis. The AI ​​engine uses OpenCV to analyze the video data and TensorFlow to analyze the audio data. This allows the facial expressions and tone of voice of students and workers to be analyzed. The results of this analysis are sent to the server.

[1554] Step 6:

[1555] The server receives the analysis results and adjusts the curriculum and work instructions in real time based on them.The server generates feedback on lesson content and work instructions based on the analysis results of the AI ​​engine and sends that feedback to the device.

[1556] Step 7:

[1557] Students and workers receive real-time feedback through their devices. Specifically, instructions and points of caution are displayed on tablets or smart glasses. For example, during a lesson, a message such as "You don't fully understand this part, so we'll show you additional explanations," or while working, instructions such as "Tighten the screws a little more" are displayed.

[1558] Step 8:

[1559] The user inputs a question from a student or worker. The question is sent from the device to the server, and then passed from the server to the AI ​​engine. The AI ​​engine generates the optimal answer to the question and returns that answer to the server.

[1560] Step 9:

[1561] The server sends the generated answers to the terminal, where students or workers can check the answers. The answers are displayed and the problems are resolved.

[1562] Step 10:

[1563] The server periodically accumulates progress data of students and workers and passes it to the AI ​​engine for analysis. Based on the progress data, the AI ​​engine analyzes the performance of students and workers and generates a report of the results.

[1564] Step 11:

[1565] The server generates reports that are shared with parents and administrators. The reports include information on the progress of students and workers, as well as issues and areas for improvement, and are shared via email or other means.

[1566] 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.

[1567] The present invention is a private tutoring system that combines artificial intelligence (AI) technology and emotion analysis technology, and a specific implementation method thereof will be described below.

[1568] First, the cram school staff (users) register a new student in the system. Using a dedicated interface, users input information such as the student's goals, current academic ability, and areas of strength and weakness. The terminal receives this information and sends it to the server. The server stores the received information in a database.

[1569] Next, the server retrieves student information from the database and passes it to the AI ​​engine. The AI ​​engine uses this information to generate an optimal curriculum. The generated curriculum is then saved in the database via the server again.

[1570] Students come to a cram school and take classes using a tablet device. The device retrieves curriculum information from the server and provides the student with lesson materials based on that information. If a student has a question during class, the user (student) enters the question through the tablet device. The device sends the question to the server, which passes it on to the AI ​​engine. The AI ​​engine generates the optimal answer to the question and sends it to the device via the server. The device displays the generated answer to the student.

[1571] The system also features an emotion engine that analyzes students' facial expressions and tone of voice in real time during class. The device captures students' reactions and analyzes this data using the emotion engine. The emotion engine then performs a detailed analysis of students' emotional states, such as stress levels and excitement, and sends the analysis results to a server. The server then passes the emotion data to the AI ​​engine, which then adjusts the lesson content based on the analysis results. For example, if the AI ​​engine detects signs of student confusion, it will adjust the difficulty of the lesson or provide additional explanations.

[1572] Furthermore, all question and answer data and emotional data from lessons are stored in a database and taken into consideration when creating the next curriculum, providing a set of curriculum optimized for each individual student.

[1573] The emotion engine periodically accumulates and analyzes students' emotional data and generates reports based on progress data. These reports are shared via email and other means with parents and cram school staff via the server. This allows for a comprehensive understanding of students' learning status and emotional state, enabling appropriate countermeasures to be taken.

[1574] In this way, the present invention solves the problem of labor shortages, improves learning efficiency, meets individual needs, and provides learning support that takes into account the emotional state of students.

[1575] The processing flow will be explained below.

[1576] Step 1:

[1577] The user (a cram school staff member) enters information about a new student (goals, current academic ability, areas of strength and weakness, etc.) into a dedicated interface. The device acquires this information and sends it to the server.

[1578] Step 2:

[1579] The server receives the student information and stores it in a database, which is used for the next process.

[1580] Step 3:

[1581] The server retrieves student information from the database and provides it to the AI ​​engine, which then generates the optimal curriculum based on this information.

[1582] Step 4:

[1583] The curriculum generated by the AI ​​engine is stored in a database via the server, and this curriculum information is used in later steps.

[1584] Step 5:

[1585] Students arrive at the cram school and take classes using a tablet device. The device retrieves current curriculum information from the server and presents the student with the materials they need for class.

[1586] Step 6:

[1587] If a student has a question during class, the user (student) enters the question into the tablet device, which then sends the question to the server.

[1588] Step 7:

[1589] The server sends the question to the AI ​​engine, which generates the optimal answer to the question, and the generated answer is sent to the device via the server.

[1590] Step 8:

[1591] The device displays the generated answer to the user (student), allowing the student to immediately resolve their doubts.

[1592] Step 9:

[1593] During class, the device captures students' facial expressions and tone of voice in real time and sends them to the emotion engine, which then analyzes the data.

[1594] Step 10:

[1595] The emotion engine sends the results of its analysis to a server, which then provides them to an AI engine. The AI ​​engine then adjusts the lesson content based on the analysis results. For example, if a student's stress level is high, it will adjust the difficulty of the lesson to be lower.

[1596] Step 11:

[1597] All questions, answers, and emotional data are stored in a database, which will be used to create the next curriculum and plan lessons.

[1598] Step 12:

[1599] The AI ​​engine periodically generates progress reports for students based on the accumulated data. These reports are shared via email with parents and cram school staff via the server, allowing for a comprehensive understanding of the student's learning progress.

[1600] Through the above steps, the present invention provides a learning experience optimized to the needs of each individual student, solving the problem of labor shortages while also realizing advanced learning support that takes into account the emotional state of students.

[1601] Example 2

[1602] 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."

[1603] Conventional individualized tutoring systems struggled to adjust lesson content in real time based on students' academic ability, level of understanding, and emotional state. As a result, they were unable to provide a learning experience optimized for each student's needs, making it difficult to achieve efficient learning outcomes. It was also difficult to provide immediate and appropriate answers to students' questions, which could lead to inconsistent learning. Furthermore, there was a lack of appropriate means for sharing students' progress and emotional state with parents and tutoring staff.

[1604] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1605] In this invention, the server includes: means for inputting information such as a student's goals, current academic ability, and areas of strength and weakness; means for transmitting the information to the server; means for the server to store the information in a database; means for an AI engine to generate an optimal curriculum based on the stored information; means for storing the generated curriculum in a database; means for a student to take lessons based on the curriculum using a tablet device; means for accepting questions from students during lessons and transmitting the questions to the AI ​​engine; means for the AI ​​engine to generate answers to the questions and return the answers to the students; means for analyzing students' reactions (facial expressions, tone of voice, etc.) in real time and transmitting the information to the server; means for an emotion analysis engine to periodically accumulate and analyze students' emotional data and transmit the analysis results to the server; means for the AI ​​engine to analyze students' reactions and adjust lesson content in real time; means for sharing student progress data with parents and cram school staff; and means for automatically adjusting lesson content based on the student's emotional state. This makes it possible to adjust lesson content in real time according to the student's academic ability, level of understanding, and emotional state, thereby providing an optimized learning experience for each student.

[1606] "Student goals" refer to the specific outcomes or goals that students want to achieve through their studies.

[1607] "Current academic ability" is an assessment of the level of knowledge and skills that a student currently possesses.

[1608] "Strong and weak areas" refers to subjects or areas in which a student is particularly strong and weak.

[1609] A "server" refers to the central device of a computer system that stores and processes data.

[1610] A "database" is a system for organizing and storing information and data.

[1611] An "AI engine" refers to a program that uses machine learning and data analysis to generate optimal curriculum and answers.

[1612] "Curriculum" refers to an educational plan organized according to specific goals or learning objectives.

[1613] "Tablet device" refers to a portable computing device with a touchscreen.

[1614] "Questions" refer to matters that students are unsure about or want to confirm while studying.

[1615] "Answer" refers to the answer or explanation provided to a question.

[1616] "Responses" refer to non-verbal feedback such as facial expressions and tone of voice shown by students during class.

[1617] An "emotion analysis engine" refers to a system that analyzes students' facial expressions, voices, etc. to evaluate their emotional state.

[1618] "Progress Data" refers to data that shows a student's learning process and academic progress.

[1619] "Guardians" refers to the parents or guardians of students attending cram schools.

[1620] "Cram school personnel" refers to staff, teachers, and other personnel who work at cram schools.

[1621] "Class content" refers to the teaching materials, content taught, learning activities, etc. used in class.

[1622] "Storage" refers to the collection and storage of information or data.

[1623] "Analysis" refers to the detailed examination and analysis of information or data.

[1624] The present invention is a private tutoring system that combines artificial intelligence (AI) technology and emotion analysis technology. This system provides an optimal curriculum based on a student's learning status and can personalize the learning experience by analyzing their reactions and emotional state in real time. A specific method for implementing this invention is described below.

[1625] First, to register a new student in the system, the user (cram school staff) enters information such as the student's goals, current academic ability, and areas of strength and weakness through a dedicated interface. The device (PC or tablet) sends this information to the server. The server stores the received information in a database. Specifically, the information is managed using a relational database such as MySQL or PostgreSQL.

[1626] The server then retrieves student information from the database and passes it to the AI ​​engine, which uses machine learning frameworks such as TensorFlow and PyTorch to analyze student characteristics and generate an optimal curriculum. This generated curriculum is then stored in the database via the server.

[1627] When a student comes to a cram school and takes a class using a tablet device, the device retrieves curriculum information from the server and provides the student with lesson materials based on that information. If a student has a question during class, the user (student) inputs the question through the tablet device. The device sends the question to the server, which then passes it on to the AI ​​engine. The AI ​​engine generates the optimal answer to the question and sends it to the device via the server. The device then displays the generated answer to the student.

[1628] For emotion analysis, the device captures students' facial expressions and tone of voice in real time and sends them to the emotion engine. The emotion engine uses technologies such as OpenCV and Dlib to analyze the student's stress level and excitement. The analysis results are sent to a server, which passes them on to an AI engine. The AI ​​engine then adjusts the lesson content based on this data. For example, if a student is confused, the AI ​​engine may instruct the teacher to lower the difficulty of the lesson or provide additional explanations.

[1629] Every time a student takes a class, all their questions, answers, and emotional data are stored in a database. This information is taken into account when generating the next curriculum, providing a more personalized learning experience.

[1630] Furthermore, the emotion engine periodically accumulates and analyzes students' emotional data and generates reports based on progress data. The server then shares these reports with parents and cram school staff via email, etc. This allows for a comprehensive understanding of students' learning status and emotional state, enabling appropriate countermeasures to be taken.

[1631] Examples of examples and prompts:

[1632] For example, if a new student wants to learn the basics of mathematics, the user (a cram school staff member) fills in a special input form with the following information: "Goal: Understand the basics of mathematics, Current academic level: Intermediate, Strong areas: Arithmetic, Weak areas: Algebra." Based on this information, the AI ​​engine generates a curriculum that starts with basic arithmetic and gradually progresses to Algebra.

[1633] Example prompt:

[1634] Prompt for user (cram school staff): "Please enter registration information for a new student. Please include their goals, current academic ability, and areas of strength and weakness."

[1635] Prompt for students: "If you have any questions during class, please use the tablet to type your question and we will provide you with an immediate answer."

[1636] This invention will solve the problem of labor shortages, improve learning efficiency, and meet individual needs, and will also provide learning support that takes into account the emotional state of students.

[1637] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1638] Step 1:

[1639] The user (cram school staff) enters information such as the student's goals, current academic ability, and areas of strength and weakness using a dedicated interface (e.g., web form or app). After entering the information, the device sends it to the server, which then stores the received information in a database.

[1640] Input: Information such as student goals, current academic ability, strengths and weaknesses

[1641] Output: Save student information to database

[1642] Specific operation: The user enters the required information into a dedicated web form and clicks the "Submit" button. The device sends this information to the server, which then stores it in a database.

[1643] Step 2:

[1644] The server retrieves student information from the database and passes it to the AI ​​engine. The AI ​​engine uses machine learning frameworks such as TensorFlow and PyTorch to analyze the student's characteristics. Based on this, it generates an optimal curriculum. The generated curriculum is then saved in the database via the server.

[1645] Input: Student information stored in the database

[1646] Output: Save the generated curriculum to a database

[1647] Specific operation: The server periodically checks for newly added student information and forwards this information to the AI ​​engine. The AI ​​engine generates an optimal curriculum and sends it back to the server. The server stores the curriculum in a database.

[1648] Step 3:

[1649] When students come to the cram school and take classes using a tablet device, the device retrieves curriculum information from the server and provides the students with lesson materials based on that information.

[1650] Input: Curriculum information stored in the database

[1651] Output: Lesson materials provided to students

[1652] Specific operation: When a student logs in to a tablet device, the system automatically downloads the student's curriculum from the server and then displays the first lesson slide to the student.

[1653] Step 4:

[1654] If a student has a question during class, the user (student) inputs the question through a tablet device. The device sends the question to the server, which passes it to the AI ​​engine. The AI ​​engine generates the optimal answer to the question and sends it to the device via the server. The device then displays the generated answer to the student.

[1655] Input: Student question

[1656] Output: Answer from the AI ​​engine

[1657] Specific operation: The student taps the "Ask a question" button and enters the question text. The question is sent to the server, where the AI ​​engine analyzes it and generates an answer. The device receives this and displays it to the student.

[1658] Step 5:

[1659] The device captures the student's facial expressions and tone of voice in real time and sends them to the emotion engine, which analyzes the student's stress level and excitement level and sends the results to the server.

[1660] Input: Facial expressions and tone of voice captured in real time

[1661] Output: Emotion analysis results

[1662] How it works: The tablet's camera and microphone capture the student's face and voice, and send them to the emotion engine every few seconds. The analyzed data is then sent to the server.

[1663] Step 6:

[1664] The server passes the emotional data to an AI engine, which then adjusts the lesson content based on the data. For example, if a student is confused, the AI ​​engine can lower the difficulty of the lesson or provide additional explanations.

[1665] Input: Sentiment analysis results

[1666] Output: Adjusted lesson content

[1667] Specific operation: The server receives the analysis results from the emotion engine and forwards them to the AI ​​engine. The AI ​​engine gradually adjusts the lesson content and sends it to the device via the server. The device then displays the new instructions to the student.

[1668] Step 7:

[1669] All questions, answers, and emotional data from lessons are stored in a database, and this data is taken into account when generating the next curriculum.

[1670] Input: Questions and answers, emotion data

[1671] Output: Individual data to be reflected in the next curriculum

[1672] Specific operation: After the lesson ends, the device automatically sends all learning data to the server, which stores this data in a database and uses it as a reference when the AI ​​engine generates the next curriculum.

[1673] Step 8:

[1674] The emotion engine periodically analyzes students' emotion data and generates reports based on their progress. The server then shares these reports with parents and school staff via email or other means.

[1675] Input: Accumulated emotion data

[1676] Output: Progress report

[1677] How it works: The emotion engine analyzes students' emotion data monthly and generates a report. The server converts this report into PDF format and sends it to the email addresses of parents and other relevant parties.

[1678] (Application example 2)

[1679] 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."

[1680] Conventional learning support systems and customer service support systems in brick-and-mortar stores have had difficulty accurately grasping the emotional state of individual customers or students in real time and providing appropriate instruction or customer service based on that information. Furthermore, there was a lack of efficient means for suggesting optimal products based on customers' emotions and purchasing history.

[1681] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means. In this invention, the server includes: means for inputting information such as a student's goals, current academic ability, and areas of strength and weakness; means for transmitting the information to the server; means for the server to store the information in a database; means for an AI engine to generate an optimal curriculum based on the stored information; means for storing the generated curriculum in a database; means for a student to take lessons based on the curriculum using a tablet device; means for accepting questions from students during lessons and transmitting the questions to the AI ​​engine; means for the AI ​​engine to generate answers to the questions and return the answers to the students; means for analyzing students' reactions (facial expressions, tone of voice, etc.) in real time and transmitting the information to the server; means for the AI ​​engine to analyze students' reactions and adjust lesson content in real time; means for sharing student progress data with parents and cram school personnel; means for analyzing customers' facial expressions and tone of voice in a store to grasp their emotional state; means for the AI ​​engine to generate optimal customer service methods and product suggestions based on the customer's emotional state and purchase history; and means for notifying store staff of the customer service methods and product suggestions. This will enable individually optimized learning support and personalized customer service in physical stores.

[1682] "Student goals" are the specific learning outcomes or objectives that students want to achieve during the learning process.

[1683] "Current academic ability" refers to the level of knowledge and skills that a student currently possesses.

[1684] "Strong and weak areas" refer to subjects or areas that are relatively easy for students to understand and master, and subjects or areas that are difficult for students to understand and master.

[1685] "Means for inputting information" refers to the interface or device through which a user provides information about a student or customer to the system.

[1686] "Means for sending to the server" refers to the communication protocol or technology used to transfer data from the terminal to the server.

[1687] "Means for storing data in a database" refers to a mechanism for efficiently recording received data and making it possible to search and update it as needed.

[1688] An "AI engine" is software that uses artificial intelligence to analyze data and generate solutions or suggestions for specific problems.

[1689] "Curriculum generation means" refers to algorithms or processes for constructing appropriate lesson plans and materials based on student information.

[1690] A "tablet device" is a portable computer that allows input and operation via a touch screen.

[1691] "Means for accepting questions and sending them to the AI ​​engine" refers to a mechanism that allows students or customers to input doubts or queries into the system and forward them to the AI ​​engine.

[1692] "Means for generating and returning an answer" refers to the mechanism by which the AI ​​engine creates the optimal answer to a question and provides that answer to the questioner.

[1693] "Means for analyzing reactions in real time" refers to technology that instantly evaluates the reactions of students or customers, such as facial expressions and tone of voice, and analyzes their emotional state.

[1694] "Means for sharing progress data" refers to a system for notifying relevant parties of progress data on students' learning status and customer purchasing behavior.

[1695] "Means of analyzing facial expressions and tone of voice to grasp emotional state" refers to technology that analyzes data acquired using a camera or microphone to identify the subject's emotions.

[1696] "Means for generating optimal customer service methods and product suggestions based on purchasing history" refers to a system in which AI uses customers' past purchasing data to generate optimal customer service methods and suggested products for purchase.

[1697] "Means of notifying store staff of customer service methods and product suggestions" refers to a system that provides information generated by AI to store staff in real time or at any time.

[1698] This invention is a personalized learning and customer service support system that combines AI technology and emotion analysis technology. First, we will explain the overall flow of the system.

[1699] 1. Enter student and customer information

[1700] The user enters information such as the student's goals, current academic ability, areas of strength and weakness, as well as the customer's purchasing history and preferred categories through a dedicated interface. This information is sent from the terminal to the server.

[1701] 2. Storing data and sending it to the AI ​​engine

[1702] The server stores the received information in a database. The server then sends the stored information to the AI ​​engine. The AI ​​engine generates the optimal curriculum and customer service methods based on the received information, and stores them in the database again via the server.

[1703] 3. Teaching and customer service using tablet devices

[1704] Students come to the cram school and take lessons using a tablet device. The device provides lessons based on curriculum information obtained from the server. In physical stores, store staff use smart glasses or smartphones to capture customers' facial expressions and tone of voice. This real-time data is sent to the server for analysis.

[1705] 4. Questions and Answers

[1706] If a student has a question during class, they can input it into their tablet device. The device sends the question to the server, which passes it on to the AI ​​engine. The AI ​​engine generates the optimal answer and sends it back to the device via the server. Similarly, when dealing with customers in-store, the AI ​​engine will suggest the best product and customer service methods.

[1707] 5. Sentiment analysis and adjustment of lesson content and customer service content

[1708] During lessons, the devices capture students' facial expressions and tone of voice in real time and send them to a server. An emotion analysis engine analyzes this data to determine students' stress levels and excitement levels. The AI ​​engine adjusts lesson content in real time based on the emotional data. In-store, customer service methods and product recommendations are adjusted based on customer emotional data.

[1709] 6. Sharing progress data

[1710] All questions and answers during lessons, as well as student emotional data, are stored in a database. This data is taken into consideration when creating the next curriculum and proposing customer service methods. Progress reports are generated by an AI engine and shared with parents, cram school staff, and store personnel. This allows for a comprehensive understanding of the status of students and customers and allows for appropriate countermeasures to be taken.

[1711] Hardware and software used

[1712] Hardware: Tablets, smart glasses, smartphones

[1713] Software: Python-based AI engine, OpenCV (image processing library), Emotion Analysis API, database management system

[1714] Examples of specific examples and prompts

[1715] As a specific example, when dealing with customers in a physical store, if the AI ​​engine detects signs of confusion in the customer, it will suggest to the store staff that they "speak in a calm tone and explain about new products in the store."

[1716] Example prompt sentence:

[1717] "If a customer is confused, please suggest the best way to serve them."

[1718] In this way, the system provides both individually optimized learning support and customer service in a physical store, solving conventional problems.

[1719] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1720] Step 1:

[1721] The user enters information such as the student's goals, current academic ability, areas of strength and weakness, as well as the customer's purchasing history and preferred categories into a dedicated interface. The entered information is sent from the terminal to the server.

[1722] Input: Student and Customer Information

[1723] Output: Information data sent to the server

[1724] How it works: The user uses a dedicated interface to input information via a keyboard or touchscreen. The device collects this data and sends it to the server via an HTTP request.

[1725] Step 2:

[1726] The server stores the received information in a database.

[1727] Input: Information data sent from the terminal

[1728] Output: Information stored in the database

[1729] Specific operations: The server stores the received data in a structured format using a database management system, and inserts it into the database using an SQL query.

[1730] Step 3:

[1731] The server sends the stored information to the AI ​​engine, which then generates the optimal curriculum and customer service methods based on the received information, and stores them in the database again via the server.

[1732] Input: Information stored in a database

[1733] Output: Generated curriculum and customer service methods

[1734] Specific operation: The server sends data to the AI ​​engine using an API request. The AI ​​engine analyzes the data using a machine learning model and generates the optimal curriculum and customer service method. The generated data is sent to the server as an API response, and the server stores it in the database again.

[1735] Step 4:

[1736] Students come to the cram school and use tablets to take lessons based on the curriculum, while store staff use smart glasses or smartphones to capture customers' facial expressions and tone of voice.

[1737] Input: Curriculum information obtained from the server, customer facial expressions and tone of voice

[1738] Output: Lesson content delivered, real-time data captured

[1739] How it works: The tablet device retrieves curriculum information from the server and displays lesson content accordingly. The smart glasses or smartphone uses a camera and microphone to capture the customer's facial expressions and tone of voice in real time, formatting the data and sending it to the server.

[1740] Step 5:

[1741] If a student has a question during class, they can enter it into their tablet device, which then sends it to the server, which then passes it on to the AI ​​engine.

[1742] Input: Student question

[1743] Output: Question data sent to the server

[1744] How it works: Students enter questions into their tablet devices, which then capture and send them to the server. The server then passes the received question data to the AI ​​engine via an API request.

[1745] Step 6:

[1746] The AI ​​engine generates the optimal answer and sends it to the device via the server.

[1747] Input: Question data sent from the server

[1748] Output: Answer data returned to the student

[1749] How it works: The AI ​​engine analyzes the question data and uses machine learning models to generate the best answer. The generated answer is returned to the server via an API response, and the server then sends it to the student's device.

[1750] Step 7:

[1751] During class, the device captures students' facial expressions and tone of voice in real time and sends them to a server. An AI engine analyzes this data to determine students' stress levels and excitement levels.

[1752] Input: Real-time facial expression data and tone of voice data of students

[1753] Output: Parsed emotion data

[1754] How it works: The tablet uses a camera and microphone to capture students' facial expressions and tone of voice, and sends the data to a server. An AI engine analyzes this data and identifies their emotional state.

[1755] Step 8:

[1756] The AI ​​engine adjusts lesson content in real time based on emotional data, and in-store customer service methods and product recommendations are adjusted based on customer emotional data.

[1757] Input: Parsed emotion data

[1758] Output: Adjusted lesson content and customer service methods

[1759] Specific actions: Based on the analysis results, the AI ​​engine adjusts the lesson content to lower the difficulty level or provide additional explanations as needed. In physical stores, it changes and adjusts customer service methods and product recommendations based on the customer's emotional state.

[1760] Step 9:

[1761] All questions and answers during lessons, as well as student emotional data, are stored in a database and are taken into consideration when creating the next curriculum and proposing customer service methods.

[1762] Input: Question and answer data during class, emotion data

[1763] Output: Progress data stored in a database

[1764] Specific operation: The server saves questions, answers, and emotion data from lessons in a database. This data is used to generate the next curriculum and improve customer service methods.

[1765] Step 10:

[1766] Progress reports are generated by an AI engine and shared with parents, cram school staff, and store personnel.

[1767] Input: Progress data stored in the database

[1768] Output: Generated progress report

[1769] How it works: The AI ​​engine analyzes the progress data and creates a report. The report is then shared via email with parents, cram school staff, and store staff via a server.

[1770] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice 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 voice data.

[1771] 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.

[1772] 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 robot 414.

[1773] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1774] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arrang...

Claims

1. A means to input information such as students' goals, current academic ability, areas of strength and weakness, and means for transmitting the information to a server; a means for the server to store the information in a database; A means for the AI ​​engine to generate the optimal curriculum based on the stored information, a means for storing the generated curriculum in a database; A means for students to take curriculum-based lessons using tablet devices; A means to accept questions from students during class and send them to the AI ​​engine, A means for the AI ​​engine to generate answers to questions and return those answers to students; A means for analyzing student responses in real time and transmitting that information to a server; The AI ​​engine analyzes students' responses and adjusts lesson content in real time. A means to share student progress data with parents and cram school staff, A system including:

2. 2. The system according to claim 1, further comprising means for storing the questions and their answers in a database and reflecting the information in the next curriculum.

3. 10. The system of claim 1, further comprising means for generating a progress report for the student by the AI ​​engine and transmitting the report to parents and cram school personnel.

Images