system

Abstract

We provide the system. [Solution] Methods for evaluating students' academic abilities, A means of generating individualized curricula based on academic performance assessment results, A means of providing learning content based on a generated individual curriculum, A means of recording and evaluating students' learning progress, A means of providing information to teachers based on the generated individual curriculum and learning progress, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In conventional educational systems, it has been difficult to provide an individual curriculum suitable for the academic ability and learning progress of each student. Also, there has been a problem that teachers tend to lack information for grasping the situation of each student and providing appropriate guidance, which increases the workload of teachers. Furthermore, there have been limited means for providing effective learning opportunities for students who have difficulty commuting to school. It has been required to solve these problems.

Means for Solving the Problems

[0005] To solve the above problems, the present invention provides a system that includes means for evaluating students' academic ability, means for generating individual curricula based on the results of the academic ability evaluation, means for providing learning content based on the generated individual curricula, means for recording and evaluating students' learning progress, and means for providing information to teachers based on the generated individual curricula and learning progress. This system can provide learning opportunities tailored to each student and reduce the workload of teachers. Specifically, the academic ability evaluation means includes an online test taken by the student via a terminal, and the individual curriculum generation means is configured to generate a curriculum based on the student's academic ability evaluation results and past learning history.

[0006] "Methods for assessing academic ability" refer to tools and processes used to measure students' current academic level, particularly those that evaluate learning comprehension through online tests and the like.

[0007] "Individualized curriculum generation method" refers to a process or system that creates a learning plan and materials optimized for a specific student based on the student's academic performance evaluation results and past learning history.

[0008] "Means of providing learning content" refers to the means of providing students with necessary learning materials (e.g., practice problems, explanatory videos, etc.) based on the generated individual curriculum.

[0009] "Learning progress evaluation tools" refer to tools or methods for monitoring students' learning progress and evaluating the degree of their progress.

[0010] "Information provision means" refers to methods for providing teachers with generated individual curricula and learning progress information, enabling teachers to understand the learning status of students. [Brief explanation of the drawing]

[0011] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0012] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0013] First, the terms used in the following description will be explained.

[0014] In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0015] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0016] In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0017] In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor and 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), or Bluetooth (registered trademark), etc.

[0018] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0019] [First Embodiment]

[0020] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0021] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0022] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0023] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0024] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0025] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0026] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0027] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0028] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0029] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0030] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0031] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0032] This invention relates to a system that provides customized education tailored to each student's academic ability and learning progress. This system operates through the collaboration of three entities: a server, terminals, and users (students and teachers). The following describes in detail how each entity functions.

[0033] Methods for assessing academic ability

[0034] The user (student) starts the test.

[0035] Device: Student A logs in and accesses the academic achievement test page. The device displays the "Start Test" button.

[0036] Implementation of academic achievement tests

[0037] User (student): Student A clicks the "Start Test" button.

[0038] Terminal: Retrieves academic achievement test questions from the server and displays them on the screen.

[0039] User (student): Student A enters their answers to each question.

[0040] Terminal: Temporarily saves responses and sends them to the server once all responses have been entered.

[0041] Analysis and transmission of test results

[0042] Server: Receives student A's answer data and calculates the correct answer rate for each question.

[0043] Server: Based on the analysis results, evaluate student A's academic level and save the data.

[0044] Individual Curriculum Generation Method

[0045] Curriculum generation

[0046] Server: Automatically generates an optimal learning curriculum for student A based on academic performance evaluation results and past learning history data.

[0047] Server: Saves the generated curriculum to the database.

[0048] Means of providing learning content

[0049] Distribution of curriculum and teaching materials

[0050] Terminal: Student A logs in and accesses their My Page. The server receives the My Page request and retrieves customized curriculum information for Student A.

[0051] Server: Sends curriculum information and corresponding teaching material data to the terminal.

[0052] Terminal: Displays the curriculum and teaching materials on the screen.

[0053] Learning progress

[0054] User (student): Student A views the learning materials and works on the practice problems.

[0055] Terminal: Saves student A's progress in real time.

[0056] Server: Records student A's learning progress data and updates learning materials as needed.

[0057] Learning progress evaluation method

[0058] Submission and evaluation of learning outcomes

[0059] User (student): Student A answers the practice questions and submits the results.

[0060] Terminal: Sends the response results to the server.

[0061] Server: Analyzes the response results, updates student A's learning progress, and saves the evaluation results.

[0062] Information provision means

[0063] Information provision to teachers

[0064] User (Teacher): Teacher B logs into the administration panel and accesses the dashboard.

[0065] Terminal: Sends the teacher's request to the server.

[0066] Server: Retrieves the latest learning progress data for each student and sends the aggregated dashboard data to the terminal.

[0067] Terminal: Display the dashboard so that Teacher B can see each student's learning progress at a glance.

[0068] Specific example

[0069] For example, if the server determines that student A's academic ability is at an "intermediate" level, the following will occur: The server will automatically generate a set of math practice problems and explanatory videos appropriate for the intermediate level and deliver them to the terminal. The user (student) will then use the provided materials to study and report their progress to the server. At the same time, teacher B will monitor student A's learning progress in real time through a dashboard and provide additional instruction as needed.

[0070] This system not only improves students' learning efficiency but also streamlines teachers' work and enables appropriate instruction for each individual student.

[0071] The following describes the processing flow.

[0072] Processing steps for academic ability assessment methods

[0073] Step 1:

[0074] Terminal: Student A logs in and accesses the academic achievement test page.

[0075] Terminal: Displays the button to start the academic ability assessment test.

[0076] Step 2:

[0077] User (student): Student A clicks the "Start Test" button.

[0078] Terminal: Retrieves academic achievement test questions from the server and displays them on the screen.

[0079] Step 3:

[0080] User (student): Student A enters their answers to each question.

[0081] Terminal: Temporarily saves response data.

[0082] Step 4:

[0083] User (student): Student A completes the test and clicks the submit button.

[0084] Terminal: Sends all responses to the server.

[0085] Step 5:

[0086] Server: Receives student A's answer data and calculates the correct answer rate for each question.

[0087] Step 6:

[0088] Server: Based on the analysis results, evaluate student A's academic level and save the data.

[0089] Processing steps of the individual curriculum generation means

[0090] Step 1:

[0091] Server: Automatically generates an individualized curriculum based on the academic performance evaluation results of student A.

[0092] Step 2:

[0093] Server: Optimizes curriculum content based on past learning history data.

[0094] Step 3:

[0095] Server: Saves the generated curriculum to the database.

[0096] Processing steps for learning content delivery methods

[0097] Step 1:

[0098] Terminal: Student A logs in and accesses their My Page.

[0099] Server: Receives a request for My Page and retrieves customized curriculum information for Student A.

[0100] Step 2:

[0101] Server: Sends curriculum information and corresponding teaching material data to the terminal.

[0102] Step 3:

[0103] Terminal: Displays the curriculum and teaching materials on the screen.

[0104] Step 4:

[0105] User (student): Student A views the learning materials and works on the practice problems.

[0106] Terminal: Saves student A's progress in real time.

[0107] Processing steps for learning progress evaluation means

[0108] Step 1:

[0109] User (student): Student A answers the practice questions and submits the results.

[0110] Terminal: Sends the response results to the server.

[0111] Step 2:

[0112] Server: Analyzes the response results and updates student A's learning progress.

[0113] Step 3:

[0114] Server: Saves the analysis results and adjusts the next learning content as needed.

[0115] Processing steps of information provision means

[0116] Step 1:

[0117] User (Teacher): Teacher B logs into the administration panel and accesses the dashboard.

[0118] Terminal: Sends the teacher's request to the server.

[0119] Step 2:

[0120] Server: Retrieves the latest learning progress data for each student.

[0121] Step 3:

[0122] Server: Sends the aggregated dashboard data to the terminal.

[0123] Step 4:

[0124] Terminal: Display the dashboard so that Teacher B can check the learning progress of each student.

[0125] (Example 1)

[0126] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0127] Traditional education systems struggle to provide appropriate curricula and materials tailored to each student's academic ability and learning progress, resulting in inefficient learning. Furthermore, there is a lack of sufficient information for teachers to monitor each student's learning progress in real time and provide necessary guidance.

[0128] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0129] In this invention, the server includes means for evaluating students' academic ability, means for generating individual curricula based on the academic ability evaluation results, means for providing learning content based on the generated individual curricula, means for recording and evaluating students' learning progress, means for providing information to instructors based on the generated individual curricula and learning progress, means for analyzing academic ability evaluation results and automatically generating curriculum and corresponding teaching material data, and means for recording students' learning activities and progress in real time and updating teaching materials as necessary. This enables the provision of an optimal learning plan for each individual, real-time monitoring of students' progress, and appropriate instruction.

[0130] The term "student" refers to a person who belongs to an educational institution and engages in learning.

[0131] "Academic ability assessment" refers to the process of measuring students' academic ability levels and evaluating their understanding and proficiency in learning.

[0132] "Means" refers to the methods or devices used to achieve a specific objective.

[0133] "Individualized curriculum" refers to a learning plan customized based on each student's academic ability and learning progress.

[0134] "Learning content" refers to educational materials such as textbooks, workbooks, and video explanations that students use for their studies.

[0135] "Learning progress" refers to data that indicates how far a student has progressed in their studies or their level of learning achievement.

[0136] The term "instructor" refers to someone who has the role of supporting students' learning and providing education.

[0137] A "server" refers to a computer system that provides services and data over a network.

[0138] "Terminal" refers to a device such as a computer or smartphone that is directly operated by the user.

[0139] An "online test" refers to a test for assessing academic ability that is conducted via the internet.

[0140] A "database" refers to a system used to efficiently store, search, and manage large amounts of data.

[0141] "Educational material data" refers to digital data of various educational materials used in learning.

[0142] "Analysis" refers to the process of analyzing data in detail and extracting information suitable for a specific purpose.

[0143] "Automatic generation" refers to the process by which a computer system automatically creates programs or data based on specific conditions.

[0144] "Real-time" refers to processing that occurs instantly without delay.

[0145] "Information provision" refers to the act of providing information to users for a specific purpose.

[0146] This invention relates to a system that provides customized education tailored to each student's academic ability and learning progress. This system operates through the collaboration of three entities: a server, terminals, and users (students and instructors). The following describes in detail how each entity functions.

[0147] Methods for assessing academic ability

[0148] The user (student) starts the test.

[0149] The user (student) logs into the system via their device and accesses the academic achievement test page. The device displays a "Start Test" button. When the student clicks the "Start Test" button, the device sends the request to the server.

[0150] Implementation of academic achievement tests

[0151] The server generates a set of questions for an academic assessment test and sends them to the terminal. The terminal displays the received test questions on its screen. The user (student) enters their answers to each question, and these answers are temporarily stored by the terminal. Once all answers have been entered, the terminal sends them back to the server.

[0152] Analysis and transmission of test results

[0153] Analysis of the answer results

[0154] The server receives student response data and calculates the correct answer rate for each question. Based on the analysis results, it evaluates the students' academic level and stores that data in a database.

[0155] Individual Curriculum Generation Method

[0156] Generating the optimal curriculum

[0157] The server retrieves students' academic performance evaluation results and past learning history data, and generates an optimal learning curriculum based on this data. The generated curriculum is stored in a database.

[0158] Means of providing learning content

[0159] Curriculum and material provision

[0160] When a user (student) accesses their My Page, the device sends a request to the server. The server retrieves customized curriculum information and corresponding learning materials for the student and sends them to the device. The device then displays the curriculum and learning materials on its screen.

[0161] Learning progress

[0162] Record of learning activities

[0163] Users (students) view learning materials and work on practice problems. The device saves the user's learning activities and progress in real time. The server periodically collects learning progress data and updates the learning materials as needed.

[0164] Learning progress evaluation method

[0165] Evaluation and recording of results

[0166] Users (students) input their answers to practice problems and send the results to the server via their terminal. The server analyzes the answers and evaluates the student's learning progress. The evaluation results are stored in a database.

[0167] Information provision means

[0168] Dashboard display

[0169] When a user (instructor) logs into the administration panel and accesses the dashboard, the device sends a request to the server. The server retrieves the latest learning progress data for each student, aggregates it, and sends it to the device. The device then displays the dashboard, allowing instructors to monitor each student's learning status in real time.

[0170] Examples of specific actions

[0171] For example, if the server determines a student's academic performance to be "intermediate," it automatically generates a set of math practice problems and explanatory videos appropriate for that level and delivers them to the student's device. The user (student) then uses the provided materials to learn and reports their progress to the server. Simultaneously, the instructor monitors the student's learning progress in real time via a dashboard and provides additional instruction as needed.

[0172] Example of a prompt

[0173] "Use this system to assess students' academic abilities and generate individualized curricula. Furthermore, explain how to provide students with learning materials based on those curricula and how to monitor their learning progress in real time."

[0174] This system not only improves students' learning efficiency but also streamlines instructors' work and enables appropriate instruction for each individual student.

[0175] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0176] Step 1:

[0177] The user (student) starts the test.

[0178] Input: The student logs into the system.

[0179] Device operation: Display the student's personal page and present a link to the academic achievement test.

[0180] User (student) action: Click the link for the academic achievement test and press the "Start Test" button.

[0181] Terminal action: Sends a test start request to the server.

[0182] Output: A request for the academic achievement test is sent to the server.

[0183] Step 2:

[0184] Implementation of academic achievement tests

[0185] Input: Test start request.

[0186] Server operation: Generates a set of questions for the academic achievement test and sends them to the terminal.

[0187] Device operation: Displays the received test questions on the screen.

[0188] User (student) action: Enter answers for each question.

[0189] Terminal operation: The user's responses are temporarily stored, and once all responses have been entered, they are sent to the server.

[0190] Output: Student response data is sent to the server.

[0191] Step 3:

[0192] Analysis and transmission of test results

[0193] Input: Student response data.

[0194] Server operation: Receives response data and calculates the correct answer rate for each question.

[0195] Data processing: Extract the number of correct answers from the response data and calculate the correct answer rate by dividing it by the total number of questions.

[0196] Server operation: Based on the analysis results, the system evaluates students' academic levels and saves that data to a database.

[0197] Output: Academic performance evaluation results are saved to the database.

[0198] Step 4:

[0199] Generating the optimal curriculum

[0200] Input: Academic performance evaluation results and past learning history data.

[0201] Server operation: Retrieves students' academic performance evaluation results and past learning history data.

[0202] Data processing: Analyze academic performance evaluation results and past data to generate an optimal learning plan.

[0203] Server operation: Generates the optimal learning curriculum and saves it to the database.

[0204] Output: The generated curriculum is saved to the database.

[0205] Step 5:

[0206] Curriculum and material provision

[0207] Input: Student access request.

[0208] User (student) action: Accesses My Page.

[0209] Terminal action: Sends a request to the server.

[0210] Server operation: Retrieves customized curriculum information and corresponding teaching material data, and sends it to the terminal.

[0211] Device operation: Displays the curriculum and learning materials on the screen.

[0212] Output: Customized curriculum and materials are displayed to students.

[0213] Step 6:

[0214] Record of learning activities

[0215] Input: Student learning activities.

[0216] User (student) actions: View learning materials and work on practice problems.

[0217] Device operation: Records learning activities and progress in real time.

[0218] Server operation: Regularly collects learning progress data and updates learning materials as needed.

[0219] Output: Learning progress data is saved to the server.

[0220] Step 7:

[0221] Evaluation and recording of results

[0222] Input: Student practice problem answer data.

[0223] User (student) action: Enter answers to practice problems and send the results to the server.

[0224] Terminal operation: Sends the response results to the server.

[0225] Server operation: Analyzes the response results and evaluates the students' learning progress.

[0226] Data processing: Analyze the response data and calculate the accuracy rate and the degree of achievement of learning objectives.

[0227] Server operation: Save evaluation results to the database.

[0228] Output: Learning progress evaluation data is saved to the database.

[0229] Step 8:

[0230] Dashboard display

[0231] Input: Instructor access request.

[0232] User (instructor) action: Log in to the administration screen and access the dashboard.

[0233] Terminal operation: Sends an access request to the dashboard to the server.

[0234] Server operation: The server retrieves the latest learning progress data for each student and sends the aggregated data to the terminal.

[0235] Device operation: Displays a dashboard, allowing instructors to see each student's learning progress at a glance.

[0236] Output: Learning progress is displayed on the dashboard.

[0237] As described above, this system efficiently processes each step and provides an optimal educational environment for students and instructors.

[0238] (Application Example 1)

[0239] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0240] Traditional factory worker training systems offer a uniform training program, making it difficult to customize the program to suit the individual skill levels and progress of each worker. Therefore, there is a need to provide an optimal training program for each worker to efficiently promote skill acquisition. Furthermore, progress management and evaluation are often done manually, placing a heavy burden on supervisors.

[0241] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0242] In this invention, the server includes means for performing a worker's technical evaluation, means for generating an individualized training program based on the technical evaluation results, means for providing training content based on the generated individualized training program, means for recording and evaluating the worker's progress, and means for providing information to the supervisor based on the generated individualized training program and progress. This enables the provision of customized training programs tailored to each worker's technical level and progress, as well as automated management and evaluation of progress.

[0243] A "worker" refers to a person who works in a factory or manufacturing industry and performs tasks using specific skills and techniques.

[0244] "Technical evaluation" refers to the process of measuring the skill and knowledge level of workers and collecting information necessary to provide appropriate training programs.

[0245] An "individualized training program" refers to training content that is customized based on the worker's technical evaluation results and according to the skills and knowledge that the worker needs to acquire.

[0246] "Training content" refers to educational materials and tools that workers use to learn skills and knowledge according to their individual training programs.

[0247] "Progress" refers to the state or status of how far an employee is progressing toward the goals in a training program.

[0248] A "supervisor" is a person whose role is to manage the training and progress and results of workers' daily work, and to provide guidance and advice as needed.

[0249] This invention relates to a system that provides customized training programs tailored to the skills and progress of each individual worker in a factory. This system operates through the collaboration of three entities: a server, terminals, and users (workers and supervisors). The following describes in detail how each entity functions.

[0250] Technical evaluation methods

[0251] The user (worker) starts the evaluation test.

[0252] Terminal: Worker A logs in and accesses the technical evaluation test page. The terminal displays the "Start Test" button.

[0253] Implementation of technical evaluation tests

[0254] User (worker): Worker A clicks the Start Test button.

[0255] Terminal: Retrieves technical evaluation test questions from the server and displays them on the screen.

[0256] User (worker): Worker A enters the answers to each question.

[0257] Terminal: Temporarily saves responses and sends them to the server once all responses have been entered.

[0258] Analysis and transmission of test results

[0259] Server: Receives worker A's response data and calculates the correct answer rate for each question.

[0260] Server: Based on the analysis results, evaluate the skill level of worker A and save the data.

[0261] Individual training program generation method

[0262] Training program generation

[0263] Server: Automatically generates the optimal training program for worker A based on technical evaluation results and past training history data.

[0264] Server: Saves the generated training program to the database.

[0265] Training content delivery methods

[0266] Distribution of training programs and materials

[0267] Terminal: Worker A logs in and accesses their My Page. The server receives the My Page request and retrieves customized training program information for Worker A.

[0268] Server: Sends training program information and corresponding training material data to the terminal.

[0269] Terminal: Displays the training program and materials on the screen.

[0270] Training progress

[0271] User (worker): Worker A views the training materials and works on the practice problems.

[0272] Terminal: Saves the progress of worker A in real time.

[0273] Server: Records worker A's training progress data and updates training materials as needed.

[0274] Progress evaluation means

[0275] Transmission and evaluation of training results

[0276] User (operator): Operator A answers practice questions and transmits the results.

[0277] Terminal: Transmits the answer result to the server.

[0278] Server: Analyzes the answer result, updates the training progress of Operator A, and saves the evaluation result.

[0279] Information provision means

[0280] Provision of information to the supervisor

[0281] User (supervisor): Supervisor B logs in to the management screen and accesses the dashboard. <http: / / www.example.com /

[0282] Terminal: Transmits the supervisor's request to the server.

[0283] Server: Obtains the latest training progress data of each operator, aggregates the data, and transmits the aggregated dashboard data to the terminal.

[0284] Terminal: Displays the dashboard so that Supervisor B can quickly check the training status of each operator.

[0285] With this system, training is provided according to the technical level and progress of each worker, enabling efficient skill acquisition and progress management. For example, when new employee Worker A starts training at the factory site, an initial evaluation test is conducted, and their technical level is evaluated as "intermediate". Based on this result, a training program for intermediate-level workers is automatically generated and distributed to the terminal. Worker A acquires skills according to the provided program, and when the progress exceeds 50%, a new evaluation test is conducted and the technical level is re-evaluated. In this way, Worker A can efficiently improve their technical ability.

[0286] Example of a prompt sentence to input into the generative AI model:

[0287] When a new employee worker starts training at the factory site, proceed with the training system in the following steps. First, conduct an initial evaluation test, and the technical level is evaluated as "intermediate". Based on this result, a training program for intermediate-level workers is automatically generated and distributed to the terminal. The worker acquires skills according to the provided program, and the progress is recorded in the system in real time. When the progress exceeds 50%, conduct a new evaluation test and re-evaluate the technical level. In this way, the worker can efficiently improve their technical ability.

[0288] This system operates through a Python program and can use a smartphone or tablet terminal. Also, the server requires a Python environment for evaluation analysis and data storage. With this system, the improvement of individual workers' capabilities and efficient management are realized.

[0289] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0290] Step 1:

[0291] The user (worker) starts the evaluation test

[0292] Input: The worker logs into the terminal and accesses the evaluation test page.

[0293] Specific operation: The terminal displays a "Start Test" button to the operator. When operator A clicks this button, the terminal requests the server to start the test.

[0294] Output: A request to start the evaluation test is sent to the server.

[0295] Step 2:

[0296] The server provides the evaluation test questions.

[0297] Input: The server receives a request to start the evaluation test.

[0298] Specific operation: The server retrieves the set of assessment test questions from the database and sends them to the terminal.

[0299] Output: The evaluation test questions are displayed on the terminal.

[0300] Step 3:

[0301] The user (worker) conducts the evaluation test.

[0302] Input: Worker A enters the answers to the test questions.

[0303] Specific operation: The terminal temporarily stores each answer entered by worker A, and once all answers have been entered, it sends that data to the server.

[0304] Output: Worker A's response data is sent to the server.

[0305] Step 4:

[0306] The server analyzes the test results.

[0307] Input: The server receives the response data of Worker A.

[0308] Specific operation: The server calculates the correct answer rate for each question and evaluates the technical level of Worker A. The evaluation result is saved in the database.

[0309] Output: The technical level evaluation result of Worker A is saved in the database.

[0310] Step 5:

[0311] The server generates an individual training program

[0312] Input: The server obtains the technical evaluation result and past training history data.

[0313] Specific operation: Based on these data, the server automatically generates an optimal training program for Worker A. The generated training program is saved in the database.

[0314] Output: The individual training program is saved in the database.

[0315] Step 6:

[0316] The server provides the training program

[0317] Input: Worker A logs in to the terminal and accesses the my page.

[0318] Specific operation: The server receives the request for the my page and sends the customized training program information to Worker A's terminal.

[0319] Output: The customized training program information is displayed on the terminal.

[0320] Step 7:

[0321] The user (worker) takes the training.

[0322] Input: Worker A answers practice problems according to the training program.

[0323] Specific operation: The terminal saves worker A's progress in real time and sends that data to the server.

[0324] Output: Worker A's progress data is saved to the server.

[0325] Step 8:

[0326] The server evaluates and updates the progress.

[0327] Input: The server receives progress data for worker A.

[0328] Specific operation: The server analyzes the progress data, updates worker A's training progress, and saves the evaluation results to the database.

[0329] Output: The updated progress evaluation data is saved to the database.

[0330] Step 9:

[0331] The server provides information to the supervisor.

[0332] Input: Supervisor B logs into the administration panel and accesses the dashboard.

[0333] Specific operation: The server retrieves the latest training progress data for each worker and sends the aggregated dashboard data to the terminal.

[0334] Output: Supervisor dashboard data is displayed on the terminal.

[0335] This processing flow allows each worker to receive the most appropriate technical training, and supervisors can evaluate and manage their progress in real time.

[0336] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0337] This invention relates to a system that provides customized education tailored to each student's academic ability, learning progress, and emotional state. This system operates through the collaboration of four entities: a server, terminals, users (students and teachers), and an emotion engine. The following describes in detail how each entity functions.

[0338] Methods for assessing academic ability and methods for generating individual curricula

[0339] Methods for assessing academic ability

[0340] Device: Student A logs in and accesses the academic achievement test page. The device displays the "Start Test" button.

[0341] User (student): Student A clicks the "Start Test" button, and the server displays the test questions.

[0342] User (student): Student A enters their answers to each question and sends the results from their terminal to the server.

[0343] Server: Analyzes the response data, evaluates student A's academic level, and saves the results.

[0344] Individual Curriculum Generation Method

[0345] Server: Automatically generates an optimal learning curriculum for student A based on academic performance evaluation results and past learning history data.

[0346] Server: Saves the generated curriculum to the database.

[0347] Means of providing learning content and means of evaluating learning progress

[0348] Means of providing learning content

[0349] Terminal: Student A logs in and accesses their My Page. The server retrieves customized curriculum information and delivers it to Student A.

[0350] Terminal: The curriculum and learning materials are displayed on the screen, and student A learns based on them.

[0351] User (Student): Student A views the learning materials and works on practice problems. The device saves their progress in real time.

[0352] Learning progress evaluation method

[0353] User (student): Student A answers a practice problem and sends the result from their terminal to the server.

[0354] Server: Analyzes the response results, updates student A's learning progress, and saves the evaluation results.

[0355] Emotion engines and the use of emotional data

[0356] How the emotion engine works

[0357] Device: When students are learning, data such as their facial expressions, voice, and behavior are collected in real time and sent to the emotion engine.

[0358] Emotion Engine: Analyzes received data to identify the student's emotional state (e.g., excitement, concentration, fatigue, indifference).

[0359] Use of emotional data

[0360] Server: Based on emotional data received from the emotion engine, it evaluates students' learning efficiency and dynamically adjusts learning content and delivery methods as needed.

[0361] Server: Reflect emotion data on the teacher's dashboard, enabling teachers to provide instruction based on students' emotional states.

[0362] Information provision means

[0363] Information provision to teachers

[0364] User (Teacher): Teacher B logs into the administration panel and accesses the dashboard.

[0365] Terminal: Sends the teacher's request to the server.

[0366] Server: Retrieves the latest learning progress and sentiment data for each student and sends the aggregated dashboard data to the terminal.

[0367] Terminal: Displays a dashboard, allowing teacher B to see each student's learning progress and emotional state at a glance.

[0368] Specific example

[0369] For example, if the server determines that student A's academic performance is "intermediate" and the emotion engine recognizes student A's emotional state as "focused," the system will operate as follows: The server generates a set of practice problems and explanatory videos appropriate for the intermediate level and delivers them to the terminal. Accordingly, the user (student) uses the provided materials to study and reports their progress and emotional state to the server. Meanwhile, teacher B monitors student A's learning progress and emotional state in real time through a dashboard and provides additional instruction as needed.

[0370] This system not only improves students' learning efficiency but also streamlines teachers' work and enables appropriate instruction for each individual student. By taking students' emotional states into consideration, it allows for more personalized and appropriate education.

[0371] The following describes the processing flow.

[0372] Processing steps for academic ability assessment methods

[0373] Step 1:

[0374] Device: Student A logs in and accesses the academic achievement test page. The device displays a button to start the academic achievement test.

[0375] Step 2:

[0376] User (student): Student A clicks the "Start Test" button. The device sends a request to the server to retrieve the test questions.

[0377] Step 3:

[0378] Server: Sends the academic achievement test questions to the terminal.

[0379] Step 4:

[0380] Terminal: Displays the acquired test questions on the screen.

[0381] Step 5:

[0382] User (student): Student A answers each question and enters the answer data.

[0383] Step 6:

[0384] Terminal: Temporarily saves the entered response data.

[0385] Step 7:

[0386] User (student): Student A completes the test and clicks the submit button.

[0387] Step 8:

[0388] Terminal: Sends all response data to the server.

[0389] Step 9:

[0390] Server: Receives student A's answer data and calculates the correct answer rate for each question.

[0391] Step 10:

[0392] Server: Based on the analysis results, evaluate student A's academic level and save the data.

[0393] Processing steps of the individual curriculum generation means

[0394] Step 1:

[0395] Server: Receives student A's academic performance evaluation results and starts the curriculum generation process.

[0396] Step 2:

[0397] Server: Retrieves past learning history data from the database and integrates it with current academic performance evaluation results.

[0398] Step 3:

[0399] Server: Based on integrated data, it automatically generates the optimal learning curriculum for student A.

[0400] Step 4:

[0401] Server: Saves the generated curriculum to the database.

[0402] Processing steps for learning content delivery methods

[0403] Step 1:

[0404] Terminal: Student A logs in and accesses their My Page.

[0405] Step 2:

[0406] Server: Receives a request for My Page and retrieves customized curriculum information for Student A.

[0407] Step 3:

[0408] Server: Searches for curriculum information and corresponding teaching material data, and sends it to the terminal.

[0409] Step 4:

[0410] Terminal: Displays the curriculum and teaching materials on the screen.

[0411] Step 5:

[0412] User (student): Student A views the learning materials and works on the practice problems.

[0413] Step 6:

[0414] Terminal: Saves student A's progress in real time.

[0415] Processing steps for learning progress evaluation means

[0416] Step 1:

[0417] User (student): Student A answers the practice questions and saves the results to their device.

[0418] Step 2:

[0419] Terminal: Sends the response results to the server.

[0420] Step 3:

[0421] Server: Analyzes the submitted response data and updates student A's learning progress.

[0422] Step 4:

[0423] Server: Saves updated progress data to the database.

[0424] Emotion engine and processing steps for using emotional data

[0425] Step 1:

[0426] Device: Sensors collect data such as students' facial expressions, voices, and behaviors while they are learning, and transmit this data to the emotion engine.

[0427] Step 2:

[0428] Emotion Engine: Analyzes received data to identify the student's emotional state (e.g., excitement, concentration, fatigue, indifference, etc.).

[0429] Step 3:

[0430] Emotion Engine: Sends emotional state data to the server.

[0431] Step 4:

[0432] Server: Based on emotional data, evaluate student A's learning efficiency and adjust the content delivery method as needed.

[0433] Step 5:

[0434] Server: Reflect emotion data on the teacher's dashboard, enabling teachers to provide instruction based on students' emotional states.

[0435] Processing steps of information provision means

[0436] Step 1:

[0437] User (Teacher): Teacher B logs into the administration panel and accesses the dashboard.

[0438] Step 2:

[0439] Terminal: Sends the teacher's request to the server.

[0440] Step 3:

[0441] Server: Retrieves the latest learning progress and sentiment data for each student and sends the aggregated dashboard data to the terminal.

[0442] Step 4:

[0443] Terminal: Displays a dashboard, allowing Teacher B to check each student's learning progress and emotional state.

[0444] This system not only improves students' learning efficiency but also streamlines teachers' work and enables appropriate instruction for each individual student. Furthermore, by considering students' emotional states through the emotion engine, it can provide more individualized and appropriate education.

[0445] (Example 2)

[0446] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0447] Traditional education systems have struggled to provide individualized curricula based on each student's academic ability and learning progress. Furthermore, they were unable to grasp students' emotional states in real time and use that information to improve learning efficiency or provide appropriate guidance. Therefore, providing students with the optimal learning environment was difficult.

[0448] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for evaluating students' academic ability, means for generating individual curricula based on the academic ability evaluation results, means for providing learning content based on the generated individual curricula, means for recording and evaluating students' learning progress, means for analyzing students' emotional state, and means for providing information to teachers based on the generated individual curricula, learning progress, and emotional state. This makes it possible to provide an optimal learning environment tailored to each student's academic ability, learning progress, and emotional state.

[0449] "Methods for evaluating academic ability" refer to functions for measuring and evaluating students' academic abilities.

[0450] The "individualized curriculum generation method" is a function that automatically creates an optimal learning curriculum for each student based on the results of academic performance assessments and past learning history.

[0451] "Learning content delivery method" refers to a function that provides learning materials and practice problems tailored to each student's needs, based on the generated individual curriculum, to their device.

[0452] A "learning progress evaluation tool" is a function for recording students' learning activities and evaluating their progress.

[0453] The "emotional state analysis method" is a function that analyzes students' facial expressions, voice, and behavior to grasp their emotional state in real time during learning.

[0454] "Information provision means" refers to a function that provides teachers with necessary information in a timely manner based on the generated individual curriculum, learning progress, and emotional state.

[0455] This invention relates to a system that provides customized education tailored to each student's academic ability, learning progress, and emotional state. This system operates through the coordinated efforts of four entities: a server, terminals, users (students and teachers), and an emotion engine.

[0456] Methods for assessing academic ability and methods for generating individual curricula

[0457] Methods for assessing academic ability

[0458] Device: The student logs in and accesses the academic achievement test page. The device displays a button to start the test.

[0459] User (student): When a student clicks the "Start Test" button, the server displays the test questions on their device.

[0460] User (student): The student answers each question and sends the answer data from their device to the server.

[0461] Server: The server analyzes the response data, evaluates the students' academic level, and saves the results.

[0462] Individual Curriculum Generation Method

[0463] Server: Based on academic performance evaluation results and past learning history data, it uses a generative AI model to automatically generate the optimal learning curriculum for each student.

[0464] Server: Saves the generated curriculum to the database.

[0465] Means of providing learning content and means of evaluating learning progress

[0466] Means of providing learning content

[0467] Device: When a student logs in and accesses their My Page, the server retrieves customized curriculum information and sends it to the device.

[0468] Terminal: Displays the curriculum and learning materials on the screen, allowing students to learn based on them.

[0469] Learning progress evaluation method

[0470] User (student): The student answers the practice questions and sends the results from their device to the server.

[0471] Server: The server analyzes the response results, updates the students' learning progress, and saves the evaluation results.

[0472] Emotion engines and the use of emotional data

[0473] How the emotion engine works

[0474] Device: Collects data such as facial expressions, voice, and behavior in real time as students learn, and sends it to the emotion engine.

[0475] Emotional Engine: Analyzes received data to identify the student's emotional state. For example, it analyzes excitement, concentration, fatigue, apathy, etc.

[0476] Use of emotional data

[0477] Server: Based on emotional data received from the emotion engine, it evaluates students' learning efficiency and dynamically adjusts learning content and delivery methods as needed.

[0478] Server: Emotional data is also sent to a teacher dashboard, enabling teachers to provide instruction based on students' emotional states.

[0479] Information provision means

[0480] Information provision to teachers

[0481] User (Teacher): The teacher logs into the administration panel and accesses the dashboard.

[0482] Terminal: Sends the teacher's request to the server.

[0483] Server: Retrieves the latest learning progress and sentiment data for each student and sends the aggregated dashboard data to the terminal.

[0484] Device: Displays a dashboard that allows teachers to see each student's learning progress and emotional state at a glance.

[0485] Specific example

[0486] For example, the following describes the process when the server determines a student's academic performance to be "intermediate" and the emotion engine recognizes the student's emotional state as "focused." The server generates a set of practice problems and explanatory videos appropriate for the intermediate level and delivers them to the student's device. The student then uses the provided materials to study and reports their progress and emotional state to the server. Meanwhile, the teacher monitors the student's learning progress and emotional state in real time through a dashboard and provides additional instruction as needed.

[0487] Example of a prompt

[0488] Examples of prompt statements to input into the generative AI model are shown below.

[0489] Prompt: If a student's academic performance is assessed as "intermediate" and the emotional engine recognizes them as "focused," please describe the specific processing steps for generating individualized curricula and utilizing emotional data.

[0490] In this way, this system can provide each student with an optimal learning environment and improve learning efficiency.

[0491] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0492] Step 1:

[0493] Input: Student login information (username and password)

[0494] Process: The student enters their authentication information on the login screen.

[0495] Terminal: The terminal sends login information to the server.

[0496] Server: The server verifies the authentication information, and if authentication is successful, redirects the user to their My Page.

[0497] Output: Login success status and My Page URL

[0498] Step 2:

[0499] Input: URL of the student's academic assessment test page after successful login

[0500] Process: The student accesses the academic achievement test page.

[0501] Terminal: The terminal displays a button to start the test.

[0502] Output: Start Test button

[0503] Step 3:

[0504] Input: Click event of the test start button

[0505] Process: The student clicks the "Start Test" button.

[0506] User (student): The student clicks the "Start Test" button.

[0507] Server: The server sends the academic achievement test questions to the terminals.

[0508] Output: Questions from the academic achievement test

[0509] Step 4:

[0510] Input: Answer data for each question (text, multiple choice)

[0511] Processing: Students answer each question and input the answer data.

[0512] Terminal: The terminal sends the response data to the server.

[0513] User (student): The student answers each question.

[0514] Output: Response data

[0515] Step 5:

[0516] Input: Submitted response data

[0517] Processing: The server receives the response data and runs an analysis algorithm to evaluate the students' academic level.

[0518] Server: The server analyzes the response data, evaluates the academic level, and stores it in a database.

[0519] Output: Academic performance evaluation results

[0520] Step 6:

[0521] Input: Academic performance evaluation results and past learning history data

[0522] Processing: Based on academic performance assessment results and past learning history data, a generative AI model is used to automatically generate the optimal learning curriculum for each student.

[0523] Server: The server retrieves academic performance evaluation results and past learning history from the database and automatically generates the curriculum.

[0524] Output: Generated learning curriculum

[0525] Step 7:

[0526] Input: Generated learning curriculum

[0527] Process: Save the generated curriculum to the database.

[0528] Server: The server saves the generated curriculum to the database.

[0529] Output: Saved curriculum

[0530] Step 8:

[0531] Input: Access to the student's My Page

[0532] Processing: After the student logs in, they access their My Page.

[0533] Terminal: The terminal sends a request to the server to access the My Page.

[0534] Server: The server retrieves customized curriculum information from the database and sends it to the terminal.

[0535] Output: Customized curriculum information

[0536] Step 9:

[0537] Input: Customized curriculum information

[0538] Processing: The curriculum and learning materials are displayed on the screen, and students learn based on them.

[0539] Terminal: The terminal displays the curriculum and learning materials on its screen.

[0540] Output: Displayed curriculum and materials

[0541] Step 10:

[0542] Input: Data used by students to answer practice problems.

[0543] Processing: Students answer practice problems, and their progress is saved in real time on their devices.

[0544] Terminal: The terminal sends progress data to the server.

[0545] Output: Sending progress data

[0546] Step 11:

[0547] Input: Submitted practice problem answer data

[0548] Processing: The server analyzes the response results and updates the students' learning progress.

[0549] Server: The server saves the analysis progress data to the database.

[0550] Output: Updated progress data

[0551] Step 12:

[0552] Input: Student facial expressions, voice, and behavioral data during learning.

[0553] Processing: Data such as facial expressions, voice, and behavior are collected in real time as students learn and sent to the emotion engine.

[0554] Device: The device sends the collected data to the emotion engine.

[0555] Output: Sent sentiment data

[0556] Step 13:

[0557] Input: Emotional data analyzed by the emotion engine

[0558] Processing: The emotion engine analyzes the received data to identify the student's emotional state. For example, it analyzes excitement, concentration, fatigue, apathy, etc.

[0559] Emotional Engine: Analyzes emotional states.

[0560] Output: Emotional state data from the analysis results

[0561] Step 14:

[0562] Input: Emotion engine analysis results and student learning progress data

[0563] Processing: The server evaluates learning efficiency based on sentiment data and dynamically adjusts the learning content and delivery method as needed.

[0564] Server: Saves the adjusted learning content to the database.

[0565] Output: Adjusted learning content

[0566] Step 15:

[0567] Input: Adjusted learning content and emotional state data

[0568] Processing: The server reflects the information on the teacher's dashboard.

[0569] Server: Generates teacher dashboard data and sends it to the terminal.

[0570] Output: Sending dashboard data

[0571] Step 16:

[0572] Input: Generated dashboard data

[0573] Process: The teacher logs into the administration panel and accesses the dashboard.

[0574] Device: Displays a dashboard, allowing teachers to monitor each student's learning progress and emotional state.

[0575] Output: Displayed dashboard

[0576] (Application Example 2)

[0577] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0578] Conventional education systems and work equipment management systems require flexible responses tailored to the individual academic abilities, efficiency, and progress of students and work equipment. In particular, it is difficult to consider real-time factors such as emotions and fatigue, which can lead to delays in providing appropriate learning and training. Furthermore, it is difficult for instructors to provide accurate guidance based on the individual's condition. The objective of this invention is to solve these problems and provide an efficient and effective education and training system.

[0579] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0580] In this invention, the server includes means for evaluating students' academic abilities, means for generating individual curricula based on the academic ability evaluation results, means for providing learning content based on the generated individual curricula, means for recording and evaluating students' learning progress, means for providing information to instructors based on the generated individual curricula and learning progress, means for collecting and evaluating the work efficiency and historical data of work equipment, means for generating training programs based on the evaluation results, means for analyzing the emotional state of work equipment, and means for providing information to instructors based on the emotional state and training program. This enables flexible and effective education and training based on the individual learning status and state of students and work equipment.

[0581] "Methods for evaluating academic ability" refer to systems or methods designed to assess students' academic abilities.

[0582] "Individualized curriculum generation means" refers to a system or method that automatically generates an optimal curriculum for a specific student based on the results of an academic performance assessment.

[0583] "Means of providing learning content" refers to a system or method that provides students with appropriate learning materials and problems based on a generated individual curriculum.

[0584] A "learning progress recording and evaluation means" is a system or method for recording students' learning status and evaluating their progress.

[0585] "Instructor information provision means" refers to a system or method that provides instructors with necessary information based on the generated individual curriculum and learning progress.

[0586] A "means for evaluating the work efficiency of work equipment" refers to a system or method for collecting and evaluating the work efficiency and historical data of work equipment.

[0587] "Training program generation means" refers to a system or method that generates an optimal training program based on the evaluation results of work equipment.

[0588] "Emotional state analysis means" refers to a system or method for analyzing the emotional state of work equipment and workers and collecting the data.

[0589] This invention provides a system that offers optimal education and training programs based on the individual academic abilities, work efficiency, and progress of students and work equipment. This system operates through the coordinated efforts of four entities: a server, terminals, users (students, workers, instructors), and an emotion engine.

[0590] System-wide configuration

[0591] The server includes means for evaluating academic ability, generating individual curricula, providing learning content, recording and evaluating learning progress, providing instructor information, evaluating the work efficiency of work equipment, generating training programs, and analyzing emotional states. By using this system, flexible and effective education and training based on the individual circumstances of students and work equipment becomes possible.

[0592] Methods for assessing academic ability and methods for generating individual curricula

[0593] Methods for assessing academic ability

[0594] Students' academic abilities will be assessed through online tests conducted via their devices.

[0595] The user (student) clicks the "Start Test" button and answers the questions presented by the server.

[0596] The server analyzes the response data, evaluates the academic level, and saves the results.

[0597] Individual Curriculum Generation Method

[0598] The server generates an optimal individual curriculum for each student based on their academic performance evaluation results and past learning history data.

[0599] The generated curriculum is stored in a database.

[0600] Means for providing learning content and means for recording and evaluating learning progress

[0601] Means of providing learning content

[0602] Students log in via their devices, and the server delivers customized curriculum information.

[0603] The device displays the provided curriculum and learning materials on its screen, and the user (student) learns based on them.

[0604] Learning progress recording and evaluation method

[0605] Users (students) view learning materials and work on practice problems.

[0606] The progress is recorded in real time by the device and sent to the server.

[0607] The server analyzes the response results, updates the learning progress, and saves the evaluation results.

[0608] Emotion engines and the use of emotional data

[0609] How the emotion engine works

[0610] The device collects facial expressions, voices, and behavioral data of students and workers in real time and transmits them to the emotion engine.

[0611] The emotion engine analyzes incoming data to identify emotional states (e.g., excitement, concentration, fatigue, indifference, etc.).

[0612] Use of emotional data

[0613] Based on emotional data received from the emotion engine, the server evaluates the learning and work efficiency of students and workers, and dynamically adjusts the learning and training content as needed.

[0614] Furthermore, emotional data is reflected in the instructor's dashboard, enabling instructors to provide guidance based on the emotional state of students and workers.

[0615] Means of providing information to leaders

[0616] Providing information to leaders

[0617] The instructor logs into the administration panel and sends a request to the server.

[0618] The server retrieves the latest learning progress and sentiment data for each student and work device, and provides the instructor with aggregated dashboard data.

[0619] The device displays a dashboard, allowing instructors to see each student's learning progress and emotional state at a glance.

[0620] Hardware and software used

[0621] Hardware: Devices used by students or workers (PCs, tablets), cameras and microphones for using the emotion engine, and management terminals for instructors.

[0622] Software: Evaluation algorithms using Python, database management system, and real-time sentiment analysis software (EmotionEngine).

[0623] Examples of specific cases and prompt statements

[0624] Specific example

[0625] The emotion engine analyzed student A's facial expressions and voice data while they were taking the online test and determined that they were fatigued. Based on this result, the server displayed a message on student A's device prompting them to take a break and made adjustments to ensure that their learning progress was maintained appropriately.

[0626] Example of a prompt

[0627] "Create a program that evaluates students' emotional states based on the following data and generates an optimal learning program. Sensor data includes temperature, work time, etc."

[0628] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0629] Step 1:

[0630] When a user (student) logs in and accesses the academic achievement test page, the server displays the test start page. The input data is the student's login information, and the output data is the web page containing the test start button.

[0631] Step 2:

[0632] The user (student) clicks the test start button, and the server delivers the test questions. In this process, the input is the test start signal clicked by the student, and the output is the test questions.

[0633] Step 3:

[0634] The user (student) enters their answers to each test question and sends them from their terminal to the server. The input data is the student's answer information, and the output data is the answer result.

[0635] Step 4:

[0636] The server analyzes the received response data and evaluates the students' academic ability levels. The input data is the response data, and the output data is the evaluation of the students' academic ability. Specifically, it analyzes the accuracy rate of the answers and the response time.

[0637] Step 5:

[0638] The server generates an optimal individual curriculum for each student based on their academic performance evaluation results and past learning history data. The input data consists of academic performance evaluation results and past learning history data, while the output data is the generated individual curriculum.

[0639] Step 6:

[0640] When a user (student) logs in, the terminal receives and displays individual curriculum information provided by the server. The input data is curriculum information, and the output data is the displayed learning content.

[0641] Step 7:

[0642] Users (students) view the displayed learning content and materials and work on practice problems. Their progress is recorded in real time by the device and sent to the server. Input data consists of answers to practice problems and viewing history, while output data is the recorded progress.

[0643] Step 8:

[0644] The server analyzes the received progress data and evaluates the learning progress. The input data is the progress data, and the output data is the evaluated progress status.

[0645] Step 9:

[0646] The device collects facial expressions, voice, and behavioral data in real time during student learning and transmits it to the emotion engine. The input data is data related to the student's emotional state, and the output data is emotional data transmitted to the emotion engine.

[0647] Step 10:

[0648] The emotion engine analyzes received data to identify the student's emotional state. Input data includes facial expressions, voice, and behavioral data, while output data is the analyzed emotional state.

[0649] Step 11:

[0650] The server evaluates students' learning efficiency based on emotional data received from the emotion engine and dynamically adjusts the learning content and delivery method as needed. The input data is emotional data, and the output data is the adjusted learning content and delivery method.

[0651] Step 12:

[0652] The server displays the latest student learning progress and sentiment data on the instructor's dashboard. The input data consists of learning progress and sentiment data, while the output data is the aggregated data displayed on the dashboard.

[0653] Step 13:

[0654] Instructors monitor students' learning progress and emotional state through a dashboard and provide additional instruction as needed. Input data is the data displayed on the dashboard, while output data represents the additional instruction provided.

[0655] This generated processing step allows the system to provide students and workers with personalized learning and training, as well as appropriate guidance based on their emotional state in real time.

[0656] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0657] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0658] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0659] [Second Embodiment]

[0660] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0661] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0662] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0663] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0664] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0665] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0666] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0667] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0668] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0669] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0670] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0671] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0672] This invention relates to a system that provides customized education tailored to each student's academic ability and learning progress. This system operates through the collaboration of three entities: a server, terminals, and users (students and teachers). The following describes in detail how each entity functions.

[0673] Methods for assessing academic ability

[0674] The user (student) starts the test.

[0675] Device: Student A logs in and accesses the academic achievement test page. The device displays the "Start Test" button.

[0676] Implementation of academic achievement tests

[0677] User (student): Student A clicks the "Start Test" button.

[0678] Terminal: Retrieves academic achievement test questions from the server and displays them on the screen.

[0679] User (student): Student A enters their answers to each question.

[0680] Terminal: Temporarily saves responses and sends them to the server once all responses have been entered.

[0681] Analysis and transmission of test results

[0682] Server: Receives student A's answer data and calculates the correct answer rate for each question.

[0683] Server: Based on the analysis results, evaluate student A's academic level and save the data.

[0684] Individual Curriculum Generation Method

[0685] Curriculum generation

[0686] Server: Automatically generates an optimal learning curriculum for student A based on academic performance evaluation results and past learning history data.

[0687] Server: Saves the generated curriculum to the database.

[0688] Means of providing learning content

[0689] Distribution of curriculum and teaching materials

[0690] Terminal: Student A logs in and accesses their My Page. The server receives the My Page request and retrieves customized curriculum information for Student A.

[0691] Server: Sends curriculum information and corresponding teaching material data to the terminal.

[0692] Terminal: Displays the curriculum and teaching materials on the screen.

[0693] Learning progress

[0694] User (student): Student A views the learning materials and works on the practice problems.

[0695] Terminal: Saves student A's progress in real time.

[0696] Server: Records student A's learning progress data and updates learning materials as needed.

[0697] Learning progress evaluation method

[0698] Submission and evaluation of learning outcomes

[0699] User (student): Student A answers the practice questions and submits the results.

[0700] Terminal: Sends the response results to the server.

[0701] Server: Analyzes the response results, updates student A's learning progress, and saves the evaluation results.

[0702] Information provision means

[0703] Information provision to teachers

[0704] User (Teacher): Teacher B logs into the administration panel and accesses the dashboard.

[0705] Terminal: Sends the teacher's request to the server.

[0706] Server: Retrieves the latest learning progress data for each student and sends the aggregated dashboard data to the terminal.

[0707] Terminal: Display the dashboard so that Teacher B can see each student's learning progress at a glance.

[0708] Specific example

[0709] For example, if the server determines that student A's academic ability is at an "intermediate" level, the following will occur: The server will automatically generate a set of math practice problems and explanatory videos appropriate for the intermediate level and deliver them to the terminal. The user (student) will then use the provided materials to study and report their progress to the server. At the same time, teacher B will monitor student A's learning progress in real time through a dashboard and provide additional instruction as needed.

[0710] This system not only improves students' learning efficiency but also streamlines teachers' work and enables appropriate instruction for each individual student.

[0711] The following describes the processing flow.

[0712] Processing steps for academic ability assessment methods

[0713] Step 1:

[0714] Terminal: Student A logs in and accesses the academic achievement test page.

[0715] Terminal: Displays the button to start the academic ability assessment test.

[0716] Step 2:

[0717] User (student): Student A clicks the "Start Test" button.

[0718] Terminal: Retrieves academic achievement test questions from the server and displays them on the screen.

[0719] Step 3:

[0720] User (student): Student A enters their answers to each question.

[0721] Terminal: Temporarily saves response data.

[0722] Step 4:

[0723] User (student): Student A completes the test and clicks the submit button.

[0724] Terminal: Sends all responses to the server.

[0725] Step 5:

[0726] Server: Receives student A's answer data and calculates the correct answer rate for each question.

[0727] Step 6:

[0728] Server: Based on the analysis results, evaluate student A's academic level and save the data.

[0729] Processing steps of the individual curriculum generation means

[0730] Step 1:

[0731] Server: Automatically generates an individualized curriculum based on the academic performance evaluation results of student A.

[0732] Step 2:

[0733] Server: Optimizes curriculum content based on past learning history data.

[0734] Step 3:

[0735] Server: Saves the generated curriculum to the database.

[0736] Processing steps for learning content delivery methods

[0737] Step 1:

[0738] Terminal: Student A logs in and accesses their My Page.

[0739] Server: Receives a request for My Page and retrieves customized curriculum information for Student A.

[0740] Step 2:

[0741] Server: Sends curriculum information and corresponding teaching material data to the terminal.

[0742] Step 3:

[0743] Terminal: Displays the curriculum and teaching materials on the screen.

[0744] Step 4:

[0745] User (student): Student A views the learning materials and works on the practice problems.

[0746] Terminal: Saves student A's progress in real time.

[0747] Processing steps for learning progress evaluation means

[0748] Step 1:

[0749] User (student): Student A answers the practice questions and submits the results.

[0750] Terminal: Sends the response results to the server.

[0751] Step 2:

[0752] Server: Analyzes the response results and updates student A's learning progress.

[0753] Step 3:

[0754] Server: Saves the analysis results and adjusts the next learning content as needed.

[0755] Processing steps of information provision means

[0756] Step 1:

[0757] User (Teacher): Teacher B logs into the administration panel and accesses the dashboard.

[0758] Terminal: Sends the teacher's request to the server.

[0759] Step 2:

[0760] Server: Retrieves the latest learning progress data for each student.

[0761] Step 3:

[0762] Server: Sends the aggregated dashboard data to the terminal.

[0763] Step 4:

[0764] Terminal: Display the dashboard so that Teacher B can check the learning progress of each student.

[0765] (Example 1)

[0766] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0767] Traditional education systems struggle to provide appropriate curricula and materials tailored to each student's academic ability and learning progress, resulting in inefficient learning. Furthermore, there is a lack of sufficient information for teachers to monitor each student's learning progress in real time and provide necessary guidance.

[0768] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0769] In this invention, the server includes means for evaluating students' academic ability, means for generating individual curricula based on the academic ability evaluation results, means for providing learning content based on the generated individual curricula, means for recording and evaluating students' learning progress, means for providing information to instructors based on the generated individual curricula and learning progress, means for analyzing academic ability evaluation results and automatically generating curriculum and corresponding teaching material data, and means for recording students' learning activities and progress in real time and updating teaching materials as necessary. This enables the provision of an optimal learning plan for each individual, real-time monitoring of students' progress, and appropriate instruction.

[0770] The term "student" refers to a person who belongs to an educational institution and engages in learning.

[0771] "Academic ability assessment" refers to the process of measuring students' academic ability levels and evaluating their understanding and proficiency in learning.

[0772] "Means" refers to the methods or devices used to achieve a specific objective.

[0773] "Individualized curriculum" refers to a learning plan customized based on each student's academic ability and learning progress.

[0774] "Learning content" refers to educational materials such as textbooks, workbooks, and video explanations that students use for their studies.

[0775] "Learning progress" refers to data that indicates how far a student has progressed in their studies or their level of learning achievement.

[0776] The term "instructor" refers to someone who has the role of supporting students' learning and providing education.

[0777] A "server" refers to a computer system that provides services and data over a network.

[0778] "Terminal" refers to a device such as a computer or smartphone that is directly operated by the user.

[0779] An "online test" refers to a test for assessing academic ability that is conducted via the internet.

[0780] A "database" refers to a system used to efficiently store, search, and manage large amounts of data.

[0781] "Educational material data" refers to digital data of various educational materials used in learning.

[0782] "Analysis" refers to the process of analyzing data in detail and extracting information suitable for a specific purpose.

[0783] "Automatic generation" refers to the process by which a computer system automatically creates programs or data based on specific conditions.

[0784] "Real-time" refers to processing that occurs instantly without delay.

[0785] "Information provision" refers to the act of providing information to users for a specific purpose.

[0786] This invention relates to a system that provides customized education tailored to each student's academic ability and learning progress. This system operates through the collaboration of three entities: a server, terminals, and users (students and instructors). The following describes in detail how each entity functions.

[0787] Methods for assessing academic ability

[0788] The user (student) starts the test.

[0789] The user (student) logs into the system via their device and accesses the academic achievement test page. The device displays a "Start Test" button. When the student clicks the "Start Test" button, the device sends the request to the server.

[0790] Implementation of academic achievement tests

[0791] The server generates a set of questions for an academic assessment test and sends them to the terminal. The terminal displays the received test questions on its screen. The user (student) enters their answers to each question, and these answers are temporarily stored by the terminal. Once all answers have been entered, the terminal sends them back to the server.

[0792] Analysis and transmission of test results

[0793] Analysis of the answer results

[0794] The server receives student response data and calculates the correct answer rate for each question. Based on the analysis results, it evaluates the students' academic level and stores that data in a database.

[0795] Individual Curriculum Generation Method

[0796] Generating the optimal curriculum

[0797] The server retrieves students' academic performance evaluation results and past learning history data, and generates an optimal learning curriculum based on this data. The generated curriculum is stored in a database.

[0798] Means of providing learning content

[0799] Curriculum and material provision

[0800] When a user (student) accesses their My Page, the device sends a request to the server. The server retrieves customized curriculum information and corresponding learning materials for the student and sends them to the device. The device then displays the curriculum and learning materials on its screen.

[0801] Learning progress

[0802] Record of learning activities

[0803] Users (students) view learning materials and work on practice problems. The device saves the user's learning activities and progress in real time. The server periodically collects learning progress data and updates the learning materials as needed.

[0804] Learning progress evaluation method

[0805] Evaluation and recording of results

[0806] Users (students) input their answers to practice problems and send the results to the server via their terminal. The server analyzes the answers and evaluates the student's learning progress. The evaluation results are stored in a database.

[0807] Information provision means

[0808] Dashboard display

[0809] When a user (instructor) logs into the administration panel and accesses the dashboard, the device sends a request to the server. The server retrieves the latest learning progress data for each student, aggregates it, and sends it to the device. The device then displays the dashboard, allowing instructors to monitor each student's learning status in real time.

[0810] Examples of specific actions

[0811] For example, if the server determines a student's academic performance to be "intermediate," it automatically generates a set of math practice problems and explanatory videos appropriate for that level and delivers them to the student's device. The user (student) then uses the provided materials to learn and reports their progress to the server. Simultaneously, the instructor monitors the student's learning progress in real time via a dashboard and provides additional instruction as needed.

[0812] Example of a prompt

[0813] "Use this system to assess students' academic abilities and generate individualized curricula. Furthermore, explain how to provide students with learning materials based on those curricula and how to monitor their learning progress in real time."

[0814] This system not only improves students' learning efficiency but also streamlines instructors' work and enables appropriate instruction for each individual student.

[0815] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0816] Step 1:

[0817] The user (student) starts the test.

[0818] Input: The student logs into the system.

[0819] Device operation: Display the student's personal page and present a link to the academic achievement test.

[0820] User (student) action: Click the link for the academic achievement test and press the "Start Test" button.

[0821] Terminal action: Sends a test start request to the server.

[0822] Output: A request for the academic achievement test is sent to the server.

[0823] Step 2:

[0824] Implementation of academic achievement tests

[0825] Input: Test start request.

[0826] Server operation: Generates a set of questions for the academic achievement test and sends them to the terminal.

[0827] Device operation: Displays the received test questions on the screen.

[0828] User (student) action: Enter answers for each question.

[0829] Terminal operation: The user's responses are temporarily stored, and once all responses have been entered, they are sent to the server.

[0830] Output: Student response data is sent to the server.

[0831] Step 3:

[0832] Analysis and transmission of test results

[0833] Input: Student response data.

[0834] Server operation: Receives response data and calculates the correct answer rate for each question.

[0835] Data processing: Extract the number of correct answers from the response data and calculate the correct answer rate by dividing it by the total number of questions.

[0836] Server operation: Based on the analysis results, the system evaluates students' academic levels and saves that data to a database.

[0837] Output: Academic performance evaluation results are saved to the database.

[0838] Step 4:

[0839] Generating the optimal curriculum

[0840] Input: Academic performance evaluation results and past learning history data.

[0841] Server operation: Retrieves students' academic performance evaluation results and past learning history data.

[0842] Data processing: Analyze academic performance evaluation results and past data to generate an optimal learning plan.

[0843] Server operation: Generates the optimal learning curriculum and saves it to the database.

[0844] Output: The generated curriculum is saved to the database.

[0845] Step 5:

[0846] Curriculum and material provision

[0847] Input: Student access request.

[0848] User (student) action: Accesses My Page.

[0849] Terminal action: Sends a request to the server.

[0850] Server operation: Retrieves customized curriculum information and corresponding teaching material data, and sends it to the terminal.

[0851] Device operation: Displays the curriculum and learning materials on the screen.

[0852] Output: Customized curriculum and materials are displayed to students.

[0853] Step 6:

[0854] Record of learning activities

[0855] Input: Student learning activities.

[0856] User (student) actions: View learning materials and work on practice problems.

[0857] Device operation: Records learning activities and progress in real time.

[0858] Server operation: Regularly collects learning progress data and updates learning materials as needed.

[0859] Output: Learning progress data is saved to the server.

[0860] Step 7:

[0861] Evaluation and recording of results

[0862] Input: Student practice problem answer data.

[0863] User (student) action: Enter answers to practice problems and send the results to the server.

[0864] Terminal operation: Sends the response results to the server.

[0865] Server operation: Analyzes the response results and evaluates the students' learning progress.

[0866] Data processing: Analyze the response data and calculate the accuracy rate and the degree of achievement of learning objectives.

[0867] Server operation: Save evaluation results to the database.

[0868] Output: Learning progress evaluation data is saved to the database.

[0869] Step 8:

[0870] Dashboard display

[0871] Input: Instructor access request.

[0872] User (instructor) action: Log in to the administration screen and access the dashboard.

[0873] Terminal operation: Sends an access request to the dashboard to the server.

[0874] Server operation: The server retrieves the latest learning progress data for each student and sends the aggregated data to the terminal.

[0875] Device operation: Displays a dashboard, allowing instructors to see each student's learning progress at a glance.

[0876] Output: Learning progress is displayed on the dashboard.

[0877] As described above, this system efficiently processes each step and provides an optimal educational environment for students and instructors.

[0878] (Application Example 1)

[0879] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0880] Traditional factory worker training systems offer a uniform training program, making it difficult to customize the program to suit the individual skill levels and progress of each worker. Therefore, there is a need to provide an optimal training program for each worker to efficiently promote skill acquisition. Furthermore, progress management and evaluation are often done manually, placing a heavy burden on supervisors.

[0881] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0882] In this invention, the server includes means for performing a worker's technical evaluation, means for generating an individualized training program based on the technical evaluation results, means for providing training content based on the generated individualized training program, means for recording and evaluating the worker's progress, and means for providing information to the supervisor based on the generated individualized training program and progress. This enables the provision of customized training programs tailored to each worker's technical level and progress, as well as automated management and evaluation of progress.

[0883] A "worker" refers to a person who works in a factory or manufacturing industry and performs tasks using specific skills and techniques.

[0884] "Technical evaluation" refers to the process of measuring the skill and knowledge level of workers and collecting information necessary to provide appropriate training programs.

[0885] An "individualized training program" refers to training content that is customized based on the worker's technical evaluation results and according to the skills and knowledge that the worker needs to acquire.

[0886] "Training content" refers to educational materials and tools that workers use to learn skills and knowledge according to their individual training programs.

[0887] "Progress" refers to the state or status of how far an employee is progressing toward the goals in a training program.

[0888] A "supervisor" is a person whose role is to manage the training and progress and results of workers' daily work, and to provide guidance and advice as needed.

[0889] This invention relates to a system that provides customized training programs tailored to the skills and progress of each individual worker in a factory. This system operates through the collaboration of three entities: a server, terminals, and users (workers and supervisors). The following describes in detail how each entity functions.

[0890] Technical evaluation methods

[0891] The user (worker) starts the evaluation test.

[0892] Terminal: Worker A logs in and accesses the technical evaluation test page. The terminal displays the "Start Test" button.

[0893] Implementation of technical evaluation tests

[0894] User (worker): Worker A clicks the Start Test button.

[0895] Terminal: Retrieves technical evaluation test questions from the server and displays them on the screen.

[0896] User (worker): Worker A enters the answers to each question.

[0897] Terminal: Temporarily saves responses and sends them to the server once all responses have been entered.

[0898] Analysis and transmission of test results

[0899] Server: Receives worker A's response data and calculates the correct answer rate for each question.

[0900] Server: Based on the analysis results, evaluate the skill level of worker A and save the data.

[0901] Individual training program generation method

[0902] Training program generation

[0903] Server: Automatically generates the optimal training program for worker A based on technical evaluation results and past training history data.

[0904] Server: Saves the generated training program to the database.

[0905] Training content delivery methods

[0906] Distribution of training programs and materials

[0907] Terminal: Worker A logs in and accesses their My Page. The server receives the My Page request and retrieves customized training program information for Worker A.

[0908] Server: Sends training program information and corresponding training material data to the terminal.

[0909] Terminal: Displays the training program and materials on the screen.

[0910] Training progress

[0911] User (worker): Worker A views the training materials and works on the practice problems.

[0912] Terminal: Saves the progress of worker A in real time.

[0913] Server: Records worker A's training progress data and updates training materials as needed.

[0914] Progress evaluation methods

[0915] Submission and evaluation of training results

[0916] User (worker): Worker A answers the practice questions and submits the results.

[0917] Terminal: Sends the response results to the server.

[0918] Server: Analyzes the response results, updates worker A's training progress, and saves the evaluation results.

[0919] Information provision means

[0920] Information provided to supervisors

[0921] User (Supervisor): Supervisor B logs into the administration panel and accesses the dashboard.

[0922] Terminal: Sends the supervisor's request to the server.

[0923] Server: Retrieves the latest training progress data for each worker and sends the aggregated dashboard data to the terminal.

[0924] Terminal: Displays a dashboard, allowing supervisor B to see each worker's training status at a glance.

[0925] This system enables training tailored to each worker's skill level and progress, facilitating efficient skill acquisition and progress management. For example, when a new employee, worker A, begins training on the factory floor, an initial evaluation test is conducted, and their skill level is assessed as "intermediate." Based on this result, an intermediate-level training program is automatically generated and delivered to their terminal. Worker A acquires skills according to the provided program, and once their progress exceeds 50%, a new evaluation test is conducted to reassess their skill level. In this way, worker A can efficiently improve their skills.

[0926] Examples of prompts to input into a generative AI model:

[0927] When new employees begin on-site training at the factory, the training system is used in the following manner: First, an initial assessment test is administered, and their skill level is evaluated as "intermediate." Based on this result, an intermediate-level training program is automatically generated and delivered to their terminal. The worker acquires skills according to the provided program, and their progress is recorded in the system in real time. When progress exceeds 50%, a new assessment test is administered to re-evaluate their skill level. In this way, workers can efficiently improve their technical skills.

[0928] This system operates via a Python program and can be accessed using a smartphone or tablet. A Python environment is required on the server for evaluation, analysis, and data storage. This system enables improved individual worker skills and efficient management.

[0929] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0930] Step 1:

[0931] The user (worker) starts the evaluation test.

[0932] Input: The worker logs into the terminal and accesses the evaluation test page.

[0933] Specific operation: The terminal displays a "Start Test" button to the operator. When operator A clicks this button, the terminal requests the server to start the test.

[0934] Output: A request to start the evaluation test is sent to the server.

[0935] Step 2:

[0936] The server provides the evaluation test questions.

[0937] Input: The server receives a request to start the evaluation test.

[0938] Specific operation: The server retrieves the set of assessment test questions from the database and sends them to the terminal.

[0939] Output: The evaluation test questions are displayed on the terminal.

[0940] Step 3:

[0941] The user (worker) conducts the evaluation test.

[0942] Input: Worker A enters the answers to the test questions.

[0943] Specific operation: The terminal temporarily stores each answer entered by worker A, and once all answers have been entered, it sends that data to the server.

[0944] Output: Worker A's response data is sent to the server.

[0945] Step 4:

[0946] The server analyzes the test results.

[0947] Input: The server receives the response data from worker A.

[0948] Specific operation: The server calculates the accuracy rate for each problem and evaluates the skill level of worker A. The evaluation results are saved to the database.

[0949] Output: The technical skill level evaluation results for worker A are saved to the database.

[0950] Step 5:

[0951] The server generates individual training programs.

[0952] Input: The server retrieves technical evaluation results and historical training data.

[0953] Specific operation: Based on this data, the server automatically generates the optimal training program for worker A. The generated training program is saved to the database.

[0954] Output: Individual training programs are saved to the database.

[0955] Step 6:

[0956] The server provides the training program.

[0957] Input: Worker A logs into the terminal and accesses their My Page.

[0958] Specific operation: The server receives a request for My Page and sends customized training program information to worker A's terminal.

[0959] Output: Customized training program information is displayed on the terminal.

[0960] Step 7:

[0961] The user (worker) takes the training.

[0962] Input: Worker A answers practice problems according to the training program.

[0963] Specific operation: The terminal saves worker A's progress in real time and sends that data to the server.

[0964] Output: Worker A's progress data is saved to the server.

[0965] Step 8:

[0966] The server evaluates and updates the progress.

[0967] Input: The server receives progress data for worker A.

[0968] Specific operation: The server analyzes the progress data, updates worker A's training progress, and saves the evaluation results to the database.

[0969] Output: The updated progress evaluation data is saved to the database.

[0970] Step 9:

[0971] The server provides information to the supervisor.

[0972] Input: Supervisor B logs into the administration panel and accesses the dashboard.

[0973] Specific operation: The server retrieves the latest training progress data for each worker and sends the aggregated dashboard data to the terminal.

[0974] Output: Supervisor dashboard data is displayed on the terminal.

[0975] This processing flow allows each worker to receive the most appropriate technical training, and supervisors can evaluate and manage their progress in real time.

[0976] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0977] This invention relates to a system that provides customized education tailored to each student's academic ability, learning progress, and emotional state. This system operates through the collaboration of four entities: a server, terminals, users (students and teachers), and an emotion engine. The following describes in detail how each entity functions.

[0978] Methods for assessing academic ability and methods for generating individual curricula

[0979] Methods for assessing academic ability

[0980] Device: Student A logs in and accesses the academic achievement test page. The device displays the "Start Test" button.

[0981] User (student): Student A clicks the "Start Test" button, and the server displays the test questions.

[0982] User (student): Student A enters their answers to each question and sends the results from their terminal to the server.

[0983] Server: Analyzes the response data, evaluates student A's academic level, and saves the results.

[0984] Individual Curriculum Generation Method

[0985] Server: Automatically generates an optimal learning curriculum for student A based on academic performance evaluation results and past learning history data.

[0986] Server: Saves the generated curriculum to the database.

[0987] Means of providing learning content and means of evaluating learning progress

[0988] Means of providing learning content

[0989] Terminal: Student A logs in and accesses their My Page. The server retrieves customized curriculum information and delivers it to Student A.

[0990] Terminal: The curriculum and learning materials are displayed on the screen, and student A learns based on them.

[0991] User (Student): Student A views the learning materials and works on practice problems. The device saves their progress in real time.

[0992] Learning progress evaluation method

[0993] User (student): Student A answers a practice problem and sends the result from their terminal to the server.

[0994] Server: Analyzes the response results, updates student A's learning progress, and saves the evaluation results.

[0995] Emotion engines and the use of emotional data

[0996] How the emotion engine works

[0997] Device: When students are learning, data such as their facial expressions, voice, and behavior are collected in real time and sent to the emotion engine.

[0998] Emotion Engine: Analyzes received data to identify the student's emotional state (e.g., excitement, concentration, fatigue, indifference).

[0999] Use of emotional data

[1000] Server: Based on emotional data received from the emotion engine, it evaluates students' learning efficiency and dynamically adjusts learning content and delivery methods as needed.

[1001] Server: Reflect emotion data on the teacher's dashboard, enabling teachers to provide instruction based on students' emotional states.

[1002] Information provision means

[1003] Information provision to teachers

[1004] User (Teacher): Teacher B logs into the administration panel and accesses the dashboard.

[1005] Terminal: Sends the teacher's request to the server.

[1006] Server: Retrieves the latest learning progress and sentiment data for each student and sends the aggregated dashboard data to the terminal.

[1007] Terminal: Displays a dashboard, allowing teacher B to see each student's learning progress and emotional state at a glance.

[1008] Specific example

[1009] For example, if the server determines that student A's academic performance is "intermediate" and the emotion engine recognizes student A's emotional state as "focused," the system will operate as follows: The server generates a set of practice problems and explanatory videos appropriate for the intermediate level and delivers them to the terminal. Accordingly, the user (student) uses the provided materials to study and reports their progress and emotional state to the server. Meanwhile, teacher B monitors student A's learning progress and emotional state in real time through a dashboard and provides additional instruction as needed.

[1010] This system not only improves students' learning efficiency but also streamlines teachers' work and enables appropriate instruction for each individual student. By taking students' emotional states into consideration, it allows for more personalized and appropriate education.

[1011] The following describes the processing flow.

[1012] Processing steps for academic ability assessment methods

[1013] Step 1:

[1014] Device: Student A logs in and accesses the academic achievement test page. The device displays a button to start the academic achievement test.

[1015] Step 2:

[1016] User (student): Student A clicks the "Start Test" button. The device sends a request to the server to retrieve the test questions.

[1017] Step 3:

[1018] Server: Sends the academic achievement test questions to the terminal.

[1019] Step 4:

[1020] Terminal: Displays the acquired test questions on the screen.

[1021] Step 5:

[1022] User (student): Student A answers each question and enters the answer data.

[1023] Step 6:

[1024] Terminal: Temporarily saves the entered response data.

[1025] Step 7:

[1026] User (student): Student A completes the test and clicks the submit button.

[1027] Step 8:

[1028] Terminal: Sends all response data to the server.

[1029] Step 9:

[1030] Server: Receives student A's answer data and calculates the correct answer rate for each question.

[1031] Step 10:

[1032] Server: Based on the analysis results, evaluate student A's academic level and save the data.

[1033] Processing steps of the individual curriculum generation means

[1034] Step 1:

[1035] Server: Receives student A's academic performance evaluation results and starts the curriculum generation process.

[1036] Step 2:

[1037] Server: Retrieves past learning history data from the database and integrates it with current academic performance evaluation results.

[1038] Step 3:

[1039] Server: Based on integrated data, it automatically generates the optimal learning curriculum for student A.

[1040] Step 4:

[1041] Server: Saves the generated curriculum to the database.

[1042] Processing steps for learning content delivery methods

[1043] Step 1:

[1044] Terminal: Student A logs in and accesses their My Page.

[1045] Step 2:

[1046] Server: Receives a request for My Page and retrieves customized curriculum information for Student A.

[1047] Step 3:

[1048] Server: Searches for curriculum information and corresponding teaching material data, and sends it to the terminal.

[1049] Step 4:

[1050] Terminal: Displays the curriculum and teaching materials on the screen.

[1051] Step 5:

[1052] User (student): Student A views the learning materials and works on the practice problems.

[1053] Step 6:

[1054] Terminal: Saves student A's progress in real time.

[1055] Processing steps for learning progress evaluation means

[1056] Step 1:

[1057] User (student): Student A answers the practice questions and saves the results to their device.

[1058] Step 2:

[1059] Terminal: Sends the response results to the server.

[1060] Step 3:

[1061] Server: Analyzes the submitted response data and updates student A's learning progress.

[1062] Step 4:

[1063] Server: Saves updated progress data to the database.

[1064] Emotion engine and processing steps for using emotional data

[1065] Step 1:

[1066] Device: Sensors collect data such as students' facial expressions, voices, and behaviors while they are learning, and transmit this data to the emotion engine.

[1067] Step 2:

[1068] Emotion Engine: Analyzes received data to identify the student's emotional state (e.g., excitement, concentration, fatigue, indifference, etc.).

[1069] Step 3:

[1070] Emotion Engine: Sends emotional state data to the server.

[1071] Step 4:

[1072] Server: Based on emotional data, evaluate student A's learning efficiency and adjust the content delivery method as needed.

[1073] Step 5:

[1074] Server: Reflect emotion data on the teacher's dashboard, enabling teachers to provide instruction based on students' emotional states.

[1075] Processing steps of information provision means

[1076] Step 1:

[1077] User (Teacher): Teacher B logs into the administration panel and accesses the dashboard.

[1078] Step 2:

[1079] Terminal: Sends the teacher's request to the server.

[1080] Step 3:

[1081] Server: Retrieves the latest learning progress and sentiment data for each student and sends the aggregated dashboard data to the terminal.

[1082] Step 4:

[1083] Terminal: Displays a dashboard, allowing Teacher B to check each student's learning progress and emotional state.

[1084] This system not only improves students' learning efficiency but also streamlines teachers' work and enables appropriate instruction for each individual student. Furthermore, by considering students' emotional states through the emotion engine, it can provide more individualized and appropriate education.

[1085] (Example 2)

[1086] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[1087] Traditional education systems have struggled to provide individualized curricula based on each student's academic ability and learning progress. Furthermore, they were unable to grasp students' emotional states in real time and use that information to improve learning efficiency or provide appropriate guidance. Therefore, providing students with the optimal learning environment was difficult.

[1088] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for evaluating students' academic ability, means for generating individual curricula based on the academic ability evaluation results, means for providing learning content based on the generated individual curricula, means for recording and evaluating students' learning progress, means for analyzing students' emotional state, and means for providing information to teachers based on the generated individual curricula, learning progress, and emotional state. This makes it possible to provide an optimal learning environment tailored to each student's academic ability, learning progress, and emotional state.

[1089] "Methods for evaluating academic ability" refer to functions for measuring and evaluating students' academic abilities.

[1090] The "individualized curriculum generation method" is a function that automatically creates an optimal learning curriculum for each student based on the results of academic performance assessments and past learning history.

[1091] "Learning content delivery method" refers to a function that provides learning materials and practice problems tailored to each student's needs, based on the generated individual curriculum, to their device.

[1092] A "learning progress evaluation tool" is a function for recording students' learning activities and evaluating their progress.

[1093] The "emotional state analysis method" is a function that analyzes students' facial expressions, voice, and behavior to grasp their emotional state in real time during learning.

[1094] "Information provision means" refers to a function that provides teachers with necessary information in a timely manner based on the generated individual curriculum, learning progress, and emotional state.

[1095] This invention relates to a system that provides customized education tailored to each student's academic ability, learning progress, and emotional state. This system operates through the coordinated efforts of four entities: a server, terminals, users (students and teachers), and an emotion engine.

[1096] Methods for assessing academic ability and methods for generating individual curricula

[1097] Methods for assessing academic ability

[1098] Device: The student logs in and accesses the academic achievement test page. The device displays a button to start the test.

[1099] User (student): When a student clicks the "Start Test" button, the server displays the test questions on their device.

[1100] User (student): The student answers each question and sends the answer data from their device to the server.

[1101] Server: The server analyzes the response data, evaluates the students' academic level, and saves the results.

[1102] Individual Curriculum Generation Method

[1103] Server: Based on academic performance evaluation results and past learning history data, it uses a generative AI model to automatically generate the optimal learning curriculum for each student.

[1104] Server: Saves the generated curriculum to the database.

[1105] Means of providing learning content and means of evaluating learning progress

[1106] Means of providing learning content

[1107] Device: When a student logs in and accesses their My Page, the server retrieves customized curriculum information and sends it to the device.

[1108] Terminal: Displays the curriculum and learning materials on the screen, allowing students to learn based on them.

[1109] Learning progress evaluation method

[1110] User (student): The student answers the practice questions and sends the results from their device to the server.

[1111] Server: The server analyzes the response results, updates the students' learning progress, and saves the evaluation results.

[1112] Emotion engines and the use of emotional data

[1113] How the emotion engine works

[1114] Device: Collects data such as facial expressions, voice, and behavior in real time as students learn, and sends it to the emotion engine.

[1115] Emotional Engine: Analyzes received data to identify the student's emotional state. For example, it analyzes excitement, concentration, fatigue, apathy, etc.

[1116] Use of emotional data

[1117] Server: Based on emotional data received from the emotion engine, it evaluates students' learning efficiency and dynamically adjusts learning content and delivery methods as needed.

[1118] Server: Emotional data is also sent to a teacher dashboard, enabling teachers to provide instruction based on students' emotional states.

[1119] Information provision means

[1120] Information provision to teachers

[1121] User (Teacher): The teacher logs into the administration panel and accesses the dashboard.

[1122] Terminal: Sends the teacher's request to the server.

[1123] Server: Retrieves the latest learning progress and sentiment data for each student and sends the aggregated dashboard data to the terminal.

[1124] Device: Displays a dashboard that allows teachers to see each student's learning progress and emotional state at a glance.

[1125] Specific example

[1126] For example, the following describes the process when the server determines a student's academic performance to be "intermediate" and the emotion engine recognizes the student's emotional state as "focused." The server generates a set of practice problems and explanatory videos appropriate for the intermediate level and delivers them to the student's device. The student then uses the provided materials to study and reports their progress and emotional state to the server. Meanwhile, the teacher monitors the student's learning progress and emotional state in real time through a dashboard and provides additional instruction as needed.

[1127] Example of a prompt

[1128] Examples of prompt statements to input into the generative AI model are shown below.

[1129] Prompt: If a student's academic performance is assessed as "intermediate" and the emotional engine recognizes them as "focused," please describe the specific processing steps for generating individualized curricula and utilizing emotional data.

[1130] In this way, this system can provide each student with an optimal learning environment and improve learning efficiency.

[1131] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1132] Step 1:

[1133] Input: Student login information (username and password)

[1134] Process: The student enters their authentication information on the login screen.

[1135] Terminal: The terminal sends login information to the server.

[1136] Server: The server verifies the authentication information, and if authentication is successful, redirects the user to their My Page.

[1137] Output: Login success status and My Page URL

[1138] Step 2:

[1139] Input: URL of the student's academic assessment test page after successful login

[1140] Process: The student accesses the academic achievement test page.

[1141] Terminal: The terminal displays a button to start the test.

[1142] Output: Start Test button

[1143] Step 3:

[1144] Input: Click event of the test start button

[1145] Process: The student clicks the "Start Test" button.

[1146] User (student): The student clicks the "Start Test" button.

[1147] Server: The server sends the academic achievement test questions to the terminals.

[1148] Output: Questions from the academic achievement test

[1149] Step 4:

[1150] Input: Answer data for each question (text, multiple choice)

[1151] Processing: Students answer each question and input the answer data.

[1152] Terminal: The terminal sends the response data to the server.

[1153] User (student): The student answers each question.

[1154] Output: Response data

[1155] Step 5:

[1156] Input: Submitted response data

[1157] Processing: The server receives the response data and runs an analysis algorithm to evaluate the students' academic level.

[1158] Server: The server analyzes the response data, evaluates the academic level, and stores it in a database.

[1159] Output: Academic performance evaluation results

[1160] Step 6:

[1161] Input: Academic performance evaluation results and past learning history data

[1162] Processing: Based on academic performance assessment results and past learning history data, a generative AI model is used to automatically generate the optimal learning curriculum for each student.

[1163] Server: The server retrieves academic performance evaluation results and past learning history from the database and automatically generates the curriculum.

[1164] Output: Generated learning curriculum

[1165] Step 7:

[1166] Input: Generated learning curriculum

[1167] Process: Save the generated curriculum to the database.

[1168] Server: The server saves the generated curriculum to the database.

[1169] Output: Saved curriculum

[1170] Step 8:

[1171] Input: Access to the student's My Page

[1172] Processing: After the student logs in, they access their My Page.

[1173] Terminal: The terminal sends a request to the server to access the My Page.

[1174] Server: The server retrieves customized curriculum information from the database and sends it to the terminal.

[1175] Output: Customized curriculum information

[1176] Step 9:

[1177] Input: Customized curriculum information

[1178] Processing: The curriculum and learning materials are displayed on the screen, and students learn based on them.

[1179] Terminal: The terminal displays the curriculum and learning materials on its screen.

[1180] Output: Displayed curriculum and materials

[1181] Step 10:

[1182] Input: Data used by students to answer practice problems.

[1183] Processing: Students answer practice problems, and their progress is saved in real time on their devices.

[1184] Terminal: The terminal sends progress data to the server.

[1185] Output: Sending progress data

[1186] Step 11:

[1187] Input: Submitted practice problem answer data

[1188] Processing: The server analyzes the response results and updates the students' learning progress.

[1189] Server: The server saves the analysis progress data to the database.

[1190] Output: Updated progress data

[1191] Step 12:

[1192] Input: Student facial expressions, voice, and behavioral data during learning.

[1193] Processing: Data such as facial expressions, voice, and behavior are collected in real time as students learn and sent to the emotion engine.

[1194] Device: The device sends the collected data to the emotion engine.

[1195] Output: Sent sentiment data

[1196] Step 13:

[1197] Input: Emotional data analyzed by the emotion engine

[1198] Processing: The emotion engine analyzes the received data to identify the student's emotional state. For example, it analyzes excitement, concentration, fatigue, apathy, etc.

[1199] Emotional Engine: Analyzes emotional states.

[1200] Output: Emotional state data from the analysis results

[1201] Step 14:

[1202] Input: Emotion engine analysis results and student learning progress data

[1203] Processing: The server evaluates learning efficiency based on sentiment data and dynamically adjusts the learning content and delivery method as needed.

[1204] Server: Saves the adjusted learning content to the database.

[1205] Output: Adjusted learning content

[1206] Step 15:

[1207] Input: Adjusted learning content and emotional state data

[1208] Processing: The server reflects the information on the teacher's dashboard.

[1209] Server: Generates teacher dashboard data and sends it to the terminal.

[1210] Output: Sending dashboard data

[1211] Step 16:

[1212] Input: Generated dashboard data

[1213] Process: The teacher logs into the administration panel and accesses the dashboard.

[1214] Device: Displays a dashboard, allowing teachers to monitor each student's learning progress and emotional state.

[1215] Output: Displayed dashboard

[1216] (Application Example 2)

[1217] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[1218] Conventional education systems and work equipment management systems require flexible responses tailored to the individual academic abilities, efficiency, and progress of students and work equipment. In particular, it is difficult to consider real-time factors such as emotions and fatigue, which can lead to delays in providing appropriate learning and training. Furthermore, it is difficult for instructors to provide accurate guidance based on the individual's condition. The objective of this invention is to solve these problems and provide an efficient and effective education and training system.

[1219] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1220] In this invention, the server includes means for evaluating students' academic abilities, means for generating individual curricula based on the academic ability evaluation results, means for providing learning content based on the generated individual curricula, means for recording and evaluating students' learning progress, means for providing information to instructors based on the generated individual curricula and learning progress, means for collecting and evaluating the work efficiency and historical data of work equipment, means for generating training programs based on the evaluation results, means for analyzing the emotional state of work equipment, and means for providing information to instructors based on the emotional state and training program. This enables flexible and effective education and training based on the individual learning status and state of students and work equipment.

[1221] "Methods for evaluating academic ability" refer to systems or methods designed to assess students' academic abilities.

[1222] "Individualized curriculum generation means" refers to a system or method that automatically generates an optimal curriculum for a specific student based on the results of an academic performance assessment.

[1223] "Means of providing learning content" refers to a system or method that provides students with appropriate learning materials and problems based on a generated individual curriculum.

[1224] A "learning progress recording and evaluation means" is a system or method for recording students' learning status and evaluating their progress.

[1225] "Instructor information provision means" refers to a system or method that provides instructors with necessary information based on the generated individual curriculum and learning progress.

[1226] A "means for evaluating the work efficiency of work equipment" refers to a system or method for collecting and evaluating the work efficiency and historical data of work equipment.

[1227] "Training program generation means" refers to a system or method that generates an optimal training program based on the evaluation results of work equipment.

[1228] "Emotional state analysis means" refers to a system or method for analyzing the emotional state of work equipment and workers and collecting the data.

[1229] This invention provides a system that offers optimal education and training programs based on the individual academic abilities, work efficiency, and progress of students and work equipment. This system operates through the coordinated efforts of four entities: a server, terminals, users (students, workers, instructors), and an emotion engine.

[1230] System-wide configuration

[1231] The server includes means for evaluating academic ability, generating individual curricula, providing learning content, recording and evaluating learning progress, providing instructor information, evaluating the work efficiency of work equipment, generating training programs, and analyzing emotional states. By using this system, flexible and effective education and training based on the individual circumstances of students and work equipment becomes possible.

[1232] Methods for assessing academic ability and methods for generating individual curricula

[1233] Methods for assessing academic ability

[1234] Students' academic abilities will be assessed through online tests conducted via their devices.

[1235] The user (student) clicks the "Start Test" button and answers the questions presented by the server.

[1236] The server analyzes the response data, evaluates the academic level, and saves the results.

[1237] Individual Curriculum Generation Method

[1238] The server generates an optimal individual curriculum for each student based on their academic performance evaluation results and past learning history data.

[1239] The generated curriculum is stored in a database.

[1240] Means for providing learning content and means for recording and evaluating learning progress

[1241] Means of providing learning content

[1242] Students log in via their devices, and the server delivers customized curriculum information.

[1243] The device displays the provided curriculum and learning materials on its screen, and the user (student) learns based on them.

[1244] Learning progress recording and evaluation method

[1245] Users (students) view learning materials and work on practice problems.

[1246] The progress is recorded in real time by the device and sent to the server.

[1247] The server analyzes the response results, updates the learning progress, and saves the evaluation results.

[1248] Emotion engines and the use of emotional data

[1249] How the emotion engine works

[1250] The device collects facial expressions, voices, and behavioral data of students and workers in real time and transmits them to the emotion engine.

[1251] The emotion engine analyzes incoming data to identify emotional states (e.g., excitement, concentration, fatigue, indifference, etc.).

[1252] Use of emotional data

[1253] Based on emotional data received from the emotion engine, the server evaluates the learning and work efficiency of students and workers, and dynamically adjusts the learning and training content as needed.

[1254] Furthermore, emotional data is reflected in the instructor's dashboard, enabling instructors to provide guidance based on the emotional state of students and workers.

[1255] Means of providing information to leaders

[1256] Providing information to leaders

[1257] The instructor logs into the administration panel and sends a request to the server.

[1258] The server retrieves the latest learning progress and sentiment data for each student and work device, and provides the instructor with aggregated dashboard data.

[1259] The device displays a dashboard, allowing instructors to see each student's learning progress and emotional state at a glance.

[1260] Hardware and software used

[1261] Hardware: Devices used by students or workers (PCs, tablets), cameras and microphones for using the emotion engine, and management terminals for instructors.

[1262] Software: Evaluation algorithms using Python, database management system, and real-time sentiment analysis software (EmotionEngine).

[1263] Examples of specific cases and prompt statements

[1264] Specific example

[1265] The emotion engine analyzed student A's facial expressions and voice data while they were taking the online test and determined that they were fatigued. Based on this result, the server displayed a message on student A's device prompting them to take a break and made adjustments to ensure that their learning progress was maintained appropriately.

[1266] Example of a prompt

[1267] "Create a program that evaluates students' emotional states based on the following data and generates an optimal learning program. Sensor data includes temperature, work time, etc."

[1268] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1269] Step 1:

[1270] When a user (student) logs in and accesses the academic achievement test page, the server displays the test start page. The input data is the student's login information, and the output data is the web page containing the test start button.

[1271] Step 2:

[1272] The user (student) clicks the test start button, and the server delivers the test questions. In this process, the input is the test start signal clicked by the student, and the output is the test questions.

[1273] Step 3:

[1274] The user (student) enters their answers to each test question and sends them from their terminal to the server. The input data is the student's answer information, and the output data is the answer result.

[1275] Step 4:

[1276] The server analyzes the received response data and evaluates the students' academic ability levels. The input data is the response data, and the output data is the evaluation of the students' academic ability. Specifically, it analyzes the accuracy rate of the answers and the response time.

[1277] Step 5:

[1278] The server generates an optimal individual curriculum for each student based on their academic performance evaluation results and past learning history data. The input data consists of academic performance evaluation results and past learning history data, while the output data is the generated individual curriculum.

[1279] Step 6:

[1280] When a user (student) logs in, the terminal receives and displays individual curriculum information provided by the server. The input data is curriculum information, and the output data is the displayed learning content.

[1281] Step 7:

[1282] Users (students) view the displayed learning content and materials and work on practice problems. Their progress is recorded in real time by the device and sent to the server. Input data consists of answers to practice problems and viewing history, while output data is the recorded progress.

[1283] Step 8:

[1284] The server analyzes the received progress data and evaluates the learning progress. The input data is the progress data, and the output data is the evaluated progress status.

[1285] Step 9:

[1286] The device collects facial expressions, voice, and behavioral data in real time during student learning and transmits it to the emotion engine. The input data is data related to the student's emotional state, and the output data is emotional data transmitted to the emotion engine.

[1287] Step 10:

[1288] The emotion engine analyzes received data to identify the student's emotional state. Input data includes facial expressions, voice, and behavioral data, while output data is the analyzed emotional state.

[1289] Step 11:

[1290] The server evaluates students' learning efficiency based on emotional data received from the emotion engine and dynamically adjusts the learning content and delivery method as needed. The input data is emotional data, and the output data is the adjusted learning content and delivery method.

[1291] Step 12:

[1292] The server displays the latest student learning progress and sentiment data on the instructor's dashboard. The input data consists of learning progress and sentiment data, while the output data is the aggregated data displayed on the dashboard.

[1293] Step 13:

[1294] Instructors monitor students' learning progress and emotional state through a dashboard and provide additional instruction as needed. Input data is the data displayed on the dashboard, while output data represents the additional instruction provided.

[1295] This generated processing step allows the system to provide students and workers with personalized learning and training, as well as appropriate guidance based on their emotional state in real time.

[1296] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1297] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1298] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[1299] [Third Embodiment]

[1300] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[1301] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1302] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1303] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[1304] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1305] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1306] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1307] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1308] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1309] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1310] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1311] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[1312] This invention relates to a system that provides customized education tailored to each student's academic ability and learning progress. This system operates through the collaboration of three entities: a server, terminals, and users (students and teachers). The following describes in detail how each entity functions.

[1313] Methods for assessing academic ability

[1314] The user (student) starts the test.

[1315] Device: Student A logs in and accesses the academic achievement test page. The device displays the "Start Test" button.

[1316] Implementation of academic achievement tests

[1317] User (student): Student A clicks the "Start Test" button.

[1318] Terminal: Retrieves academic achievement test questions from the server and displays them on the screen.

[1319] User (student): Student A enters their answers to each question.

[1320] Terminal: Temporarily saves responses and sends them to the server once all responses have been entered.

[1321] Analysis and transmission of test results

[1322] Server: Receives student A's answer data and calculates the correct answer rate for each question.

[1323] Server: Based on the analysis results, evaluate student A's academic level and save the data.

[1324] Individual Curriculum Generation Method

[1325] Curriculum generation

[1326] Server: Automatically generates an optimal learning curriculum for student A based on academic performance evaluation results and past learning history data.

[1327] Server: Saves the generated curriculum to the database.

[1328] Means of providing learning content

[1329] Distribution of curriculum and teaching materials

[1330] Terminal: Student A logs in and accesses their My Page. The server receives the My Page request and retrieves customized curriculum information for Student A.

[1331] Server: Sends curriculum information and corresponding teaching material data to the terminal.

[1332] Terminal: Displays the curriculum and teaching materials on the screen.

[1333] Learning progress

[1334] User (student): Student A views the learning materials and works on the practice problems.

[1335] Terminal: Saves student A's progress in real time.

[1336] Server: Records student A's learning progress data and updates learning materials as needed.

[1337] Learning progress evaluation method

[1338] Submission and evaluation of learning outcomes

[1339] User (student): Student A answers the practice questions and submits the results.

[1340] Terminal: Sends the response results to the server.

[1341] Server: Analyzes the response results, updates student A's learning progress, and saves the evaluation results.

[1342] Information provision means

[1343] Information provision to teachers

[1344] User (Teacher): Teacher B logs into the administration panel and accesses the dashboard.

[1345] Terminal: Sends the teacher's request to the server.

[1346] Server: Retrieves the latest learning progress data for each student and sends the aggregated dashboard data to the terminal.

[1347] Terminal: Display the dashboard so that Teacher B can see each student's learning progress at a glance.

[1348] Specific example

[1349] For example, if the server determines that student A's academic ability is at an "intermediate" level, the following will occur: The server will automatically generate a set of math practice problems and explanatory videos appropriate for the intermediate level and deliver them to the terminal. The user (student) will then use the provided materials to study and report their progress to the server. At the same time, teacher B will monitor student A's learning progress in real time through a dashboard and provide additional instruction as needed.

[1350] This system not only improves students' learning efficiency but also streamlines teachers' work and enables appropriate instruction for each individual student.

[1351] The following describes the processing flow.

[1352] Processing steps for academic ability assessment methods

[1353] Step 1:

[1354] Terminal: Student A logs in and accesses the academic achievement test page.

[1355] Terminal: Displays the button to start the academic ability assessment test.

[1356] Step 2:

[1357] User (student): Student A clicks the "Start Test" button.

[1358] Terminal: Retrieves academic achievement test questions from the server and displays them on the screen.

[1359] Step 3:

[1360] User (student): Student A enters their answers to each question.

[1361] Terminal: Temporarily saves response data.

[1362] Step 4:

[1363] User (student): Student A completes the test and clicks the submit button.

[1364] Terminal: Sends all responses to the server.

[1365] Step 5:

[1366] Server: Receives student A's answer data and calculates the correct answer rate for each question.

[1367] Step 6:

[1368] Server: Based on the analysis results, evaluate student A's academic level and save the data.

[1369] Processing steps of the individual curriculum generation means

[1370] Step 1:

[1371] Server: Automatically generates an individualized curriculum based on the academic performance evaluation results of student A.

[1372] Step 2:

[1373] Server: Optimizes curriculum content based on past learning history data.

[1374] Step 3:

[1375] Server: Saves the generated curriculum to the database.

[1376] Processing steps for learning content delivery methods

[1377] Step 1:

[1378] Terminal: Student A logs in and accesses their My Page.

[1379] Server: Receives a request for My Page and retrieves customized curriculum information for Student A.

[1380] Step 2:

[1381] Server: Sends curriculum information and corresponding teaching material data to the terminal.

[1382] Step 3:

[1383] Terminal: Displays the curriculum and teaching materials on the screen.

[1384] Step 4:

[1385] User (student): Student A views the learning materials and works on the practice problems.

[1386] Terminal: Saves student A's progress in real time.

[1387] Processing steps for learning progress evaluation means

[1388] Step 1:

[1389] User (student): Student A answers the practice questions and submits the results.

[1390] Terminal: Sends the response results to the server.

[1391] Step 2:

[1392] Server: Analyzes the response results and updates student A's learning progress.

[1393] Step 3:

[1394] Server: Saves the analysis results and adjusts the next learning content as needed.

[1395] Processing steps of information provision means

[1396] Step 1:

[1397] User (Teacher): Teacher B logs into the administration panel and accesses the dashboard.

[1398] Terminal: Sends the teacher's request to the server.

[1399] Step 2:

[1400] Server: Retrieves the latest learning progress data for each student.

[1401] Step 3:

[1402] Server: Sends the aggregated dashboard data to the terminal.

[1403] Step 4:

[1404] Terminal: Display the dashboard so that Teacher B can check the learning progress of each student.

[1405] (Example 1)

[1406] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1407] Traditional education systems struggle to provide appropriate curricula and materials tailored to each student's academic ability and learning progress, resulting in inefficient learning. Furthermore, there is a lack of sufficient information for teachers to monitor each student's learning progress in real time and provide necessary guidance.

[1408] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1409] In this invention, the server includes means for evaluating students' academic ability, means for generating individual curricula based on the academic ability evaluation results, means for providing learning content based on the generated individual curricula, means for recording and evaluating students' learning progress, means for providing information to instructors based on the generated individual curricula and learning progress, means for analyzing academic ability evaluation results and automatically generating curriculum and corresponding teaching material data, and means for recording students' learning activities and progress in real time and updating teaching materials as necessary. This enables the provision of an optimal learning plan for each individual, real-time monitoring of students' progress, and appropriate instruction.

[1410] The term "student" refers to a person who belongs to an educational institution and engages in learning.

[1411] "Academic ability assessment" refers to the process of measuring students' academic ability levels and evaluating their understanding and proficiency in learning.

[1412] "Means" refers to the methods or devices used to achieve a specific objective.

[1413] "Individualized curriculum" refers to a learning plan customized based on each student's academic ability and learning progress.

[1414] "Learning content" refers to educational materials such as textbooks, workbooks, and video explanations that students use for their studies.

[1415] "Learning progress" refers to data that indicates how far a student has progressed in their studies or their level of learning achievement.

[1416] The term "instructor" refers to someone who has the role of supporting students' learning and providing education.

[1417] A "server" refers to a computer system that provides services and data over a network.

[1418] "Terminal" refers to a device such as a computer or smartphone that is directly operated by the user.

[1419] An "online test" refers to a test for assessing academic ability that is conducted via the internet.

[1420] A "database" refers to a system used to efficiently store, search, and manage large amounts of data.

[1421] "Educational material data" refers to digital data of various educational materials used in learning.

[1422] "Analysis" refers to the process of analyzing data in detail and extracting information suitable for a specific purpose.

[1423] "Automatic generation" refers to the process by which a computer system automatically creates programs or data based on specific conditions.

[1424] "Real-time" refers to processing that occurs instantly without delay.

[1425] "Information provision" refers to the act of providing information to users for a specific purpose.

[1426] This invention relates to a system that provides customized education tailored to each student's academic ability and learning progress. This system operates through the collaboration of three entities: a server, terminals, and users (students and instructors). The following describes in detail how each entity functions.

[1427] Methods for assessing academic ability

[1428] The user (student) starts the test.

[1429] The user (student) logs into the system via their device and accesses the academic achievement test page. The device displays a "Start Test" button. When the student clicks the "Start Test" button, the device sends the request to the server.

[1430] Implementation of academic achievement tests

[1431] The server generates a set of questions for an academic assessment test and sends them to the terminal. The terminal displays the received test questions on its screen. The user (student) enters their answers to each question, and these answers are temporarily stored by the terminal. Once all answers have been entered, the terminal sends them back to the server.

[1432] Analysis and transmission of test results

[1433] Analysis of the answer results

[1434] The server receives student response data and calculates the correct answer rate for each question. Based on the analysis results, it evaluates the students' academic level and stores that data in a database.

[1435] Individual Curriculum Generation Method

[1436] Generating the optimal curriculum

[1437] The server retrieves students' academic performance evaluation results and past learning history data, and generates an optimal learning curriculum based on this data. The generated curriculum is stored in a database.

[1438] Means of providing learning content

[1439] Curriculum and material provision

[1440] When a user (student) accesses their My Page, the device sends a request to the server. The server retrieves customized curriculum information and corresponding learning materials for the student and sends them to the device. The device then displays the curriculum and learning materials on its screen.

[1441] Learning progress

[1442] Record of learning activities

[1443] Users (students) view learning materials and work on practice problems. The device saves the user's learning activities and progress in real time. The server periodically collects learning progress data and updates the learning materials as needed.

[1444] Learning progress evaluation method

[1445] Evaluation and recording of results

[1446] Users (students) input their answers to practice problems and send the results to the server via their terminal. The server analyzes the answers and evaluates the student's learning progress. The evaluation results are stored in a database.

[1447] Information provision means

[1448] Dashboard display

[1449] When a user (instructor) logs into the administration panel and accesses the dashboard, the device sends a request to the server. The server retrieves the latest learning progress data for each student, aggregates it, and sends it to the device. The device then displays the dashboard, allowing instructors to monitor each student's learning status in real time.

[1450] Examples of specific actions

[1451] For example, if the server determines a student's academic performance to be "intermediate," it automatically generates a set of math practice problems and explanatory videos appropriate for that level and delivers them to the student's device. The user (student) then uses the provided materials to learn and reports their progress to the server. Simultaneously, the instructor monitors the student's learning progress in real time via a dashboard and provides additional instruction as needed.

[1452] Example of a prompt

[1453] "Use this system to assess students' academic abilities and generate individualized curricula. Furthermore, explain how to provide students with learning materials based on those curricula and how to monitor their learning progress in real time."

[1454] This system not only improves students' learning efficiency but also streamlines instructors' work and enables appropriate instruction for each individual student.

[1455] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1456] Step 1:

[1457] The user (student) starts the test.

[1458] Input: The student logs into the system.

[1459] Device operation: Display the student's personal page and present a link to the academic achievement test.

[1460] User (student) action: Click the link for the academic achievement test and press the "Start Test" button.

[1461] Terminal action: Sends a test start request to the server.

[1462] Output: A request for the academic achievement test is sent to the server.

[1463] Step 2:

[1464] Implementation of academic achievement tests

[1465] Input: Test start request.

[1466] Server operation: Generates a set of questions for the academic achievement test and sends them to the terminal.

[1467] Device operation: Displays the received test questions on the screen.

[1468] User (student) action: Enter answers for each question.

[1469] Terminal operation: The user's responses are temporarily stored, and once all responses have been entered, they are sent to the server.

[1470] Output: Student response data is sent to the server.

[1471] Step 3:

[1472] Analysis and transmission of test results

[1473] Input: Student response data.

[1474] Server operation: Receives response data and calculates the correct answer rate for each question.

[1475] Data processing: Extract the number of correct answers from the response data and calculate the correct answer rate by dividing it by the total number of questions.

[1476] Server operation: Based on the analysis results, the system evaluates students' academic levels and saves that data to a database.

[1477] Output: Academic performance evaluation results are saved to the database.

[1478] Step 4:

[1479] Generating the optimal curriculum

[1480] Input: Academic performance evaluation results and past learning history data.

[1481] Server operation: Retrieves students' academic performance evaluation results and past learning history data.

[1482] Data processing: Analyze academic performance evaluation results and past data to generate an optimal learning plan.

[1483] Server operation: Generates the optimal learning curriculum and saves it to the database.

[1484] Output: The generated curriculum is saved to the database.

[1485] Step 5:

[1486] Curriculum and material provision

[1487] Input: Student access request.

[1488] User (student) action: Accesses My Page.

[1489] Terminal action: Sends a request to the server.

[1490] Server operation: Retrieves customized curriculum information and corresponding teaching material data, and sends it to the terminal.

[1491] Device operation: Displays the curriculum and learning materials on the screen.

[1492] Output: Customized curriculum and materials are displayed to students.

[1493] Step 6:

[1494] Record of learning activities

[1495] Input: Student learning activities.

[1496] User (student) actions: View learning materials and work on practice problems.

[1497] Device operation: Records learning activities and progress in real time.

[1498] Server operation: Regularly collects learning progress data and updates learning materials as needed.

[1499] Output: Learning progress data is saved to the server.

[1500] Step 7:

[1501] Evaluation and recording of results

[1502] Input: Student practice problem answer data.

[1503] User (student) action: Enter answers to practice problems and send the results to the server.

[1504] Terminal operation: Sends the response results to the server.

[1505] Server operation: Analyzes the response results and evaluates the students' learning progress.

[1506] Data processing: Analyze the response data and calculate the accuracy rate and the degree of achievement of learning objectives.

[1507] Server operation: Save evaluation results to the database.

[1508] Output: Learning progress evaluation data is saved to the database.

[1509] Step 8:

[1510] Dashboard display

[1511] Input: Instructor access request.

[1512] User (instructor) action: Log in to the administration screen and access the dashboard.

[1513] Terminal operation: Sends an access request to the dashboard to the server.

[1514] Server operation: The server retrieves the latest learning progress data for each student and sends the aggregated data to the terminal.

[1515] Device operation: Displays a dashboard, allowing instructors to see each student's learning progress at a glance.

[1516] Output: Learning progress is displayed on the dashboard.

[1517] As described above, this system efficiently processes each step and provides an optimal educational environment for students and instructors.

[1518] (Application Example 1)

[1519] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1520] Traditional factory worker training systems offer a uniform training program, making it difficult to customize the program to suit the individual skill levels and progress of each worker. Therefore, there is a need to provide an optimal training program for each worker to efficiently promote skill acquisition. Furthermore, progress management and evaluation are often done manually, placing a heavy burden on supervisors.

[1521] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1522] In this invention, the server includes means for performing a worker's technical evaluation, means for generating an individualized training program based on the technical evaluation results, means for providing training content based on the generated individualized training program, means for recording and evaluating the worker's progress, and means for providing information to the supervisor based on the generated individualized training program and progress. This enables the provision of customized training programs tailored to each worker's technical level and progress, as well as automated management and evaluation of progress.

[1523] A "worker" refers to a person who works in a factory or manufacturing industry and performs tasks using specific skills and techniques.

[1524] "Technical evaluation" refers to the process of measuring the skill and knowledge level of workers and collecting information necessary to provide appropriate training programs.

[1525] An "individualized training program" refers to training content that is customized based on the worker's technical evaluation results and according to the skills and knowledge that the worker needs to acquire.

[1526] "Training content" refers to educational materials and tools that workers use to learn skills and knowledge according to their individual training programs.

[1527] "Progress" refers to the state or status of how far an employee is progressing toward the goals in a training program.

[1528] A "supervisor" is a person whose role is to manage the training and progress and results of workers' daily work, and to provide guidance and advice as needed.

[1529] This invention relates to a system that provides customized training programs tailored to the skills and progress of each individual worker in a factory. This system operates through the collaboration of three entities: a server, terminals, and users (workers and supervisors). The following describes in detail how each entity functions.

[1530] Technical evaluation methods

[1531] The user (worker) starts the evaluation test.

[1532] Terminal: Worker A logs in and accesses the technical evaluation test page. The terminal displays the "Start Test" button.

[1533] Implementation of technical evaluation tests

[1534] User (worker): Worker A clicks the Start Test button.

[1535] Terminal: Retrieves technical evaluation test questions from the server and displays them on the screen.

[1536] User (worker): Worker A enters the answers to each question.

[1537] Terminal: Temporarily saves responses and sends them to the server once all responses have been entered.

[1538] Analysis and transmission of test results

[1539] Server: Receives worker A's response data and calculates the correct answer rate for each question.

[1540] Server: Based on the analysis results, evaluate the skill level of worker A and save the data.

[1541] Individual training program generation method

[1542] Training program generation

[1543] Server: Automatically generates the optimal training program for worker A based on technical evaluation results and past training history data.

[1544] Server: Saves the generated training program to the database.

[1545] Training content delivery methods

[1546] Distribution of training programs and materials

[1547] Terminal: Worker A logs in and accesses their My Page. The server receives the My Page request and retrieves customized training program information for Worker A.

[1548] Server: Sends training program information and corresponding training material data to the terminal.

[1549] Terminal: Displays the training program and materials on the screen.

[1550] Training progress

[1551] User (worker): Worker A views the training materials and works on the practice problems.

[1552] Terminal: Saves the progress of worker A in real time.

[1553] Server: Records worker A's training progress data and updates training materials as needed.

[1554] Progress evaluation methods

[1555] Submission and evaluation of training results

[1556] User (worker): Worker A answers the practice questions and submits the results.

[1557] Terminal: Sends the response results to the server.

[1558] Server: Analyzes the response results, updates worker A's training progress, and saves the evaluation results.

[1559] Information provision means

[1560] Information provided to supervisors

[1561] User (Supervisor): Supervisor B logs into the administration panel and accesses the dashboard.

[1562] Terminal: Sends the supervisor's request to the server.

[1563] Server: Retrieves the latest training progress data for each worker and sends the aggregated dashboard data to the terminal.

[1564] Terminal: Displays a dashboard, allowing supervisor B to see each worker's training status at a glance.

[1565] This system enables training tailored to each worker's skill level and progress, facilitating efficient skill acquisition and progress management. For example, when a new employee, worker A, begins training on the factory floor, an initial evaluation test is conducted, and their skill level is assessed as "intermediate." Based on this result, an intermediate-level training program is automatically generated and delivered to their terminal. Worker A acquires skills according to the provided program, and once their progress exceeds 50%, a new evaluation test is conducted to reassess their skill level. In this way, worker A can efficiently improve their skills.

[1566] Examples of prompts to input into a generative AI model:

[1567] When new employees begin on-site training at the factory, the training system is used in the following manner: First, an initial assessment test is administered, and their skill level is evaluated as "intermediate." Based on this result, an intermediate-level training program is automatically generated and delivered to their terminal. The worker acquires skills according to the provided program, and their progress is recorded in the system in real time. When progress exceeds 50%, a new assessment test is administered to re-evaluate their skill level. In this way, workers can efficiently improve their technical skills.

[1568] This system operates via a Python program and can be accessed using a smartphone or tablet. A Python environment is required on the server for evaluation, analysis, and data storage. This system enables improved individual worker skills and efficient management.

[1569] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1570] Step 1:

[1571] The user (worker) starts the evaluation test.

[1572] Input: The worker logs into the terminal and accesses the evaluation test page.

[1573] Specific operation: The terminal displays a "Start Test" button to the operator. When operator A clicks this button, the terminal requests the server to start the test.

[1574] Output: A request to start the evaluation test is sent to the server.

[1575] Step 2:

[1576] The server provides the evaluation test questions.

[1577] Input: The server receives a request to start the evaluation test.

[1578] Specific operation: The server retrieves the set of assessment test questions from the database and sends them to the terminal.

[1579] Output: The evaluation test questions are displayed on the terminal.

[1580] Step 3:

[1581] The user (worker) conducts the evaluation test.

[1582] Input: Worker A enters the answers to the test questions.

[1583] Specific operation: The terminal temporarily stores each answer entered by worker A, and once all answers have been entered, it sends that data to the server.

[1584] Output: Worker A's response data is sent to the server.

[1585] Step 4:

[1586] The server analyzes the test results.

[1587] Input: The server receives the response data from worker A.

[1588] Specific operation: The server calculates the accuracy rate for each problem and evaluates the skill level of worker A. The evaluation results are saved to the database.

[1589] Output: The technical skill level evaluation results for worker A are saved to the database.

[1590] Step 5:

[1591] The server generates individual training programs.

[1592] Input: The server retrieves technical evaluation results and historical training data.

[1593] Specific operation: Based on this data, the server automatically generates the optimal training program for worker A. The generated training program is saved to the database.

[1594] Output: Individual training programs are saved to the database.

[1595] Step 6:

[1596] The server provides the training program.

[1597] Input: Worker A logs into the terminal and accesses their My Page.

[1598] Specific operation: The server receives a request for My Page and sends customized training program information to worker A's terminal.

[1599] Output: Customized training program information is displayed on the terminal.

[1600] Step 7:

[1601] The user (worker) takes the training.

[1602] Input: Worker A answers practice problems according to the training program.

[1603] Specific operation: The terminal saves worker A's progress in real time and sends that data to the server.

[1604] Output: Worker A's progress data is saved to the server.

[1605] Step 8:

[1606] The server evaluates and updates the progress.

[1607] Input: The server receives progress data for worker A.

[1608] Specific operation: The server analyzes the progress data, updates worker A's training progress, and saves the evaluation results to the database.

[1609] Output: The updated progress evaluation data is saved to the database.

[1610] Step 9:

[1611] The server provides information to the supervisor.

[1612] Input: Supervisor B logs into the administration panel and accesses the dashboard.

[1613] Specific operation: The server retrieves the latest training progress data for each worker and sends the aggregated dashboard data to the terminal.

[1614] Output: Supervisor dashboard data is displayed on the terminal.

[1615] This processing flow allows each worker to receive the most appropriate technical training, and supervisors can evaluate and manage their progress in real time.

[1616] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1617] This invention relates to a system that provides customized education tailored to each student's academic ability, learning progress, and emotional state. This system operates through the collaboration of four entities: a server, terminals, users (students and teachers), and an emotion engine. The following describes in detail how each entity functions.

[1618] Methods for assessing academic ability and methods for generating individual curricula

[1619] Methods for assessing academic ability

[1620] Device: Student A logs in and accesses the academic achievement test page. The device displays the "Start Test" button.

[1621] User (student): Student A clicks the "Start Test" button, and the server displays the test questions.

[1622] User (student): Student A enters their answers to each question and sends the results from their terminal to the server.

[1623] Server: Analyzes the response data, evaluates student A's academic level, and saves the results.

[1624] Individual Curriculum Generation Method

[1625] Server: Automatically generates an optimal learning curriculum for student A based on academic performance evaluation results and past learning history data.

[1626] Server: Saves the generated curriculum to the database.

[1627] Means of providing learning content and means of evaluating learning progress

[1628] Means of providing learning content

[1629] Terminal: Student A logs in and accesses their My Page. The server retrieves customized curriculum information and delivers it to Student A.

[1630] Terminal: The curriculum and learning materials are displayed on the screen, and student A learns based on them.

[1631] User (Student): Student A views the learning materials and works on practice problems. The device saves their progress in real time.

[1632] Learning progress evaluation method

[1633] User (student): Student A answers a practice problem and sends the result from their terminal to the server.

[1634] Server: Analyzes the response results, updates student A's learning progress, and saves the evaluation results.

[1635] Emotion engines and the use of emotional data

[1636] How the emotion engine works

[1637] Device: When students are learning, data such as their facial expressions, voice, and behavior are collected in real time and sent to the emotion engine.

[1638] Emotion Engine: Analyzes received data to identify the student's emotional state (e.g., excitement, concentration, fatigue, indifference).

[1639] Use of emotional data

[1640] Server: Based on emotional data received from the emotion engine, it evaluates students' learning efficiency and dynamically adjusts learning content and delivery methods as needed.

[1641] Server: Reflect emotion data on the teacher's dashboard, enabling teachers to provide instruction based on students' emotional states.

[1642] Information provision means

[1643] Information provision to teachers

[1644] User (Teacher): Teacher B logs into the administration panel and accesses the dashboard.

[1645] Terminal: Sends the teacher's request to the server.

[1646] Server: Retrieves the latest learning progress and sentiment data for each student and sends the aggregated dashboard data to the terminal.

[1647] Terminal: Displays a dashboard, allowing teacher B to see each student's learning progress and emotional state at a glance.

[1648] Specific example

[1649] For example, if the server determines that student A's academic performance is "intermediate" and the emotion engine recognizes student A's emotional state as "focused," the system will operate as follows: The server generates a set of practice problems and explanatory videos appropriate for the intermediate level and delivers them to the terminal. Accordingly, the user (student) uses the provided materials to study and reports their progress and emotional state to the server. Meanwhile, teacher B monitors student A's learning progress and emotional state in real time through a dashboard and provides additional instruction as needed.

[1650] This system not only improves students' learning efficiency but also streamlines teachers' work and enables appropriate instruction for each individual student. By taking students' emotional states into consideration, it allows for more personalized and appropriate education.

[1651] The following describes the processing flow.

[1652] Processing steps for academic ability assessment methods

[1653] Step 1:

[1654] Device: Student A logs in and accesses the academic achievement test page. The device displays a button to start the academic achievement test.

[1655] Step 2:

[1656] User (student): Student A clicks the "Start Test" button. The device sends a request to the server to retrieve the test questions.

[1657] Step 3:

[1658] Server: Sends the academic achievement test questions to the terminal.

[1659] Step 4:

[1660] Terminal: Displays the acquired test questions on the screen.

[1661] Step 5:

[1662] User (student): Student A answers each question and enters the answer data.

[1663] Step 6:

[1664] Terminal: Temporarily saves the entered response data.

[1665] Step 7:

[1666] User (student): Student A completes the test and clicks the submit button.

[1667] Step 8:

[1668] Terminal: Sends all response data to the server.

[1669] Step 9:

[1670] Server: Receives student A's answer data and calculates the correct answer rate for each question.

[1671] Step 10:

[1672] Server: Based on the analysis results, evaluate student A's academic level and save the data.

[1673] Processing steps of the individual curriculum generation means

[1674] Step 1:

[1675] Server: Receives student A's academic performance evaluation results and starts the curriculum generation process.

[1676] Step 2:

[1677] Server: Retrieves past learning history data from the database and integrates it with current academic performance evaluation results.

[1678] Step 3:

[1679] Server: Based on integrated data, it automatically generates the optimal learning curriculum for student A.

[1680] Step 4:

[1681] Server: Saves the generated curriculum to the database.

[1682] Processing steps for learning content delivery methods

[1683] Step 1:

[1684] Terminal: Student A logs in and accesses their My Page.

[1685] Step 2:

[1686] Server: Receives a request for My Page and retrieves customized curriculum information for Student A.

[1687] Step 3:

[1688] Server: Searches for curriculum information and corresponding teaching material data, and sends it to the terminal.

[1689] Step 4:

[1690] Terminal: Displays the curriculum and teaching materials on the screen.

[1691] Step 5:

[1692] User (student): Student A views the learning materials and works on the practice problems.

[1693] Step 6:

[1694] Terminal: Saves student A's progress in real time.

[1695] Processing steps for learning progress evaluation means

[1696] Step 1:

[1697] User (student): Student A answers the practice questions and saves the results to their device.

[1698] Step 2:

[1699] Terminal: Sends the response results to the server.

[1700] Step 3:

[1701] Server: Analyzes the submitted response data and updates student A's learning progress.

[1702] Step 4:

[1703] Server: Saves updated progress data to the database.

[1704] Emotion engine and processing steps for using emotional data

[1705] Step 1:

[1706] Device: Sensors collect data such as students' facial expressions, voices, and behaviors while they are learning, and transmit this data to the emotion engine.

[1707] Step 2:

[1708] Emotion Engine: Analyzes received data to identify the student's emotional state (e.g., excitement, concentration, fatigue, indifference, etc.).

[1709] Step 3:

[1710] Emotion Engine: Sends emotional state data to the server.

[1711] Step 4:

[1712] Server: Based on emotional data, evaluate student A's learning efficiency and adjust the content delivery method as needed.

[1713] Step 5:

[1714] Server: Reflect emotion data on the teacher's dashboard, enabling teachers to provide instruction based on students' emotional states.

[1715] Processing steps of information provision means

[1716] Step 1:

[1717] User (Teacher): Teacher B logs into the administration panel and accesses the dashboard.

[1718] Step 2:

[1719] Terminal: Sends the teacher's request to the server.

[1720] Step 3:

[1721] Server: Retrieves the latest learning progress and sentiment data for each student and sends the aggregated dashboard data to the terminal.

[1722] Step 4:

[1723] Terminal: Displays a dashboard, allowing Teacher B to check each student's learning progress and emotional state.

[1724] This system not only improves students' learning efficiency but also streamlines teachers' work and enables appropriate instruction for each individual student. Furthermore, by considering students' emotional states through the emotion engine, it can provide more individualized and appropriate education.

[1725] (Example 2)

[1726] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1727] Traditional education systems have struggled to provide individualized curricula based on each student's academic ability and learning progress. Furthermore, they were unable to grasp students' emotional states in real time and use that information to improve learning efficiency or provide appropriate guidance. Therefore, providing students with the optimal learning environment was difficult.

[1728] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for evaluating students' academic ability, means for generating individual curricula based on the academic ability evaluation results, means for providing learning content based on the generated individual curricula, means for recording and evaluating students' learning progress, means for analyzing students' emotional state, and means for providing information to teachers based on the generated individual curricula, learning progress, and emotional state. This makes it possible to provide an optimal learning environment tailored to each student's academic ability, learning progress, and emotional state.

[1729] "Methods for evaluating academic ability" refer to functions for measuring and evaluating students' academic abilities.

[1730] The "individualized curriculum generation method" is a function that automatically creates an optimal learning curriculum for each student based on the results of academic performance assessments and past learning history.

[1731] "Learning content delivery method" refers to a function that provides learning materials and practice problems tailored to each student's needs, based on the generated individual curriculum, to their device.

[1732] A "learning progress evaluation tool" is a function for recording students' learning activities and evaluating their progress.

[1733] The "emotional state analysis method" is a function that analyzes students' facial expressions, voice, and behavior to grasp their emotional state in real time during learning.

[1734] "Information provision means" refers to a function that provides teachers with necessary information in a timely manner based on the generated individual curriculum, learning progress, and emotional state.

[1735] This invention relates to a system that provides customized education tailored to each student's academic ability, learning progress, and emotional state. This system operates through the coordinated efforts of four entities: a server, terminals, users (students and teachers), and an emotion engine.

[1736] Methods for assessing academic ability and methods for generating individual curricula

[1737] Methods for assessing academic ability

[1738] Device: The student logs in and accesses the academic achievement test page. The device displays a button to start the test.

[1739] User (student): When a student clicks the "Start Test" button, the server displays the test questions on their device.

[1740] User (student): The student answers each question and sends the answer data from their device to the server.

[1741] Server: The server analyzes the response data, evaluates the students' academic level, and saves the results.

[1742] Individual Curriculum Generation Method

[1743] Server: Based on academic performance evaluation results and past learning history data, it uses a generative AI model to automatically generate the optimal learning curriculum for each student.

[1744] Server: Saves the generated curriculum to the database.

[1745] Means of providing learning content and means of evaluating learning progress

[1746] Means of providing learning content

[1747] Device: When a student logs in and accesses their My Page, the server retrieves customized curriculum information and sends it to the device.

[1748] Terminal: Displays the curriculum and learning materials on the screen, allowing students to learn based on them.

[1749] Learning progress evaluation method

[1750] User (student): The student answers the practice questions and sends the results from their device to the server.

[1751] Server: The server analyzes the response results, updates the students' learning progress, and saves the evaluation results.

[1752] Emotion engines and the use of emotional data

[1753] How the emotion engine works

[1754] Device: Collects data such as facial expressions, voice, and behavior in real time as students learn, and sends it to the emotion engine.

[1755] Emotional Engine: Analyzes received data to identify the student's emotional state. For example, it analyzes excitement, concentration, fatigue, apathy, etc.

[1756] Use of emotional data

[1757] Server: Based on emotional data received from the emotion engine, it evaluates students' learning efficiency and dynamically adjusts learning content and delivery methods as needed.

[1758] Server: Emotional data is also sent to a teacher dashboard, enabling teachers to provide instruction based on students' emotional states.

[1759] Information provision means

[1760] Information provision to teachers

[1761] User (Teacher): The teacher logs into the administration panel and accesses the dashboard.

[1762] Terminal: Sends the teacher's request to the server.

[1763] Server: Retrieves the latest learning progress and sentiment data for each student and sends the aggregated dashboard data to the terminal.

[1764] Device: Displays a dashboard that allows teachers to see each student's learning progress and emotional state at a glance.

[1765] Specific example

[1766] For example, the following describes the process when the server determines a student's academic performance to be "intermediate" and the emotion engine recognizes the student's emotional state as "focused." The server generates a set of practice problems and explanatory videos appropriate for the intermediate level and delivers them to the student's device. The student then uses the provided materials to study and reports their progress and emotional state to the server. Meanwhile, the teacher monitors the student's learning progress and emotional state in real time through a dashboard and provides additional instruction as needed.

[1767] Example of a prompt

[1768] Examples of prompt statements to input into the generative AI model are shown below.

[1769] Prompt: If a student's academic performance is assessed as "intermediate" and the emotional engine recognizes them as "focused," please describe the specific processing steps for generating individualized curricula and utilizing emotional data.

[1770] In this way, this system can provide each student with an optimal learning environment and improve learning efficiency.

[1771] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1772] Step 1:

[1773] Input: Student login information (username and password)

[1774] Process: The student enters their authentication information on the login screen.

[1775] Terminal: The terminal sends login information to the server.

[1776] Server: The server verifies the authentication information, and if authentication is successful, redirects the user to their My Page.

[1777] Output: Login success status and My Page URL

[1778] Step 2:

[1779] Input: URL of the student's academic assessment test page after successful login

[1780] Process: The student accesses the academic achievement test page.

[1781] Terminal: The terminal displays a button to start the test.

[1782] Output: Start Test button

[1783] Step 3:

[1784] Input: Click event of the test start button

[1785] Process: The student clicks the "Start Test" button.

[1786] User (student): The student clicks the "Start Test" button.

[1787] Server: The server sends the academic achievement test questions to the terminals.

[1788] Output: Questions from the academic achievement test

[1789] Step 4:

[1790] Input: Answer data for each question (text, multiple choice)

[1791] Processing: Students answer each question and input the answer data.

[1792] Terminal: The terminal sends the response data to the server.

[1793] User (student): The student answers each question.

[1794] Output: Response data

[1795] Step 5:

[1796] Input: Submitted response data

[1797] Processing: The server receives the response data and runs an analysis algorithm to evaluate the students' academic level.

[1798] Server: The server analyzes the response data, evaluates the academic level, and stores it in a database.

[1799] Output: Academic performance evaluation results

[1800] Step 6:

[1801] Input: Academic performance evaluation results and past learning history data

[1802] Processing: Based on academic performance assessment results and past learning history data, a generative AI model is used to automatically generate the optimal learning curriculum for each student.

[1803] Server: The server retrieves academic performance evaluation results and past learning history from the database and automatically generates the curriculum.

[1804] Output: Generated learning curriculum

[1805] Step 7:

[1806] Input: Generated learning curriculum

[1807] Process: Save the generated curriculum to the database.

[1808] Server: The server saves the generated curriculum to the database.

[1809] Output: Saved curriculum

[1810] Step 8:

[1811] Input: Access to the student's My Page

[1812] Processing: After the student logs in, they access their My Page.

[1813] Terminal: The terminal sends a request to the server to access the My Page.

[1814] Server: The server retrieves customized curriculum information from the database and sends it to the terminal.

[1815] Output: Customized curriculum information

[1816] Step 9:

[1817] Input: Customized curriculum information

[1818] Processing: The curriculum and learning materials are displayed on the screen, and students learn based on them.

[1819] Terminal: The terminal displays the curriculum and learning materials on its screen.

[1820] Output: Displayed curriculum and materials

[1821] Step 10:

[1822] Input: Data used by students to answer practice problems.

[1823] Processing: Students answer practice problems, and their progress is saved in real time on their devices.

[1824] Terminal: The terminal sends progress data to the server.

[1825] Output: Sending progress data

[1826] Step 11:

[1827] Input: Submitted practice problem answer data

[1828] Processing: The server analyzes the response results and updates the students' learning progress.

[1829] Server: The server saves the analysis progress data to the database.

[1830] Output: Updated progress data

[1831] Step 12:

[1832] Input: Student facial expressions, voice, and behavioral data during learning.

[1833] Processing: Data such as facial expressions, voice, and behavior are collected in real time as students learn and sent to the emotion engine.

[1834] Device: The device sends the collected data to the emotion engine.

[1835] Output: Sent sentiment data

[1836] Step 13:

[1837] Input: Emotional data analyzed by the emotion engine

[1838] Processing: The emotion engine analyzes the received data to identify the student's emotional state. For example, it analyzes excitement, concentration, fatigue, apathy, etc.

[1839] Emotional Engine: Analyzes emotional states.

[1840] Output: Emotional state data from the analysis results

[1841] Step 14:

[1842] Input: Emotion engine analysis results and student learning progress data

[1843] Processing: The server evaluates learning efficiency based on sentiment data and dynamically adjusts the learning content and delivery method as needed.

[1844] Server: Saves the adjusted learning content to the database.

[1845] Output: Adjusted learning content

[1846] Step 15:

[1847] Input: Adjusted learning content and emotional state data

[1848] Processing: The server reflects the information on the teacher's dashboard.

[1849] Server: Generates teacher dashboard data and sends it to the terminal.

[1850] Output: Sending dashboard data

[1851] Step 16:

[1852] Input: Generated dashboard data

[1853] Process: The teacher logs into the administration panel and accesses the dashboard.

[1854] Device: Displays a dashboard, allowing teachers to monitor each student's learning progress and emotional state.

[1855] Output: Displayed dashboard

[1856] (Application Example 2)

[1857] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1858] Conventional education systems and work equipment management systems require flexible responses tailored to the individual academic abilities, efficiency, and progress of students and work equipment. In particular, it is difficult to consider real-time factors such as emotions and fatigue, which can lead to delays in providing appropriate learning and training. Furthermore, it is difficult for instructors to provide accurate guidance based on the individual's condition. The objective of this invention is to solve these problems and provide an efficient and effective education and training system.

[1859] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1860] In this invention, the server includes means for evaluating students' academic abilities, means for generating individual curricula based on the academic ability evaluation results, means for providing learning content based on the generated individual curricula, means for recording and evaluating students' learning progress, means for providing information to instructors based on the generated individual curricula and learning progress, means for collecting and evaluating the work efficiency and historical data of work equipment, means for generating training programs based on the evaluation results, means for analyzing the emotional state of work equipment, and means for providing information to instructors based on the emotional state and training program. This enables flexible and effective education and training based on the individual learning status and state of students and work equipment.

[1861] "Methods for evaluating academic ability" refer to systems or methods designed to assess students' academic abilities.

[1862] "Individualized curriculum generation means" refers to a system or method that automatically generates an optimal curriculum for a specific student based on the results of an academic performance assessment.

[1863] "Means of providing learning content" refers to a system or method that provides students with appropriate learning materials and problems based on a generated individual curriculum.

[1864] A "learning progress recording and evaluation means" is a system or method for recording students' learning status and evaluating their progress.

[1865] "Instructor information provision means" refers to a system or method that provides instructors with necessary information based on the generated individual curriculum and learning progress.

[1866] A "means for evaluating the work efficiency of work equipment" refers to a system or method for collecting and evaluating the work efficiency and historical data of work equipment.

[1867] "Training program generation means" refers to a system or method that generates an optimal training program based on the evaluation results of work equipment.

[1868] "Emotional state analysis means" refers to a system or method for analyzing the emotional state of work equipment and workers and collecting the data.

[1869] This invention provides a system that offers optimal education and training programs based on the individual academic abilities, work efficiency, and progress of students and work equipment. This system operates through the coordinated efforts of four entities: a server, terminals, users (students, workers, instructors), and an emotion engine.

[1870] System-wide configuration

[1871] The server includes means for evaluating academic ability, generating individual curricula, providing learning content, recording and evaluating learning progress, providing instructor information, evaluating the work efficiency of work equipment, generating training programs, and analyzing emotional states. By using this system, flexible and effective education and training based on the individual circumstances of students and work equipment becomes possible.

[1872] Methods for assessing academic ability and methods for generating individual curricula

[1873] Methods for assessing academic ability

[1874] Students' academic abilities will be assessed through online tests conducted via their devices.

[1875] The user (student) clicks the "Start Test" button and answers the questions presented by the server.

[1876] The server analyzes the response data, evaluates the academic level, and saves the results.

[1877] Individual Curriculum Generation Method

[1878] The server generates an optimal individual curriculum for each student based on their academic performance evaluation results and past learning history data.

[1879] The generated curriculum is stored in a database.

[1880] Means for providing learning content and means for recording and evaluating learning progress

[1881] Means of providing learning content

[1882] Students log in via their devices, and the server delivers customized curriculum information.

[1883] The device displays the provided curriculum and learning materials on its screen, and the user (student) learns based on them.

[1884] Learning progress recording and evaluation method

[1885] Users (students) view learning materials and work on practice problems.

[1886] The progress is recorded in real time by the device and sent to the server.

[1887] The server analyzes the response results, updates the learning progress, and saves the evaluation results.

[1888] Emotion engines and the use of emotional data

[1889] How the emotion engine works

[1890] The device collects facial expressions, voices, and behavioral data of students and workers in real time and transmits them to the emotion engine.

[1891] The emotion engine analyzes incoming data to identify emotional states (e.g., excitement, concentration, fatigue, indifference, etc.).

[1892] Use of emotional data

[1893] Based on emotional data received from the emotion engine, the server evaluates the learning and work efficiency of students and workers, and dynamically adjusts the learning and training content as needed.

[1894] Furthermore, emotional data is reflected in the instructor's dashboard, enabling instructors to provide guidance based on the emotional state of students and workers.

[1895] Means of providing information to leaders

[1896] Providing information to leaders

[1897] The instructor logs into the administration panel and sends a request to the server.

[1898] The server retrieves the latest learning progress and sentiment data for each student and work device, and provides the instructor with aggregated dashboard data.

[1899] The device displays a dashboard, allowing instructors to see each student's learning progress and emotional state at a glance.

[1900] Hardware and software used

[1901] Hardware: Devices used by students or workers (PCs, tablets), cameras and microphones for using the emotion engine, and management terminals for instructors.

[1902] Software: Evaluation algorithms using Python, database management system, and real-time sentiment analysis software (EmotionEngine).

[1903] Examples of specific cases and prompt statements

[1904] Specific example

[1905] The emotion engine analyzed student A's facial expressions and voice data while they were taking the online test and determined that they were fatigued. Based on this result, the server displayed a message on student A's device prompting them to take a break and made adjustments to ensure that their learning progress was maintained appropriately.

[1906] Example of a prompt

[1907] "Create a program that evaluates students' emotional states based on the following data and generates an optimal learning program. Sensor data includes temperature, work time, etc."

[1908] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1909] Step 1:

[1910] When a user (student) logs in and accesses the academic achievement test page, the server displays the test start page. The input data is the student's login information, and the output data is the web page containing the test start button.

[1911] Step 2:

[1912] The user (student) clicks the test start button, and the server delivers the test questions. In this process, the input is the test start signal clicked by the student, and the output is the test questions.

[1913] Step 3:

[1914] The user (student) enters their answers to each test question and sends them from their terminal to the server. The input data is the student's answer information, and the output data is the answer result.

[1915] Step 4:

[1916] The server analyzes the received response data and evaluates the students' academic ability levels. The input data is the response data, and the output data is the evaluation of the students' academic ability. Specifically, it analyzes the accuracy rate of the answers and the response time.

[1917] Step 5:

[1918] The server generates an optimal individual curriculum for each student based on their academic performance evaluation results and past learning history data. The input data consists of academic performance evaluation results and past learning history data, while the output data is the generated individual curriculum.

[1919] Step 6:

[1920] When a user (student) logs in, the terminal receives and displays individual curriculum information provided by the server. The input data is curriculum information, and the output data is the displayed learning content.

[1921] Step 7:

[1922] Users (students) view the displayed learning content and materials and work on practice problems. Their progress is recorded in real time by the device and sent to the server. Input data consists of answers to practice problems and viewing history, while output data is the recorded progress.

[1923] Step 8:

[1924] The server analyzes the received progress data and evaluates the learning progress. The input data is the progress data, and the output data is the evaluated progress status.

[1925] Step 9:

[1926] The device collects facial expressions, voice, and behavioral data in real time during student learning and transmits it to the emotion engine. The input data is data related to the student's emotional state, and the output data is emotional data transmitted to the emotion engine.

[1927] Step 10:

[1928] The emotion engine analyzes received data to identify the student's emotional state. Input data includes facial expressions, voice, and behavioral data, while output data is the analyzed emotional state.

[1929] Step 11:

[1930] The server evaluates students' learning efficiency based on emotional data received from the emotion engine and dynamically adjusts the learning content and delivery method as needed. The input data is emotional data, and the output data is the adjusted learning content and delivery method.

[1931] Step 12:

[1932] The server displays the latest student learning progress and sentiment data on the instructor's dashboard. The input data consists of learning progress and sentiment data, while the output data is the aggregated data displayed on the dashboard.

[1933] Step 13:

[1934] Instructors monitor students' learning progress and emotional state through a dashboard and provide additional instruction as needed. Input data is the data displayed on the dashboard, while output data represents the additional instruction provided.

[1935] This generated processing step allows the system to provide students and workers with personalized learning and training, as well as appropriate guidance based on their emotional state in real time.

[1936] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1937] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1938] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1939] [Fourth Embodiment]

[1940] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1941] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1942] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1943] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1944] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1945] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1946] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1947] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1948] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1949] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1950] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1951] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1952] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1953] This invention relates to a system that provides customized education tailored to each student's academic ability and learning progress. This system operates through the collaboration of three entities: a server, terminals, and users (students and teachers). The following describes in detail how each entity functions.

[1954] Methods for assessing academic ability

[1955] The user (student) starts the test.

[1956] Device: Student A logs in and accesses the academic achievement test page. The device displays the "Start Test" button.

[1957] Implementation of academic achievement tests

[1958] User (student): Student A clicks the "Start Test" button.

[1959] Terminal: Retrieves academic achievement test questions from the server and displays them on the screen.

[1960] User (student): Student A enters their answers to each question.

[1961] Terminal: Temporarily saves responses and sends them to the server once all responses have been entered.

[1962] Analysis and transmission of test results

[1963] Server: Receives student A's answer data and calculates the correct answer rate for each question.

[1964] Server: Based on the analysis results, evaluate student A's academic level and save the data.

[1965] Individual Curriculum Generation Method

[1966] Curriculum generation

[1967] Server: Automatically generates an optimal learning curriculum for student A based on academic performance evaluation results and past learning history data.

[1968] Server: Saves the generated curriculum to the database.

[1969] Means of providing learning content

[1970] Distribution of curriculum and teaching materials

[1971] Terminal: Student A logs in and accesses their My Page. The server receives the My Page request and retrieves customized curriculum information for Student A.

[1972] Server: Sends curriculum information and corresponding teaching material data to the terminal.

[1973] Terminal: Displays the curriculum and teaching materials on the screen.

[1974] Learning progress

[1975] User (student): Student A views the learning materials and works on the practice problems.

[1976] Terminal: Saves student A's progress in real time.

[1977] Server: Records student A's learning progress data and updates learning materials as needed.

[1978] Learning progress evaluation method

[1979] Submission and evaluation of learning outcomes

[1980] User (student): Student A answers the practice questions and submits the results.

[1981] Terminal: Sends the response results to the server.

[1982] Server: Analyzes the response results, updates student A's learning progress, and saves the evaluation results.

[1983] Information provision means

[1984] Information provision to teachers

[1985] User (Teacher): Teacher B logs into the administration panel and accesses the dashboard.

[1986] Terminal: Sends the teacher's request to the server.

[1987] Server: Retrieves the latest learning progress data for each student and sends the aggregated dashboard data to the terminal.

[1988] Terminal: Display the dashboard so that Teacher B can see each student's learning progress at a glance.

[1989] Specific example

[1990] For example, if the server determines that student A's academic ability is at an "intermediate" level, the following will occur: The server will automatically generate a set of math practice problems and explanatory videos appropriate for the intermediate level and deliver them to the terminal. The user (student) will then use the provided materials to study and report their progress to the server. At the same time, teacher B will monitor student A's learning progress in real time through a dashboard and provide additional instruction as needed.

[1991] This system not only improves students' learning efficiency but also streamlines teachers' work and enables appropriate instruction for each individual student.

[1992] The following describes the processing flow.

[1993] Processing steps for academic ability assessment methods

[1994] Step 1:

[1995] Terminal: Student A logs in and accesses the academic achievement test page.

[1996] Terminal: Displays the button to start the academic ability assessment test.

[1997] Step 2:

[1998] User (student): Student A clicks the "Start Test" button.

[1999] Terminal: Retrieves academic achievement test questions from the server and displays them on the screen.

[2000] Step 3:

[2001] User (student): Student A enters their answers to each question.

[2002] Terminal: Temporarily saves response data.

[2003] Step 4:

[2004] User (student): Student A completes the test and clicks the submit button.

[2005] Terminal: Sends all responses to the server.

[2006] Step 5:

[2007] Server: Receives student A's answer data and calculates the correct answer rate for each question.

[2008] Step 6:

[2009] Server: Based on the analysis results, evaluate student A's academic level and save the data.

[2010] Processing steps of the individual curriculum generation means

[2011] Step 1:

[2012] Server: Automatically generates an individualized curriculum based on the academic performance evaluation results of student A.

[2013] Step 2:

[2014] Server: Optimizes curriculum content based on past learning history data.

[2015] Step 3:

[2016] Server: Saves the generated curriculum to the database.

[2017] Processing steps for learning content delivery methods

[2018] Step 1:

[2019] Terminal: Student A logs in and accesses their My Page.

[2020] Server: Receives a request for My Page and retrieves customized curriculum information for Student A.

[2021] Step 2:

[2022] Server: Sends curriculum information and corresponding teaching material data to the terminal.

[2023] Step 3:

[2024] Terminal: Displays the curriculum and teaching materials on the screen.

[2025] Step 4:

[2026] User (student): Student A views the learning materials and works on the practice problems.

[2027] Terminal: Saves student A's progress in real time.

[2028] Processing steps for learning progress evaluation means

[2029] Step 1:

[2030] User (student): Student A answers the practice questions and submits the results.

[2031] Terminal: Sends the response results to the server.

[2032] Step 2:

[2033] Server: Analyzes the response results and updates student A's learning progress.

[2034] Step 3:

[2035] Server: Saves the analysis results and adjusts the next learning content as needed.

[2036] Processing steps of information provision means

[2037] Step 1:

[2038] User (Teacher): Teacher B logs into the administration panel and accesses the dashboard.

[2039] Terminal: Sends the teacher's request to the server.

[2040] Step 2:

[2041] Server: Retrieves the latest learning progress data for each student.

[2042] Step 3:

[2043] Server: Sends the aggregated dashboard data to the terminal.

[2044] Step 4:

[2045] Terminal: Display the dashboard so that Teacher B can check the learning progress of each student.

[2046] (Example 1)

[2047] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2048] Traditional education systems struggle to provide appropriate curricula and materials tailored to each student's academic ability and learning progress, resulting in inefficient learning. Furthermore, there is a lack of sufficient information for teachers to monitor each student's learning progress in real time and provide necessary guidance.

[2049] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[2050] In this invention, the server includes means for evaluating students' academic ability, means for generating individual curricula based on the academic ability evaluation results, means for providing learning content based on the generated individual curricula, means for recording and evaluating students' learning progress, means for providing information to instructors based on the generated individual curricula and learning progress, means for analyzing academic ability evaluation results and automatically generating curriculum and corresponding teaching material data, and means for recording students' learning activities and progress in real time and updating teaching materials as necessary. This enables the provision of an optimal learning plan for each individual, real-time monitoring of students' progress, and appropriate instruction.

[2051] The term "student" refers to a person who belongs to an educational institution and engages in learning.

[2052] "Academic ability assessment" refers to the process of measuring students' academic ability levels and evaluating their understanding and proficiency in learning.

[2053] "Means" refers to the methods or devices used to achieve a specific objective.

[2054] "Individualized curriculum" refers to a learning plan customized based on each student's academic ability and learning progress.

[2055] "Learning content" refers to educational materials such as textbooks, workbooks, and video explanations that students use for their studies.

[2056] "Learning progress" refers to data that indicates how far a student has progressed in their studies or their level of learning achievement.

[2057] The term "instructor" refers to someone who has the role of supporting students' learning and providing education.

[2058] A "server" refers to a computer system that provides services and data over a network.

[2059] "Terminal" refers to a device such as a computer or smartphone that is directly operated by the user.

[2060] An "online test" refers to a test for assessing academic ability that is conducted via the internet.

[2061] A "database" refers to a system used to efficiently store, search, and manage large amounts of data.

[2062] "Educational material data" refers to digital data of various educational materials used in learning.

[2063] "Analysis" refers to the process of analyzing data in detail and extracting information suitable for a specific purpose.

[2064] "Automatic generation" refers to the process by which a computer system automatically creates programs or data based on specific conditions.

[2065] "Real-time" refers to processing that occurs instantly without delay.

[2066] "Information provision" refers to the act of providing information to users for a specific purpose.

[2067] This invention relates to a system that provides customized education tailored to each student's academic ability and learning progress. This system operates through the collaboration of three entities: a server, terminals, and users (students and instructors). The following describes in detail how each entity functions.

[2068] Methods for assessing academic ability

[2069] The user (student) starts the test.

[2070] The user (student) logs into the system via their device and accesses the academic achievement test page. The device displays a "Start Test" button. When the student clicks the "Start Test" button, the device sends the request to the server.

[2071] Implementation of academic achievement tests

[2072] The server generates a set of questions for an academic assessment test and sends them to the terminal. The terminal displays the received test questions on its screen. The user (student) enters their answers to each question, and these answers are temporarily stored by the terminal. Once all answers have been entered, the terminal sends them back to the server.

[2073] Analysis and transmission of test results

[2074] Analysis of the answer results

[2075] The server receives student response data and calculates the correct answer rate for each question. Based on the analysis results, it evaluates the students' academic level and stores that data in a database.

[2076] Individual Curriculum Generation Method

[2077] Generating the optimal curriculum

[2078] The server retrieves students' academic performance evaluation results and past learning history data, and generates an optimal learning curriculum based on this data. The generated curriculum is stored in a database.

[2079] Means of providing learning content

[2080] Curriculum and material provision

[2081] When a user (student) accesses their My Page, the device sends a request to the server. The server retrieves customized curriculum information and corresponding learning materials for the student and sends them to the device. The device then displays the curriculum and learning materials on its screen.

[2082] Learning progress

[2083] Record of learning activities

[2084] Users (students) view learning materials and work on practice problems. The device saves the user's learning activities and progress in real time. The server periodically collects learning progress data and updates the learning materials as needed.

[2085] Learning progress evaluation method

[2086] Evaluation and recording of results

[2087] Users (students) input their answers to practice problems and send the results to the server via their terminal. The server analyzes the answers and evaluates the student's learning progress. The evaluation results are stored in a database.

[2088] Information provision means

[2089] Dashboard display

[2090] When a user (instructor) logs into the administration panel and accesses the dashboard, the device sends a request to the server. The server retrieves the latest learning progress data for each student, aggregates it, and sends it to the device. The device then displays the dashboard, allowing instructors to monitor each student's learning status in real time.

[2091] Examples of specific actions

[2092] For example, if the server determines a student's academic performance to be "intermediate," it automatically generates a set of math practice problems and explanatory videos appropriate for that level and delivers them to the student's device. The user (student) then uses the provided materials to learn and reports their progress to the server. Simultaneously, the instructor monitors the student's learning progress in real time via a dashboard and provides additional instruction as needed.

[2093] Example of a prompt

[2094] "Use this system to assess students' academic abilities and generate individualized curricula. Furthermore, explain how to provide students with learning materials based on those curricula and how to monitor their learning progress in real time."

[2095] This system not only improves students' learning efficiency but also streamlines instructors' work and enables appropriate instruction for each individual student.

[2096] The flow of the specific processing in Example 1 will be explained using Figure 11.

[2097] Step 1:

[2098] The user (student) starts the test.

[2099] Input: The student logs into the system.

[2100] Device operation: Display the student's personal page and present a link to the academic achievement test.

[2101] User (student) action: Click the link for the academic achievement test and press the "Start Test" button.

[2102] Terminal action: Sends a test start request to the server.

[2103] Output: A request for the academic achievement test is sent to the server.

[2104] Step 2:

[2105] Implementation of academic achievement tests

[2106] Input: Test start request.

[2107] Server operation: Generates a set of questions for the academic achievement test and sends them to the terminal.

[2108] Device operation: Displays the received test questions on the screen.

[2109] User (student) action: Enter answers for each question.

[2110] Terminal operation: The user's responses are temporarily stored, and once all responses have been entered, they are sent to the server.

[2111] Output: Student response data is sent to the server.

[2112] Step 3:

[2113] Analysis and transmission of test results

[2114] Input: Student response data.

[2115] Server operation: Receives response data and calculates the correct answer rate for each question.

[2116] Data processing: Extract the number of correct answers from the response data and calculate the correct answer rate by dividing it by the total number of questions.

[2117] Server operation: Based on the analysis results, the system evaluates students' academic levels and saves that data to a database.

[2118] Output: Academic performance evaluation results are saved to the database.

[2119] Step 4:

[2120] Generating the optimal curriculum

[2121] Input: Academic performance evaluation results and past learning history data.

[2122] Server operation: Retrieves students' academic performance evaluation results and past learning history data.

[2123] Data processing: Analyze academic performance evaluation results and past data to generate an optimal learning plan.

[2124] Server operation: Generates the optimal learning curriculum and saves it to the database.

[2125] Output: The generated curriculum is saved to the database.

[2126] Step 5:

[2127] Curriculum and material provision

[2128] Input: Student access request.

[2129] User (student) action: Accesses My Page.

[2130] Terminal action: Sends a request to the server.

[2131] Server operation: Retrieves customized curriculum information and corresponding teaching material data, and sends it to the terminal.

[2132] Device operation: Displays the curriculum and learning materials on the screen.

[2133] Output: Customized curriculum and materials are displayed to students.

[2134] Step 6:

[2135] Record of learning activities

[2136] Input: Student learning activities.

[2137] User (student) actions: View learning materials and work on practice problems.

[2138] Device operation: Records learning activities and progress in real time.

[2139] Server operation: Regularly collects learning progress data and updates learning materials as needed.

[2140] Output: Learning progress data is saved to the server.

[2141] Step 7:

[2142] Evaluation and recording of results

[2143] Input: Student practice problem answer data.

[2144] User (student) action: Enter answers to practice problems and send the results to the server.

[2145] Terminal operation: Sends the response results to the server.

[2146] Server operation: Analyzes the response results and evaluates the students' learning progress.

[2147] Data processing: Analyze the response data and calculate the accuracy rate and the degree of achievement of learning objectives.

[2148] Server operation: Save evaluation results to the database.

[2149] Output: Learning progress evaluation data is saved to the database.

[2150] Step 8:

[2151] Dashboard display

[2152] Input: Instructor access request.

[2153] User (instructor) action: Log in to the administration screen and access the dashboard.

[2154] Terminal operation: Sends an access request to the dashboard to the server.

[2155] Server operation: The server retrieves the latest learning progress data for each student and sends the aggregated data to the terminal.

[2156] Device operation: Displays a dashboard, allowing instructors to see each student's learning progress at a glance.

[2157] Output: Learning progress is displayed on the dashboard.

[2158] As described above, this system efficiently processes each step and provides an optimal educational environment for students and instructors.

[2159] (Application Example 1)

[2160] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2161] Traditional factory worker training systems offer a uniform training program, making it difficult to customize the program to suit the individual skill levels and progress of each worker. Therefore, there is a need to provide an optimal training program for each worker to efficiently promote skill acquisition. Furthermore, progress management and evaluation are often done manually, placing a heavy burden on supervisors.

[2162] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[2163] In this invention, the server includes means for performing a worker's technical evaluation, means for generating an individualized training program based on the technical evaluation results, means for providing training content based on the generated individualized training program, means for recording and evaluating the worker's progress, and means for providing information to the supervisor based on the generated individualized training program and progress. This enables the provision of customized training programs tailored to each worker's technical level and progress, as well as automated management and evaluation of progress.

[2164] A "worker" refers to a person who works in a factory or manufacturing industry and performs tasks using specific skills and techniques.

[2165] "Technical evaluation" refers to the process of measuring the skill and knowledge level of workers and collecting information necessary to provide appropriate training programs.

[2166] An "individualized training program" refers to training content that is customized based on the worker's technical evaluation results and according to the skills and knowledge that the worker needs to acquire.

[2167] "Training content" refers to educational materials and tools that workers use to learn skills and knowledge according to their individual training programs.

[2168] "Progress" refers to the state or status of how far an employee is progressing toward the goals in a training program.

[2169] A "supervisor" is a person whose role is to manage the training and progress and results of workers' daily work, and to provide guidance and advice as needed.

[2170] This invention relates to a system that provides customized training programs tailored to the skills and progress of each individual worker in a factory. This system operates through the collaboration of three entities: a server, terminals, and users (workers and supervisors). The following describes in detail how each entity functions.

[2171] Technical evaluation methods

[2172] The user (worker) starts the evaluation test.

[2173] Terminal: Worker A logs in and accesses the technical evaluation test page. The terminal displays the "Start Test" button.

[2174] Implementation of technical evaluation tests

[2175] User (worker): Worker A clicks the Start Test button.

[2176] Terminal: Retrieves technical evaluation test questions from the server and displays them on the screen.

[2177] User (worker): Worker A enters the answers to each question.

[2178] Terminal: Temporarily saves responses and sends them to the server once all responses have been entered.

[2179] Analysis and transmission of test results

[2180] Server: Receives worker A's response data and calculates the correct answer rate for each question.

[2181] Server: Based on the analysis results, evaluate the skill level of worker A and save the data.

[2182] Individual training program generation method

[2183] Training program generation

[2184] Server: Automatically generates the optimal training program for worker A based on technical evaluation results and past training history data.

[2185] Server: Saves the generated training program to the database.

[2186] Training content delivery methods

[2187] Distribution of training programs and materials

[2188] Terminal: Worker A logs in and accesses their My Page. The server receives the My Page request and retrieves customized training program information for Worker A.

[2189] Server: Sends training program information and corresponding training material data to the terminal.

[2190] Terminal: Displays the training program and materials on the screen.

[2191] Training progress

[2192] User (worker): Worker A views the training materials and works on the practice problems.

[2193] Terminal: Saves the progress of worker A in real time.

[2194] Server: Records worker A's training progress data and updates training materials as needed.

[2195] Progress evaluation methods

[2196] Submission and evaluation of training results

[2197] User (worker): Worker A answers the practice questions and submits the results.

[2198] Terminal: Sends the response results to the server.

[2199] Server: Analyzes the response results, updates worker A's training progress, and saves the evaluation results.

[2200] Information provision means

[2201] Information provided to supervisors

[2202] User (Supervisor): Supervisor B logs into the administration panel and accesses the dashboard.

[2203] Terminal: Sends the supervisor's request to the server.

[2204] Server: Retrieves the latest training progress data for each worker and sends the aggregated dashboard data to the terminal.

[2205] Terminal: Displays a dashboard, allowing supervisor B to see each worker's training status at a glance.

[2206] This system enables training tailored to each worker's skill level and progress, facilitating efficient skill acquisition and progress management. For example, when a new employee, worker A, begins training on the factory floor, an initial evaluation test is conducted, and their skill level is assessed as "intermediate." Based on this result, an intermediate-level training program is automatically generated and delivered to their terminal. Worker A acquires skills according to the provided program, and once their progress exceeds 50%, a new evaluation test is conducted to reassess their skill level. In this way, worker A can efficiently improve their skills.

[2207] Examples of prompts to input into a generative AI model:

[2208] When new employees begin on-site training at the factory, the training system is used in the following manner: First, an initial assessment test is administered, and their skill level is evaluated as "intermediate." Based on this result, an intermediate-level training program is automatically generated and delivered to their terminal. The worker acquires skills according to the provided program, and their progress is recorded in the system in real time. When progress exceeds 50%, a new assessment test is administered to re-evaluate their skill level. In this way, workers can efficiently improve their technical skills.

[2209] This system operates via a Python program and can be accessed using a smartphone or tablet. A Python environment is required on the server for evaluation, analysis, and data storage. This system enables improved individual worker skills and efficient management.

[2210] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[2211] Step 1:

[2212] The user (worker) starts the evaluation test.

[2213] Input: The worker logs into the terminal and accesses the evaluation test page.

[2214] Specific operation: The terminal displays a "Start Test" button to the operator. When operator A clicks this button, the terminal requests the server to start the test.

[2215] Output: A request to start the evaluation test is sent to the server.

[2216] Step 2:

[2217] The server provides the evaluation test questions.

[2218] Input: The server receives a request to start the evaluation test.

[2219] Specific operation: The server retrieves the set of assessment test questions from the database and sends them to the terminal.

[2220] Output: The evaluation test questions are displayed on the terminal.

[2221] Step 3:

[2222] The user (worker) conducts the evaluation test.

[2223] Input: Worker A enters the answers to the test questions.

[2224] Specific operation: The terminal temporarily stores each answer entered by worker A, and once all answers have been entered, it sends that data to the server.

[2225] Output: Worker A's response data is sent to the server.

[2226] Step 4:

[2227] The server analyzes the test results.

[2228] Input: The server receives the response data from worker A.

[2229] Specific operation: The server calculates the accuracy rate for each problem and evaluates the skill level of worker A. The evaluation results are saved to the database.

[2230] Output: The technical skill level evaluation results for worker A are saved to the database.

[2231] Step 5:

[2232] The server generates individual training programs.

[2233] Input: The server retrieves technical evaluation results and historical training data.

[2234] Specific operation: Based on this data, the server automatically generates the optimal training program for worker A. The generated training program is saved to the database.

[2235] Output: Individual training programs are saved to the database.

[2236] Step 6:

[2237] The server provides the training program.

[2238] Input: Worker A logs into the terminal and accesses their My Page.

[2239] Specific operation: The server receives a request for My Page and sends customized training program information to worker A's terminal.

[2240] Output: Customized training program information is displayed on the terminal.

[2241] Step 7:

[2242] The user (worker) takes the training.

[2243] Input: Worker A answers practice problems according to the training program.

[2244] Specific operation: The terminal saves worker A's progress in real time and sends that data to the server.

[2245] Output: Worker A's progress data is saved to the server.

[2246] Step 8:

[2247] The server evaluates and updates the progress.

[2248] Input: The server receives progress data for worker A.

[2249] Specific operation: The server analyzes the progress data, updates worker A's training progress, and saves the evaluation results to the database.

[2250] Output: The updated progress evaluation data is saved to the database.

[2251] Step 9:

[2252] The server provides information to the supervisor.

[2253] Input: Supervisor B logs into the administration panel and accesses the dashboard.

[2254] Specific operation: The server retrieves the latest training progress data for each worker and sends the aggregated dashboard data to the terminal.

[2255] Output: Supervisor dashboard data is displayed on the terminal.

[2256] This processing flow allows each worker to receive the most appropriate technical training, and supervisors can evaluate and manage their progress in real time.

[2257] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[2258] This invention relates to a system that provides customized education tailored to each student's academic ability, learning progress, and emotional state. This system operates through the collaboration of four entities: a server, terminals, users (students and teachers), and an emotion engine. The following describes in detail how each entity functions.

[2259] Methods for assessing academic ability and methods for generating individual curricula

[2260] Methods for assessing academic ability

[2261] Device: Student A logs in and accesses the academic achievement test page. The device displays the "Start Test" button.

[2262] User (student): Student A clicks the "Start Test" button, and the server displays the test questions.

[2263] User (student): Student A enters their answers to each question and sends the results from their terminal to the server.

[2264] Server: Analyzes the response data, evaluates student A's academic level, and saves the results.

[2265] Individual Curriculum Generation Method

[2266] Server: Automatically generates an optimal learning curriculum for student A based on academic performance evaluation results and past learning history data.

[2267] Server: Saves the generated curriculum to the database.

[2268] Means of providing learning content and means of evaluating learning progress

[2269] Means of providing learning content

[2270] Terminal: Student A logs in and accesses their My Page. The server retrieves customized curriculum information and delivers it to Student A.

[2271] Terminal: The curriculum and learning materials are displayed on the screen, and student A learns based on them.

[2272] User (Student): Student A views the learning materials and works on practice problems. The device saves their progress in real time.

[2273] Learning progress evaluation method

[2274] User (student): Student A answers a practice problem and sends the result from their terminal to the server.

[2275] Server: Analyzes the response results, updates student A's learning progress, and saves the evaluation results.

[2276] Emotion engines and the use of emotional data

[2277] How the emotion engine works

[2278] Device: When students are learning, data such as their facial expressions, voice, and behavior are collected in real time and sent to the emotion engine.

[2279] Emotion Engine: Analyzes received data to identify the student's emotional state (e.g., excitement, concentration, fatigue, indifference).

[2280] Use of emotional data

[2281] Server: Based on emotional data received from the emotion engine, it evaluates students' learning efficiency and dynamically adjusts learning content and delivery methods as needed.

[2282] Server: Reflect emotion data on the teacher's dashboard, enabling teachers to provide instruction based on students' emotional states.

[2283] Information provision means

[2284] Information provision to teachers

[2285] User (Teacher): Teacher B logs into the administration panel and accesses the dashboard.

[2286] Terminal: Sends the teacher's request to the server.

[2287] Server: Retrieves the latest learning progress and sentiment data for each student and sends the aggregated dashboard data to the terminal.

[2288] Terminal: Displays a dashboard, allowing teacher B to see each student's learning progress and emotional state at a glance.

[2289] Specific example

[2290] For example, if the server determines that student A's academic performance is "intermediate" and the emotion engine recognizes student A's emotional state as "focused," the system will operate as follows: The server generates a set of practice problems and explanatory videos appropriate for the intermediate level and delivers them to the terminal. Accordingly, the user (student) uses the provided materials to study and reports their progress and emotional state to the server. Meanwhile, teacher B monitors student A's learning progress and emotional state in real time through a dashboard and provides additional instruction as needed.

[2291] This system not only improves students' learning efficiency but also streamlines teachers' work and enables appropriate instruction for each individual student. By taking students' emotional states into consideration, it allows for more personalized and appropriate education.

[2292] The following describes the processing flow.

[2293] Processing steps for academic ability assessment methods

[2294] Step 1:

[2295] Device: Student A logs in and accesses the academic achievement test page. The device displays a button to start the academic achievement test.

[2296] Step 2:

[2297] User (student): Student A clicks the "Start Test" button. The device sends a request to the server to retrieve the test questions.

[2298] Step 3:

[2299] Server: Sends the academic achievement test questions to the terminal.

[2300] Step 4:

[2301] Terminal: Displays the acquired test questions on the screen.

[2302] Step 5:

[2303] User (student): Student A answers each question and enters the answer data.

[2304] Step 6:

[2305] Terminal: Temporarily saves the entered response data.

[2306] Step 7:

[2307] User (student): Student A completes the test and clicks the submit button.

[2308] Step 8:

[2309] Terminal: Sends all response data to the server.

[2310] Step 9:

[2311] Server: Receives student A's answer data and calculates the correct answer rate for each question.

[2312] Step 10:

[2313] Server: Based on the analysis results, evaluate student A's academic level and save the data.

[2314] Processing steps of the individual curriculum generation means

[2315] Step 1:

[2316] Server: Receives student A's academic performance evaluation results and starts the curriculum generation process.

[2317] Step 2:

[2318] Server: Retrieves past learning history data from the database and integrates it with current academic performance evaluation results.

[2319] Step 3:

[2320] Server: Based on integrated data, it automatically generates the optimal learning curriculum for student A.

[2321] Step 4:

[2322] Server: Saves the generated curriculum to the database.

[2323] Processing steps for learning content delivery methods

[2324] Step 1:

[2325] Terminal: Student A logs in and accesses their My Page.

[2326] Step 2:

[2327] Server: Receives a request for My Page and retrieves customized curriculum information for Student A.

[2328] Step 3:

[2329] Server: Searches for curriculum information and corresponding teaching material data, and sends it to the terminal.

[2330] Step 4:

[2331] Terminal: Displays the curriculum and teaching materials on the screen.

[2332] Step 5:

[2333] User (student): Student A views the learning materials and works on the practice problems.

[2334] Step 6:

[2335] Terminal: Saves student A's progress in real time.

[2336] Processing steps for learning progress evaluation means

[2337] Step 1:

[2338] User (student): Student A answers the practice questions and saves the results to their device.

[2339] Step 2:

[2340] Terminal: Sends the response results to the server.

[2341] Step 3:

[2342] Server: Analyzes the submitted response data and updates student A's learning progress.

[2343] Step 4:

[2344] Server: Saves updated progress data to the database.

[2345] Emotion engine and processing steps for using emotional data

[2346] Step 1:

[2347] Device: Sensors collect data such as students' facial expressions, voices, and behaviors while they are learning, and transmit this data to the emotion engine.

[2348] Step 2:

[2349] Emotion Engine: Analyzes received data to identify the student's emotional state (e.g., excitement, concentration, fatigue, indifference, etc.).

[2350] Step 3:

[2351] Emotion Engine: Sends emotional state data to the server.

[2352] Step 4:

[2353] Server: Based on emotional data, evaluate student A's learning efficiency and adjust the content delivery method as needed.

[2354] Step 5:

[2355] Server: Reflect emotion data on the teacher's dashboard, enabling teachers to provide instruction based on students' emotional states.

[2356] Processing steps of information provision means

[2357] Step 1:

[2358] User (Teacher): Teacher B logs into the administration panel and accesses the dashboard.

[2359] Step 2:

[2360] Terminal: Sends the teacher's request to the server.

[2361] Step 3:

[2362] Server: Retrieves the latest learning progress and sentiment data for each student and sends the aggregated dashboard data to the terminal.

[2363] Step 4:

[2364] Terminal: Displays a dashboard, allowing Teacher B to check each student's learning progress and emotional state.

[2365] This system not only improves students' learning efficiency but also streamlines teachers' work and enables appropriate instruction for each individual student. Furthermore, by considering students' emotional states through the emotion engine, it can provide more individualized and appropriate education.

[2366] (Example 2)

[2367] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2368] Traditional education systems have struggled to provide individualized curricula based on each student's academic ability and learning progress. Furthermore, they were unable to grasp students' emotional states in real time and use that information to improve learning efficiency or provide appropriate guidance. Therefore, providing students with the optimal learning environment was difficult.

[2369] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for evaluating students' academic ability, means for generating individual curricula based on the academic ability evaluation results, means for providing learning content based on the generated individual curricula, means for recording and evaluating students' learning progress, means for analyzing students' emotional state, and means for providing information to teachers based on the generated individual curricula, learning progress, and emotional state. This makes it possible to provide an optimal learning environment tailored to each student's academic ability, learning progress, and emotional state.

[2370] "Methods for evaluating academic ability" refer to functions for measuring and evaluating students' academic abilities.

[2371] The "individualized curriculum generation method" is a function that automatically creates an optimal learning curriculum for each student based on the results of academic performance assessments and past learning history.

[2372] "Learning content delivery method" refers to a function that provides learning materials and practice problems tailored to each student's needs, based on the generated individual curriculum, to their device.

[2373] A "learning progress evaluation tool" is a function for recording students' learning activities and evaluating their progress.

[2374] The "emotional state analysis method" is a function that analyzes students' facial expressions, voice, and behavior to grasp their emotional state in real time during learning.

[2375] "Information provision means" refers to a function that provides teachers with necessary information in a timely manner based on the generated individual curriculum, learning progress, and emotional state.

[2376] This invention relates to a system that provides customized education tailored to each student's academic ability, learning progress, and emotional state. This system operates through the coordinated efforts of four entities: a server, terminals, users (students and teachers), and an emotion engine.

[2377] Methods for assessing academic ability and methods for generating individual curricula

[2378] Methods for assessing academic ability

[2379] Device: The student logs in and accesses the academic achievement test page. The device displays a button to start the test.

[2380] User (student): When a student clicks the "Start Test" button, the server displays the test questions on their device.

[2381] User (student): The student answers each question and sends the answer data from their device to the server.

[2382] Server: The server analyzes the response data, evaluates the students' academic level, and saves the results.

[2383] Individual Curriculum Generation Method

[2384] Server: Based on academic performance evaluation results and past learning history data, it uses a generative AI model to automatically generate the optimal learning curriculum for each student.

[2385] Server: Saves the generated curriculum to the database.

[2386] Means of providing learning content and means of evaluating learning progress

[2387] Means of providing learning content

[2388] Device: When a student logs in and accesses their My Page, the server retrieves customized curriculum information and sends it to the device.

[2389] Terminal: Displays the curriculum and learning materials on the screen, allowing students to learn based on them.

[2390] Learning progress evaluation method

[2391] User (student): The student answers the practice questions and sends the results from their device to the server.

[2392] Server: The server analyzes the response results, updates the students' learning progress, and saves the evaluation results.

[2393] Emotion engines and the use of emotional data

[2394] How the emotion engine works

[2395] Device: Collects data such as facial expressions, voice, and behavior in real time as students learn, and sends it to the emotion engine.

[2396] Emotional Engine: Analyzes received data to identify the student's emotional state. For example, it analyzes excitement, concentration, fatigue, apathy, etc.

[2397] Use of emotional data

[2398] Server: Based on emotional data received from the emotion engine, it evaluates students' learning efficiency and dynamically adjusts learning content and delivery methods as needed.

[2399] Server: Emotional data is also sent to a teacher dashboard, enabling teachers to provide instruction based on students' emotional states.

[2400] Information provision means

[2401] Information provision to teachers

[2402] User (Teacher): The teacher logs into the administration panel and accesses the dashboard.

[2403] Terminal: Sends the teacher's request to the server.

[2404] Server: Retrieves the latest learning progress and sentiment data for each student and sends the aggregated dashboard data to the terminal.

[2405] Device: Displays a dashboard that allows teachers to see each student's learning progress and emotional state at a glance.

[2406] Specific example

[2407] For example, the following describes the process when the server determines a student's academic performance to be "intermediate" and the emotion engine recognizes the student's emotional state as "focused." The server generates a set of practice problems and explanatory videos appropriate for the intermediate level and delivers them to the student's device. The student then uses the provided materials to study and reports their progress and emotional state to the server. Meanwhile, the teacher monitors the student's learning progress and emotional state in real time through a dashboard and provides additional instruction as needed.

[2408] Example of a prompt

[2409] Examples of prompt statements to input into the generative AI model are shown below.

[2410] Prompt: If a student's academic performance is assessed as "intermediate" and the emotional engine recognizes them as "focused," please describe the specific processing steps for generating individualized curricula and utilizing emotional data.

[2411] In this way, this system can provide each student with an optimal learning environment and improve learning efficiency.

[2412] The flow of the specific processing in Example 2 will be explained using Figure 13.

[2413] Step 1:

[2414] Input: Student login information (username and password)

[2415] Process: The student enters their authentication information on the login screen.

[2416] Terminal: The terminal sends login information to the server.

[2417] Server: The server verifies the authentication information, and if authentication is successful, redirects the user to their My Page.

[2418] Output: Login success status and My Page URL

[2419] Step 2:

[2420] Input: URL of the student's academic assessment test page after successful login

[2421] Process: The student accesses the academic achievement test page.

[2422] Terminal: The terminal displays a button to start the test.

[2423] Output: Start Test button

[2424] Step 3:

[2425] Input: Click event of the test start button

[2426] Process: The student clicks the "Start Test" button.

[2427] User (student): The student clicks the "Start Test" button.

[2428] Server: The server sends the academic achievement test questions to the terminals.

[2429] Output: Questions from the academic achievement test

[2430] Step 4:

[2431] Input: Answer data for each question (text, multiple choice)

[2432] Processing: Students answer each question and input the answer data.

[2433] Terminal: The terminal sends the response data to the server.

[2434] User (student): The student answers each question.

[2435] Output: Response data

[2436] Step 5:

[2437] Input: Submitted response data

[2438] Processing: The server receives the response data and runs an analysis algorithm to evaluate the students' academic level.

[2439] Server: The server analyzes the response data, evaluates the academic level, and stores it in a database.

[2440] Output: Academic performance evaluation results

[2441] Step 6:

[2442] Input: Academic performance evaluation results and past learning history data

[2443] Processing: Based on academic performance assessment results and past learning history data, a generative AI model is used to automatically generate the optimal learning curriculum for each student.

[2444] Server: The server retrieves academic performance evaluation results and past learning history from the database and automatically generates the curriculum.

[2445] Output: Generated learning curriculum

[2446] Step 7:

[2447] Input: Generated learning curriculum

[2448] Process: Save the generated curriculum to the database.

[2449] Server: The server saves the generated curriculum to the database.

[2450] Output: Saved curriculum

[2451] Step 8:

[2452] Input: Access to the student's My Page

[2453] Processing: After the student logs in, they access their My Page.

[2454] Terminal: The terminal sends a request to the server to access the My Page.

[2455] Server: The server retrieves customized curriculum information from the database and sends it to the terminal.

[2456] Output: Customized curriculum information

[2457] Step 9:

[2458] Input: Customized curriculum information

[2459] Processing: The curriculum and learning materials are displayed on the screen, and students learn based on them.

[2460] Terminal: The terminal displays the curriculum and learning materials on its screen.

[2461] Output: Displayed curriculum and materials

[2462] Step 10:

[2463] Input: Data used by students to answer practice problems.

[2464] Processing: Students answer practice problems, and their progress is saved in real time on their devices.

[2465] Terminal: The terminal sends progress data to the server.

[2466] Output: Sending progress data

[2467] Step 11:

[2468] Input: Submitted practice problem answer data

[2469] Processing: The server analyzes the response results and updates the students' learning progress.

[2470] Server: The server saves the analysis progress data to the database.

[2471] Output: Updated progress data

[2472] Step 12:

[2473] Input: Student facial expressions, voice, and behavioral data during learning.

[2474] Processing: Data such as facial expressions, voice, and behavior are collected in real time as students learn and sent to the emotion engine.

[2475] Device: The device sends the collected data to the emotion engine.

[2476] Output: Sent sentiment data

[2477] Step 13:

[2478] Input: Emotional data analyzed by the emotion engine

[2479] Processing: The emotion engine analyzes the received data to identify the student's emotional state. For example, it analyzes excitement, concentration, fatigue, apathy, etc.

[2480] Emotional Engine: Analyzes emotional states.

[2481] Output: Emotional state data from the analysis results

[2482] Step 14:

[2483] Input: Emotion engine analysis results and student learning progress data

[2484] Processing: The server evaluates learning efficiency based on sentiment data and dynamically adjusts the learning content and delivery method as needed.

[2485] Server: Saves the adjusted learning content to the database.

[2486] Output: Adjusted learning content

[2487] Step 15:

[2488] Input: Adjusted learning content and emotional state data

[2489] Processing: The server reflects the information on the teacher's dashboard.

[2490] Server: Generates teacher dashboard data and sends it to the terminal.

[2491] Output: Sending dashboard data

[2492] Step 16:

[2493] Input: Generated dashboard data

[2494] Process: The teacher logs into the administration panel and accesses the dashboard.

[2495] Device: Displays a dashboard, allowing teachers to monitor each student's learning progress and emotional state.

[2496] Output: Displayed dashboard

[2497] (Application Example 2)

[2498] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2499] Conventional education systems and work equipment management systems require flexible responses tailored to the individual academic abilities, efficiency, and progress of students and work equipment. In particular, it is difficult to consider real-time factors such as emotions and fatigue, which can lead to delays in providing appropriate learning and training. Furthermore, it is difficult for instructors to provide accurate guidance based on the individual's condition. The objective of this invention is to solve these problems and provide an efficient and effective education and training system.

[2500] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[2501] In this invention, the server includes means for evaluating students' academic abilities, means for generating individual curricula based on the academic ability evaluation results, means for providing learning content based on the generated individual curricula, means for recording and evaluating students' learning progress, means for providing information to instructors based on the generated individual curricula and learning progress, means for collecting and evaluating the work efficiency and historical data of work equipment, means for generating training programs based on the evaluation results, means for analyzing the emotional state of work equipment, and means for providing information to instructors based on the emotional state and training program. This enables flexible and effective education and training based on the individual learning status and state of students and work equipment.

[2502] "Methods for evaluating academic ability" refer to systems or methods designed to assess students' academic abilities.

[2503] "Individualized curriculum generation means" refers to a system or method that automatically generates an optimal curriculum for a specific student based on the results of an academic performance assessment.

[2504] "Means of providing learning content" refers to a system or method that provides students with appropriate learning materials and problems based on a generated individual curriculum.

[2505] A "learning progress recording and evaluation means" is a system or method for recording students' learning status and evaluating their progress.

[2506] "Instructor information provision means" refers to a system or method that provides instructors with necessary information based on the generated individual curriculum and learning progress.

[2507] A "means for evaluating the work efficiency of work equipment" refers to a system or method for collecting and evaluating the work efficiency and historical data of work equipment.

[2508] "Training program generation means" refers to a system or method that generates an optimal training program based on the evaluation results of work equipment.

[2509] "Emotional state analysis means" refers to a system or method for analyzing the emotional state of work equipment and workers and collecting the data.

[2510] This invention provides a system that offers optimal education and training programs based on the individual academic abilities, work efficiency, and progress of students and work equipment. This system operates through the coordinated efforts of four entities: a server, terminals, users (students, workers, instructors), and an emotion engine.

[2511] System-wide configuration

[2512] The server includes means for evaluating academic ability, generating individual curricula, providing learning content, recording and evaluating learning progress, providing instructor information, evaluating the work efficiency of work equipment, generating training programs, and analyzing emotional states. By using this system, flexible and effective education and training based on the individual circumstances of students and work equipment becomes possible.

[2513] Methods for assessing academic ability and methods for generating individual curricula

[2514] Methods for assessing academic ability

[2515] Students' academic abilities will be assessed through online tests conducted via their devices.

[2516] The user (student) clicks the "Start Test" button and answers the questions presented by the server.

[2517] The server analyzes the response data, evaluates the academic level, and saves the results.

[2518] Individual Curriculum Generation Method

[2519] The server generates an optimal individual curriculum for each student based on their academic performance evaluation results and past learning history data.

[2520] The generated curriculum is stored in a database.

[2521] Means for providing learning content and means for recording and evaluating learning progress

[2522] Means of providing learning content

[2523] Students log in via their devices, and the server delivers customized curriculum information.

[2524] The device displays the provided curriculum and learning materials on its screen, and the user (student) learns based on them.

[2525] Learning progress recording and evaluation method

[2526] Users (students) view learning materials and work on practice problems.

[2527] The progress is recorded in real time by the device and sent to the server.

[2528] The server analyzes the response results, updates the learning progress, and saves the evaluation results.

[2529] Emotion engines and the use of emotional data

[2530] How the emotion engine works

[2531] The device collects facial expressions, voices, and behavioral data of students and workers in real time and transmits them to the emotion engine.

[2532] The emotion engine analyzes incoming data to identify emotional states (e.g., excitement, concentration, fatigue, indifference, etc.).

[2533] Use of emotional data

[2534] Based on emotional data received from the emotion engine, the server evaluates the learning and work efficiency of students and workers, and dynamically adjusts the learning and training content as needed.

[2535] Furthermore, emotional data is reflected in the instructor's dashboard, enabling instructors to provide guidance based on the emotional state of students and workers.

[2536] Means of providing information to leaders

[2537] Providing information to leaders

[2538] The instructor logs into the administration panel and sends a request to the server.

[2539] The server retrieves the latest learning progress and sentiment data for each student and work device, and provides the instructor with aggregated dashboard data.

[2540] The device displays a dashboard, allowing instructors to see each student's learning progress and emotional state at a glance.

[2541] Hardware and software used

[2542] Hardware: Devices used by students or workers (PCs, tablets), cameras and microphones for using the emotion engine, and management terminals for instructors.

[2543] Software: Evaluation algorithms using Python, database management system, and real-time sentiment analysis software (EmotionEngine).

[2544] Examples of specific cases and prompt statements

[2545] Specific example

[2546] The emotion engine analyzed student A's facial expressions and voice data while they were taking the online test and determined that they were fatigued. Based on this result, the server displayed a message on student A's device prompting them to take a break and made adjustments to ensure that their learning progress was maintained appropriately.

[2547] Example of a prompt

[2548] "Create a program that evaluates students' emotional states based on the following data and generates an optimal learning program. Sensor data includes temperature, work time, etc."

[2549] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[2550] Step 1:

[2551] When a user (student) logs in and accesses the academic achievement test page, the server displays the test start page. The input data is the student's login information, and the output data is the web page containing the test start button.

[2552] Step 2:

[2553] The user (student) clicks the test start button, and the server delivers the test questions. In this process, the input is the test start signal clicked by the student, and the output is the test questions.

[2554] Step 3:

[2555] The user (student) enters their answers to each test question and sends them from their terminal to the server. The input data is the student's answer information, and the output data is the answer result.

[2556] Step 4:

[2557] The server analyzes the received response data and evaluates the students' academic ability levels. The input data is the response data, and the output data is the evaluation of the students' academic ability. Specifically, it analyzes the accuracy rate of the answers and the response time.

[2558] Step 5:

[2559] The server generates an optimal individual curriculum for each student based on their academic performance evaluation results and past learning history data. The input data consists of academic performance evaluation results and past learning history data, while the output data is the generated individual curriculum.

[2560] Step 6:

[2561] When a user (student) logs in, the terminal receives and displays individual curriculum information provided by the server. The input data is curriculum information, and the output data is the displayed learning content.

[2562] Step 7:

[2563] Users (students) view the displayed learning content and materials and work on practice problems. Their progress is recorded in real time by the device and sent to the server. Input data consists of answers to practice problems and viewing history, while output data is the recorded progress.

[2564] Step 8:

[2565] The server analyzes the received progress data and evaluates the learning progress. The input data is the progress data, and the output data is the evaluated progress status.

[2566] Step 9:

[2567] The device collects facial expressions, voice, and behavioral...

Claims

1. Methods for evaluating students' academic abilities, A means of generating individualized curricula based on academic performance assessment results, A means of providing learning content based on a generated individual curriculum, A means of recording and evaluating students' learning progress, A means of providing information to teachers based on the generated individual curriculum and learning progress, A system that includes this.

2. The system according to claim 1, wherein the means for evaluating academic ability includes an online test taken by a student via a terminal.

3. The system according to claim 1, wherein the individual curriculum generation means generates a curriculum based on the student's academic performance evaluation results and past learning history stored in a database.

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