system

Abstract

Provide a system. A device for children to use to access learning materials; a server that receives the answers entered from the terminal and automatically grades them; means for receiving the scoring results from the server and displaying the results on the terminal; a server means for storing and analyzing the child's learning history; a means for notifying educators and parents of the analysis results from the server; The system includes a means for identifying areas of strength and weakness based on the learning history and analysis results.

Description

[Technical Field]

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

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

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

[0004] With traditional educational methods, when children completed homework or drills, their results could not be immediately confirmed, and feedback was often delayed. This meant that they could not immediately know whether their answers were correct, which led to problems such as delays in self-correction and retry, and a decrease in motivation to learn. It also increased the effort required for teachers and parents to track their children's progress, making the checking process less efficient. Furthermore, it was difficult to determine each child's strengths and weaknesses, making it difficult to provide educational support tailored to each individual. [Means for solving the problem]

[0005] To solve the above-mentioned problems, the present invention provides a system including a terminal on which a child works on study materials, a server that receives answers entered from the terminal and automatically grades them, a means for receiving the graded results from the server and displaying them on the terminal, a server that stores and analyzes the child's learning history, a means for notifying educators and parents of the analysis results from the server, and a means for identifying strong and weak areas based on the learning history and analysis results. This allows children to instantly know whether their answers are correct or incorrect, making it easy for them to retry or self-correct. Furthermore, educators and parents can efficiently grasp their children's progress, and by clearly identifying each child's strong and weak areas, they can provide appropriate educational support.

[0006] A "terminal" is an electronic device that displays learning materials, allows a child to enter answers, and communicates with a server to receive marks and feedback.

[0007] The "server" is a central processing unit that receives answers sent from the terminal, automatically grades them, returns the results to the terminal, saves and analyzes learning history, and notifies educators and parents.

[0008] "Learning materials" are content that includes problems and assignments for children to work through and are displayed by the device.

[0009] "Answer" refers to the answer that the child enters into the learning material using the terminal.

[0010] The "scoring result" is the result of the server determining whether the answer is correct or incorrect based on the answer, and is notified to the terminal.

[0011] A "learning history" is a record that includes data such as the learning materials a child has worked on, their answers, their grades, and the time it took to complete the answers.

[0012] The "analysis results" are analytical data such as the child's strengths and weaknesses, which are generated by the server based on the learning history.

[0013] "Educator" refers to a person or position that has a role in supporting children's learning, such as a teacher or instructor.

[0014] A "guardian" is a parent or other person who is responsible for supporting a child's learning and monitoring their progress.

[0015] "Feedback" refers to information that the server sends to the terminal, including whether the student's answer is correct or incorrect, additional comments, and hints.

[0016] A "retry" is an action in which a child can try the same problem again if the answer is incorrect. [Brief explanation of the drawings]

[0017] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0018] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0019] First, the terms used in the following description will be explained.

[0020] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0021] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0022] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0023] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0028] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0029] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0030] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0032] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0035] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0036] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0037] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0038] The detailed description of the invention provides a method for creating a system that allows children to engage with learning material, receive immediate feedback, and effectively manage their progress.

[0039] Configuration overview

[0040] The system consists of the following main components:

[0041] 1. Terminal

[0042] 2. Server

[0043] 3. Users (children, educators, parents)

[0044] Explanation of program processing

[0045] View learning materials

[0046] The device receives new learning materials sent from the server and displays a list of them to the child, who can then select and work on the learning materials on the device.

[0047] example:

[0048] When the server uploads a new math workbook, the device displays "New math workbook added," and the child taps it to open it.

[0049] Enter your answer

[0050] The child inputs answers to questions in the learning materials displayed on the device, and the device sends the input answers to the server.

[0051] example:

[0052] When the child enters "5+3=8" and presses the "Send" button, the device sends this answer to the server.

[0053] Automatic scoring

[0054] The server automatically determines whether the answer is correct or incorrect based on the answer received from the device, and sends the result back to the device.

[0055] example:

[0056] The server checks whether "8" is the correct answer and returns the result to the terminal, saying either "Correct!" or "Incorrect."

[0057] View Feedback

[0058] The device displays the score received from the server to the child, and if the answer is incorrect, the device provides additional hints and explanations to the child.

[0059] example:

[0060] The device will display "That's right!" or "That's wrong. Try again," and if the answer is incorrect, it will provide a hint such as "Try counting again."

[0061] Doing it over and trying again

[0062] The child can retry any questions they got wrong and enter their answer, and the process repeats until they get it right.

[0063] example:

[0064] This is repeated until the child types in "7" to confirm the answer is incorrect and then types in "8" again to confirm the answer is correct.

[0065] Save learning history

[0066] The server stores data such as each child's answer history, correct answers, and answer time, which will be used for later analysis.

[0067] example:

[0068] The server stores detailed history for Child A, such as "Question 1: 5+3, correct answers: 8, number of incorrect answers: 1, number of correct answers: 1, answer time: 15 seconds."

[0069] Progress check and analysis results notification

[0070] Educators or parents can check their children's learning history through a dedicated management screen. The server generates and notifies the results of analysis.

[0071] example:

[0072] When an educator checks Child A's progress on the management screen, the server displays a list of Child A's grades and history. In addition, the server generates and notifies the educator of analysis results such as, "Child A is good at calculation problems in mathematics, but not at word problems."

[0073] Effects of implementation

[0074] By implementing this system, children can instantly know whether their answers are correct or incorrect, allowing them to study efficiently. In addition, educators and parents can easily understand their children's progress and provide appropriate feedback and support. By clarifying each child's strengths and weaknesses, the quality of education can be improved.

[0075] In this way, the system based on the aspects of the present invention is expected to solve multiple problems in educational settings and provide effective learning support.

[0076] The processing flow will be explained below.

[0077] Step 1: Upload your study materials

[0078] The server receives an upload request from an educator or system administrator. The server stores the learning material file (e.g., math drills) and associates it with each child's account. After saving, it sends a notification to the device that the upload is complete.

[0079] Step 2: View study materials

[0080] The device receives notifications of new learning materials from the server, and the user (child) selects what to work on from the list of new learning materials displayed on the device.

[0081] Step 3: Enter your answers

[0082] The user (child) enters answers to questions displayed on the terminal. The terminal sends the entered data to the server. After sending, the terminal either moves on to the next question or waits for a response.

[0083] Step 4: Automated scoring

[0084] The server analyzes the received answer, compares it with the correct answer database, and determines whether it is correct or incorrect. The server generates a judgment result (correct or incorrect) and returns it to the terminal.

[0085] Step 5: Receive and view feedback

[0086] The device receives the scoring results sent from the server. It displays the received results to the user. If the answer is correct, it prompts the user to check their progress or move on to the next step. If the answer is incorrect, it displays additional hints or explanations.

[0087] Step 6: Doing a rework

[0088] If the user (child) answers incorrectly, they can try the same question again. They receive the same answer and enter the answer again. The device then sends the new answer to the server again.

[0089] Step 7: Save your data

[0090] The server stores each user's learning history in a database, including details such as the questions answered, the answers, whether they were correct or incorrect, the time it took to answer, the number of attempts, etc. The stored data is used for later analysis.

[0091] Step 8: Review progress and provide feedback

[0092] The user (educator or guardian) sends a request to the server to check the learning history through a dedicated management screen. The server analyzes the saved learning history and displays it on the management screen. It also notifies the educator or guardian of the analysis results.

[0093] Step 9: Strengths and weaknesses analysis and notification

[0094] The server analyzes learning history data to identify each user's strengths and weaknesses. The analysis results are communicated through a dedicated management screen, allowing educators and parents to understand each child's progress and learning needs.

[0095] The above processing steps enable efficient operation of the system. Children can instantly know their results, and educators and parents can easily check detailed progress. This allows for effective educational support.

[0096] Example 1

[0097] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0098] With conventional learning support systems, feedback when children are working on learning materials tends to be delayed, making it difficult to confirm answers or provide feedback in real time. Furthermore, the means by which educators and parents can check learning histories and analysis results are limited, making it difficult to grasp each child's learning progress and strengths and weaknesses. This makes it difficult to provide support at the appropriate time, resulting in problems such as reduced learning efficiency.

[0099] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0100] In this invention, the server includes an information terminal for the child to use to study materials, an information processing device that receives answers entered from the information terminal and automatically judges them, means for receiving the judgment results from the information processing device and displaying the results on the information terminal, information processing device means for saving and analyzing the child's study history, means for notifying educators and parents of the analysis results from the information processing device, means for identifying areas of strength and weakness based on the study history and the analysis results, means for the child to select from study materials displayed on the information terminal, means for displaying additional hints and explanations when an incorrect answer is given, and means for the child to try again and transmit the study history to the information processing device. This allows the child to study efficiently while receiving feedback in real time, and allows educators and parents to provide support and feedback at appropriate times.

[0101] An "information terminal" is a device that allows a user to work through study materials and input answers.

[0102] An "information processing device" is a device that receives the answer sent from the information terminal, automatically judges it, and returns the result.

[0103] "Learning history" refers to recorded data such as the content of answers, whether they were correct or incorrect, and the time it took to answer when a child worked on learning materials.

[0104] The "analysis results" are data generated based on the learning history to identify the child's strengths and weaknesses.

[0105] "Educators and parents" refers to those responsible for overseeing a child's learning and providing support where necessary.

[0106] "Real-time feedback" refers to the ability to instantly provide a correct or incorrect answer, and possibly additional hints or explanations, immediately after a child enters their answer.

[0107] The "retry feature" is a function that allows a child to try again on a question that was answered incorrectly.

[0108] "Storage means" refers to a function for long-term storage of answers entered by children and their learning history.

[0109] "Notification means" refers to a function for notifying educators and parents of the analysis results from the server.

[0110] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described in detail below with reference to the accompanying drawings.

[0111] System configuration

[0112] The system consists of the following main components:

[0113] 1. Terminal (information terminal)

[0114] 2. Server (information processing device)

[0115] 3. Users (children, educators, parents)

[0116] Hardware and software used

[0117] Device: This is the information device used by the child, such as a PC or tablet, which displays learning materials and inputs answers.

[0118] Server: An information processing device that receives, stores, processes data from users, and generates analytical results. The server is equipped with a database and AI model.

[0119] Software: An automatic scoring algorithm implemented in Python, database management software, and a web application providing the user interface.

[0120] Data processing and calculation

[0121] The terminal does the following:

[0122] 1. Receive learning materials sent from the server and display them to the user (child).

[0123] 2. The answer entered by the user (child) is sent to the server.

[0124] 3. The scoring results received from the server are displayed to the user (child).

[0125] The server does the following:

[0126] 1. The answers received from the device are judged by an automatic scoring algorithm.

[0127] 2. The scoring results are returned to the device.

[0128] 3. The received answer data and scoring results are stored in a database.

[0129] 4. Analyze your learning history and identify your strengths and weaknesses.

[0130] 5. Notify educators and parents of the analysis results.

[0131] Specific examples

[0132] When the server uploads a new math workbook, the device will notify the user that a new math workbook has been added. The child can tap the new workbook to open it and work on the problems. For example, if the child types "5+3=8" and presses the "Submit" button, the device will send the answer to the server.

[0133] The server uses an AI model implemented in Python to check whether the received answer "8" is correct. The server then sends the result "Correct!" to the device. The device displays "Correct!" or "Incorrect. Let's try again," and if the answer is incorrect, provides a hint such as "Try counting again."

[0134] Educators or parents can check their children's learning history through a dedicated management screen. The server generates analysis results such as "Child A is good at math calculation problems but not at word problems."

[0135] Prompt Sentence Examples

[0136] Below are some example prompts to input to a generative AI model:

[0137] "Generate 10 math problems."

[0138] "Based on the child's answers, identify areas of weakness and generate hints for them."

[0139] "Implement a system that analyzes learning progress in real time and provides feedback."

[0140] Although the embodiments of the present invention have been described above, many other variations are possible in the specific implementation methods. Various changes and modifications are possible within the scope of the present invention, and these are also included.

[0141] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0142] Step 1: Receive and view study materials

[0143] The server generates new learning materials (e.g., math drills) and sends them to the terminal. The terminal displays the received learning materials to the user (child). The user (child) selects the learning material to work on from the materials.

[0144] Input: Study material data sent from the server

[0145] Output: A list of study materials displayed on the device screen

[0146] Specific behavior: When the server uploads a new math workbook, the device notifies the user that "A new math workbook has been added," and the user (child) taps it to open it.

[0147] Step 2: Enter and submit your answers

[0148] The user (child) inputs answers to questions in the study materials displayed on the terminal, and the terminal then sends the answers to the server.

[0149] Input: Answer data entered by the user (child)

[0150] Output: Answer data sent from the device to the server

[0151] Specific operation: When the user (child) enters "5+3=8" and presses the "Send" button, the device sends this answer data to the server.

[0152] Step 3: Automated scoring

[0153] The server uses a generative AI model to automatically determine whether the answer received from the device is correct or incorrect, and the result is sent back to the device.

[0154] Input: Answer data sent from the device

[0155] Output: The score results sent back from the server to the device

[0156] Specific operation: The server uses an AI model implemented in Python to check whether the received answer "8" is correct. The server then sends the result "That's correct!" to the device.

[0157] Step 4: View your feedback

[0158] The terminal displays the score received from the server to the user (child). If the answer is incorrect, the terminal provides additional hints and explanations to the user (child).

[0159] Input: The score returned from the server

[0160] Output: Feedback displayed on the device screen

[0161] Specific behavior: The device will display "Correct!" or "Incorrect. Try again," and if the answer is incorrect, it will provide a hint such as "Try counting again."

[0162] Step 5: Try again and try again

[0163] The user (child) revisits the questions that were answered incorrectly and enters the answer, and this process is repeated until the correct answer is obtained.

[0164] Input: Answer data re-entered by the user (child)

[0165] Output: Answer data sent from the device to the server, and new scoring results returned from the server.

[0166] Specific operation: The user (child) enters "7" and is incorrect, then repeats this operation until they enter "8" again and confirm the correct answer.

[0167] Step 6: Save your learning history

[0168] The server stores data on each user (child), such as answer history, correct answers, and answer time. This data is used for later analysis.

[0169] Input: User (child) answer data and scoring result data

[0170] Output: Learning history stored in the server database

[0171] Specific operation: The server stores detailed history in a database, such as "Question 1: 5+3, correct answers: 8, number of incorrect answers: 1, number of correct answers: 1, answer time: 15 seconds."

[0172] Step 7: Check progress and communicate analysis results

[0173] Educators or parents can check the learning history of users (children) through a dedicated management screen. The server generates and notifies the results of analysis.

[0174] Input: Learning history data stored on the server

[0175] Output: Analysis results displayed on the educator and parent management screen

[0176] Specific operation: The educator logs in to the management screen and checks the progress of Child A. The server displays the analysis results on the management screen, such as "Child A is good at math calculation problems, but not so good at word problems."

[0177] (Application example 1)

[0178] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0179] Learning to operate robots in factories is difficult for operators due to the complex procedures and high precision required. Conventional training methods make it difficult for operators to immediately grasp their own progress, and the slow feedback reduces efficiency. It is also difficult for managers to quickly identify an operator's strengths and weaknesses and provide appropriate guidance. Therefore, there is a need for a system that allows operators to efficiently learn robot operation procedures, receive instant feedback, and allow managers to easily grasp their progress.

[0180] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0181] In this invention, the server includes a terminal on which an operator works on the operation procedures, means for receiving answers entered from the terminal and automatically grading them, means for receiving the grading results from the server and displaying the results on the terminal, means for saving and analyzing the learning history of the operator, means for notifying an administrator of the analysis results from the server, and means for identifying areas of strength and weakness based on the learning history and the analysis results. This allows the operator to efficiently learn the robot operation procedures and receive immediate feedback, and also enables the administrator to easily understand the progress and provide appropriate guidance.

[0182] "Operator" refers to the person in charge of operating and training the robot within the factory.

[0183] A "terminal" refers to an information processing device used by an operator, such as a smartphone, tablet, or head-mounted display.

[0184] "Solution" refers to the result or answer that an operator enters when working through an operating procedure.

[0185] The "server" is a central processing unit that receives answers from operators, automatically grades them, and sends back feedback.

[0186] "Scoring" refers to the process of determining whether an operator's answer is correct.

[0187] "Feedback" refers to information about whether an answer is correct or incorrect, as well as additional advice and hints, sent from the server to the operator.

[0188] "Learning history" refers to data such as the operator's answer history, correct answers, and answer time.

[0189] "Analysis results" refers to information such as areas of strength and weakness that is generated by the server based on learning history.

[0190] "Supervisor" refers to the person in charge of the factory who monitors the progress of the operators and provides appropriate guidance.

[0191] "Notification" refers to the process by which the server communicates important information such as analysis results and operator progress to the administrator.

[0192] As an embodiment of the present invention, a method for constructing a system that enables operators in a factory to learn robot operation procedures, receive immediate feedback, and efficiently manage the progress will be described below.

[0193] Configuration overview

[0194] The system consists of the following main components:

[0195] 1. Terminal

[0196] 2. Server

[0197] 3. User (operator, administrator)

[0198] Explanation of program processing

[0199] Displaying operating instructions

[0200] The server sends new operation procedures to the terminal, which displays a list of them, allowing the operator to select and execute the operation procedure on the terminal.

[0201] Examples:

[0202] When the server uploads a new robot configuration procedure, the terminal displays "New robot configuration procedure added," and the operator taps it to open it.

[0203] Enter your answer

[0204] The operator inputs answers to the operating procedures displayed on the terminal, and the terminal sends the input answers to the server.

[0205] Examples:

[0206] When the operator types "Turn on the robot" and presses the "Send" button, the terminal sends this answer to the server.

[0207] Automatic scoring

[0208] The server automatically determines whether the answer is correct or incorrect based on the answer received from the device, and sends the result back to the device.

[0209] Examples:

[0210] The server checks whether "Turn on the robot" is the correct answer and returns the result to the terminal, saying "Correct!" or "Incorrect."

[0211] View Feedback

[0212] The terminal displays the score received from the server to the operator. If the answer is incorrect, the terminal provides additional hints and explanations to the operator.

[0213] Examples:

[0214] The device will display "That's right!" or "That's wrong. Try again," and if the answer is incorrect, it will provide a hint such as "Check the detailed instructions and try again."

[0215] Doing it over and trying again

[0216] The operator retrys the incorrect operation sequence and enters the answer, and this process is repeated until the correct answer is obtained.

[0217] Examples:

[0218] The operator types "start robot" which is an incorrect answer, and then types "power on robot" again, repeating this process until the correct answer is confirmed.

[0219] Save learning history

[0220] The server stores data such as each operator's answer history, correct answers, and answer time, which will be used for later analysis.

[0221] Examples:

[0222] The server stores detailed history of operator A, such as "Step 1: Turn on the robot, correct, number of incorrect answers: 1, number of correct answers: 1, response time: 15 seconds."

[0223] Progress check and analysis results notification

[0224] Administrators can check the learning history of operators through a dedicated management screen. The server generates and notifies the results of the analysis.

[0225] Examples:

[0226] When the administrator checks the progress of Operator A on the management screen, the server displays a list of Operator A's performance and history. In addition, the server generates and notifies the administrator of the results of an analysis, such as "Operator A is good at setting up the robot, but is not good at emergency shutdown procedures."

[0227] Hardware and software used

[0228] This system mainly uses the following hardware and software:

[0229] Hardware: Devices such as smartphones, tablets, and head-mounted displays.

[0230] Software: Server-side program using Python, terminal application for displaying operation procedures.

[0231] Example prompts to input to the generative AI model

[0232] The following is a prompt to input to a generative AI model (e.g. ChatGPT®):

[0233] "Generate guidelines for learning troubleshooting steps and getting immediate feedback for a factory robotics training application. Include the following steps:

[0234] 1. Check for abnormal robot stoppage

[0235] 2. Analysis of abnormal code

[0236] 3. Take any necessary corrective steps

[0237] 4. Check for proper operation

[0238] Please also include any explanations or advice you would like to give the operator at each step.

[0239] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0240] Step 1:

[0241] The server sends the new operating procedure to the terminal. Specifically, the server retrieves the new operating procedure from the operating procedure database and sends it to the terminal. The terminal receives this data and displays a list of operating procedures to the operator. The input information is the new operating procedure, and the output result is the list of operating procedures displayed on the operator's terminal.

[0242] Step 2:

[0243] The operator selects the item they want to learn from the operating procedures displayed on the terminal. Specifically, when the operator taps or selects an item, the terminal notifies the server of the selected operating procedure. The input information is the operating procedure selected by the operator, and the output result is a notification of the selected item to the server.

[0244] Step 3:

[0245] The server sends specific tasks related to the selected operating procedure to the terminal. Specifically, the server retrieves task details corresponding to the selected operating procedure from the database and sends them to the terminal. The terminal receives this data and displays the tasks to the operator. The input information is the selected operating procedure, and the output result is the task details displayed on the operator's terminal.

[0246] Step 4:

[0247] The operator inputs answers to each task displayed on the terminal. Specifically, the operator enters the answer in the input field and presses the send button, which causes the terminal to send the answer to the server. The input information is the answer entered by the operator, and the output result is the answer sent to the server.

[0248] Step 5:

[0249] The server automatically scores the received answers. Specifically, the server compares the answer data with a database of correct answers to determine whether they match. The input information is the operator's answer data, and the output is a judgment result of whether the answer is correct or incorrect.

[0250] Step 6:

[0251] The server sends the scoring results to the terminal. Specifically, the server generates a judgment result and sends it to the terminal. The terminal receives this data and displays the scoring results to the operator. The input information is the scoring result data, and the output is the scoring result display on the operator's terminal.

[0252] Step 7:

[0253] If the answer is incorrect, the terminal provides the operator with additional hints and explanations. Specifically, the terminal retrieves appropriate hints and explanations from a feedback database for incorrect answers and displays them to the operator. The input information is the result of the incorrect answer determination, and the output is the hint or explanation displayed on the operator terminal.

[0254] Step 8:

[0255] The operator attempts the task again if the answer was incorrect and re-enters the answer. Specifically, the operator re-enters the answer and presses the send button, causing the terminal to send the new answer to the server. The input information is the re-entered answer, and the output result is the re-sent answer sent to the server.

[0256] Step 9:

[0257] The server stores each operator's learning history, including answer history, correct / incorrect answers, and answer time. Specifically, answer data and scoring results are recorded in a database. Input information is the operator's answer history data, and output results are stored in the database.

[0258] Step 10:

[0259] The server displays the saved learning history and analysis results in response to a request from an administrator. Specifically, the server receives the administrator's request through the management screen, retrieves the saved data from the database, generates the analysis results, and displays them on the management screen. The input information is the administrator's request, and the output is the analysis results displayed on the management screen.

[0260] The above is the specific processing flow of the factory robot operation training system.

[0261] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0262] As an embodiment of the invention, the following describes how an emotion engine that recognizes user emotions can be incorporated into a system that allows children to engage with learning material and receive instant feedback to effectively manage their progress.

[0263] Configuration overview

[0264] The system consists of the following main components:

[0265] 1. Device (with emotion engine)

[0266] 2. Server

[0267] 3. Users (children, educators, parents)

[0268] Explanation of program processing

[0269] View learning materials

[0270] The terminal receives new learning materials sent from the server and displays a list of them to the child. The user (child) can select learning materials to work on on the terminal.

[0271] example:

[0272] When the server uploads a new math workbook, the device displays "New math workbook added," and the child taps it to open it.

[0273] Enter your answer

[0274] The child inputs answers to questions in the learning materials displayed on the device, and the device sends the input answers along with emotional data analyzed by the emotion engine to the server.

[0275] example:

[0276] When the child enters "5+3=8" and presses the "Send" button, the device sends this answer along with the current emotional data (e.g., confidence, joy) analyzed by the emotion engine to the server.

[0277] Automatic scoring

[0278] The server automatically determines whether the answer is correct or incorrect based on the answer received from the device, and sends the result along with the emotion data back to the device.

[0279] example:

[0280] The server checks whether "8" is the correct answer and returns the result to the terminal along with emotional data, saying "That's correct!" or "That's incorrect."

[0281] Receiving and viewing feedback

[0282] The device receives the score and emotion data sent from the server and displays them to the user. If the answer is incorrect, the device provides additional hints and explanations to the child and displays feedback according to the emotion provided by the emotion engine.

[0283] example:

[0284] The device will display "That's right!" or "That's wrong. Let's try again." If the answer is incorrect, the device will provide a hint like "Try counting again," as well as emotional feedback like "Remain calm and try again."

[0285] Doing it over and trying again

[0286] If the child answers incorrectly, they can try the same question again and send a new answer along with their emotional data to the server.

[0287] example:

[0288] The process repeats until the child enters "7" to confirm the answer is incorrect and then enters "8" again to confirm the answer is correct. Emotional data is also sent each time.

[0289] Data storage

[0290] The server stores each user's learning history and emotional data in a database, including details such as the questions answered, the answers, whether they were correct or incorrect, the time it took to answer, the number of retries, and emotional data. The stored data is used for later analysis.

[0291] example:

[0292] The server stores detailed history for Child A, such as "Question 1: 5+3, correct answers: 8, number of incorrect answers: 1, number of correct answers: 1, answer time: 15 seconds, emotional data: joy."

[0293] Progress review and feedback

[0294] Educators or parents can send a request to the server to check the learning history and emotional data through a dedicated management screen. The server analyzes the saved learning history and displays it on the management screen. It also notifies the educator or parent of the results of the analysis.

[0295] example:

[0296] When an educator checks Child A's progress on the management screen, the server displays a list of Child A's grades, history, and emotional data. The server also generates and notifies the educator of analysis results such as, "Child A is good at math calculation problems, but struggles with word problems and appears unsure of his or her answers."

[0297] Effects of implementation

[0298] By implementing this system, children can instantly know whether their answers are correct or incorrect and receive appropriate feedback based on their emotions. Educators and parents can understand detailed progress and emotional states, allowing them to provide more effective support. By clarifying each child's strengths and weaknesses, as well as their emotions at any given time, it is expected that the quality of education will be improved.

[0299] In this way, the system based on the aspects of the present invention is expected to solve multiple problems in educational settings and provide effective learning support.

[0300] The processing flow will be explained below.

[0301] Step 1: Upload your study materials

[0302] The server receives an upload request from an educator or system administrator. The server stores the learning material file (e.g., math drills) and associates it with each child's account. After the file is saved, it sends a notification to the device that the upload is complete.

[0303] Step 2: View study materials

[0304] The device receives notifications of new learning materials from the server, and the user (child) selects what to work on from the list of new learning materials displayed on the device.

[0305] example:

[0306] When the server uploads a new math workbook, the device displays "New math workbook added," and the user taps it to open it.

[0307] Step 3: Start Emotion Recognition

[0308] The device's built-in emotion engine analyzes data such as the child's facial expressions, voice, and touch pressure in real time to generate current emotion data (e.g., excitement, concentration, confusion).

[0309] example:

[0310] The device instructs the user to "relax and take a deep breath before you begin this problem," while the emotion engine collects data.

[0311] Step 4: Enter your answers

[0312] The user (child) inputs answers to questions displayed on the device. Emotional data is also continuously collected. The device transmits the input answers and emotional data to the server.

[0313] example:

[0314] When a child enters "5+3=8" and presses the "Send" button, the device sends this answer along with emotional data (e.g., confidence, joy) to the server.

[0315] Step 5: Automated scoring

[0316] The server automatically determines whether the answer is correct or incorrect based on the answer received from the device, and sends the result along with the emotion data back to the device.

[0317] example:

[0318] The server checks whether "8" is the correct answer and returns the result to the terminal along with emotional data, saying "That's correct!" or "That's incorrect."

[0319] Step 6: Receive and view feedback

[0320] The device receives the score and emotion data sent from the server and displays them to the user. If the answer is incorrect, the device provides additional hints and explanations to the child and displays feedback according to the child's emotion.

[0321] example:

[0322] The device will display "That's right!" or "That's wrong. Let's try again." If the answer is incorrect, the device will provide hints such as "Try counting again," as well as emotional feedback such as "Remain calm and try again."

[0323] Step 7: Doing a rework

[0324] If the user (child) answers incorrectly, they can try the same question again and send a new answer along with their emotion data to the server.

[0325] example:

[0326] The process repeats until the child enters "7" to confirm the answer is incorrect and then enters "8" again to confirm the answer is correct. Emotional data is also sent each time.

[0327] Step 8: Save your data

[0328] The server stores each user's learning history and emotional data in a database, including details such as the questions answered, the answers, whether they were correct or incorrect, the time it took to answer, the number of retries, and emotional data. The stored data is used for later analysis.

[0329] example:

[0330] The server stores detailed history for Child A, such as "Question 1: 5+3, correct answers: 8, number of incorrect answers: 1, number of correct answers: 1, answer time: 15 seconds, emotional data: joy."

[0331] Step 9: Review progress and provide feedback

[0332] The user (educator or parent) sends a request to the server to check the learning history and emotional data through a dedicated management screen. The server analyzes the saved learning history and displays it on the management screen. It also notifies the educator or parent of the analysis results.

[0333] example:

[0334] When an educator checks Child A's progress on the management screen, the server displays a list of Child A's grades, history, and emotional data. The server also generates and notifies the educator of analysis results such as, "Child A is good at math calculation problems, but struggles with word problems and appears unsure of his or her answers."

[0335] Effects of implementation

[0336] By implementing this system, children can instantly know whether their answers are correct or incorrect and receive appropriate feedback based on their emotions. Educators and parents can understand detailed progress and emotional states, allowing them to provide more effective support. By clarifying each child's strengths and weaknesses, as well as their emotions at any given time, it is expected that the quality of education will be improved.

[0337] In this way, the system based on the aspects of the present invention is expected to solve multiple problems in educational settings and provide effective learning support.

[0338] Example 2

[0339] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0340] In traditional educational systems, it is difficult for children to receive immediate feedback when working on learning materials. Furthermore, feedback provided does not take into account the child's emotional state, which can lead to a decrease in motivation to learn and increased stress. Educators and parents are unable to grasp a child's learning progress and emotional state in real time, making it difficult to provide appropriate support. This makes it difficult to identify individual children's strengths and weaknesses and provide effective educational support.

[0341] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving answers entered from the terminal and emotion data analyzed by the emotion engine, means for automatically scoring based on the answers and generating scoring results including emotion data, and means for receiving the scoring results from the server and displaying the results on the terminal. This allows children to instantly receive feedback based on their answers and emotions. Furthermore, educators and parents can grasp children's learning progress and emotional state in real time and provide more effective support.

[0342] "Devices" refer to electronic devices that children use to engage with learning materials and are equipped with emotion engines that can analyze emotional data.

[0343] "Answer" refers to a child's input to the study material, which is sent to the server for validation.

[0344] An "emotion engine" refers to an algorithm or software that analyzes emotions from a user's facial expressions, voice, etc.

[0345] "Emotion data" refers to data relating to the user's emotional state obtained as a result of analysis by the emotion engine.

[0346] "Server" refers to a computer system that automatically grades answers, stores and analyzes learning history and emotional data.

[0347] "Scoring result" refers to the result of whether the answer is correct or incorrect as determined by the server based on the child's answer.

[0348] "Feedback" refers to hints, encouragement, explanations, etc. that are displayed on the device based on the answer results and emotional data.

[0349] "Educators and parents" refers to adults who supervise a child's learning progress and provide appropriate support.

[0350] "Learning history" refers to a detailed record of the learning materials a child has worked on, their answers, whether correct or incorrect, how long it took to answer, and emotional data.

[0351] "Analysis results" refers to the results of analysis performed by the server based on learning history and emotional data.

[0352] "Strengths and weaknesses" refers to the range of learning content in which a child excels or struggles.

[0353] As an embodiment of the present invention, a method for incorporating an emotion engine that recognizes user emotions into a system for children to work on learning materials, receive instant feedback, and efficiently manage their progress is described below. The system is composed of terminals, a server, and users (children, educators, and parents).

[0354] Hardware and Software Used

[0355] Device: Tablet or PC equipped with emotion engine (e.g. iPad (registered trademark), Chromebook)

[0356] Server: Learning materials management and database (e.g., AWS (registered trademark) EC2, MySQL (registered trademark))

[0357] Sentiment engine: AI algorithms for sentiment analysis (e.g., Azure® Cognitive Services)

[0358] System Operation Overview

[0359] 1. The server manages the learning materials uploaded by the educator and sends them to the terminal.

[0360] 2. The terminal displays the learning materials received from the server to the child, and the child works on the learning materials.

[0361] 3. The child enters the answer to the study question, and the device sends the answer along with the emotional data analyzed by the emotion engine to the server.

[0362] 4. The server automatically scores the received answers and generates scoring results that include emotion data.

[0363] 5. The device receives the score and emotion data sent from the server and displays them to the child. Based on the emotion data, the device provides additional feedback.

[0364] 6. The server stores learning history and emotional data, and based on this identifies strengths and weaknesses in each area.

[0365] 7. Educators and parents can check learning history and analysis results through the management screen and provide effective support to their children.

[0366] Specific examples

[0367] Example 1: When the server uploads a new math workbook, the device displays "A new math workbook has been added," and the child taps it to open it. When the child enters "5+3=8" and presses the "Send" button, the device sends this answer along with emotional data (e.g., confidence, joy) to the server.

[0368] Example 2: The server checks the answer "8" and, since it is correct, sends the message "That's right!" along with emotional data to the device. The device then displays "That's right! You seem confident!" If the answer is incorrect, it provides feedback such as "Think about it again" or "Calm down and try again."

[0369] Example 3: When an educator checks a child's progress on the management screen, the server displays a list of the child's grades, history, and emotional data, and notifies them of the analysis results, such as "Child A is good at math calculation problems but not so good at word problems."

[0370] Example prompts to input to the generative AI model

[0371] "How can I be notified when new learning materials are added?"

[0372] "Please explain the process for sending the answers entered by the child to the server."

[0373] "Please explain in detail how the server scores the answers and returns the results."

[0374] By building such a system, children can efficiently understand their learning content and receive appropriate emotional feedback, allowing educators and parents to monitor their learning progress in detail and provide support tailored to each individual child.

[0375] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0376] Step 1:

[0377] The server receives the learning materials uploaded by the educator, which are stored in a database and ready to be sent to the device.

[0378] Input: Learning materials uploaded by educators (e.g., math drills)

[0379] Output: The learning materials are saved in a database ready to be sent to the device.

[0380] Specific operation: The server receives PDF files and digital text format learning materials added by educators, stores them in a database, and then generates a material ID and metadata and notifies the device.

[0381] Step 2:

[0382] The terminal displays the new learning materials received from the server to the child.

[0383] Input: Learning material notification from the server (e.g., notification of new math drills added)

[0384] Output: A list of study materials will be displayed on the child's device screen.

[0385] Specific behavior: A notification saying "New math drills have been added" will be displayed on the device screen, and users can tap to access the content.

[0386] Step 3:

[0387] The user (child) inputs answers to questions in the study materials displayed on the device. At the same time, the device generates emotion data analyzed by the emotion engine.

[0388] Input: The answer entered by the child (e.g. 5+3=8)

[0389] Output: Answer and emotion data are generated (e.g., confidence, joy)

[0390] Specific operation: When a child enters an answer and presses the send button, the device's built-in camera and microphone are activated to analyze facial expressions and voice and generate emotional data.

[0391] Step 4:

[0392] The terminal transmits the answer and emotion data to the server.

[0393] Input: Child's answers and emotion data

[0394] Output: Answers and emotion data are sent to the server

[0395] Specific operation: The device combines the answer and emotion data into a single data packet, encrypts it, and sends it to the server.

[0396] Step 5:

[0397] The server automatically determines whether the answer received from the terminal is correct or incorrect and generates a scoring result that includes emotional data.

[0398] Input: Answers and emotion data sent from the device

[0399] Output: Scoring results and emotional feedback data

[0400] What it does: The server's algorithm scores the answers, generates a "correct" or "incorrect" result, and creates a feedback message with emotional data.

[0401] Step 6:

[0402] The server returns the scoring results and emotion data to the terminal.

[0403] Input: Scoring results and emotional feedback data

[0404] Output: Feedback data sent to the device

[0405] Specific operation: The server compiles the scoring results and the emotion feedback message into a data packet and sends it to the device.

[0406] Step 7:

[0407] The device receives the score and emotion data sent from the server and displays them to the user (child). If the answer is incorrect, the device also provides additional hints and emotion-based feedback.

[0408] Input: Scoring results and emotional feedback data sent from the server

[0409] Output: Feedback displayed on the terminal screen

[0410] What it does: Show feedback on the device screen, such as "That's right!", "You look confident!", or "Think again" or "Calm down and try again."

[0411] Step 8:

[0412] If the user (child) answers incorrectly, they can try the same question again.

[0413] Input: New answer and emotion data

[0414] Output: Retry data sent to the server

[0415] What it does: If the child enters a different answer and submits it again, the new answer and emotion data are sent to the server and re-evaluated.

[0416] Step 9:

[0417] The server stores each user's learning history and emotional data in a database.

[0418] Input: Answers, emotion data, scoring results

[0419] Output: Saved learning history and emotion data

[0420] Specific operation: The server stores detailed data such as "question ID, answer, correct / incorrect answer, number of times, time, emotional data" in a database.

[0421] Step 10:

[0422] The server displays the saved learning history and emotional data on the management screen in response to requests from educators or parents, and also notifies them of the analysis results.

[0423] Input: History view request from educator or parent

[0424] Output: Learning history and analysis results displayed on the management screen

[0425] Specific operation: The server receives the request, extracts and analyzes the necessary data, and displays the analysis results on the management screen, such as "Child A is good at math calculation problems but not at word problems."

[0426] (Application example 2)

[0427] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0428] While immediate feedback and correct answers are important for children's learning, conventional systems do not provide support that takes into account the child's emotional state. This can lead to children feeling stressed and frustrated, which can decrease their motivation to learn. It is also difficult for educators and parents to properly understand a child's progress and emotional state and provide effective support.

[0429] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0430] In this invention, the server includes a means for receiving answers entered from the terminal and automatically scoring them, an emotion recognition means for the terminal to recognize the child's emotions and send the data to the server, and a means for receiving the scoring results and emotion data from the server and displaying the results on the terminal. This makes it possible to grasp the emotional state of a child while they are learning in real time and provide appropriate feedback. Furthermore, educators and parents can grasp the child's detailed progress and emotional state and provide more effective support.

[0431] A "terminal" is a device for displaying study materials and inputting user answers.

[0432] A "server" is a central computer system that receives data sent from terminals and processes and analyzes it.

[0433] The "emotion recognition means" has the function of analyzing the child's facial expressions and behavior and determining their emotional state.

[0434] The "feedback generation means" is a function for generating appropriate feedback to the child based on whether the answer is correct or incorrect.

[0435] "Learning history" is a record of data such as the learning materials a child has worked on, the content of their answers, the time it took to answer, and whether they were correct or incorrect.

[0436] "Analysis results" are the results of analysis using statistical and machine learning methods based on learning history and emotional data.

[0437] An "educator" is someone who provides educational guidance to children, i.e., a teacher or instructor.

[0438] A "guardian" is a parent or caregiver who oversees a child's life and education.

[0439] A "system" is a set of devices or software in which multiple components work together to achieve a specific function.

[0440] "Feedback" refers to advice and evaluations provided based on a user's actions and answers.

[0441] "Emotional data" is information that expresses a child's emotional state in numerical values ​​and categories.

[0442] The system for implementing this invention consists of the following main components: a terminal, a back-end server, an emotion recognition engine, and a database.

[0443] Component Details

[0444] Terminal

[0445] The terminal is a device that displays learning materials and allows users (children) to input answers. Specifically, it includes smartphones, tablets, and PCs. The terminal is equipped with an emotion recognition engine, and uses a built-in camera to capture video of the child's face and analyze the emotional data.

[0446] Backend Server

[0447] The backend server is a central computer system that receives data sent from the devices and automatically scores them. It uses cloud servers such as Node.js and AWS Lambda. The server analyzes the received answers and emotion data and generates appropriate feedback.

[0448] Emotion Recognition Engine

[0449] The emotion recognition engine uses Python, OpenCV, Google® Cloud AI / ML API, etc. to analyze a child's facial expressions and behavior and determine their emotional state.

[0450] Database

[0451] The database is used to store learning history and emotional data. Specifically, AWS RDS and MongoDB are used. The database stores details such as answer content, answer time, correct / incorrect status, number of retry attempts, and emotional data, and is used for later analysis.

[0452] Processing flow

[0453] 1. Viewing study materials

[0454] The device receives new learning materials sent from the server and displays a list of them to the child, who can then select and work on the learning materials on the device.

[0455] Example: When the server uploads a new math workbook, the device displays "New math workbook added," and the child taps it to open it.

[0456] 2. Enter your answer

[0457] The child inputs answers to questions in the learning materials displayed on the device, and the device sends the input answers along with emotional data analyzed by the emotion engine to the server.

[0458] Example: When a child enters "5+3=8" and presses the "Send" button, the device sends this answer along with the current emotional data (e.g., confidence, joy) analyzed by the emotion engine to the server.

[0459] 3. Automatic scoring

[0460] The server automatically determines whether the answer is correct or incorrect based on the answer received from the device, and sends the result along with the emotion data back to the device.

[0461] Example: The server checks whether "8" is the correct answer and returns the result to the device along with emotion data, such as "That's correct!" or "That's incorrect."

[0462] 4. Receiving and Viewing Feedback

[0463] The device receives the score and emotion data sent from the server and displays them to the user. If the answer is incorrect, the device provides additional hints and explanations to the child and displays feedback according to the emotion provided by the emotion engine.

[0464] For example, the device might say "That's right!" or "That's wrong, let's try again," and if the answer is incorrect, it might provide a hint like "Try counting again," along with emotional feedback like "Remain calm and try again."

[0465] Specific examples

[0466] Consider a case where a child logs in and starts working on a math drill. As the child enters the answer, the built-in camera analyzes the child's emotions and determines that the child is frustrated. This information is sent to the server. For example, the child enters "5+3=7," which is incorrect, and then enters "5+3=8" again, repeating this process until the correct answer is confirmed. During this process, the child's emotional data is also updated, and eventually a message such as "That's correct, but please calm down and try again" is displayed.

[0467] Prompt Sentence Examples

[0468] ---

[0469] The answer entered by the child is incorrect. The child's emotion is "irritated." Please generate a feedback sentence according to the emotion.

[0470] ---

[0471] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0472] Step 1:

[0473] The terminal receives new learning materials sent from the server and displays a list of them to the child.

[0474] Input: Learning material data from the server.

[0475] Output: Learning materials list screen.

[0476] Specific operation: The terminal receives the data of the learning materials and displays them to the child through the GUI. The child then performs operations to select learning materials.

[0477] Step 2:

[0478] The user (child) inputs answers to questions in the study materials displayed on the terminal.

[0479] Input: Child's answer data.

[0480] Output: A request with answer and sentiment data.

[0481] How it works: The child enters their answer using the touchscreen or keyboard, and the device's emotion recognition engine analyzes the facial image to obtain their current emotional data.

[0482] Step 3:

[0483] The server receives the answer data and emotion data from the terminal.

[0484] Input: Answer data and emotion data from the device.

[0485] Output: A new dataset for automatic marking and feedback generation.

[0486] Specific operation: The server passes the answer data to an automatic scoring algorithm to determine whether it is correct or incorrect. The emotion data is stored in a database.

[0487] Step 4:

[0488] The server generates feedback based on the scoring results and creates a feedback statement that takes into account the emotion data.

[0489] Input: Scoring results and emotion data.

[0490] Output: Feedback message.

[0491] Specific operation: The server uses a generative AI model to create a prompt sentence and generates a feedback sentence according to the emotion.

[0492] Example: If a child answers incorrectly and their emotion is determined to be "irritated," the following prompt sentence is input into the generative AI model:

[0493] "The answer the child entered is incorrect. The child's emotion is 'frustrated'. Please generate feedback sentences based on the emotion."

[0494] Step 5:

[0495] The server sends a feedback message and the score back to the terminal.

[0496] Input: Feedback message.

[0497] Output: Sends feedback messages to the terminal.

[0498] Specific operation: The generated feedback message and the scoring result are sent from the server to the terminal.

[0499] Step 6:

[0500] The terminal displays the feedback message and the scoring results sent from the server to the user (child).

[0501] Input: Feedback message and grading results from the server.

[0502] Output: Feedback messages and grading results displayed in the user interface.

[0503] Specific operation: The device displays feedback messages and scoring results to the child through a GUI. If the answer is incorrect, additional hints and explanations are also displayed.

[0504] Step 7:

[0505] If the user (child) answers incorrectly, they enter the answer again and send the answer and emotion data to the server using the same procedure.

[0506] Input: Answer data and emotion data as above.

[0507] Output: Answer data and emotion data for resubmission.

[0508] Specific operation: The child re-enters the answer, and the device again analyzes the facial image to obtain new emotional data, which it then sends to the server again.

[0509] Step 8:

[0510] The server stores each user's learning history and emotional data in a database.

[0511] Input: Answer data, emotion data, scoring results.

[0512] Output: Save data to database.

[0513] Specific operation: The server stores details such as the answer content, answer time, correct / incorrect status, number of retries, and emotional data in a database (AWS RDS, MongoDB, etc.).

[0514] Step 9:

[0515] Educators or parents can check learning history and emotional data through a dedicated management screen.

[0516] Input: A request from an educator or parent.

[0517] Output: Display of learning history and emotion data on the management screen.

[0518] What it does: Educators or parents send a request to the server to check their child's progress on the management screen. The server analyzes the stored data and displays it on the management screen.

[0519] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0520] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0521] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0522] [Second embodiment]

[0523] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0524] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0525] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0526] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0527] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0528] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0529] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0530] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0531] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0532] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0533] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0534] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0535] The detailed description of the invention provides a method for creating a system that allows children to engage with learning material, receive immediate feedback, and effectively manage their progress.

[0536] Configuration overview

[0537] The system consists of the following main components:

[0538] 1. Terminal

[0539] 2. Server

[0540] 3. Users (children, educators, parents)

[0541] Explanation of program processing

[0542] View learning materials

[0543] The device receives new learning materials sent from the server and displays a list of them to the child, who can then select and work on the learning materials on the device.

[0544] example:

[0545] When the server uploads a new math workbook, the device displays "New math workbook added," and the child taps it to open it.

[0546] Enter your answer

[0547] The child inputs answers to questions in the learning materials displayed on the device, and the device sends the input answers to the server.

[0548] example:

[0549] When the child enters "5+3=8" and presses the "Send" button, the device sends this answer to the server.

[0550] Automatic scoring

[0551] The server automatically determines whether the answer is correct or incorrect based on the answer received from the device, and sends the result back to the device.

[0552] example:

[0553] The server checks whether "8" is the correct answer and returns the result to the terminal, saying either "Correct!" or "Incorrect."

[0554] View Feedback

[0555] The device displays the score received from the server to the child, and if the answer is incorrect, the device provides additional hints and explanations to the child.

[0556] example:

[0557] The device will display "That's right!" or "That's wrong. Try again," and if the answer is incorrect, it will provide a hint such as "Try counting again."

[0558] Doing it over and trying again

[0559] The child can retry any questions they got wrong and enter their answer, and the process repeats until they get it right.

[0560] example:

[0561] This is repeated until the child types in "7" to confirm the answer is incorrect and then types in "8" again to confirm the answer is correct.

[0562] Save learning history

[0563] The server stores data such as each child's answer history, correct answers, and answer time, which will be used for later analysis.

[0564] example:

[0565] The server stores detailed history for Child A, such as "Question 1: 5+3, correct answers: 8, number of incorrect answers: 1, number of correct answers: 1, answer time: 15 seconds."

[0566] Progress check and analysis results notification

[0567] Educators or parents can check their children's learning history through a dedicated management screen. The server generates and notifies the results of analysis.

[0568] example:

[0569] When an educator checks Child A's progress on the management screen, the server displays a list of Child A's grades and history. In addition, the server generates and notifies the educator of analysis results such as, "Child A is good at calculation problems in mathematics, but not at word problems."

[0570] Effects of implementation

[0571] By implementing this system, children can instantly know whether their answers are correct or incorrect, allowing them to study efficiently. In addition, educators and parents can easily understand their children's progress and provide appropriate feedback and support. By clarifying each child's strengths and weaknesses, the quality of education can be improved.

[0572] In this way, the system based on the aspects of the present invention is expected to solve multiple problems in educational settings and provide effective learning support.

[0573] The processing flow will be explained below.

[0574] Step 1: Upload your study materials

[0575] The server receives an upload request from an educator or system administrator. The server stores the learning material file (e.g., math drills) and associates it with each child's account. After saving, it sends a notification to the device that the upload is complete.

[0576] Step 2: View study materials

[0577] The device receives notifications of new learning materials from the server, and the user (child) selects what to work on from the list of new learning materials displayed on the device.

[0578] Step 3: Enter your answers

[0579] The user (child) enters answers to questions displayed on the terminal. The terminal sends the entered data to the server. After sending, the terminal either moves on to the next question or waits for a response.

[0580] Step 4: Automated scoring

[0581] The server analyzes the received answer, compares it with the correct answer database, and determines whether it is correct or incorrect. The server generates a judgment result (correct or incorrect) and returns it to the terminal.

[0582] Step 5: Receive and view feedback

[0583] The device receives the scoring results sent from the server. It displays the received results to the user. If the answer is correct, it prompts the user to check their progress or move on to the next step. If the answer is incorrect, it displays additional hints or explanations.

[0584] Step 6: Doing a rework

[0585] If the user (child) answers incorrectly, they can try the same question again. They receive the same answer and enter the answer again. The device then sends the new answer to the server again.

[0586] Step 7: Save your data

[0587] The server stores each user's learning history in a database, including details such as the questions answered, the answers, whether they were correct or incorrect, the time it took to answer, the number of attempts, etc. The stored data is used for later analysis.

[0588] Step 8: Review progress and provide feedback

[0589] The user (educator or guardian) sends a request to the server to check the learning history through a dedicated management screen. The server analyzes the saved learning history and displays it on the management screen. It also notifies the educator or guardian of the analysis results.

[0590] Step 9: Strengths and weaknesses analysis and notification

[0591] The server analyzes learning history data to identify each user's strengths and weaknesses. The analysis results are communicated through a dedicated management screen, allowing educators and parents to understand each child's progress and learning needs.

[0592] The above processing steps enable efficient operation of the system. Children can instantly know their results, and educators and parents can easily check detailed progress. This allows for effective educational support.

[0593] Example 1

[0594] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0595] With conventional learning support systems, feedback when children are working on learning materials tends to be delayed, making it difficult to confirm answers or provide feedback in real time. Furthermore, the means by which educators and parents can check learning histories and analysis results are limited, making it difficult to grasp each child's learning progress and strengths and weaknesses. This makes it difficult to provide support at the appropriate time, resulting in problems such as reduced learning efficiency.

[0596] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0597] In this invention, the server includes an information terminal for the child to use to study materials, an information processing device that receives answers entered from the information terminal and automatically judges them, means for receiving the judgment results from the information processing device and displaying the results on the information terminal, information processing device means for saving and analyzing the child's study history, means for notifying educators and parents of the analysis results from the information processing device, means for identifying areas of strength and weakness based on the study history and the analysis results, means for the child to select from study materials displayed on the information terminal, means for displaying additional hints and explanations when an incorrect answer is given, and means for the child to try again and transmit the study history to the information processing device. This allows the child to study efficiently while receiving feedback in real time, and allows educators and parents to provide support and feedback at appropriate times.

[0598] An "information terminal" is a device that allows a user to work through study materials and input answers.

[0599] An "information processing device" is a device that receives the answer sent from the information terminal, automatically judges it, and returns the result.

[0600] "Learning history" refers to recorded data such as the content of answers, whether they were correct or incorrect, and the time it took to answer when a child worked on learning materials.

[0601] The "analysis results" are data generated based on the learning history to identify the child's strengths and weaknesses.

[0602] "Educators and parents" refers to those responsible for overseeing a child's learning and providing support where necessary.

[0603] "Real-time feedback" refers to the ability to instantly provide a correct or incorrect answer, and possibly additional hints or explanations, immediately after a child enters their answer.

[0604] The "retry feature" is a function that allows a child to try again on a question that was answered incorrectly.

[0605] "Storage means" refers to a function for long-term storage of answers entered by children and their learning history.

[0606] "Notification means" refers to a function for notifying educators and parents of the analysis results from the server.

[0607] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described in detail below with reference to the accompanying drawings.

[0608] System configuration

[0609] The system consists of the following main components:

[0610] 1. Terminal (information terminal)

[0611] 2. Server (information processing device)

[0612] 3. Users (children, educators, parents)

[0613] Hardware and software used

[0614] Device: This is the information device used by the child, such as a PC or tablet, which displays learning materials and inputs answers.

[0615] Server: An information processing device that receives, stores, processes data from users, and generates analytical results. The server is equipped with a database and AI model.

[0616] Software: An automatic scoring algorithm implemented in Python, database management software, and a web application providing the user interface.

[0617] Data processing and calculation

[0618] The terminal does the following:

[0619] 1. Receive learning materials sent from the server and display them to the user (child).

[0620] 2. The answer entered by the user (child) is sent to the server.

[0621] 3. The scoring results received from the server are displayed to the user (child).

[0622] The server does the following:

[0623] 1. The answers received from the device are judged by an automatic scoring algorithm.

[0624] 2. The scoring results are returned to the device.

[0625] 3. The received answer data and scoring results are stored in a database.

[0626] 4. Analyze your learning history and identify your strengths and weaknesses.

[0627] 5. Notify educators and parents of the analysis results.

[0628] Specific examples

[0629] When the server uploads a new math workbook, the device will notify the user that a new math workbook has been added. The child can tap the new workbook to open it and work on the problems. For example, if the child types "5+3=8" and presses the "Submit" button, the device will send the answer to the server.

[0630] The server uses an AI model implemented in Python to check whether the received answer "8" is correct. The server then sends the result "Correct!" to the device. The device displays "Correct!" or "Incorrect. Let's try again," and if the answer is incorrect, provides a hint such as "Try counting again."

[0631] Educators or parents can check their children's learning history through a dedicated management screen. The server generates analysis results such as "Child A is good at math calculation problems but not at word problems."

[0632] Prompt Sentence Examples

[0633] Below are some example prompts to input to a generative AI model:

[0634] "Generate 10 math problems."

[0635] "Based on the child's answers, identify areas of weakness and generate hints for them."

[0636] "Implement a system that analyzes learning progress in real time and provides feedback."

[0637] Although the embodiments of the present invention have been described above, many other variations are possible in the specific implementation methods. Various changes and modifications are possible within the scope of the present invention, and these are also included.

[0638] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0639] Step 1: Receive and view study materials

[0640] The server generates new learning materials (e.g., math drills) and sends them to the terminal. The terminal displays the received learning materials to the user (child). The user (child) selects the learning material to work on from the materials.

[0641] Input: Study material data sent from the server

[0642] Output: A list of study materials displayed on the device screen

[0643] Specific behavior: When the server uploads a new math workbook, the device notifies the user that "A new math workbook has been added," and the user (child) taps it to open it.

[0644] Step 2: Enter and submit your answers

[0645] The user (child) inputs answers to questions in the study materials displayed on the terminal, and the terminal then sends the answers to the server.

[0646] Input: Answer data entered by the user (child)

[0647] Output: Answer data sent from the device to the server

[0648] Specific operation: When the user (child) enters "5+3=8" and presses the "Send" button, the device sends this answer data to the server.

[0649] Step 3: Automated scoring

[0650] The server uses a generative AI model to automatically determine whether the answer received from the device is correct or incorrect, and the result is sent back to the device.

[0651] Input: Answer data sent from the device

[0652] Output: The score results sent back from the server to the device

[0653] Specific operation: The server uses an AI model implemented in Python to check whether the received answer "8" is correct. The server then sends the result "That's correct!" to the device.

[0654] Step 4: View your feedback

[0655] The terminal displays the score received from the server to the user (child). If the answer is incorrect, the terminal provides additional hints and explanations to the user (child).

[0656] Input: The score returned from the server

[0657] Output: Feedback displayed on the device screen

[0658] Specific behavior: The device will display "Correct!" or "Incorrect. Try again," and if the answer is incorrect, it will provide a hint such as "Try counting again."

[0659] Step 5: Try again and try again

[0660] The user (child) revisits the questions that were answered incorrectly and enters the answer, and this process is repeated until the correct answer is obtained.

[0661] Input: Answer data re-entered by the user (child)

[0662] Output: Answer data sent from the device to the server, and new scoring results returned from the server.

[0663] Specific operation: The user (child) enters "7" and is incorrect, then repeats this operation until they enter "8" again and confirm the correct answer.

[0664] Step 6: Save your learning history

[0665] The server stores data on each user (child), such as answer history, correct answers, and answer time. This data is used for later analysis.

[0666] Input: User (child) answer data and scoring result data

[0667] Output: Learning history stored in the server database

[0668] Specific operation: The server stores detailed history in a database, such as "Question 1: 5+3, correct answers: 8, number of incorrect answers: 1, number of correct answers: 1, answer time: 15 seconds."

[0669] Step 7: Check progress and communicate analysis results

[0670] Educators or parents can check the learning history of users (children) through a dedicated management screen. The server generates and notifies the results of analysis.

[0671] Input: Learning history data stored on the server

[0672] Output: Analysis results displayed on the educator and parent management screen

[0673] Specific operation: The educator logs in to the management screen and checks the progress of Child A. The server displays the analysis results on the management screen, such as "Child A is good at math calculation problems, but not so good at word problems."

[0674] (Application example 1)

[0675] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0676] Learning to operate robots in factories is difficult for operators due to the complex procedures and high precision required. Conventional training methods make it difficult for operators to immediately grasp their own progress, and the slow feedback reduces efficiency. It is also difficult for managers to quickly identify an operator's strengths and weaknesses and provide appropriate guidance. Therefore, there is a need for a system that allows operators to efficiently learn robot operation procedures, receive instant feedback, and allow managers to easily grasp their progress.

[0677] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0678] In this invention, the server includes a terminal on which an operator works on the operation procedures, means for receiving answers entered from the terminal and automatically grading them, means for receiving the grading results from the server and displaying the results on the terminal, means for saving and analyzing the learning history of the operator, means for notifying an administrator of the analysis results from the server, and means for identifying areas of strength and weakness based on the learning history and the analysis results. This allows the operator to efficiently learn the robot operation procedures and receive immediate feedback, and also enables the administrator to easily understand the progress and provide appropriate guidance.

[0679] "Operator" refers to the person in charge of operating and training the robot within the factory.

[0680] A "terminal" refers to an information processing device used by an operator, such as a smartphone, tablet, or head-mounted display.

[0681] "Solution" refers to the result or answer that an operator enters when working through an operating procedure.

[0682] The "server" is a central processing unit that receives answers from operators, automatically grades them, and sends back feedback.

[0683] "Scoring" refers to the process of determining whether an operator's answer is correct.

[0684] "Feedback" refers to information about whether an answer is correct or incorrect, as well as additional advice and hints, sent from the server to the operator.

[0685] "Learning history" refers to data such as the operator's answer history, correct answers, and answer time.

[0686] "Analysis results" refers to information such as areas of strength and weakness that is generated by the server based on learning history.

[0687] "Supervisor" refers to the person in charge of the factory who monitors the progress of the operators and provides appropriate guidance.

[0688] "Notification" refers to the process by which the server communicates important information such as analysis results and operator progress to the administrator.

[0689] As an embodiment of the present invention, a method for constructing a system that enables operators in a factory to learn robot operation procedures, receive immediate feedback, and efficiently manage the progress will be described below.

[0690] Configuration overview

[0691] The system consists of the following main components:

[0692] 1. Terminal

[0693] 2. Server

[0694] 3. User (operator, administrator)

[0695] Explanation of program processing

[0696] Displaying operating instructions

[0697] The server sends new operation procedures to the terminal, which displays a list of them, allowing the operator to select and execute the operation procedure on the terminal.

[0698] Examples:

[0699] When the server uploads a new robot configuration procedure, the terminal displays "New robot configuration procedure added," and the operator taps it to open it.

[0700] Enter your answer

[0701] The operator inputs answers to the operating procedures displayed on the terminal, and the terminal sends the input answers to the server.

[0702] Examples:

[0703] When the operator types "Turn on the robot" and presses the "Send" button, the terminal sends this answer to the server.

[0704] Automatic scoring

[0705] The server automatically determines whether the answer is correct or incorrect based on the answer received from the device, and sends the result back to the device.

[0706] Examples:

[0707] The server checks whether "Turn on the robot" is the correct answer and returns the result to the terminal, saying "Correct!" or "Incorrect."

[0708] View Feedback

[0709] The terminal displays the score received from the server to the operator. If the answer is incorrect, the terminal provides additional hints and explanations to the operator.

[0710] Examples:

[0711] The device will display "That's right!" or "That's wrong. Try again," and if the answer is incorrect, it will provide a hint such as "Check the detailed instructions and try again."

[0712] Doing it over and trying again

[0713] The operator retrys the incorrect operation sequence and enters the answer, and this process is repeated until the correct answer is obtained.

[0714] Examples:

[0715] The operator types "start robot" which is an incorrect answer, and then types "power on robot" again, repeating this process until the correct answer is confirmed.

[0716] Save learning history

[0717] The server stores data such as each operator's answer history, correct answers, and answer time, which will be used for later analysis.

[0718] Examples:

[0719] The server stores detailed history of operator A, such as "Step 1: Turn on the robot, correct, number of incorrect answers: 1, number of correct answers: 1, response time: 15 seconds."

[0720] Progress check and analysis results notification

[0721] Administrators can check the learning history of operators through a dedicated management screen. The server generates and notifies the results of the analysis.

[0722] Examples:

[0723] When the administrator checks the progress of Operator A on the management screen, the server displays a list of Operator A's performance and history. In addition, the server generates and notifies the administrator of the results of an analysis, such as "Operator A is good at setting up the robot, but is not good at emergency shutdown procedures."

[0724] Hardware and software used

[0725] This system mainly uses the following hardware and software:

[0726] Hardware: Devices such as smartphones, tablets, and head-mounted displays.

[0727] Software: Server-side program using Python, terminal application for displaying operation procedures.

[0728] Example prompts to input to the generative AI model

[0729] Here is the prompt to input to a generative AI model (e.g. ChatGPT):

[0730] "Generate guidelines for learning troubleshooting steps and getting immediate feedback for a factory robotics training application. Include the following steps:

[0731] 1. Check for abnormal robot stoppage

[0732] 2. Analysis of abnormal code

[0733] 3. Take any necessary corrective steps

[0734] 4. Check for proper operation

[0735] Please also include any explanations or advice you would like to give the operator at each step.

[0736] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0737] Step 1:

[0738] The server sends the new operating procedure to the terminal. Specifically, the server retrieves the new operating procedure from the operating procedure database and sends it to the terminal. The terminal receives this data and displays a list of operating procedures to the operator. The input information is the new operating procedure, and the output result is the list of operating procedures displayed on the operator's terminal.

[0739] Step 2:

[0740] The operator selects the item they want to learn from the operating procedures displayed on the terminal. Specifically, when the operator taps or selects an item, the terminal notifies the server of the selected operating procedure. The input information is the operating procedure selected by the operator, and the output result is a notification of the selected item to the server.

[0741] Step 3:

[0742] The server sends specific tasks related to the selected operating procedure to the terminal. Specifically, the server retrieves task details corresponding to the selected operating procedure from the database and sends them to the terminal. The terminal receives this data and displays the tasks to the operator. The input information is the selected operating procedure, and the output result is the task details displayed on the operator's terminal.

[0743] Step 4:

[0744] The operator inputs answers to each task displayed on the terminal. Specifically, the operator enters the answer in the input field and presses the send button, which causes the terminal to send the answer to the server. The input information is the answer entered by the operator, and the output result is the answer sent to the server.

[0745] Step 5:

[0746] The server automatically scores the received answers. Specifically, the server compares the answer data with a database of correct answers to determine whether they match. The input information is the operator's answer data, and the output is a judgment result of whether the answer is correct or incorrect.

[0747] Step 6:

[0748] The server sends the scoring results to the terminal. Specifically, the server generates a judgment result and sends it to the terminal. The terminal receives this data and displays the scoring results to the operator. The input information is the scoring result data, and the output is the scoring result display on the operator's terminal.

[0749] Step 7:

[0750] If the answer is incorrect, the terminal provides the operator with additional hints and explanations. Specifically, the terminal retrieves appropriate hints and explanations from a feedback database for incorrect answers and displays them to the operator. The input information is the result of the incorrect answer determination, and the output is the hint or explanation displayed on the operator terminal.

[0751] Step 8:

[0752] The operator attempts the task again if the answer was incorrect and re-enters the answer. Specifically, the operator re-enters the answer and presses the send button, causing the terminal to send the new answer to the server. The input information is the re-entered answer, and the output result is the re-sent answer sent to the server.

[0753] Step 9:

[0754] The server stores each operator's learning history, including answer history, correct / incorrect answers, and answer time. Specifically, answer data and scoring results are recorded in a database. Input information is the operator's answer history data, and output results are stored in the database.

[0755] Step 10:

[0756] The server displays the saved learning history and analysis results in response to a request from an administrator. Specifically, the server receives the administrator's request through the management screen, retrieves the saved data from the database, generates the analysis results, and displays them on the management screen. The input information is the administrator's request, and the output is the analysis results displayed on the management screen.

[0757] The above is the specific processing flow of the factory robot operation training system.

[0758] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0759] As an embodiment of the invention, the following describes how an emotion engine that recognizes user emotions can be incorporated into a system that allows children to engage with learning material and receive instant feedback to effectively manage their progress.

[0760] Configuration overview

[0761] The system consists of the following main components:

[0762] 1. Device (with emotion engine)

[0763] 2. Server

[0764] 3. Users (children, educators, parents)

[0765] Explanation of program processing

[0766] View learning materials

[0767] The terminal receives new learning materials sent from the server and displays a list of them to the child. The user (child) can select learning materials to work on on the terminal.

[0768] example:

[0769] When the server uploads a new math workbook, the device displays "New math workbook added," and the child taps it to open it.

[0770] Enter your answer

[0771] The child inputs answers to questions in the learning materials displayed on the device, and the device sends the input answers along with emotional data analyzed by the emotion engine to the server.

[0772] example:

[0773] When the child enters "5+3=8" and presses the "Send" button, the device sends this answer along with the current emotional data (e.g., confidence, joy) analyzed by the emotion engine to the server.

[0774] Automatic scoring

[0775] The server automatically determines whether the answer is correct or incorrect based on the answer received from the device, and sends the result along with the emotion data back to the device.

[0776] example:

[0777] The server checks whether "8" is the correct answer and returns the result to the terminal along with emotional data, saying "That's correct!" or "That's incorrect."

[0778] Receiving and viewing feedback

[0779] The device receives the score and emotion data sent from the server and displays them to the user. If the answer is incorrect, the device provides additional hints and explanations to the child and displays feedback according to the emotion provided by the emotion engine.

[0780] example:

[0781] The device will display "That's right!" or "That's wrong. Let's try again." If the answer is incorrect, the device will provide a hint like "Try counting again," as well as emotional feedback like "Remain calm and try again."

[0782] Doing it over and trying again

[0783] If the child answers incorrectly, they can try the same question again and send a new answer along with their emotional data to the server.

[0784] example:

[0785] The process repeats until the child enters "7" to confirm the answer is incorrect and then enters "8" again to confirm the answer is correct. Emotional data is also sent each time.

[0786] Data storage

[0787] The server stores each user's learning history and emotional data in a database, including details such as the questions answered, the answers, whether they were correct or incorrect, the time it took to answer, the number of retries, and emotional data. The stored data is used for later analysis.

[0788] example:

[0789] The server stores detailed history for Child A, such as "Question 1: 5+3, correct answers: 8, number of incorrect answers: 1, number of correct answers: 1, answer time: 15 seconds, emotional data: joy."

[0790] Progress review and feedback

[0791] Educators or parents can send a request to the server to check the learning history and emotional data through a dedicated management screen. The server analyzes the saved learning history and displays it on the management screen. It also notifies the educator or parent of the results of the analysis.

[0792] example:

[0793] When an educator checks Child A's progress on the management screen, the server displays a list of Child A's grades, history, and emotional data. The server also generates and notifies the educator of analysis results such as, "Child A is good at math calculation problems, but struggles with word problems and appears unsure of his or her answers."

[0794] Effects of implementation

[0795] By implementing this system, children can instantly know whether their answers are correct or incorrect and receive appropriate feedback based on their emotions. Educators and parents can understand detailed progress and emotional states, allowing them to provide more effective support. By clarifying each child's strengths and weaknesses, as well as their emotions at any given time, it is expected that the quality of education will be improved.

[0796] In this way, the system based on the aspects of the present invention is expected to solve multiple problems in educational settings and provide effective learning support.

[0797] The processing flow will be explained below.

[0798] Step 1: Upload your study materials

[0799] The server receives an upload request from an educator or system administrator. The server stores the learning material file (e.g., math drills) and associates it with each child's account. After the file is saved, it sends a notification to the device that the upload is complete.

[0800] Step 2: View study materials

[0801] The device receives notifications of new learning materials from the server, and the user (child) selects what to work on from the list of new learning materials displayed on the device.

[0802] example:

[0803] When the server uploads a new math workbook, the device displays "New math workbook added," and the user taps it to open it.

[0804] Step 3: Start Emotion Recognition

[0805] The device's built-in emotion engine analyzes data such as the child's facial expressions, voice, and touch pressure in real time to generate current emotion data (e.g., excitement, concentration, confusion).

[0806] example:

[0807] The device instructs the user to "relax and take a deep breath before you begin this problem," while the emotion engine collects data.

[0808] Step 4: Enter your answers

[0809] The user (child) inputs answers to questions displayed on the device. Emotional data is also continuously collected. The device transmits the input answers and emotional data to the server.

[0810] example:

[0811] When a child enters "5+3=8" and presses the "Send" button, the device sends this answer along with emotional data (e.g., confidence, joy) to the server.

[0812] Step 5: Automated scoring

[0813] The server automatically determines whether the answer is correct or incorrect based on the answer received from the device, and sends the result along with the emotion data back to the device.

[0814] example:

[0815] The server checks whether "8" is the correct answer and returns the result to the terminal along with emotional data, saying "That's correct!" or "That's incorrect."

[0816] Step 6: Receive and view feedback

[0817] The device receives the score and emotion data sent from the server and displays them to the user. If the answer is incorrect, the device provides additional hints and explanations to the child and displays feedback according to the child's emotion.

[0818] example:

[0819] The device will display "That's right!" or "That's wrong. Let's try again." If the answer is incorrect, the device will provide hints such as "Try counting again," as well as emotional feedback such as "Remain calm and try again."

[0820] Step 7: Doing a rework

[0821] If the user (child) answers incorrectly, they can try the same question again and send a new answer along with their emotion data to the server.

[0822] example:

[0823] The process repeats until the child enters "7" to confirm the answer is incorrect and then enters "8" again to confirm the answer is correct. Emotional data is also sent each time.

[0824] Step 8: Save your data

[0825] The server stores each user's learning history and emotional data in a database, including details such as the questions answered, the answers, whether they were correct or incorrect, the time it took to answer, the number of retries, and emotional data. The stored data is used for later analysis.

[0826] example:

[0827] The server stores detailed history for Child A, such as "Question 1: 5+3, correct answers: 8, number of incorrect answers: 1, number of correct answers: 1, answer time: 15 seconds, emotional data: joy."

[0828] Step 9: Review progress and provide feedback

[0829] The user (educator or parent) sends a request to the server to check the learning history and emotional data through a dedicated management screen. The server analyzes the saved learning history and displays it on the management screen. It also notifies the educator or parent of the analysis results.

[0830] example:

[0831] When an educator checks Child A's progress on the management screen, the server displays a list of Child A's grades, history, and emotional data. The server also generates and notifies the educator of analysis results such as, "Child A is good at math calculation problems, but struggles with word problems and appears unsure of his or her answers."

[0832] Effects of implementation

[0833] By implementing this system, children can instantly know whether their answers are correct or incorrect and receive appropriate feedback based on their emotions. Educators and parents can understand detailed progress and emotional states, allowing them to provide more effective support. By clarifying each child's strengths and weaknesses, as well as their emotions at any given time, it is expected that the quality of education will be improved.

[0834] In this way, the system based on the aspects of the present invention is expected to solve multiple problems in educational settings and provide effective learning support.

[0835] Example 2

[0836] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0837] In traditional educational systems, it is difficult for children to receive immediate feedback when working on learning materials. Furthermore, feedback provided does not take into account the child's emotional state, which can lead to a decrease in motivation to learn and increased stress. Educators and parents are unable to grasp a child's learning progress and emotional state in real time, making it difficult to provide appropriate support. This makes it difficult to identify individual children's strengths and weaknesses and provide effective educational support.

[0838] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving answers entered from the terminal and emotion data analyzed by the emotion engine, means for automatically scoring based on the answers and generating scoring results including emotion data, and means for receiving the scoring results from the server and displaying the results on the terminal. This allows children to instantly receive feedback based on their answers and emotions. Furthermore, educators and parents can grasp children's learning progress and emotional state in real time and provide more effective support.

[0839] "Devices" refer to electronic devices that children use to engage with learning materials and are equipped with emotion engines that can analyze emotional data.

[0840] "Answer" refers to a child's input to the study material, which is sent to the server for validation.

[0841] An "emotion engine" refers to an algorithm or software that analyzes emotions from a user's facial expressions, voice, etc.

[0842] "Emotion data" refers to data relating to the user's emotional state obtained as a result of analysis by the emotion engine.

[0843] "Server" refers to a computer system that automatically grades answers, stores and analyzes learning history and emotional data.

[0844] "Scoring result" refers to the result of whether the answer is correct or incorrect as determined by the server based on the child's answer.

[0845] "Feedback" refers to hints, encouragement, explanations, etc. that are displayed on the device based on the answer results and emotional data.

[0846] "Educators and parents" refers to adults who supervise a child's learning progress and provide appropriate support.

[0847] "Learning history" refers to a detailed record of the learning materials a child has worked on, their answers, whether correct or incorrect, how long it took to answer, and emotional data.

[0848] "Analysis results" refers to the results of analysis performed by the server based on learning history and emotional data.

[0849] "Strengths and weaknesses" refers to the range of learning content in which a child excels or struggles.

[0850] As an embodiment of the present invention, a method for incorporating an emotion engine that recognizes user emotions into a system for children to work on learning materials, receive instant feedback, and efficiently manage their progress is described below. The system is composed of terminals, a server, and users (children, educators, and parents).

[0851] Hardware and Software Used

[0852] Device: Tablet or PC with emotion engine (e.g. iPad, Chromebook)

[0853] Server: Learning materials management and database (e.g. AWS EC2, MySQL)

[0854] Sentiment engine: AI algorithms for sentiment analysis (e.g. Azure Cognitive Services)

[0855] System Operation Overview

[0856] 1. The server manages the learning materials uploaded by the educator and sends them to the terminal.

[0857] 2. The terminal displays the learning materials received from the server to the child, and the child works on the learning materials.

[0858] 3. The child enters the answer to the study question, and the device sends the answer along with the emotional data analyzed by the emotion engine to the server.

[0859] 4. The server automatically scores the received answers and generates scoring results that include emotion data.

[0860] 5. The device receives the score and emotion data sent from the server and displays them to the child. Based on the emotion data, the device provides additional feedback.

[0861] 6. The server stores learning history and emotional data, and based on this identifies strengths and weaknesses in each area.

[0862] 7. Educators and parents can check learning history and analysis results through the management screen and provide effective support to their children.

[0863] Specific examples

[0864] Example 1: When the server uploads a new math workbook, the device displays "A new math workbook has been added," and the child taps it to open it. When the child enters "5+3=8" and presses the "Send" button, the device sends this answer along with emotional data (e.g., confidence, joy) to the server.

[0865] Example 2: The server checks the answer "8" and, since it is correct, sends the message "That's right!" along with emotional data to the device. The device then displays "That's right! You seem confident!" If the answer is incorrect, it provides feedback such as "Think about it again" or "Calm down and try again."

[0866] Example 3: When an educator checks a child's progress on the management screen, the server displays a list of the child's grades, history, and emotional data, and notifies them of the analysis results, such as "Child A is good at math calculation problems but not so good at word problems."

[0867] Example prompts to input to the generative AI model

[0868] "How can I be notified when new learning materials are added?"

[0869] "Please explain the process for sending the answers entered by the child to the server."

[0870] "Please explain in detail how the server scores the answers and returns the results."

[0871] By building such a system, children can efficiently understand their learning content and receive appropriate emotional feedback, allowing educators and parents to monitor their learning progress in detail and provide support tailored to each individual child.

[0872] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0873] Step 1:

[0874] The server receives the learning materials uploaded by the educator, which are stored in a database and ready to be sent to the device.

[0875] Input: Learning materials uploaded by educators (e.g., math drills)

[0876] Output: The learning materials are saved in a database ready to be sent to the device.

[0877] Specific operation: The server receives PDF files and digital text format learning materials added by educators, stores them in a database, and then generates a material ID and metadata and notifies the device.

[0878] Step 2:

[0879] The terminal displays the new learning materials received from the server to the child.

[0880] Input: Learning material notification from the server (e.g., notification of new math drills added)

[0881] Output: A list of study materials will be displayed on the child's device screen.

[0882] Specific behavior: A notification saying "New math drills have been added" will be displayed on the device screen, and users can tap to access the content.

[0883] Step 3:

[0884] The user (child) inputs answers to questions in the study materials displayed on the device. At the same time, the device generates emotion data analyzed by the emotion engine.

[0885] Input: The answer entered by the child (e.g. 5+3=8)

[0886] Output: Answer and emotion data are generated (e.g., confidence, joy)

[0887] Specific operation: When a child enters an answer and presses the send button, the device's built-in camera and microphone are activated to analyze facial expressions and voice and generate emotional data.

[0888] Step 4:

[0889] The terminal transmits the answer and emotion data to the server.

[0890] Input: Child's answers and emotion data

[0891] Output: Answers and emotion data are sent to the server

[0892] Specific operation: The device combines the answer and emotion data into a single data packet, encrypts it, and sends it to the server.

[0893] Step 5:

[0894] The server automatically determines whether the answer received from the terminal is correct or incorrect and generates a scoring result that includes emotional data.

[0895] Input: Answers and emotion data sent from the device

[0896] Output: Scoring results and emotional feedback data

[0897] What it does: The server's algorithm scores the answers, generates a "correct" or "incorrect" result, and creates a feedback message with emotional data.

[0898] Step 6:

[0899] The server returns the scoring results and emotion data to the terminal.

[0900] Input: Scoring results and emotional feedback data

[0901] Output: Feedback data sent to the device

[0902] Specific operation: The server compiles the scoring results and the emotion feedback message into a data packet and sends it to the device.

[0903] Step 7:

[0904] The device receives the score and emotion data sent from the server and displays them to the user (child). If the answer is incorrect, the device also provides additional hints and emotion-based feedback.

[0905] Input: Scoring results and emotional feedback data sent from the server

[0906] Output: Feedback displayed on the terminal screen

[0907] What it does: Show feedback on the device screen, such as "That's right!", "You look confident!", or "Think again" or "Calm down and try again."

[0908] Step 8:

[0909] If the user (child) answers incorrectly, they can try the same question again.

[0910] Input: New answer and emotion data

[0911] Output: Retry data sent to the server

[0912] What it does: If the child enters a different answer and submits it again, the new answer and emotion data are sent to the server and re-evaluated.

[0913] Step 9:

[0914] The server stores each user's learning history and emotional data in a database.

[0915] Input: Answers, emotion data, scoring results

[0916] Output: Saved learning history and emotion data

[0917] Specific operation: The server stores detailed data such as "question ID, answer, correct / incorrect answer, number of times, time, emotional data" in a database.

[0918] Step 10:

[0919] The server displays the saved learning history and emotional data on the management screen in response to requests from educators or parents, and also notifies them of the analysis results.

[0920] Input: History view request from educator or parent

[0921] Output: Learning history and analysis results displayed on the management screen

[0922] Specific operation: The server receives the request, extracts and analyzes the necessary data, and displays the analysis results on the management screen, such as "Child A is good at math calculation problems but not at word problems."

[0923] (Application example 2)

[0924] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0925] While immediate feedback and correct answers are important for children's learning, conventional systems do not provide support that takes into account the child's emotional state. This can lead to children feeling stressed and frustrated, which can decrease their motivation to learn. It is also difficult for educators and parents to properly understand a child's progress and emotional state and provide effective support.

[0926] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0927] In this invention, the server includes a means for receiving answers entered from the terminal and automatically scoring them, an emotion recognition means for the terminal to recognize the child's emotions and send the data to the server, and a means for receiving the scoring results and emotion data from the server and displaying the results on the terminal. This makes it possible to grasp the emotional state of a child while they are learning in real time and provide appropriate feedback. Furthermore, educators and parents can grasp the child's detailed progress and emotional state and provide more effective support.

[0928] A "terminal" is a device for displaying study materials and inputting user answers.

[0929] A "server" is a central computer system that receives data sent from terminals and processes and analyzes it.

[0930] The "emotion recognition means" has the function of analyzing the child's facial expressions and behavior and determining their emotional state.

[0931] The "feedback generation means" is a function for generating appropriate feedback to the child based on whether the answer is correct or incorrect.

[0932] "Learning history" is a record of data such as the learning materials a child has worked on, the content of their answers, the time it took to answer, and whether they were correct or incorrect.

[0933] "Analysis results" are the results of analysis using statistical and machine learning methods based on learning history and emotional data.

[0934] An "educator" is someone who provides educational guidance to children, i.e., a teacher or instructor.

[0935] A "guardian" is a parent or caregiver who oversees a child's life and education.

[0936] A "system" is a set of devices or software in which multiple components work together to achieve a specific function.

[0937] "Feedback" refers to advice and evaluations provided based on a user's actions and answers.

[0938] "Emotional data" is information that expresses a child's emotional state in numerical values ​​and categories.

[0939] The system for implementing this invention consists of the following main components: a terminal, a back-end server, an emotion recognition engine, and a database.

[0940] Component Details

[0941] Terminal

[0942] The terminal is a device that displays learning materials and allows users (children) to input answers. Specifically, it includes smartphones, tablets, and PCs. The terminal is equipped with an emotion recognition engine, and uses a built-in camera to capture video of the child's face and analyze the emotional data.

[0943] Backend Server

[0944] The backend server is a central computer system that receives data sent from the devices and automatically scores them. It uses cloud servers such as Node.js and AWS Lambda. The server analyzes the received answers and emotion data and generates appropriate feedback.

[0945] Emotion Recognition Engine

[0946] The emotion recognition engine uses Python, OpenCV, Google Cloud AI / ML API, etc. to analyze a child's facial expressions and behavior and determine their emotional state.

[0947] Database

[0948] The database is used to store learning history and emotional data. Specifically, AWS RDS and MongoDB are used. The database stores details such as answer content, answer time, correct / incorrect status, number of retry attempts, and emotional data, and is used for later analysis.

[0949] Processing flow

[0950] 1. Viewing study materials

[0951] The device receives new learning materials sent from the server and displays a list of them to the child, who can then select and work on the learning materials on the device.

[0952] Example: When the server uploads a new math workbook, the device displays "New math workbook added," and the child taps it to open it.

[0953] 2. Enter your answer

[0954] The child inputs answers to questions in the learning materials displayed on the device, and the device sends the input answers along with emotional data analyzed by the emotion engine to the server.

[0955] Example: When a child enters "5+3=8" and presses the "Send" button, the device sends this answer along with the current emotional data (e.g., confidence, joy) analyzed by the emotion engine to the server.

[0956] 3. Automatic scoring

[0957] The server automatically determines whether the answer is correct or incorrect based on the answer received from the device, and sends the result along with the emotion data back to the device.

[0958] Example: The server checks whether "8" is the correct answer and returns the result to the device along with emotion data, such as "That's correct!" or "That's incorrect."

[0959] 4. Receiving and Viewing Feedback

[0960] The device receives the score and emotion data sent from the server and displays them to the user. If the answer is incorrect, the device provides additional hints and explanations to the child and displays feedback according to the emotion provided by the emotion engine.

[0961] For example, the device might say "That's right!" or "That's wrong, let's try again," and if the answer is incorrect, it might provide a hint like "Try counting again," along with emotional feedback like "Remain calm and try again."

[0962] Specific examples

[0963] Consider a case where a child logs in and starts working on a math drill. As the child enters the answer, the built-in camera analyzes the child's emotions and determines that the child is frustrated. This information is sent to the server. For example, the child enters "5+3=7," which is incorrect, and then enters "5+3=8" again, repeating this process until the correct answer is confirmed. During this process, the child's emotional data is also updated, and eventually a message such as "That's correct, but please calm down and try again" is displayed.

[0964] Prompt Sentence Examples

[0965] ---

[0966] The answer entered by the child is incorrect. The child's emotion is "irritated." Please generate a feedback sentence according to the emotion.

[0967] ---

[0968] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0969] Step 1:

[0970] The terminal receives new learning materials sent from the server and displays a list of them to the child.

[0971] Input: Learning material data from the server.

[0972] Output: Learning materials list screen.

[0973] Specific operation: The terminal receives the data of the learning materials and displays them to the child through the GUI. The child then performs operations to select learning materials.

[0974] Step 2:

[0975] The user (child) inputs answers to questions in the study materials displayed on the terminal.

[0976] Input: Child's answer data.

[0977] Output: A request with answer and sentiment data.

[0978] How it works: The child enters their answer using the touchscreen or keyboard, and the device's emotion recognition engine analyzes the facial image to obtain their current emotional data.

[0979] Step 3:

[0980] The server receives the answer data and emotion data from the terminal.

[0981] Input: Answer data and emotion data from the device.

[0982] Output: A new dataset for automatic marking and feedback generation.

[0983] Specific operation: The server passes the answer data to an automatic scoring algorithm to determine whether it is correct or incorrect. The emotion data is stored in a database.

[0984] Step 4:

[0985] The server generates feedback based on the scoring results and creates a feedback statement that takes into account the emotion data.

[0986] Input: Scoring results and emotion data.

[0987] Output: Feedback message.

[0988] Specific operation: The server uses a generative AI model to create a prompt sentence and generates a feedback sentence according to the emotion.

[0989] Example: If a child answers incorrectly and their emotion is determined to be "irritated," the following prompt sentence is input into the generative AI model:

[0990] "The answer the child entered is incorrect. The child's emotion is 'frustrated'. Please generate feedback sentences based on the emotion."

[0991] Step 5:

[0992] The server sends a feedback message and the score back to the terminal.

[0993] Input: Feedback message.

[0994] Output: Sends feedback messages to the terminal.

[0995] Specific operation: The generated feedback message and the scoring result are sent from the server to the terminal.

[0996] Step 6:

[0997] The terminal displays the feedback message and the scoring results sent from the server to the user (child).

[0998] Input: Feedback message and grading results from the server.

[0999] Output: Feedback messages and grading results displayed in the user interface.

[1000] Specific operation: The device displays feedback messages and scoring results to the child through a GUI. If the answer is incorrect, additional hints and explanations are also displayed.

[1001] Step 7:

[1002] If the user (child) answers incorrectly, they enter the answer again and send the answer and emotion data to the server using the same procedure.

[1003] Input: Answer data and emotion data as above.

[1004] Output: Answer data and emotion data for resubmission.

[1005] Specific operation: The child re-enters the answer, and the device again analyzes the facial image to obtain new emotional data, which it then sends to the server again.

[1006] Step 8:

[1007] The server stores each user's learning history and emotional data in a database.

[1008] Input: Answer data, emotion data, scoring results.

[1009] Output: Save data to database.

[1010] Specific operation: The server stores details such as the answer content, answer time, correct / incorrect status, number of retries, and emotional data in a database (AWS RDS, MongoDB, etc.).

[1011] Step 9:

[1012] Educators or parents can check learning history and emotional data through a dedicated management screen.

[1013] Input: A request from an educator or parent.

[1014] Output: Display of learning history and emotion data on the management screen.

[1015] What it does: Educators or parents send a request to the server to check their child's progress on the management screen. The server analyzes the stored data and displays it on the management screen.

[1016] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1017] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1018] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1019] [Third embodiment]

[1020] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1021] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1022] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1023] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1024] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1025] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1026] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1027] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1028] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1029] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1030] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1031] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1032] The detailed description of the invention provides a method for creating a system that allows children to engage with learning material, receive immediate feedback, and effectively manage their progress.

[1033] Configuration overview

[1034] The system consists of the following main components:

[1035] 1. Terminal

[1036] 2. Server

[1037] 3. Users (children, educators, parents)

[1038] Explanation of program processing

[1039] View learning materials

[1040] The device receives new learning materials sent from the server and displays a list of them to the child, who can then select and work on the learning materials on the device.

[1041] example:

[1042] When the server uploads a new math workbook, the device displays "New math workbook added," and the child taps it to open it.

[1043] Enter your answer

[1044] The child inputs answers to questions in the learning materials displayed on the device, and the device sends the input answers to the server.

[1045] example:

[1046] When the child enters "5+3=8" and presses the "Send" button, the device sends this answer to the server.

[1047] Automatic scoring

[1048] The server automatically determines whether the answer is correct or incorrect based on the answer received from the device, and sends the result back to the device.

[1049] example:

[1050] The server checks whether "8" is the correct answer and returns the result to the terminal, saying either "Correct!" or "Incorrect."

[1051] View Feedback

[1052] The device displays the score received from the server to the child, and if the answer is incorrect, the device provides additional hints and explanations to the child.

[1053] example:

[1054] The device will display "That's right!" or "That's wrong. Try again," and if the answer is incorrect, it will provide a hint such as "Try counting again."

[1055] Doing it over and trying again

[1056] The child can retry any questions they got wrong and enter their answer, and the process repeats until they get it right.

[1057] example:

[1058] This is repeated until the child types in "7" to confirm the answer is incorrect and then types in "8" again to confirm the answer is correct.

[1059] Save learning history

[1060] The server stores data such as each child's answer history, correct answers, and answer time, which will be used for later analysis.

[1061] example:

[1062] The server stores detailed history for Child A, such as "Question 1: 5+3, correct answers: 8, number of incorrect answers: 1, number of correct answers: 1, answer time: 15 seconds."

[1063] Progress check and analysis results notification

[1064] Educators or parents can check their children's learning history through a dedicated management screen. The server generates and notifies the results of analysis.

[1065] example:

[1066] When an educator checks Child A's progress on the management screen, the server displays a list of Child A's grades and history. In addition, the server generates and notifies the educator of analysis results such as, "Child A is good at calculation problems in mathematics, but not at word problems."

[1067] Effects of implementation

[1068] By implementing this system, children can instantly know whether their answers are correct or incorrect, allowing them to study efficiently. In addition, educators and parents can easily understand their children's progress and provide appropriate feedback and support. By clarifying each child's strengths and weaknesses, the quality of education can be improved.

[1069] In this way, the system based on the aspects of the present invention is expected to solve multiple problems in educational settings and provide effective learning support.

[1070] The processing flow will be explained below.

[1071] Step 1: Upload your study materials

[1072] The server receives an upload request from an educator or system administrator. The server stores the learning material file (e.g., math drills) and associates it with each child's account. After saving, it sends a notification to the device that the upload is complete.

[1073] Step 2: View study materials

[1074] The device receives notifications of new learning materials from the server, and the user (child) selects what to work on from the list of new learning materials displayed on the device.

[1075] Step 3: Enter your answers

[1076] The user (child) enters answers to questions displayed on the terminal. The terminal sends the entered data to the server. After sending, the terminal either moves on to the next question or waits for a response.

[1077] Step 4: Automated scoring

[1078] The server analyzes the received answer, compares it with the correct answer database, and determines whether it is correct or incorrect. The server generates a judgment result (correct or incorrect) and returns it to the terminal.

[1079] Step 5: Receive and view feedback

[1080] The device receives the scoring results sent from the server. It displays the received results to the user. If the answer is correct, it prompts the user to check their progress or move on to the next step. If the answer is incorrect, it displays additional hints or explanations.

[1081] Step 6: Doing a rework

[1082] If the user (child) answers incorrectly, they can try the same question again. They receive the same answer and enter the answer again. The device then sends the new answer to the server again.

[1083] Step 7: Save your data

[1084] The server stores each user's learning history in a database, including details such as the questions answered, the answers, whether they were correct or incorrect, the time it took to answer, the number of attempts, etc. The stored data is used for later analysis.

[1085] Step 8: Review progress and provide feedback

[1086] The user (educator or guardian) sends a request to the server to check the learning history through a dedicated management screen. The server analyzes the saved learning history and displays it on the management screen. It also notifies the educator or guardian of the analysis results.

[1087] Step 9: Strengths and weaknesses analysis and notification

[1088] The server analyzes learning history data to identify each user's strengths and weaknesses. The analysis results are communicated through a dedicated management screen, allowing educators and parents to understand each child's progress and learning needs.

[1089] The above processing steps enable efficient operation of the system. Children can instantly know their results, and educators and parents can easily check detailed progress. This allows for effective educational support.

[1090] Example 1

[1091] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1092] With conventional learning support systems, feedback when children are working on learning materials tends to be delayed, making it difficult to confirm answers or provide feedback in real time. Furthermore, the means by which educators and parents can check learning histories and analysis results are limited, making it difficult to grasp each child's learning progress and strengths and weaknesses. This makes it difficult to provide support at the appropriate time, resulting in problems such as reduced learning efficiency.

[1093] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1094] In this invention, the server includes an information terminal for the child to use to study materials, an information processing device that receives answers entered from the information terminal and automatically judges them, means for receiving the judgment results from the information processing device and displaying the results on the information terminal, information processing device means for saving and analyzing the child's study history, means for notifying educators and parents of the analysis results from the information processing device, means for identifying areas of strength and weakness based on the study history and the analysis results, means for the child to select from study materials displayed on the information terminal, means for displaying additional hints and explanations when an incorrect answer is given, and means for the child to try again and transmit the study history to the information processing device. This allows the child to study efficiently while receiving feedback in real time, and allows educators and parents to provide support and feedback at appropriate times.

[1095] An "information terminal" is a device that allows a user to work through study materials and input answers.

[1096] An "information processing device" is a device that receives the answer sent from the information terminal, automatically judges it, and returns the result.

[1097] "Learning history" refers to recorded data such as the content of answers, whether they were correct or incorrect, and the time it took to answer when a child worked on learning materials.

[1098] The "analysis results" are data generated based on the learning history to identify the child's strengths and weaknesses.

[1099] "Educators and parents" refers to those responsible for overseeing a child's learning and providing support where necessary.

[1100] "Real-time feedback" refers to the ability to instantly provide a correct or incorrect answer, and possibly additional hints or explanations, immediately after a child enters their answer.

[1101] The "retry feature" is a function that allows a child to try again on a question that was answered incorrectly.

[1102] "Storage means" refers to a function for long-term storage of answers entered by children and their learning history.

[1103] "Notification means" refers to a function for notifying educators and parents of the analysis results from the server.

[1104] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described in detail below with reference to the accompanying drawings.

[1105] System configuration

[1106] The system consists of the following main components:

[1107] 1. Terminal (information terminal)

[1108] 2. Server (information processing device)

[1109] 3. Users (children, educators, parents)

[1110] Hardware and software used

[1111] Device: This is the information device used by the child, such as a PC or tablet, which displays learning materials and inputs answers.

[1112] Server: An information processing device that receives, stores, processes data from users, and generates analytical results. The server is equipped with a database and AI model.

[1113] Software: An automatic scoring algorithm implemented in Python, database management software, and a web application providing the user interface.

[1114] Data processing and calculation

[1115] The terminal does the following:

[1116] 1. Receive learning materials sent from the server and display them to the user (child).

[1117] 2. The answer entered by the user (child) is sent to the server.

[1118] 3. The scoring results received from the server are displayed to the user (child).

[1119] The server does the following:

[1120] 1. The answers received from the device are judged by an automatic scoring algorithm.

[1121] 2. The scoring results are returned to the device.

[1122] 3. The received answer data and scoring results are stored in a database.

[1123] 4. Analyze your learning history and identify your strengths and weaknesses.

[1124] 5. Notify educators and parents of the analysis results.

[1125] Specific examples

[1126] When the server uploads a new math workbook, the device will notify the user that a new math workbook has been added. The child can tap the new workbook to open it and work on the problems. For example, if the child types "5+3=8" and presses the "Submit" button, the device will send the answer to the server.

[1127] The server uses an AI model implemented in Python to check whether the received answer "8" is correct. The server then sends the result "Correct!" to the device. The device displays "Correct!" or "Incorrect. Let's try again," and if the answer is incorrect, provides a hint such as "Try counting again."

[1128] Educators or parents can check their children's learning history through a dedicated management screen. The server generates analysis results such as "Child A is good at math calculation problems but not at word problems."

[1129] Prompt Sentence Examples

[1130] Below are some example prompts to input to a generative AI model:

[1131] "Generate 10 math problems."

[1132] "Based on the child's answers, identify areas of weakness and generate hints for them."

[1133] "Implement a system that analyzes learning progress in real time and provides feedback."

[1134] Although the embodiments of the present invention have been described above, many other variations are possible in the specific implementation methods. Various changes and modifications are possible within the scope of the present invention, and these are also included.

[1135] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1136] Step 1: Receive and view study materials

[1137] The server generates new learning materials (e.g., math drills) and sends them to the terminal. The terminal displays the received learning materials to the user (child). The user (child) selects the learning material to work on from the materials.

[1138] Input: Study material data sent from the server

[1139] Output: A list of study materials displayed on the device screen

[1140] Specific behavior: When the server uploads a new math workbook, the device notifies the user that "A new math workbook has been added," and the user (child) taps it to open it.

[1141] Step 2: Enter and submit your answers

[1142] The user (child) inputs answers to questions in the study materials displayed on the terminal, and the terminal then sends the answers to the server.

[1143] Input: Answer data entered by the user (child)

[1144] Output: Answer data sent from the device to the server

[1145] Specific operation: When the user (child) enters "5+3=8" and presses the "Send" button, the device sends this answer data to the server.

[1146] Step 3: Automated scoring

[1147] The server uses a generative AI model to automatically determine whether the answer received from the device is correct or incorrect, and the result is sent back to the device.

[1148] Input: Answer data sent from the device

[1149] Output: The score results sent back from the server to the device

[1150] Specific operation: The server uses an AI model implemented in Python to check whether the received answer "8" is correct. The server then sends the result "That's correct!" to the device.

[1151] Step 4: View your feedback

[1152] The terminal displays the score received from the server to the user (child). If the answer is incorrect, the terminal provides additional hints and explanations to the user (child).

[1153] Input: The score returned from the server

[1154] Output: Feedback displayed on the device screen

[1155] Specific behavior: The device will display "Correct!" or "Incorrect. Try again," and if the answer is incorrect, it will provide a hint such as "Try counting again."

[1156] Step 5: Try again and try again

[1157] The user (child) revisits the questions that were answered incorrectly and enters the answer, and this process is repeated until the correct answer is obtained.

[1158] Input: Answer data re-entered by the user (child)

[1159] Output: Answer data sent from the device to the server, and new scoring results returned from the server.

[1160] Specific operation: The user (child) enters "7" and is incorrect, then repeats this operation until they enter "8" again and confirm the correct answer.

[1161] Step 6: Save your learning history

[1162] The server stores data on each user (child), such as answer history, correct answers, and answer time. This data is used for later analysis.

[1163] Input: User (child) answer data and scoring result data

[1164] Output: Learning history stored in the server database

[1165] Specific operation: The server stores detailed history in a database, such as "Question 1: 5+3, correct answers: 8, number of incorrect answers: 1, number of correct answers: 1, answer time: 15 seconds."

[1166] Step 7: Check progress and communicate analysis results

[1167] Educators or parents can check the learning history of users (children) through a dedicated management screen. The server generates and notifies the results of analysis.

[1168] Input: Learning history data stored on the server

[1169] Output: Analysis results displayed on the educator and parent management screen

[1170] Specific operation: The educator logs in to the management screen and checks the progress of Child A. The server displays the analysis results on the management screen, such as "Child A is good at math calculation problems, but not so good at word problems."

[1171] (Application example 1)

[1172] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1173] Learning to operate robots in factories is difficult for operators due to the complex procedures and high precision required. Conventional training methods make it difficult for operators to immediately grasp their own progress, and the slow feedback reduces efficiency. It is also difficult for managers to quickly identify an operator's strengths and weaknesses and provide appropriate guidance. Therefore, there is a need for a system that allows operators to efficiently learn robot operation procedures, receive instant feedback, and allow managers to easily grasp their progress.

[1174] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1175] In this invention, the server includes a terminal on which an operator works on the operation procedures, means for receiving answers entered from the terminal and automatically grading them, means for receiving the grading results from the server and displaying the results on the terminal, means for saving and analyzing the learning history of the operator, means for notifying an administrator of the analysis results from the server, and means for identifying areas of strength and weakness based on the learning history and the analysis results. This allows the operator to efficiently learn the robot operation procedures and receive immediate feedback, and also enables the administrator to easily understand the progress and provide appropriate guidance.

[1176] "Operator" refers to the person in charge of operating and training the robot within the factory.

[1177] A "terminal" refers to an information processing device used by an operator, such as a smartphone, tablet, or head-mounted display.

[1178] "Solution" refers to the result or answer that an operator enters when working through an operating procedure.

[1179] The "server" is a central processing unit that receives answers from operators, automatically grades them, and sends back feedback.

[1180] "Scoring" refers to the process of determining whether an operator's answer is correct.

[1181] "Feedback" refers to information about whether an answer is correct or incorrect, as well as additional advice and hints, sent from the server to the operator.

[1182] "Learning history" refers to data such as the operator's answer history, correct answers, and answer time.

[1183] "Analysis results" refers to information such as areas of strength and weakness that is generated by the server based on learning history.

[1184] "Supervisor" refers to the person in charge of the factory who monitors the progress of the operators and provides appropriate guidance.

[1185] "Notification" refers to the process by which the server communicates important information such as analysis results and operator progress to the administrator.

[1186] As an embodiment of the present invention, a method for constructing a system that enables operators in a factory to learn robot operation procedures, receive immediate feedback, and efficiently manage the progress will be described below.

[1187] Configuration overview

[1188] The system consists of the following main components:

[1189] 1. Terminal

[1190] 2. Server

[1191] 3. User (operator, administrator)

[1192] Explanation of program processing

[1193] Displaying operating instructions

[1194] The server sends new operation procedures to the terminal, which displays a list of them, allowing the operator to select and execute the operation procedure on the terminal.

[1195] Examples:

[1196] When the server uploads a new robot configuration procedure, the terminal displays "New robot configuration procedure added," and the operator taps it to open it.

[1197] Enter your answer

[1198] The operator inputs answers to the operating procedures displayed on the terminal, and the terminal sends the input answers to the server.

[1199] Examples:

[1200] When the operator types "Turn on the robot" and presses the "Send" button, the terminal sends this answer to the server.

[1201] Automatic scoring

[1202] The server automatically determines whether the answer is correct or incorrect based on the answer received from the device, and sends the result back to the device.

[1203] Examples:

[1204] The server checks whether "Turn on the robot" is the correct answer and returns the result to the terminal, saying "Correct!" or "Incorrect."

[1205] View Feedback

[1206] The terminal displays the score received from the server to the operator. If the answer is incorrect, the terminal provides additional hints and explanations to the operator.

[1207] Examples:

[1208] The device will display "That's right!" or "That's wrong. Try again," and if the answer is incorrect, it will provide a hint such as "Check the detailed instructions and try again."

[1209] Doing it over and trying again

[1210] The operator retrys the incorrect operation sequence and enters the answer, and this process is repeated until the correct answer is obtained.

[1211] Examples:

[1212] The operator types "start robot" which is an incorrect answer, and then types "power on robot" again, repeating this process until the correct answer is confirmed.

[1213] Save learning history

[1214] The server stores data such as each operator's answer history, correct answers, and answer time, which will be used for later analysis.

[1215] Examples:

[1216] The server stores detailed history of operator A, such as "Step 1: Turn on the robot, correct, number of incorrect answers: 1, number of correct answers: 1, response time: 15 seconds."

[1217] Progress check and analysis results notification

[1218] Administrators can check the learning history of operators through a dedicated management screen. The server generates and notifies the results of the analysis.

[1219] Examples:

[1220] When the administrator checks the progress of Operator A on the management screen, the server displays a list of Operator A's performance and history. In addition, the server generates and notifies the administrator of the results of an analysis, such as "Operator A is good at setting up the robot, but is not good at emergency shutdown procedures."

[1221] Hardware and software used

[1222] This system mainly uses the following hardware and software:

[1223] Hardware: Devices such as smartphones, tablets, and head-mounted displays.

[1224] Software: Server-side program using Python, terminal application for displaying operation procedures.

[1225] Example prompts to input to the generative AI model

[1226] Here is the prompt to input to a generative AI model (e.g. ChatGPT):

[1227] "Generate guidelines for learning troubleshooting steps and getting immediate feedback for a factory robotics training application. Include the following steps:

[1228] 1. Check for abnormal robot stoppage

[1229] 2. Analysis of abnormal code

[1230] 3. Take any necessary corrective steps

[1231] 4. Check for proper operation

[1232] Please also include any explanations or advice you would like to give the operator at each step.

[1233] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1234] Step 1:

[1235] The server sends the new operating procedure to the terminal. Specifically, the server retrieves the new operating procedure from the operating procedure database and sends it to the terminal. The terminal receives this data and displays a list of operating procedures to the operator. The input information is the new operating procedure, and the output result is the list of operating procedures displayed on the operator's terminal.

[1236] Step 2:

[1237] The operator selects the item they want to learn from the operating procedures displayed on the terminal. Specifically, when the operator taps or selects an item, the terminal notifies the server of the selected operating procedure. The input information is the operating procedure selected by the operator, and the output result is a notification of the selected item to the server.

[1238] Step 3:

[1239] The server sends specific tasks related to the selected operating procedure to the terminal. Specifically, the server retrieves task details corresponding to the selected operating procedure from the database and sends them to the terminal. The terminal receives this data and displays the tasks to the operator. The input information is the selected operating procedure, and the output result is the task details displayed on the operator's terminal.

[1240] Step 4:

[1241] The operator inputs answers to each task displayed on the terminal. Specifically, the operator enters the answer in the input field and presses the send button, which causes the terminal to send the answer to the server. The input information is the answer entered by the operator, and the output result is the answer sent to the server.

[1242] Step 5:

[1243] The server automatically scores the received answers. Specifically, the server compares the answer data with a database of correct answers to determine whether they match. The input information is the operator's answer data, and the output is a judgment result of whether the answer is correct or incorrect.

[1244] Step 6:

[1245] The server sends the scoring results to the terminal. Specifically, the server generates a judgment result and sends it to the terminal. The terminal receives this data and displays the scoring results to the operator. The input information is the scoring result data, and the output is the scoring result display on the operator's terminal.

[1246] Step 7:

[1247] If the answer is incorrect, the terminal provides the operator with additional hints and explanations. Specifically, the terminal retrieves appropriate hints and explanations from a feedback database for incorrect answers and displays them to the operator. The input information is the result of the incorrect answer determination, and the output is the hint or explanation displayed on the operator terminal.

[1248] Step 8:

[1249] The operator attempts the task again if the answer was incorrect and re-enters the answer. Specifically, the operator re-enters the answer and presses the send button, causing the terminal to send the new answer to the server. The input information is the re-entered answer, and the output result is the re-sent answer sent to the server.

[1250] Step 9:

[1251] The server stores each operator's learning history, including answer history, correct / incorrect answers, and answer time. Specifically, answer data and scoring results are recorded in a database. Input information is the operator's answer history data, and output results are stored in the database.

[1252] Step 10:

[1253] The server displays the saved learning history and analysis results in response to a request from an administrator. Specifically, the server receives the administrator's request through the management screen, retrieves the saved data from the database, generates the analysis results, and displays them on the management screen. The input information is the administrator's request, and the output is the analysis results displayed on the management screen.

[1254] The above is the specific processing flow of the factory robot operation training system.

[1255] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1256] As an embodiment of the invention, the following describes how an emotion engine that recognizes user emotions can be incorporated into a system that allows children to engage with learning material and receive instant feedback to effectively manage their progress.

[1257] Configuration overview

[1258] The system consists of the following main components:

[1259] 1. Device (with emotion engine)

[1260] 2. Server

[1261] 3. Users (children, educators, parents)

[1262] Explanation of program processing

[1263] View learning materials

[1264] The terminal receives new learning materials sent from the server and displays a list of them to the child. The user (child) can select learning materials to work on on the terminal.

[1265] example:

[1266] When the server uploads a new math workbook, the device displays "New math workbook added," and the child taps it to open it.

[1267] Enter your answer

[1268] The child inputs answers to questions in the learning materials displayed on the device, and the device sends the input answers along with emotional data analyzed by the emotion engine to the server.

[1269] example:

[1270] When the child enters "5+3=8" and presses the "Send" button, the device sends this answer along with the current emotional data (e.g., confidence, joy) analyzed by the emotion engine to the server.

[1271] Automatic scoring

[1272] The server automatically determines whether the answer is correct or incorrect based on the answer received from the device, and sends the result along with the emotion data back to the device.

[1273] example:

[1274] The server checks whether "8" is the correct answer and returns the result to the terminal along with emotional data, saying "That's correct!" or "That's incorrect."

[1275] Receiving and viewing feedback

[1276] The device receives the score and emotion data sent from the server and displays them to the user. If the answer is incorrect, the device provides additional hints and explanations to the child and displays feedback according to the emotion provided by the emotion engine.

[1277] example:

[1278] The device will display "That's right!" or "That's wrong. Let's try again." If the answer is incorrect, the device will provide a hint like "Try counting again," as well as emotional feedback like "Remain calm and try again."

[1279] Doing it over and trying again

[1280] If the child answers incorrectly, they can try the same question again and send a new answer along with their emotional data to the server.

[1281] example:

[1282] The process repeats until the child enters "7" to confirm the answer is incorrect and then enters "8" again to confirm the answer is correct. Emotional data is also sent each time.

[1283] Data storage

[1284] The server stores each user's learning history and emotional data in a database, including details such as the questions answered, the answers, whether they were correct or incorrect, the time it took to answer, the number of retries, and emotional data. The stored data is used for later analysis.

[1285] example:

[1286] The server stores detailed history for Child A, such as "Question 1: 5+3, correct answers: 8, number of incorrect answers: 1, number of correct answers: 1, answer time: 15 seconds, emotional data: joy."

[1287] Progress review and feedback

[1288] Educators or parents can send a request to the server to check the learning history and emotional data through a dedicated management screen. The server analyzes the saved learning history and displays it on the management screen. It also notifies the educator or parent of the results of the analysis.

[1289] example:

[1290] When an educator checks Child A's progress on the management screen, the server displays a list of Child A's grades, history, and emotional data. The server also generates and notifies the educator of analysis results such as, "Child A is good at math calculation problems, but struggles with word problems and appears unsure of his or her answers."

[1291] Effects of implementation

[1292] By implementing this system, children can instantly know whether their answers are correct or incorrect and receive appropriate feedback based on their emotions. Educators and parents can understand detailed progress and emotional states, allowing them to provide more effective support. By clarifying each child's strengths and weaknesses, as well as their emotions at any given time, it is expected that the quality of education will be improved.

[1293] In this way, the system based on the aspects of the present invention is expected to solve multiple problems in educational settings and provide effective learning support.

[1294] The processing flow will be explained below.

[1295] Step 1: Upload your study materials

[1296] The server receives an upload request from an educator or system administrator. The server stores the learning material file (e.g., math drills) and associates it with each child's account. After the file is saved, it sends a notification to the device that the upload is complete.

[1297] Step 2: View study materials

[1298] The device receives notifications of new learning materials from the server, and the user (child) selects what to work on from the list of new learning materials displayed on the device.

[1299] example:

[1300] When the server uploads a new math workbook, the device displays "New math workbook added," and the user taps it to open it.

[1301] Step 3: Start Emotion Recognition

[1302] The device's built-in emotion engine analyzes data such as the child's facial expressions, voice, and touch pressure in real time to generate current emotion data (e.g., excitement, concentration, confusion).

[1303] example:

[1304] The device instructs the user to "relax and take a deep breath before you begin this problem," while the emotion engine collects data.

[1305] Step 4: Enter your answers

[1306] The user (child) inputs answers to questions displayed on the device. Emotional data is also continuously collected. The device transmits the input answers and emotional data to the server.

[1307] example:

[1308] When a child enters "5+3=8" and presses the "Send" button, the device sends this answer along with emotional data (e.g., confidence, joy) to the server.

[1309] Step 5: Automated scoring

[1310] The server automatically determines whether the answer is correct or incorrect based on the answer received from the device, and sends the result along with the emotion data back to the device.

[1311] example:

[1312] The server checks whether "8" is the correct answer and returns the result to the terminal along with emotional data, saying "That's correct!" or "That's incorrect."

[1313] Step 6: Receive and view feedback

[1314] The device receives the score and emotion data sent from the server and displays them to the user. If the answer is incorrect, the device provides additional hints and explanations to the child and displays feedback according to the child's emotion.

[1315] example:

[1316] The device will display "That's right!" or "That's wrong. Let's try again." If the answer is incorrect, the device will provide hints such as "Try counting again," as well as emotional feedback such as "Remain calm and try again."

[1317] Step 7: Doing a rework

[1318] If the user (child) answers incorrectly, they can try the same question again and send a new answer along with their emotion data to the server.

[1319] example:

[1320] The process repeats until the child enters "7" to confirm the answer is incorrect and then enters "8" again to confirm the answer is correct. Emotional data is also sent each time.

[1321] Step 8: Save your data

[1322] The server stores each user's learning history and emotional data in a database, including details such as the questions answered, the answers, whether they were correct or incorrect, the time it took to answer, the number of retries, and emotional data. The stored data is used for later analysis.

[1323] example:

[1324] The server stores detailed history for Child A, such as "Question 1: 5+3, correct answers: 8, number of incorrect answers: 1, number of correct answers: 1, answer time: 15 seconds, emotional data: joy."

[1325] Step 9: Review progress and provide feedback

[1326] The user (educator or parent) sends a request to the server to check the learning history and emotional data through a dedicated management screen. The server analyzes the saved learning history and displays it on the management screen. It also notifies the educator or parent of the analysis results.

[1327] example:

[1328] When an educator checks Child A's progress on the management screen, the server displays a list of Child A's grades, history, and emotional data. The server also generates and notifies the educator of analysis results such as, "Child A is good at math calculation problems, but struggles with word problems and appears unsure of his or her answers."

[1329] Effects of implementation

[1330] By implementing this system, children can instantly know whether their answers are correct or incorrect and receive appropriate feedback based on their emotions. Educators and parents can understand detailed progress and emotional states, allowing them to provide more effective support. By clarifying each child's strengths and weaknesses, as well as their emotions at any given time, it is expected that the quality of education will be improved.

[1331] In this way, the system based on the aspects of the present invention is expected to solve multiple problems in educational settings and provide effective learning support.

[1332] Example 2

[1333] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1334] In traditional educational systems, it is difficult for children to receive immediate feedback when working on learning materials. Furthermore, feedback provided does not take into account the child's emotional state, which can lead to a decrease in motivation to learn and increased stress. Educators and parents are unable to grasp a child's learning progress and emotional state in real time, making it difficult to provide appropriate support. This makes it difficult to identify individual children's strengths and weaknesses and provide effective educational support.

[1335] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving answers entered from the terminal and emotion data analyzed by the emotion engine, means for automatically scoring based on the answers and generating scoring results including emotion data, and means for receiving the scoring results from the server and displaying the results on the terminal. This allows children to instantly receive feedback based on their answers and emotions. Furthermore, educators and parents can grasp children's learning progress and emotional state in real time and provide more effective support.

[1336] "Devices" refer to electronic devices that children use to engage with learning materials and are equipped with emotion engines that can analyze emotional data.

[1337] "Answer" refers to a child's input to the study material, which is sent to the server for validation.

[1338] An "emotion engine" refers to an algorithm or software that analyzes emotions from a user's facial expressions, voice, etc.

[1339] "Emotion data" refers to data relating to the user's emotional state obtained as a result of analysis by the emotion engine.

[1340] "Server" refers to a computer system that automatically grades answers, stores and analyzes learning history and emotional data.

[1341] "Scoring result" refers to the result of whether the answer is correct or incorrect as determined by the server based on the child's answer.

[1342] "Feedback" refers to hints, encouragement, explanations, etc. that are displayed on the device based on the answer results and emotional data.

[1343] "Educators and parents" refers to adults who supervise a child's learning progress and provide appropriate support.

[1344] "Learning history" refers to a detailed record of the learning materials a child has worked on, their answers, whether correct or incorrect, how long it took to answer, and emotional data.

[1345] "Analysis results" refers to the results of analysis performed by the server based on learning history and emotional data.

[1346] "Strengths and weaknesses" refers to the range of learning content in which a child excels or struggles.

[1347] As an embodiment of the present invention, a method for incorporating an emotion engine that recognizes user emotions into a system for children to work on learning materials, receive instant feedback, and efficiently manage their progress is described below. The system is composed of terminals, a server, and users (children, educators, and parents).

[1348] Hardware and Software Used

[1349] Device: Tablet or PC with emotion engine (e.g. iPad, Chromebook)

[1350] Server: Learning materials management and database (e.g. AWS EC2, MySQL)

[1351] Sentiment engine: AI algorithms for sentiment analysis (e.g. Azure Cognitive Services)

[1352] System Operation Overview

[1353] 1. The server manages the learning materials uploaded by the educator and sends them to the terminal.

[1354] 2. The terminal displays the learning materials received from the server to the child, and the child works on the learning materials.

[1355] 3. The child enters the answer to the study question, and the device sends the answer along with the emotional data analyzed by the emotion engine to the server.

[1356] 4. The server automatically scores the received answers and generates scoring results that include emotion data.

[1357] 5. The device receives the score and emotion data sent from the server and displays them to the child. Based on the emotion data, the device provides additional feedback.

[1358] 6. The server stores learning history and emotional data, and based on this identifies strengths and weaknesses in each area.

[1359] 7. Educators and parents can check learning history and analysis results through the management screen and provide effective support to their children.

[1360] Specific examples

[1361] Example 1: When the server uploads a new math workbook, the device displays "A new math workbook has been added," and the child taps it to open it. When the child enters "5+3=8" and presses the "Send" button, the device sends this answer along with emotional data (e.g., confidence, joy) to the server.

[1362] Example 2: The server checks the answer "8" and, since it is correct, sends the message "That's right!" along with emotional data to the device. The device then displays "That's right! You seem confident!" If the answer is incorrect, it provides feedback such as "Think about it again" or "Calm down and try again."

[1363] Example 3: When an educator checks a child's progress on the management screen, the server displays a list of the child's grades, history, and emotional data, and notifies them of the analysis results, such as "Child A is good at math calculation problems but not so good at word problems."

[1364] Example prompts to input to the generative AI model

[1365] "How can I be notified when new learning materials are added?"

[1366] "Please explain the process for sending the answers entered by the child to the server."

[1367] "Please explain in detail how the server scores the answers and returns the results."

[1368] By building such a system, children can efficiently understand their learning content and receive appropriate emotional feedback, allowing educators and parents to monitor their learning progress in detail and provide support tailored to each individual child.

[1369] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1370] Step 1:

[1371] The server receives the learning materials uploaded by the educator, which are stored in a database and ready to be sent to the device.

[1372] Input: Learning materials uploaded by educators (e.g., math drills)

[1373] Output: The learning materials are saved in a database ready to be sent to the device.

[1374] Specific operation: The server receives PDF files and digital text format learning materials added by educators, stores them in a database, and then generates a material ID and metadata and notifies the device.

[1375] Step 2:

[1376] The terminal displays the new learning materials received from the server to the child.

[1377] Input: Learning material notification from the server (e.g., notification of new math drills added)

[1378] Output: A list of study materials will be displayed on the child's device screen.

[1379] Specific behavior: A notification saying "New math drills have been added" will be displayed on the device screen, and users can tap to access the content.

[1380] Step 3:

[1381] The user (child) inputs answers to questions in the study materials displayed on the device. At the same time, the device generates emotion data analyzed by the emotion engine.

[1382] Input: The answer entered by the child (e.g. 5+3=8)

[1383] Output: Answer and emotion data are generated (e.g., confidence, joy)

[1384] Specific operation: When a child enters an answer and presses the send button, the device's built-in camera and microphone are activated to analyze facial expressions and voice and generate emotional data.

[1385] Step 4:

[1386] The terminal transmits the answer and emotion data to the server.

[1387] Input: Child's answers and emotion data

[1388] Output: Answers and emotion data are sent to the server

[1389] Specific operation: The device combines the answer and emotion data into a single data packet, encrypts it, and sends it to the server.

[1390] Step 5:

[1391] The server automatically determines whether the answer received from the terminal is correct or incorrect and generates a scoring result that includes emotional data.

[1392] Input: Answers and emotion data sent from the device

[1393] Output: Scoring results and emotional feedback data

[1394] What it does: The server's algorithm scores the answers, generates a "correct" or "incorrect" result, and creates a feedback message with emotional data.

[1395] Step 6:

[1396] The server returns the scoring results and emotion data to the terminal.

[1397] Input: Scoring results and emotional feedback data

[1398] Output: Feedback data sent to the device

[1399] Specific operation: The server compiles the scoring results and the emotion feedback message into a data packet and sends it to the device.

[1400] Step 7:

[1401] The device receives the score and emotion data sent from the server and displays them to the user (child). If the answer is incorrect, the device also provides additional hints and emotion-based feedback.

[1402] Input: Scoring results and emotional feedback data sent from the server

[1403] Output: Feedback displayed on the terminal screen

[1404] What it does: Show feedback on the device screen, such as "That's right!", "You look confident!", or "Think again" or "Calm down and try again."

[1405] Step 8:

[1406] If the user (child) answers incorrectly, they can try the same question again.

[1407] Input: New answer and emotion data

[1408] Output: Retry data sent to the server

[1409] What it does: If the child enters a different answer and submits it again, the new answer and emotion data are sent to the server and re-evaluated.

[1410] Step 9:

[1411] The server stores each user's learning history and emotional data in a database.

[1412] Input: Answers, emotion data, scoring results

[1413] Output: Saved learning history and emotion data

[1414] Specific operation: The server stores detailed data such as "question ID, answer, correct / incorrect answer, number of times, time, emotional data" in a database.

[1415] Step 10:

[1416] The server displays the saved learning history and emotional data on the management screen in response to requests from educators or parents, and also notifies them of the analysis results.

[1417] Input: History view request from educator or parent

[1418] Output: Learning history and analysis results displayed on the management screen

[1419] Specific operation: The server receives the request, extracts and analyzes the necessary data, and displays the analysis results on the management screen, such as "Child A is good at math calculation problems but not at word problems."

[1420] (Application example 2)

[1421] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1422] While immediate feedback and correct answers are important for children's learning, conventional systems do not provide support that takes into account the child's emotional state. This can lead to children feeling stressed and frustrated, which can decrease their motivation to learn. It is also difficult for educators and parents to properly understand a child's progress and emotional state and provide effective support.

[1423] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1424] In this invention, the server includes a means for receiving answers entered from the terminal and automatically scoring them, an emotion recognition means for the terminal to recognize the child's emotions and send the data to the server, and a means for receiving the scoring results and emotion data from the server and displaying the results on the terminal. This makes it possible to grasp the emotional state of a child while they are learning in real time and provide appropriate feedback. Furthermore, educators and parents can grasp the child's detailed progress and emotional state and provide more effective support.

[1425] A "terminal" is a device for displaying study materials and inputting user answers.

[1426] A "server" is a central computer system that receives data sent from terminals and processes and analyzes it.

[1427] The "emotion recognition means" has the function of analyzing the child's facial expressions and behavior and determining their emotional state.

[1428] The "feedback generation means" is a function for generating appropriate feedback to the child based on whether the answer is correct or incorrect.

[1429] "Learning history" is a record of data such as the learning materials a child has worked on, the content of their answers, the time it took to answer, and whether they were correct or incorrect.

[1430] "Analysis results" are the results of analysis using statistical and machine learning methods based on learning history and emotional data.

[1431] An "educator" is someone who provides educational guidance to children, i.e., a teacher or instructor.

[1432] A "guardian" is a parent or caregiver who oversees a child's life and education.

[1433] A "system" is a set of devices or software in which multiple components work together to achieve a specific function.

[1434] "Feedback" refers to advice and evaluations provided based on a user's actions and answers.

[1435] "Emotional data" is information that expresses a child's emotional state in numerical values ​​and categories.

[1436] The system for implementing this invention consists of the following main components: a terminal, a back-end server, an emotion recognition engine, and a database.

[1437] Component Details

[1438] Terminal

[1439] The terminal is a device that displays learning materials and allows users (children) to input answers. Specifically, it includes smartphones, tablets, and PCs. The terminal is equipped with an emotion recognition engine, and uses a built-in camera to capture video of the child's face and analyze the emotional data.

[1440] Backend Server

[1441] The backend server is a central computer system that receives data sent from the devices and automatically scores them. It uses cloud servers such as Node.js and AWS Lambda. The server analyzes the received answers and emotion data and generates appropriate feedback.

[1442] Emotion Recognition Engine

[1443] The emotion recognition engine uses Python, OpenCV, Google Cloud AI / ML API, etc. to analyze a child's facial expressions and behavior and determine their emotional state.

[1444] Database

[1445] The database is used to store learning history and emotional data. Specifically, AWS RDS and MongoDB are used. The database stores details such as answer content, answer time, correct / incorrect status, number of retry attempts, and emotional data, and is used for later analysis.

[1446] Processing flow

[1447] 1. Viewing study materials

[1448] The device receives new learning materials sent from the server and displays a list of them to the child, who can then select and work on the learning materials on the device.

[1449] Example: When the server uploads a new math workbook, the device displays "New math workbook added," and the child taps it to open it.

[1450] 2. Enter your answer

[1451] The child inputs answers to questions in the learning materials displayed on the device, and the device sends the input answers along with emotional data analyzed by the emotion engine to the server.

[1452] Example: When a child enters "5+3=8" and presses the "Send" button, the device sends this answer along with the current emotional data (e.g., confidence, joy) analyzed by the emotion engine to the server.

[1453] 3. Automatic scoring

[1454] The server automatically determines whether the answer is correct or incorrect based on the answer received from the device, and sends the result along with the emotion data back to the device.

[1455] Example: The server checks whether "8" is the correct answer and returns the result to the device along with emotion data, such as "That's correct!" or "That's incorrect."

[1456] 4. Receiving and Viewing Feedback

[1457] The device receives the score and emotion data sent from the server and displays them to the user. If the answer is incorrect, the device provides additional hints and explanations to the child and displays feedback according to the emotion provided by the emotion engine.

[1458] For example, the device might say "That's right!" or "That's wrong, let's try again," and if the answer is incorrect, it might provide a hint like "Try counting again," along with emotional feedback like "Remain calm and try again."

[1459] Specific examples

[1460] Consider a case where a child logs in and starts working on a math drill. As the child enters the answer, the built-in camera analyzes the child's emotions and determines that the child is frustrated. This information is sent to the server. For example, the child enters "5+3=7," which is incorrect, and then enters "5+3=8" again, repeating this process until the correct answer is confirmed. During this process, the child's emotional data is also updated, and eventually a message such as "That's correct, but please calm down and try again" is displayed.

[1461] Prompt Sentence Examples

[1462] ---

[1463] The answer entered by the child is incorrect. The child's emotion is "irritated." Please generate a feedback sentence according to the emotion.

[1464] ---

[1465] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1466] Step 1:

[1467] The terminal receives new learning materials sent from the server and displays a list of them to the child.

[1468] Input: Learning material data from the server.

[1469] Output: Learning materials list screen.

[1470] Specific operation: The terminal receives the data of the learning materials and displays them to the child through the GUI. The child then performs operations to select learning materials.

[1471] Step 2:

[1472] The user (child) inputs answers to questions in the study materials displayed on the terminal.

[1473] Input: Child's answer data.

[1474] Output: A request with answer and sentiment data.

[1475] How it works: The child enters their answer using the touchscreen or keyboard, and the device's emotion recognition engine analyzes the facial image to obtain their current emotional data.

[1476] Step 3:

[1477] The server receives the answer data and emotion data from the terminal.

[1478] Input: Answer data and emotion data from the device.

[1479] Output: A new dataset for automatic marking and feedback generation.

[1480] Specific operation: The server passes the answer data to an automatic scoring algorithm to determine whether it is correct or incorrect. The emotion data is stored in a database.

[1481] Step 4:

[1482] The server generates feedback based on the scoring results and creates a feedback statement that takes into account the emotion data.

[1483] Input: Scoring results and emotion data.

[1484] Output: Feedback message.

[1485] Specific operation: The server uses a generative AI model to create a prompt sentence and generates a feedback sentence according to the emotion.

[1486] Example: If a child answers incorrectly and their emotion is determined to be "irritated," the following prompt sentence is input into the generative AI model:

[1487] "The answer the child entered is incorrect. The child's emotion is 'frustrated'. Please generate feedback sentences based on the emotion."

[1488] Step 5:

[1489] The server sends a feedback message and the score back to the terminal.

[1490] Input: Feedback message.

[1491] Output: Sends feedback messages to the terminal.

[1492] Specific operation: The generated feedback message and the scoring result are sent from the server to the terminal.

[1493] Step 6:

[1494] The terminal displays the feedback message and the scoring results sent from the server to the user (child).

[1495] Input: Feedback message and grading results from the server.

[1496] Output: Feedback messages and grading results displayed in the user interface.

[1497] Specific operation: The device displays feedback messages and scoring results to the child through a GUI. If the answer is incorrect, additional hints and explanations are also displayed.

[1498] Step 7:

[1499] If the user (child) answers incorrectly, they enter the answer again and send the answer and emotion data to the server using the same procedure.

[1500] Input: Answer data and emotion data as above.

[1501] Output: Answer data and emotion data for resubmission.

[1502] Specific operation: The child re-enters the answer, and the device again analyzes the facial image to obtain new emotional data, which it then sends to the server again.

[1503] Step 8:

[1504] The server stores each user's learning history and emotional data in a database.

[1505] Input: Answer data, emotion data, scoring results.

[1506] Output: Save data to database.

[1507] Specific operation: The server stores details such as the answer content, answer time, correct / incorrect status, number of retries, and emotional data in a database (AWS RDS, MongoDB, etc.).

[1508] Step 9:

[1509] Educators or parents can check learning history and emotional data through a dedicated management screen.

[1510] Input: A request from an educator or parent.

[1511] Output: Display of learning history and emotion data on the management screen.

[1512] What it does: Educators or parents send a request to the server to check their child's progress on the management screen. The server analyzes the stored data and displays it on the management screen.

[1513] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1514] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1515] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1516] [Fourth embodiment]

[1517] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1518] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1519] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1520] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1521] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1522] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1523] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1524] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1525] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1526] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1527] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1528] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1529] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1530] The detailed description of the invention provides a method for creating a system that allows children to engage with learning material, receive immediate feedback, and effectively manage their progress.

[1531] Configuration overview

[1532] The system consists of the following main components:

[1533] 1. Terminal

[1534] 2. Server

[1535] 3. Users (children, educators, parents)

[1536] Explanation of program processing

[1537] View learning materials

[1538] The device receives new learning materials sent from the server and displays a list of them to the child, who can then select and work on the learning materials on the device.

[1539] example:

[1540] When the server uploads a new math workbook, the device displays "New math workbook added," and the child taps it to open it.

[1541] Enter your answer

[1542] The child inputs answers to questions in the learning materials displayed on the device, and the device sends the input answers to the server.

[1543] example:

[1544] When the child enters "5+3=8" and presses the "Send" button, the device sends this answer to the server.

[1545] Automatic scoring

[1546] The server automatically determines whether the answer is correct or incorrect based on the answer received from the device, and sends the result back to the device.

[1547] example:

[1548] The server checks whether "8" is the correct answer and returns the result to the terminal, saying either "Correct!" or "Incorrect."

[1549] View Feedback

[1550] The device displays the score received from the server to the child, and if the answer is incorrect, the device provides additional hints and explanations to the child.

[1551] example:

[1552] The device will display "That's right!" or "That's wrong. Try again," and if the answer is incorrect, it will provide a hint such as "Try counting again."

[1553] Doing it over and trying again

[1554] The child can retry any questions they got wrong and enter their answer, and the process repeats until they get it right.

[1555] example:

[1556] This is repeated until the child types in "7" to confirm the answer is incorrect and then types in "8" again to confirm the answer is correct.

[1557] Save learning history

[1558] The server stores data such as each child's answer history, correct answers, and answer time, which will be used for later analysis.

[1559] example:

[1560] The server stores detailed history for Child A, such as "Question 1: 5+3, correct answers: 8, number of incorrect answers: 1, number of correct answers: 1, answer time: 15 seconds."

[1561] Progress check and analysis results notification

[1562] Educators or parents can check their children's learning history through a dedicated management screen. The server generates and notifies the results of analysis.

[1563] example:

[1564] When an educator checks Child A's progress on the management screen, the server displays a list of Child A's grades and history. In addition, the server generates and notifies the educator of analysis results such as, "Child A is good at calculation problems in mathematics, but not at word problems."

[1565] Effects of implementation

[1566] By implementing this system, children can instantly know whether their answers are correct or incorrect, allowing them to study efficiently. In addition, educators and parents can easily understand their children's progress and provide appropriate feedback and support. By clarifying each child's strengths and weaknesses, the quality of education can be improved.

[1567] In this way, the system based on the aspects of the present invention is expected to solve multiple problems in educational settings and provide effective learning support.

[1568] The processing flow will be explained below.

[1569] Step 1: Upload your study materials

[1570] The server receives an upload request from an educator or system administrator. The server stores the learning material file (e.g., math drills) and associates it with each child's account. After saving, it sends a notification to the device that the upload is complete.

[1571] Step 2: View study materials

[1572] The device receives notifications of new learning materials from the server, and the user (child) selects what to work on from the list of new learning materials displayed on the device.

[1573] Step 3: Enter your answers

[1574] The user (child) enters answers to questions displayed on the terminal. The terminal sends the entered data to the server. After sending, the terminal either moves on to the next question or waits for a response.

[1575] Step 4: Automated scoring

[1576] The server analyzes the received answer, compares it with the correct answer database, and determines whether it is correct or incorrect. The server generates a judgment result (correct or incorrect) and returns it to the terminal.

[1577] Step 5: Receive and view feedback

[1578] The device receives the scoring results sent from the server. It displays the received results to the user. If the answer is correct, it prompts the user to check their progress or move on to the next step. If the answer is incorrect, it displays additional hints or explanations.

[1579] Step 6: Doing a rework

[1580] If the user (child) answers incorrectly, they can try the same question again. They receive the same answer and enter the answer again. The device then sends the new answer to the server again.

[1581] Step 7: Save your data

[1582] The server stores each user's learning history in a database, including details such as the questions answered, the answers, whether they were correct or incorrect, the time it took to answer, the number of attempts, etc. The stored data is used for later analysis.

[1583] Step 8: Review progress and provide feedback

[1584] The user (educator or guardian) sends a request to the server to check the learning history through a dedicated management screen. The server analyzes the saved learning history and displays it on the management screen. It also notifies the educator or guardian of the analysis results.

[1585] Step 9: Strengths and weaknesses analysis and notification

[1586] The server analyzes learning history data to identify each user's strengths and weaknesses. The analysis results are communicated through a dedicated management screen, allowing educators and parents to understand each child's progress and learning needs.

[1587] The above processing steps enable efficient operation of the system. Children can instantly know their results, and educators and parents can easily check detailed progress. This allows for effective educational support.

[1588] Example 1

[1589] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1590] With conventional learning support systems, feedback when children are working on learning materials tends to be delayed, making it difficult to confirm answers or provide feedback in real time. Furthermore, the means by which educators and parents can check learning histories and analysis results are limited, making it difficult to grasp each child's learning progress and strengths and weaknesses. This makes it difficult to provide support at the appropriate time, resulting in problems such as reduced learning efficiency.

[1591] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1592] In this invention, the server includes an information terminal for the child to use to study materials, an information processing device that receives answers entered from the information terminal and automatically judges them, means for receiving the judgment results from the information processing device and displaying the results on the information terminal, information processing device means for saving and analyzing the child's study history, means for notifying educators and parents of the analysis results from the information processing device, means for identifying areas of strength and weakness based on the study history and the analysis results, means for the child to select from study materials displayed on the information terminal, means for displaying additional hints and explanations when an incorrect answer is given, and means for the child to try again and transmit the study history to the information processing device. This allows the child to study efficiently while receiving feedback in real time, and allows educators and parents to provide support and feedback at appropriate times.

[1593] An "information terminal" is a device that allows a user to work through study materials and input answers.

[1594] An "information processing device" is a device that receives the answer sent from the information terminal, automatically judges it, and returns the result.

[1595] "Learning history" refers to recorded data such as the content of answers, whether they were correct or incorrect, and the time it took to answer when a child worked on learning materials.

[1596] The "analysis results" are data generated based on the learning history to identify the child's strengths and weaknesses.

[1597] "Educators and parents" refers to those responsible for overseeing a child's learning and providing support where necessary.

[1598] "Real-time feedback" refers to the ability to instantly provide a correct or incorrect answer, and possibly additional hints or explanations, immediately after a child enters their answer.

[1599] The "retry feature" is a function that allows a child to try again on a question that was answered incorrectly.

[1600] "Storage means" refers to a function for long-term storage of answers entered by children and their learning history.

[1601] "Notification means" refers to a function for notifying educators and parents of the analysis results from the server.

[1602] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described in detail below with reference to the accompanying drawings.

[1603] System configuration

[1604] The system consists of the following main components:

[1605] 1. Terminal (information terminal)

[1606] 2. Server (information processing device)

[1607] 3. Users (children, educators, parents)

[1608] Hardware and software used

[1609] Device: This is the information device used by the child, such as a PC or tablet, which displays learning materials and inputs answers.

[1610] Server: An information processing device that receives, stores, processes data from users, and generates analytical results. The server is equipped with a database and AI model.

[1611] Software: An automatic scoring algorithm implemented in Python, database management software, and a web application providing the user interface.

[1612] Data processing and calculation

[1613] The terminal does the following:

[1614] 1. Receive learning materials sent from the server and display them to the user (child).

[1615] 2. The answer entered by the user (child) is sent to the server.

[1616] 3. The scoring results received from the server are displayed to the user (child).

[1617] The server does the following:

[1618] 1. The answers received from the device are judged by an automatic scoring algorithm.

[1619] 2. The scoring results are returned to the device.

[1620] 3. The received answer data and scoring results are stored in a database.

[1621] 4. Analyze your learning history and identify your strengths and weaknesses.

[1622] 5. Notify educators and parents of the analysis results.

[1623] Specific examples

[1624] When the server uploads a new math workbook, the device will notify the user that a new math workbook has been added. The child can tap the new workbook to open it and work on the problems. For example, if the child types "5+3=8" and presses the "Submit" button, the device will send the answer to the server.

[1625] The server uses an AI model implemented in Python to check whether the received answer "8" is correct. The server then sends the result "Correct!" to the device. The device displays "Correct!" or "Incorrect. Let's try again," and if the answer is incorrect, provides a hint such as "Try counting again."

[1626] Educators or parents can check their children's learning history through a dedicated management screen. The server generates analysis results such as "Child A is good at math calculation problems but not at word problems."

[1627] Prompt Sentence Examples

[1628] Below are some example prompts to input to a generative AI model:

[1629] "Generate 10 math problems."

[1630] "Based on the child's answers, identify areas of weakness and generate hints for them."

[1631] "Implement a system that analyzes learning progress in real time and provides feedback."

[1632] Although the embodiments of the present invention have been described above, many other variations are possible in the specific implementation methods. Various changes and modifications are possible within the scope of the present invention, and these are also included.

[1633] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1634] Step 1: Receive and view study materials

[1635] The server generates new learning materials (e.g., math drills) and sends them to the terminal. The terminal displays the received learning materials to the user (child). The user (child) selects the learning material to work on from the materials.

[1636] Input: Study material data sent from the server

[1637] Output: A list of study materials displayed on the device screen

[1638] Specific behavior: When the server uploads a new math workbook, the device notifies the user that "A new math workbook has been added," and the user (child) taps it to open it.

[1639] Step 2: Enter and submit your answers

[1640] The user (child) inputs answers to questions in the study materials displayed on the terminal, and the terminal then sends the answers to the server.

[1641] Input: Answer data entered by the user (child)

[1642] Output: Answer data sent from the device to the server

[1643] Specific operation: When the user (child) enters "5+3=8" and presses the "Send" button, the device sends this answer data to the server.

[1644] Step 3: Automated scoring

[1645] The server uses a generative AI model to automatically determine whether the answer received from the device is correct or incorrect, and the result is sent back to the device.

[1646] Input: Answer data sent from the device

[1647] Output: The score results sent back from the server to the device

[1648] Specific operation: The server uses an AI model implemented in Python to check whether the received answer "8" is correct. The server then sends the result "That's correct!" to the device.

[1649] Step 4: View your feedback

[1650] The terminal displays the score received from the server to the user (child). If the answer is incorrect, the terminal provides additional hints and explanations to the user (child).

[1651] Input: The score returned from the server

[1652] Output: Feedback displayed on the device screen

[1653] Specific behavior: The device will display "Correct!" or "Incorrect. Try again," and if the answer is incorrect, it will provide a hint such as "Try counting again."

[1654] Step 5: Try again and try again

[1655] The user (child) revisits the questions that were answered incorrectly and enters the answer, and this process is repeated until the correct answer is obtained.

[1656] Input: Answer data re-entered by the user (child)

[1657] Output: Answer data sent from the device to the server, and new scoring results returned from the server.

[1658] Specific operation: The user (child) enters "7" and is incorrect, then repeats this operation until they enter "8" again and confirm the correct answer.

[1659] Step 6: Save your learning history

[1660] The server stores data on each user (child), such as answer history, correct answers, and answer time. This data is used for later analysis.

[1661] Input: User (child) answer data and scoring result data

[1662] Output: Learning history stored in the server database

[1663] Specific operation: The server stores detailed history in a database, such as "Question 1: 5+3, correct answers: 8, number of incorrect answers: 1, number of correct answers: 1, answer time: 15 seconds."

[1664] Step 7: Check progress and communicate analysis results

[1665] Educators or parents can check the learning history of users (children) through a dedicated management screen. The server generates and notifies the results of analysis.

[1666] Input: Learning history data stored on the server

[1667] Output: Analysis results displayed on the educator and parent management screen

[1668] Specific operation: The educator logs in to the management screen and checks the progress of Child A. The server displays the analysis results on the management screen, such as "Child A is good at math calculation problems, but not so good at word problems."

[1669] (Application example 1)

[1670] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1671] Learning to operate robots in factories is difficult for operators due to the complex procedures and high precision required. Conventional training methods make it difficult for operators to immediately grasp their own progress, and the slow feedback reduces efficiency. It is also difficult for managers to quickly identify an operator's strengths and weaknesses and provide appropriate guidance. Therefore, there is a need for a system that allows operators to efficiently learn robot operation procedures, receive instant feedback, and allow managers to easily grasp their progress.

[1672] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1673] In this invention, the server includes a terminal on which an operator works on the operation procedures, means for receiving answers entered from the terminal and automatically grading them, means for receiving the grading results from the server and displaying the results on the terminal, means for saving and analyzing the learning history of the operator, means for notifying an administrator of the analysis results from the server, and means for identifying areas of strength and weakness based on the learning history and the analysis results. This allows the operator to efficiently learn the robot operation procedures and receive immediate feedback, and also enables the administrator to easily understand the progress and provide appropriate guidance.

[1674] "Operator" refers to the person in charge of operating and training the robot within the factory.

[1675] A "terminal" refers to an information processing device used by an operator, such as a smartphone, tablet, or head-mounted display.

[1676] "Solution" refers to the result or answer that an operator enters when working through an operating procedure.

[1677] The "server" is a central processing unit that receives answers from operators, automatically grades them, and sends back feedback.

[1678] "Scoring" refers to the process of determining whether an operator's answer is correct.

[1679] "Feedback" refers to information about whether an answer is correct or incorrect, as well as additional advice and hints, sent from the server to the operator.

[1680] "Learning history" refers to data such as the operator's answer history, correct answers, and answer time.

[1681] "Analysis results" refers to information such as areas of strength and weakness that is generated by the server based on learning history.

[1682] "Supervisor" refers to the person in charge of the factory who monitors the progress of the operators and provides appropriate guidance.

[1683] "Notification" refers to the process by which the server communicates important information such as analysis results and operator progress to the administrator.

[1684] As an embodiment of the present invention, a method for constructing a system that enables operators in a factory to learn robot operation procedures, receive immediate feedback, and efficiently manage the progress will be described below.

[1685] Configuration overview

[1686] The system consists of the following main components:

[1687] 1. Terminal

[1688] 2. Server

[1689] 3. User (operator, administrator)

[1690] Explanation of program processing

[1691] Displaying operating instructions

[1692] The server sends new operation procedures to the terminal, which displays a list of them, allowing the operator to select and execute the operation procedure on the terminal.

[1693] Examples:

[1694] When the server uploads a new robot configuration procedure, the terminal displays "New robot configuration procedure added," and the operator taps it to open it.

[1695] Enter your answer

[1696] The operator inputs answers to the operating procedures displayed on the terminal, and the terminal sends the input answers to the server.

[1697] Examples:

[1698] When the operator types "Turn on the robot" and presses the "Send" button, the terminal sends this answer to the server.

[1699] Automatic scoring

[1700] The server automatically determines whether the answer is correct or incorrect based on the answer received from the device, and sends the result back to the device.

[1701] Examples:

[1702] The server checks whether "Turn on the robot" is the correct answer and returns the result to the terminal, saying "Correct!" or "Incorrect."

[1703] View Feedback

[1704] The terminal displays the score received from the server to the operator. If the answer is incorrect, the terminal provides additional hints and explanations to the operator.

[1705] Examples:

[1706] The device will display "That's right!" or "That's wrong. Try again," and if the answer is incorrect, it will provide a hint such as "Check the detailed instructions and try again."

[1707] Doing it over and trying again

[1708] The operator retrys the incorrect operation sequence and enters the answer, and this process is repeated until the correct answer is obtained.

[1709] Examples:

[1710] The operator types "start robot" which is an incorrect answer, and then types "power on robot" again, repeating this process until the correct answer is confirmed.

[1711] Save learning history

[1712] The server stores data such as each operator's answer history, correct answers, and answer time, which will be used for later analysis.

[1713] Examples:

[1714] The server stores detailed history of operator A, such as "Step 1: Turn on the robot, correct, number of incorrect answers: 1, number of correct answers: 1, response time: 15 seconds."

[1715] Progress check and analysis results notification

[1716] Administrators can check the learning history of operators through a dedicated management screen. The server generates and notifies the results of the analysis.

[1717] Examples:

[1718] When the administrator checks the progress of Operator A on the management screen, the server displays a list of Operator A's performance and history. In addition, the server generates and notifies the administrator of the results of an analysis, such as "Operator A is good at setting up the robot, but is not good at emergency shutdown procedures."

[1719] Hardware and software used

[1720] This system mainly uses the following hardware and software:

[1721] Hardware: Devices such as smartphones, tablets, and head-mounted displays.

[1722] Software: Server-side program using Python, terminal application for displaying operation procedures.

[1723] Example prompts to input to the generative AI model

[1724] Here is the prompt to input to a generative AI model (e.g. ChatGPT):

[1725] "Generate guidelines for learning troubleshooting steps and getting immediate feedback for a factory robotics training application. Include the following steps:

[1726] 1. Check for abnormal robot stoppage

[1727] 2. Analysis of abnormal code

[1728] 3. Take any necessary corrective steps

[1729] 4. Check for proper operation

[1730] Please also include any explanations or advice you would like to give the operator at each step.

[1731] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1732] Step 1:

[1733] The server sends the new operating procedure to the terminal. Specifically, the server retrieves the new operating procedure from the operating procedure database and sends it to the terminal. The terminal receives this data and displays a list of operating procedures to the operator. The input information is the new operating procedure, and the output result is the list of operating procedures displayed on the operator's terminal.

[1734] Step 2:

[1735] The operator selects the item they want to learn from the operating procedures displayed on the terminal. Specifically, when the operator taps or selects an item, the terminal notifies the server of the selected operating procedure. The input information is the operating procedure selected by the operator, and the output result is a notification of the selected item to the server.

[1736] Step 3:

[1737] The server sends specific tasks related to the selected operating procedure to the terminal. Specifically, the server retrieves task details corresponding to the selected operating procedure from the database and sends them to the terminal. The terminal receives this data and displays the tasks to the operator. The input information is the selected operating procedure, and the output result is the task details displayed on the operator's terminal.

[1738] Step 4:

[1739] The operator inputs answers to each task displayed on the terminal. Specifically, the operator enters the answer in the input field and presses the send button, which causes the terminal to send the answer to the server. The input information is the answer entered by the operator, and the output result is the answer sent to the server.

[1740] Step 5:

[1741] The server automatically scores the received answers. Specifically, the server compares the answer data with a database of correct answers to determine whether they match. The input information is the operator's answer data, and the output is a judgment result of whether the answer is correct or incorrect.

[1742] Step 6:

[1743] The server sends the scoring results to the terminal. Specifically, the server generates a judgment result and sends it to the terminal. The terminal receives this data and displays the scoring results to the operator. The input information is the scoring result data, and the output is the scoring result display on the operator's terminal.

[1744] Step 7:

[1745] If the answer is incorrect, the terminal provides the operator with additional hints and explanations. Specifically, the terminal retrieves appropriate hints and explanations from a feedback database for incorrect answers and displays them to the operator. The input information is the result of the incorrect answer determination, and the output is the hint or explanation displayed on the operator terminal.

[1746] Step 8:

[1747] The operator attempts the task again if the answer was incorrect and re-enters the answer. Specifically, the operator re-enters the answer and presses the send button, causing the terminal to send the new answer to the server. The input information is the re-entered answer, and the output result is the re-sent answer sent to the server.

[1748] Step 9:

[1749] The server stores each operator's learning history, including answer history, correct / incorrect answers, and answer time. Specifically, answer data and scoring results are recorded in a database. Input information is the operator's answer history data, and output results are stored in the database.

[1750] Step 10:

[1751] The server displays the saved learning history and analysis results in response to a request from an administrator. Specifically, the server receives the administrator's request through the management screen, retrieves the saved data from the database, generates the analysis results, and displays them on the management screen. The input information is the administrator's request, and the output is the analysis results displayed on the management screen.

[1752] The above is the specific processing flow of the factory robot operation training system.

[1753] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1754] As an embodiment of the invention, the following describes how an emotion engine that recognizes user emotions can be incorporated into a system that allows children to engage with learning material and receive instant feedback to effectively manage their progress.

[1755] Configuration overview

[1756] The system consists of the following main components:

[1757] 1. Device (with emotion engine)

[1758] 2. Server

[1759] 3. Users (children, educators, parents)

[1760] Explanation of program processing

[1761] View learning materials

[1762] The terminal receives new learning materials sent from the server and displays a list of them to the child. The user (child) can select learning materials to work on on the terminal.

[1763] example:

[1764] When the server uploads a new math workbook, the device displays "New math workbook added," and the child taps it to open it.

[1765] Enter your answer

[1766] The child inputs answers to questions in the learning materials displayed on the device, and the device sends the input answers along with emotional data analyzed by the emotion engine to the server.

[1767] example:

[1768] When the child enters "5+3=8" and presses the "Send" button, the device sends this answer along with the current emotional data (e.g., confidence, joy) analyzed by the emotion engine to the server.

[1769] Automatic scoring

[1770] The server automatically determines whether the answer is correct or incorrect based on the answer received from the device, and sends the result along with the emotion data back to the device.

[1771] example:

[1772] The server checks whether "8" is the correct answer and returns the result to the terminal along with emotional data, saying "That's correct!" or "That's incorrect."

[1773] Receiving and viewing feedback

[1774] The device receives the score and emotion data sent from the server and displays them to the user. If the answer is incorrect, the device provides additional hints and explanations to the child and displays feedback according to the emotion provided by the emotion engine.

[1775] example:

[1776] The device will display "That's right!" or "That's wrong. Let's try again." If the answer is incorrect, the device will provide a hint like "Try counting again," as well as emotional feedback like "Remain calm and try again."

[1777] Doing it over and trying again

[1778] If the child answers incorrectly, they can try the same question again and send a new answer along with their emotional data to the server.

[1779] example:

[1780] The process repeats until the child enters "7" to confirm the answer is incorrect and then enters "8" again to confirm the answer is correct. Emotional data is also sent each time.

[1781] Data storage

[1782] The server stores each user's learning history and emotional data in a database, including details such as the questions answered, the answers, whether they were correct or incorrect, the time it took to answer, the number of retries, and emotional data. The stored data is used for later analysis.

[1783] example:

[1784] The server stores detailed history for Child A, such as "Question 1: 5+3, correct answers: 8, number of incorrect answers: 1, number of correct answers: 1, answer time: 15 seconds, emotional data: joy."

[1785] Progress review and feedback

[1786] Educators or parents can send a request to the server to check the learning history and emotional data through a dedicated management screen. The server analyzes the saved learning history and displays it on the management screen. It also notifies the educator or parent of the results of the analysis.

[1787] example:

[1788] When an educator checks Child A's progress on the management screen, the server displays a list of Child A's grades, history, and emotional data. The server also generates and notifies the educator of analysis results such as, "Child A is good at math calculation problems, but struggles with word problems and appears unsure of his or her answers."

[1789] Effects of implementation

[1790] By implementing this system, children can instantly know whether their answers are correct or incorrect and receive appropriate feedback based on their emotions. Educators and parents can understand detailed progress and emotional states, allowing them to provide more effective support. By clarifying each child's strengths and weaknesses, as well as their emotions at any given time, it is expected that the quality of education will be improved.

[1791] In this way, the system based on the aspects of the present invention is expected to solve multiple problems in educational settings and provide effective learning support.

[1792] The processing flow will be explained below.

[1793] Step 1: Upload your study materials

[1794] The server receives an upload request from an educator or system administrator. The server stores the learning material file (e.g., math drills) and associates it with each child's account. After the file is saved, it sends a notification to the device that the upload is complete.

[1795] Step 2: View study materials

[1796] The device receives notifications of new learning materials from the server, and the user (child) selects what to work on from the list of new learning materials displayed on the device.

[1797] example:

[1798] When the server uploads a new math workbook, the device displays "New math workbook added," and the user taps it to open it.

[1799] Step 3: Start Emotion Recognition

[1800] The device's built-in emotion engine analyzes data such as the child's facial expressions, voice, and touch pressure in real time to generate current emotion data (e.g., excitement, concentration, confusion).

[1801] example:

[1802] The device instructs the user to "relax and take a deep breath before you begin this problem," while the emotion engine collects data.

[1803] Step 4: Enter your answers

[1804] The user (child) inputs answers to questions displayed on the device. Emotional data is also continuously collected. The device transmits the input answers and emotional data to the server.

[1805] example:

[1806] When a child enters "5+3=8" and presses the "Send" button, the device sends this answer along with emotional data (e.g., confidence, joy) to the server.

[1807] Step 5: Automated scoring

[1808] The server automatically determines whether the answer is correct or incorrect based on the answer received from the device, and sends the result along with the emotion data back to the device.

[1809] example:

[1810] The server checks whether "8" is the correct answer and returns the result to the terminal along with emotional data, saying "That's correct!" or "That's incorrect."

[1811] Step 6: Receive and view feedback

[1812] The device receives the score and emotion data sent from the server and displays them to the user. If the answer is incorrect, the device provides additional hints and explanations to the child and displays feedback according to the child's emotion.

[1813] example:

[1814] The device will display "That's right!" or "That's wrong. Let's try again." If the answer is incorrect, the device will provide hints such as "Try counting again," as well as emotional feedback such as "Remain calm and try again."

[1815] Step 7: Doing a rework

[1816] If the user (child) answers incorrectly, they can try the same question again and send a new answer along with their emotion data to the server.

[1817] example:

[1818] The process repeats until the child enters "7" to confirm the answer is incorrect and then enters "8" again to confirm the answer is correct. Emotional data is also sent each time.

[1819] Step 8: Save your data

[1820] The server stores each user's learning history and emotional data in a database, including details such as the questions answered, the answers, whether they were correct or incorrect, the time it took to answer, the number of retries, and emotional data. The stored data is used for later analysis.

[1821] example:

[1822] The server stores detailed history for Child A, such as "Question 1: 5+3, correct answers: 8, number of incorrect answers: 1, number of correct answers: 1, answer time: 15 seconds, emotional data: joy."

[1823] Step 9: Review progress and provide feedback

[1824] The user (educator or parent) sends a request to the server to check the learning history and emotional data through a dedicated management screen. The server analyzes the saved learning history and displays it on the management screen. It also notifies the educator or parent of the analysis results.

[1825] example:

[1826] When an educator checks Child A's progress on the management screen, the server displays a list of Child A's grades, history, and emotional data. The server also generates and notifies the educator of analysis results such as, "Child A is good at math calculation problems, but struggles with word problems and appears unsure of his or her answers."

[1827] Effects of implementation

[1828] By implementing this system, children can instantly know whether their answers are correct or incorrect and receive appropriate feedback based on their emotions. Educators and parents can understand detailed progress and emotional states, allowing them to provide more effective support. By clarifying each child's strengths and weaknesses, as well as their emotions at any given time, it is expected that the quality of education will be improved.

[1829] In this way, the system based on the aspects of the present invention is expected to solve multiple problems in educational settings and provide effective learning support.

[1830] Example 2

[1831] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1832] In traditional educational systems, it is difficult for children to receive immediate feedback when working on learning materials. Furthermore, feedback provided does not take into account the child's emotional state, which can lead to a decrease in motivation to learn and increased stress. Educators and parents are unable to grasp a child's learning progress and emotional state in real time, making it difficult to provide appropriate support. This makes it difficult to identify individual children's strengths and weaknesses and provide effective educational support.

[1833] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving answers entered from the terminal and emotion data analyzed by the emotion engine, means for automatically scoring based on the answers and generating scoring results including emotion data, and means for receiving the scoring results from the server and displaying the results on the terminal. This allows children to instantly receive feedback based on their answers and emotions. Furthermore, educators and parents can grasp children's learning progress and emotional state in real time and provide more effective support.

[1834] "Devices" refer to electronic devices that children use to engage with learning materials and are equipped with emotion engines that can analyze emotional data.

[1835] "Answer" refers to a child's input to the study material, which is sent to the server for validation.

[1836] An "emotion engine" refers to an algorithm or software that analyzes emotions from a user's facial expressions, voice, etc.

[1837] "Emotion data" refers to data relating to the user's emotional state obtained as a result of analysis by the emotion engine.

[1838] "Server" refers to a computer system that automatically grades answers, stores and analyzes learning history and emotional data.

[1839] "Scoring result" refers to the result of whether the answer is correct or incorrect as determined by the server based on the child's answer.

[1840] "Feedback" refers to hints, encouragement, explanations, etc. that are displayed on the device based on the answer results and emotional data.

[1841] "Educators and parents" refers to adults who supervise a child's learning progress and provide appropriate support.

[1842] "Learning history" refers to a detailed record of the learning materials a child has worked on, their answers, whether correct or incorrect, how long it took to answer, and emotional data.

[1843] "Analysis results" refers to the results of analysis performed by the server based on learning history and emotional data.

[1844] "Strengths and weaknesses" refers to the range of learning content in which a child excels or struggles.

[1845] As an embodiment of the present invention, a method for incorporating an emotion engine that recognizes user emotions into a system for children to work on learning materials, receive instant feedback, and efficiently manage their progress is described below. The system is composed of terminals, a server, and users (children, educators, and parents).

[1846] Hardware and Software Used

[1847] Device: Tablet or PC with emotion engine (e.g. iPad, Chromebook)

[1848] Server: Learning materials management and database (e.g. AWS EC2, MySQL)

[1849] Sentiment engine: AI algorithms for sentiment analysis (e.g. Azure Cognitive Services)

[1850] System Operation Overview

[1851] 1. The server manages the learning materials uploaded by the educator and sends them to the terminal.

[1852] 2. The terminal displays the learning materials received from the server to the child, and the child works on the learning materials.

[1853] 3. The child enters the answer to the study question, and the device sends the answer along with the emotional data analyzed by the emotion engine to the server.

[1854] 4. The server automatically scores the received answers and generates scoring results that include emotion data.

[1855] 5. The device receives the score and emotion data sent from the server and displays them to the child. Based on the emotion data, the device provides additional feedback.

[1856] 6. The server stores learning history and emotional data, and based on this identifies strengths and weaknesses in each area.

[1857] 7. Educators and parents can check learning history and analysis results through the management screen and provide effective support to their children.

[1858] Specific examples

[1859] Example 1: When the server uploads a new math workbook, the device displays "A new math workbook has been added," and the child taps it to open it. When the child enters "5+3=8" and presses the "Send" button, the device sends this answer along with emotional data (e.g., confidence, joy) to the server.

[1860] Example 2: The server checks the answer "8" and, since it is correct, sends the message "That's right!" along with emotional data to the device. The device then displays "That's right! You seem confident!" If the answer is incorrect, it provides feedback such as "Think about it again" or "Calm down and try again."

[1861] Example 3: When an educator checks a child's progress on the management screen, the server displays a list of the child's grades, history, and emotional data, and notifies them of the analysis results, such as "Child A is good at math calculation problems but not so good at word problems."

[1862] Example prompts to input to the generative AI model

[1863] "How can I be notified when new learning materials are added?"

[1864] "Please explain the process for sending the answers entered by the child to the server."

[1865] "Please explain in detail how the server scores the answers and returns the results."

[1866] By building such a system, children can efficiently understand their learning content and receive appropriate emotional feedback, allowing educators and parents to monitor their learning progress in detail and provide support tailored to each individual child.

[1867] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1868] Step 1:

[1869] The server receives the learning materials uploaded by the educator, which are stored in a database and ready to be sent to the device.

[1870] Input: Learning materials uploaded by educators (e.g., math drills)

[1871] Output: The learning materials are saved in a database ready to be sent to the device.

[1872] Specific operation: The server receives PDF files and digital text format learning materials added by educators, stores them in a database, and then generates a material ID and metadata and notifies the device.

[1873] Step 2:

[1874] The terminal displays the new learning materials received from the server to the child.

[1875] Input: Learning material notification from the server (e.g., notification of new math drills added)

[1876] Output: A list of study materials will be displayed on the child's device screen.

[1877] Specific behavior: A notification saying "New math drills have been added" will be displayed on the device screen, and users can tap to access the content.

[1878] Step 3:

[1879] The user (child) inputs answers to questions in the study materials displayed on the device. At the same time, the device generates emotion data analyzed by the emotion engine.

[1880] Input: The answer entered by the child (e.g. 5+3=8)

[1881] Output: Answer and emotion data are generated (e.g., confidence, joy)

[1882] Specific operation: When a child enters an answer and presses the send button, the device's built-in camera and microphone are activated to analyze facial expressions and voice and generate emotional data.

[1883] Step 4:

[1884] The terminal transmits the answer and emotion data to the server.

[1885] Input: Child's answers and emotion data

[1886] Output: Answers and emotion data are sent to the server

[1887] Specific operation: The device combines the answer and emotion data into a single data packet, encrypts it, and sends it to the server.

[1888] Step 5:

[1889] The server automatically determines whether the answer received from the terminal is correct or incorrect and generates a scoring result that includes emotional data.

[1890] Input: Answers and emotion data sent from the device

[1891] Output: Scoring results and emotional feedback data

[1892] What it does: The server's algorithm scores the answers, generates a "correct" or "incorrect" result, and creates a feedback message with emotional data.

[1893] Step 6:

[1894] The server returns the scoring results and emotion data to the terminal.

[1895] Input: Scoring results and emotional feedback data

[1896] Output: Feedback data sent to the device

[1897] Specific operation: The server compiles the scoring results and the emotion feedback message into a data packet and sends it to the device.

[1898] Step 7:

[1899] The device receives the score and emotion data sent from the server and displays them to the user (child). If the answer is incorrect, the device also provides additional hints and emotion-based feedback.

[1900] Input: Scoring results and emotional feedback data sent from the server

[1901] Output: Feedback displayed on the terminal screen

[1902] What it does: Show feedback on the device screen, such as "That's right!", "You look confident!", or "Think again" or "Calm down and try again."

[1903] Step 8:

[1904] If the user (child) answers incorrectly, they can try the same question again.

[1905] Input: New answer and emotion data

[1906] Output: Retry data sent to the server

[1907] What it does: If the child enters a different answer and submits it again, the new answer and emotion data are sent to the server and re-evaluated.

[1908] Step 9:

[1909] The server stores each user's learning history and emotional data in a database.

[1910] Input: Answers, emotion data, scoring results

[1911] Output: Saved learning history and emotion data

[1912] Specific operation: The server stores detailed data such as "question ID, answer, correct / incorrect answer, number of times, time, emotional data" in a database.

[1913] Step 10:

[1914] The server displays the saved learning history and emotional data on the management screen in response to requests from educators or parents, and also notifies them of the analysis results.

[1915] Input: History view request from educator or parent

[1916] Output: Learning history and analysis results displayed on the management screen

[1917] Specific operation: The server receives the request, extracts and analyzes the necessary data, and displays the analysis results on the management screen, such as "Child A is good at math calculation problems but not at word problems."

[1918] (Application example 2)

[1919] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1920] While immediate feedback and correct answers are important for children's learning, conventional systems do not provide support that takes into account the child's emotional state. This can lead to children feeling stressed and frustrated, which can decrease their motivation to learn. It is also difficult for educators and parents to properly understand a child's progress and emotional state and provide effective support.

[1921] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1922] In this invention, the server includes a means for receiving answers entered from the terminal and automatically scoring them, an emotion recognition means for the terminal to recognize the child's emotions and send the data to the server, and a means for receiving the scoring results and emotion data from the server and displaying the results on the terminal. This makes it possible to grasp the emotional state of a child while they are learning in real time and provide appropriate feedback. Furthermore, educators and parents can grasp the child's detailed progress and emotional state and provide more effective support.

[1923] A "terminal" is a device for displaying study materials and inputting user answers.

[1924] A "server" is a central computer system that receives data sent from terminals and processes and analyzes it.

[1925] The "emotion recognition means" has the function of analyzing the child's facial expressions and behavior and determining their emotional state.

[1926] The "feedback generation means" is a function for generating appropriate feedback to the child based on whether the answer is correct or incorrect.

[1927] "Learning history" is a record of data such as the learning materials a child has worked on, the content of their answers, the time it took to answer, and whether they were correct or incorrect.

[1928] "Analysis results" are the results of analysis using statistical and machine learning methods based on learning history and emotional data.

[1929] An "educator" is someone who provides educational guidance to children, i.e., a teacher or instructor.

[1930] A "guardian" is a parent or caregiver who oversees a child's life and education.

[1931] A "system" is a set of devices or software in which multiple components work together to achieve a specific function.

[1932] "Feedback" refers to advice and evaluations provided based on a user's actions and answers.

[1933] "Emotional data" is information that expresses a child's emotional state in numerical values ​​and categories.

[1934] The system for implementing this invention consists of the following main components: a terminal, a back-end server, an emotion recognition engine, and a database.

[1935] Component Details

[1936] Terminal

[1937] The terminal is a device that displays learning materials and allows users (children) to input answers. Specifically, it includes smartphones, tablets, and PCs. The terminal is equipped with an emotion recognition engine, and uses a built-in camera to capture video of the child's face and analyze the emotional data.

[1938] Backend Server

[1939] The backend server is a central computer system that receives data sent from the devices and automatically scores them. It uses cloud servers such as Node.js and AWS Lambda. The server analyzes the received answers and emotion data and generates appropriate feedback.

[1940] Emotion Recognition Engine

[1941] The emotion recognition engine uses Python, OpenCV, Google Cloud AI / ML API, etc. to analyze a child's facial expressions and behavior and determine their emotional state.

[1942] Database

[1943] The database is used to store learning history and emotional data. Specifically, AWS RDS and MongoDB are used. The database stores details such as answer content, answer time, correct / incorrect status, number of retry attempts, and emotional data, and is used for later analysis.

[1944] Processing flow

[1945] 1. Viewing study materials

[1946] The device receives new learning materials sent from the server and displays a list of them to the child, who can then select and work on the learning materials on the device.

[1947] Example: When the server uploads a new math workbook, the device displays "New math workbook added," and the child taps it to open it.

[1948] 2. Enter your answer

[1949] The child inputs answers to questions in the learning materials displayed on the device, and the device sends the input answers along with emotional data analyzed by the emotion engine to the server.

[1950] Example: When a child enters "5+3=8" and presses the "Send" button, the device sends this answer along with the current emotional data (e.g., confidence, joy) analyzed by the emotion engine to the server.

[1951] 3. Automatic scoring

[1952] The server automatically determines whether the answer is correct or incorrect based on the answer received from the device, and sends the result along with the emotion data back to the device.

[1953] Example: The server checks whether "8" is the correct answer and returns the result to the device along with emotion data, such as "That's correct!" or "That's incorrect."

[1954] 4. Receiving and Viewing Feedback

[1955] The device receives the score and emotion data sent from the server and displays them to the user. If the answer is incorrect, the device provides additional hints and explanations to the child and displays feedback according to the emotion provided by the emotion engine.

[1956] For example, the device might say "That's right!" or "That's wrong, let's try again," and if the answer is incorrect, it might provide a hint like "Try counting again," along with emotional feedback like "Remain calm and try again."

[1957] Specific examples

[1958] Consider a case where a child logs in and starts working on a math drill. As the child enters the answer, the built-in camera analyzes the child's emotions and determines that the child is frustrated. This information is sent to the server. For example, the child enters "5+3=7," which is incorrect, and then enters "5+3=8" again, repeating this process until the correct answer is confirmed. During this process, the child's emotional data is also updated, and eventually a message such as "That's correct, but please calm down and try again" is displayed.

[1959] Prompt Sentence Examples

[1960] ---

[1961] The answer entered by the child is incorrect. The child's emotion is "irritated." Please generate a feedback sentence according to the emotion.

[1962] ---

[1963] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1964] Step 1:

[1965] The terminal receives new learning materials sent from the server and displays a list of them to the child.

[1966] Input: Learning material data from the server.

[1967] Output: Learning materials list screen.

[1968] Specific operation: The terminal receives the data of the learning materials and displays them to the child through the GUI. The child then performs operations to select learning materials.

[1969] Step 2:

[1970] The user (child) inputs answers to questions in the study materials displayed on the terminal.

[1971] Input: Child's answer data.

[1972] Output: A request with answer and sentiment data.

[1973] How it works: The child enters their answer using the touchscreen or keyboard, and the device's emotion recognition engine analyzes the facial image to obtain their current emotional data.

[1974] Step 3:

[1975] The server receives the answer data and emotion data from the terminal.

[1976] Input: Answer data and emotion data from the device.

[1977] Output: A new dataset for automatic marking and feedback generation.

[1978] Specific operation: The server passes the answer data to an automatic scoring algorithm to determine whether it is correct or incorrect. The emotion data is stored in a database.

[1979] Step 4:

[1980] The server generates feedback based on the scoring results and creates a feedback statement that takes into account the emotion data.

[1981] Input: Scoring results and emotion data.

[1982] Output: Feedback message.

[1983] Specific operation: The server uses a generative AI model to create a prompt sentence and generates a feedback sentence according to the emotion.

[1984] Example: If a child answers incorrectly and their emotion is determined to be "irritated," the following prompt sentence is input into the generative AI model:

[1985] "The answer the child entered is incorrect. The child's emotion is 'frustrated'. Please generate feedback sentences based on the emotion."

[1986] Step 5:

[1987] The server sends a feedback message and the score back to the terminal.

[1988] Input: Feedback message.

[1989] Output: Sends feedback messages to the terminal.

[1990] Specific operation: The generated feedback message and the scoring result are sent from the server to the terminal.

[1991] Step 6:

[1992] The terminal displays the feedback message and the scoring results sent from the server to the user (child).

[1993] Input: Feedback message and grading results from the server.

[1994] Output: Feedback messages and grading results displayed in the user interface.

[1995] Specific operation: The device displays feedback messages and scoring results to the child through a GUI. If the answer is incorrect, additional hints and explanations are also displayed.

[1996] Step 7:

[1997] If the user (child) answers incorrectly, they enter the answer again and send the answer and emotion data to the server using the same procedure.

[1998] Input: Answer data and emotion data as above.

[1999] Output: Answer data and emotion data for resubmission.

[2000] Specific operation: The child re-enters the answer, and the device again analyzes the facial image to obtain new emotional data, which it then sends to the server again.

[2001] Step 8:

[2002] The server stores each user's learning history and emotional data in a database.

[2003] Input: Answer data, emotion data, scoring results.

[2004] Output: Save data to database.

[2005] Specific operation: The server stores details such as the answer content, answer time, correct / incorrect status, number of retries, and emotional data in a database (AWS RDS, MongoDB, etc.).

[2006] Step 9:

[2007] Educators or parents can check learning history and emotional data through a dedicated management screen.

[2008] Input: A request from an educator or parent.

[2009] Output: Display of learning history and emotion data on the management screen.

[2010] What it does: Educators or parents send a request to the server to check their child's progress on the management screen. The server analyzes the stored data and displays it on the management screen.

[2011] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2012] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2013] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2014] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2015] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2016] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2017] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2018] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2019] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2020] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2021] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2022] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2023] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2024] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[2025] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2026] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2027] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2028] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2029] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2030] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[2031] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[2032] The following is further disclosed regarding the above embodiment.

[2033] (Claim 1)

[2034] A device for children to use to access learning materials,

[2035] a server that receives the answers entered from the terminal and automatically grades them;

[2036] means for receiving the scoring results from the server and displaying the results on the terminal;

[2037] a server means for storing and analyzing the child's learning history;

[2038] a means for notifying educators and parents of the analysis results from the server;

[2039] The system includes a means for identifying areas of strength and weakness based on the learning history and analysis results.

[2040] (Claim 2)

[2041] 2. The system of claim 1, wherein the terminal includes means for displaying additional hints or explanations when an answer is incorrect.

[2042] (Claim 3)

[2043] 2. The system according to claim 1, wherein the server includ...

Claims

1. A device for children to use to access learning materials, a server that receives the answers entered from the terminal and automatically grades them; means for receiving the scoring results from the server and displaying the results on the terminal; a server means for storing and analyzing the child's learning history; a means for notifying educators and parents of the analysis results from the server; The system includes a means for identifying areas of strength and weakness based on the learning history and analysis results.

2. 2. The system of claim 1, wherein the terminal includes means for displaying additional hints or explanations when an answer is incorrect.

3. 2. The system according to claim 1, wherein the server includes means for displaying the saved learning history and analysis results in response to a request from an educator or a parent.

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